(gentle synth music) (music ends) >> Welcome back to Supercloud 2, an open industry collaboration between technologists, consultants, analysts, and of course practitioners to help shape the future of cloud. At this event, one of the key areas we're exploring is the intersection of cloud and data. And how building value on top of hyperscale clouds and across clouds is evolving, a concept of course we call "Supercloud". And we're pleased to welcome our friends from Enterprise Technology research, Erik Bradley and Darren Brabham. Guys, thanks for joining us, great to see you. we love to bring the data into these conversations. >> Thank you for having us, Dave, I appreciate it. >> Yeah, thanks. >> You bet. And so, let me do the setup on what is Supercloud. It's a concept that we've floated, Before re:Invent 2021, based on the idea that cloud infrastructure is becoming ubiquitous, incredibly powerful, but there's a lack of standards across the big three clouds. That creates friction. So we defined over the period of time, you know, better part of a year, a set of essential elements, deployment models for so-called supercloud, which create this common experience for specific cloud services that, of course, again, span multiple clouds and even on-premise data. So Erik, with that as background, I wonder if you could add your general thoughts on the term supercloud, maybe play proxy for the CIO community, 'cause you do these round tables, you talk to these guys all the time, you gather a lot of amazing information from senior IT DMs that compliment your survey. So what are your thoughts on the term and the concept? >> Yeah, sure. I'll even go back to last year when you and I did our predictions panel, right? And we threw it out there. And to your point, you know, there's some haters. Anytime you throw out a new term, "Is it marketing buzz? Is it worth it? Why are you even doing it?" But you know, from my own perspective, and then also speaking to the IT DMs that we interview on a regular basis, this is just a natural evolution. It's something that's inevitable in enterprise tech, right? The internet was not built for what it has become. It was never intended to be the underlying infrastructure of our daily lives and work. The cloud also was not built to be what it's become. But where we're at now is, we have to figure out what the cloud is and what it needs to be to be scalable, resilient, secure, and have the governance wrapped around it. And to me that's what supercloud is. It's a way to define operantly, what the next generation, the continued iteration and evolution of the cloud and what its needs to be. And that's what the supercloud means to me. And what depends, if you want to call it metacloud, supercloud, it doesn't matter. The point is that we're trying to define the next layer, the next future of work, which is inevitable in enterprise tech. Now, from the IT DM perspective, I have two interesting call outs. One is from basically a senior developer IT architecture and DevSecOps who says he uses the term all the time. And the reason he uses the term, is that because multi-cloud has a stigma attached to it, when he is talking to his business executives. (David chuckles) the stigma is because it's complex and it's expensive. So he switched to supercloud to better explain to his business executives and his CFO and his CIO what he's trying to do. And we can get into more later about what it means to him. But the inverse of that, of course, is a good CSO friend of mine for a very large enterprise says the concern with Supercloud is the reduction of complexity. And I'll explain, he believes anything that takes the requirement of specific expertise out of the equation, even a little bit, as a CSO worries him. So as you said, David, always two sides to the coin, but I do believe supercloud is a relevant term, and it is necessary because the cloud is continuing to be defined. >> You know, that's really interesting too, 'cause you know, Darren, we use Snowflake a lot as an example, sort of early supercloud, and you think from a security standpoint, we've always pushed Amazon and, "Are you ever going to kind of abstract the complexity away from all these primitives?" and their position has always been, "Look, if we produce these primitives, and offer these primitives, we we can move as the market moves. When you abstract, then it becomes harder to peel the layers." But Darren, from a data standpoint, like I say, we use Snowflake a lot. I think of like Tim Burners-Lee when Web 2.0 came out, he said, "Well this is what the internet was always supposed to be." So in a way, you know, supercloud is maybe what multi-cloud was supposed to be. But I mean, you think about data sharing, Darren, across clouds, it's always been a challenge. Snowflake always, you know, obviously trying to solve that problem, as are others. But what are your thoughts on the concept? >> Yeah, I think the concept fits, right? It is reflective of, it's a paradigm shift, right? Things, as a pendulum have swung back and forth between needing to piece together a bunch of different tools that have specific unique use cases and they're best in breed in what they do. And then focusing on the duct tape that holds 'em all together and all the engineering complexity and skill, it shifted from that end of the pendulum all the way back to, "Let's streamline this, let's simplify it. Maybe we have budget crunches and we need to consolidate tools or eliminate tools." And so then you kind of see this back and forth over time. And with data and analytics for instance, a lot of organizations were trying to bring the data closer to the business. That's where we saw self-service analytics coming in. And tools like Snowflake, what they did was they helped point to different databases, they helped unify data, and organize it in a single place that was, you know, in a sense neutral, away from a single cloud vendor or a single database, and allowed the business to kind of be more flexible in how it brought stuff together and provided it out to the business units. So Snowflake was an example of one of those times where we pulled back from the granular, multiple points of the spear, back to a simple way to do things. And I think Snowflake has continued to kind of keep that mantle to a degree, and we see other tools trying to do that, but that's all it is. It's a paradigm shift back to this kind of meta abstraction layer that kind of simplifies what is the reality, that you need a complex multi-use case, multi-region way of doing business. And it sort of reflects the reality of that. >> And you know, to me it's a spectrum. As part of Supercloud 2, we're talking to a number of of practitioners, Ionis Pharmaceuticals, US West, we got Walmart. And it's a spectrum, right? In some cases the practitioner's saying, "You know, the way I solve multi-cloud complexity is mono-cloud, I just do one cloud." (laughs) Others like Walmart are saying, "Hey, you know, we actually are building an abstraction layer ourselves, take advantage of it." So my general question to both of you is, is this a concept, is the lack of standards across clouds, you know, really a problem, you know, or is supercloud a solution looking for a problem? Or do you hear from practitioners that "No, this is really an issue, we have to bring together a set of standards to sort of unify our cloud estates." >> Allow me to answer that at a higher level, and then we're going to hand it over to Dr. Brabham because he is a little bit more detailed on the realtime streaming analytics use cases, which I think is where we're going to get to. But to answer that question, it really depends on the size and the complexity of your business. At the very large enterprise, Dave, Yes, a hundred percent. This needs to happen. There is complexity, there is not only complexity in the compute and actually deploying the applications, but the governance and the security around them. But for lower end or, you know, business use cases, and for smaller businesses, it's a little less necessary. You certainly don't need to have all of these. Some of the things that come into mind from the interviews that Darren and I have done are, you know, financial services, if you're doing real-time trading, anything that has real-time data metrics involved in your transactions, is going to be necessary. And another use case that we hear about is in online travel agencies. So I think it is very relevant, the complexity does need to be solved, and I'll allow Darren to explain a little bit more about how that's used from an analytics perspective. >> Yeah, go for it. >> Yeah, exactly. I mean, I think any modern, you know, multinational company that's going to have a footprint in the US and Europe, in China, or works in different areas like manufacturing, where you're probably going to have on-prem instances that will stay on-prem forever, for various performance reasons. You have these complicated governance and security and regulatory issues. So inherently, I think, large multinational companies and or companies that are in certain areas like finance or in, you know, online e-commerce, or things that need real-time data, they inherently are going to have a very complex environment that's going to need to be managed in some kind of cleaner way. You know, they're looking for one door to open, one pane of glass to look at, one thing to do to manage these multi points. And, streaming's a good example of that. I mean, not every organization has a real-time streaming use case, and may not ever, but a lot of organizations do, a lot of industries do. And so there's this need to use, you know, they want to use open-source tools, they want to use Apache Kafka for instance. They want to use different megacloud vendors offerings, like Google Pub/Sub or you know, Amazon Kinesis Firehose. They have all these different pieces they want to use for different use cases at different stages of maturity or proof of concept, you name it. They're going to have to have this complexity. And I think that's why we're seeing this need, to have sort of this supercloud concept, to juggle all this, to wrangle all of it. 'Cause the reality is, it's complex and you have to simplify it somehow. >> Great, thanks you guys. All right, let's bring up the graphic, and take a look. Anybody who follows the breaking analysis, which is co-branded with ETR Cube Insights powered by ETR, knows we like to bring data to the table. ETR does amazing survey work every quarter, 1200 plus 1500 practitioners that that answer a number of questions. The vertical axis here is net score, which is ETR's proprietary methodology, which is a measure of spending momentum, spending velocity. And the horizontal axis here is overlap, but it's the presence pervasiveness, and the dataset, the ends, that table insert on the bottom right shows you how the dots are plotted, the net score and then the ends in the survey. And what we've done is we've plotted a bunch of the so-called supercloud suspects, let's start in the upper right, the cloud platforms. Without these hyperscale clouds, you can't have a supercloud. And as always, Azure and AWS, up and to the right, it's amazing we're talking about, you know, 80 plus billion dollar company in AWS. Azure's business is, if you just look at the IaaS is in the 50 billion range, I mean it's just amazing to me the net scores here. Anything above 40% we consider highly elevated. And you got Azure and you got Snowflake, Databricks, HashiCorp, we'll get to them. And you got AWS, you know, right up there at that size, it's quite amazing. With really big ends as well, you know, 700 plus ends in the survey. So, you know, kind of half the survey actually has these platforms. So my question to you guys is, what are you seeing in terms of cloud adoption within the big three cloud players? I wonder if you could could comment, maybe Erik, you could start. >> Yeah, sure. Now we're talking data, now I'm happy. So yeah, we'll get into some of it. Right now, the January, 2023 TSIS is approaching 1500 survey respondents. One caveat, it's not closed yet, it will close on Friday, but with an end that big we are over statistically significant. We also recently did a cloud survey, and there's a couple of key points on that I want to get into before we get into individual vendors. What we're seeing here, is that annual spend on cloud infrastructure is expected to grow at almost a 70% CAGR over the next three years. The percentage of those workloads for cloud infrastructure are expected to grow over 70% as three years as well. And as you mentioned, Azure and AWS are still dominant. However, we're seeing some share shift spreading around a little bit. Now to get into the individual vendors you mentioned about, yes, Azure is still number one, AWS is number two. What we're seeing, which is incredibly interesting, CloudFlare is number three. It's actually beating GCP. That's the first time we've seen it. What I do want to state, is this is on net score only, which is our measure of spending intentions. When you talk about actual pervasion in the enterprise, it's not even close. But from a spending velocity intention point of view, CloudFlare is now number three above GCP, and even Salesforce is creeping up to be at GCPs level. So what we're seeing here, is a continued domination by Azure and AWS, but some of these other players that maybe might fit into your moniker. And I definitely want to talk about CloudFlare more in a bit, but I'm going to stop there. But what we're seeing is some of these other players that fit into your Supercloud moniker, are starting to creep up, Dave. >> Yeah, I just want to clarify. So as you also know, we track IaaS and PaaS revenue and we try to extract, so AWS reports in its quarterly earnings, you know, they're just IaaS and PaaS, they don't have a SaaS play, a little bit maybe, whereas Microsoft and Google include their applications and so we extract those out and if you do that, AWS is bigger, but in the surveys, you know, customers, they see cloud, SaaS to them as cloud. So that's one of the reasons why you see, you know, Microsoft as larger in pervasion. If you bring up that survey again, Alex, the survey results, you see them further to the right and they have higher spending momentum, which is consistent with what you see in the earnings calls. Now, interesting about CloudFlare because the CEO of CloudFlare actually, and CloudFlare itself uses the term supercloud basically saying, "Hey, we're building a new type of internet." So what are your thoughts? Do you have additional information on CloudFlare, Erik that you want to share? I mean, you've seen them pop up. I mean this is a really interesting company that is pretty forward thinking and vocal about how it's disrupting the industry. >> Sure, we've been tracking 'em for a long time, and even from the disruption of just a traditional CDN where they took down Akamai and what they're doing. But for me, the definition of a true supercloud provider can't just be one instance. You have to have multiple. So it's not just the cloud, it's networking aspect on top of it, it's also security. And to me, CloudFlare is the only one that has all of it. That they actually have the ability to offer all of those things. Whereas you look at some of the other names, they're still piggybacking on the infrastructure or platform as a service of the hyperscalers. CloudFlare does not need to, they actually have the cloud, the networking, and the security all themselves. So to me that lends credibility to their own internal usage of that moniker Supercloud. And also, again, just what we're seeing right here that their net score is now creeping above AGCP really does state it. And then just one real last thing, one of the other things we do in our surveys is we track adoption and replacement reasoning. And when you look at Cloudflare's adoption rate, which is extremely high, it's based on technical capabilities, the breadth of their feature set, it's also based on what we call the ability to avoid stack alignment. So those are again, really supporting reasons that makes CloudFlare a top candidate for your moniker of supercloud. >> And they've also announced an object store (chuckles) and a database. So, you know, that's going to be, it takes a while as you well know, to get database adoption going, but you know, they're ambitious and going for it. All right, let's bring the chart back up, and I want to focus Darren in on the ecosystem now, and really, we've identified Snowflake and Databricks, it's always fun to talk about those guys, and there are a number of other, you know, data platforms out there, but we use those too as really proxies for leaders. We got a bunch of the backup guys, the data protection folks, Rubric, Cohesity, and Veeam. They're sort of in a cluster, although Rubric, you know, ahead of those guys in terms of spending momentum. And then VMware, Tanzu and Red Hat as sort of the cross cloud platform. But I want to focus, Darren, on the data piece of it. We're seeing a lot of activity around data sharing, governed data sharing. Databricks is using Delta Sharing as their sort of place, Snowflakes is sort of this walled garden like the app store. What are your thoughts on, you know, in the context of Supercloud, cross cloud capabilities for the data platforms? >> Yeah, good question. You know, I think Databricks is an interesting player because they sort of have made some interesting moves, with their Data Lakehouse technology. So they're trying to kind of complicate, or not complicate, they're trying to take away the complications of, you know, the downsides of data warehousing and data lakes, and trying to find that middle ground, where you have the benefits of a managed, governed, you know, data warehouse environment, but you have sort of the lower cost, you know, capability of a data lake. And so, you know, Databricks has become really attractive, especially by data scientists, right? We've been tracking them in the AI machine learning sector for quite some time here at ETR, attractive for a data scientist because it looks and acts like a lake, but can have some managed capabilities like a warehouse. So it's kind of the best of both worlds. So in some ways I think you've seen sort of a data science driver for the adoption of Databricks that has now become a little bit more mainstream across the business. Snowflake, maybe the other direction, you know, it's a cloud data warehouse that you know, is starting to expand its capabilities and add on new things like Streamlit is a good example in the analytics space, with apps. So you see these tools starting to branch and creep out a bit, but they offer that sort of neutrality, right? We heard one IT decision maker we recently interviewed that referred to Snowflake and Databricks as the quote unquote Switzerland of what they do. And so there's this desirability from an organization to find these tools that can solve the complex multi-headed use-case of data and analytics, which every business unit needs in different ways. And figure out a way to do that, an elegant way that's governed and centrally managed, that federated kind of best of both worlds that you get by bringing the data close to the business while having a central governed instance. So these tools are incredibly powerful and I think there's only going to be room for growth, for those two especially. I think they're going to expand and do different things and maybe, you know, join forces with others and a lot of the power of what they do well is trying to define these connections and find these partnerships with other vendors, and try to be seen as the nice add-on to your existing environment that plays nicely with everyone. So I think that's where those two tools are going, but they certainly fit this sort of label of, you know, trying to be that supercloud neutral, you know, layer that unites everything. >> Yeah, and if you bring the graphic back up, please, there's obviously big data plays in each of the cloud platforms, you know, Microsoft, big database player, AWS is, you know, 11, 12, 15, data stores. And of course, you know, BigQuery and other, you know, data platforms within Google. But you know, I'm not sure the big cloud guys are going to go hard after so-called supercloud, cross-cloud services. Although, we see Oracle getting in bed with Microsoft and Azure, with a database service that is cross-cloud, certainly Google with Anthos and you know, you never say never with with AWS. I guess what I would say guys, and I'll I'll leave you with this is that, you know, just like all players today are cloud players, I feel like anybody in the business or most companies are going to be so-called supercloud players. In other words, they're going to have a cross-cloud strategy, they're going to try to build connections if they're coming from on-prem like a Dell or an HPE, you know, or Pure or you know, many of these other companies, Cohesity is another one. They're going to try to connect to their on-premise states, of course, and create a consistent experience. It's natural that they're going to have sort of some consistency across clouds. You know, the big question is, what's that spectrum look like? I think on the one hand you're going to have some, you know, maybe some rudimentary, you know, instances of supercloud or maybe they just run on the individual clouds versus where Snowflake and others and even beyond that are trying to go with a single global instance, basically building out what I would think of as their own cloud, and importantly their own ecosystem. I'll give you guys the last thought. Maybe you could each give us, you know, closing thoughts. Maybe Darren, you could start and Erik, you could bring us home on just this entire topic, the future of cloud and data. >> Yeah, I mean I think, you know, two points to make on that is, this question of these, I guess what we'll call legacy on-prem players. These, mega vendors that have been around a long time, have big on-prem footprints and a lot of people have them for that reason. I think it's foolish to assume that a company, especially a large, mature, multinational company that's been around a long time, it's foolish to think that they can just uproot and leave on-premises entirely full scale. There will almost always be an on-prem footprint from any company that was not, you know, natively born in the cloud after 2010, right? I just don't think that's reasonable anytime soon. I think there's some industries that need on-prem, things like, you know, industrial manufacturing and so on. So I don't think on-prem is going away, and I think vendors that are going to, you know, go very cloud forward, very big on the cloud, if they neglect having at least decent connectors to on-prem legacy vendors, they're going to miss out. So I think that's something that these players need to keep in mind is that they continue to reach back to some of these players that have big footprints on-prem, and make sure that those integrations are seamless and work well, or else their customers will always have a multi-cloud or hybrid experience. And then I think a second point here about the future is, you know, we talk about the three big, you know, cloud providers, the Google, Microsoft, AWS as sort of the opposite of, or different from this new supercloud paradigm that's emerging. But I want to kind of point out that, they will always try to make a play to become that and I think, you know, we'll certainly see someone like Microsoft trying to expand their licensing and expand how they play in order to become that super cloud provider for folks. So also don't want to downplay them. I think you're going to see those three big players continue to move, and take over what players like CloudFlare are doing and try to, you know, cut them off before they get too big. So, keep an eye on them as well. >> Great points, I mean, I think you're right, the first point, if you're Dell, HPE, Cisco, IBM, your strategy should be to make your on-premise state as cloud-like as possible and you know, make those differences as minimal as possible. And you know, if you're a customer, then the business case is going to be low for you to move off of that. And I think you're right. I think the cloud guys, if this is a real problem, the cloud guys are going to play in there, and they're going to make some money at it. Erik, bring us home please. >> Yeah, I'm going to revert back to our data and this on the macro side. So to kind of support this concept of a supercloud right now, you know Dave, you and I know, we check overall spending and what we're seeing right now is total year spent is expected to only be 4.6%. We ended 2022 at 5% even though it began at almost eight and a half. So this is clearly declining and in that environment, we're seeing the top two strategies to reduce spend are actually vendor consolidation with 36% of our respondents saying they're actively seeking a way to reduce their number of vendors, and consolidate into one. That's obviously supporting a supercloud type of play. Number two is reducing excess cloud resources. So when I look at both of those combined, with a drop in the overall spending reduction, I think you're on the right thread here, Dave. You know, the overall macro view that we're seeing in the data supports this happening. And if I can real quick, couple of names we did not touch on that I do think deserve to be in this conversation, one is HashiCorp. HashiCorp is the number one player in our infrastructure sector, with a 56% net score. It does multiple things within infrastructure and it is completely agnostic to your environment. And if we're also speaking about something that's just a singular feature, we would look at Rubric for data, backup, storage, recovery. They're not going to offer you your full cloud or your networking of course, but if you are looking for your backup, recovery, and storage Rubric, also number one in that sector with a 53% net score. Two other names that deserve to be in this conversation as we watch it move and evolve. >> Great, thank you for bringing that up. Yeah, we had both of those guys in the chart and I failed to focus in on HashiCorp. And clearly a Supercloud enabler. All right guys, we got to go. Thank you so much for joining us, appreciate it. Let's keep this conversation going. >> Always enjoy talking to you Dave, thanks. >> Yeah, thanks for having us. >> All right, keep it right there for more content from Supercloud 2. This is Dave Valente for John Ferg and the entire Cube team. We'll be right back. (gentle synth music) (music fades)

(upbeat music) >> Hey, guys and girls, welcome back to New York City. Lisa Martin and John Furrier are live with theCUBE at AWS Summit 22, here in The Big Apple. We're excited to be talking about security next. James Arlen joins us, the CISO at Aiven. James, thanks so much for joining us on theCUBE today. >> Absolutely, it's good to be here. >> Tell the audience a little bit about Aiven, what you guys do, what you deliver, and what some of those differentiators are. >> Oh, Aiven. Aiven is a fantastic organization. I'm actually really lucky to work there. It's a database as a service, managed databases, all open source. And we're capital S, serious about open source. So 10 different open source database products delivered as a platform, all managed services, and the game is really about being the most performant, secure, and compliant database as a service on the market, friction free for your developers. You don't need people worrying about how to run databases. You just want to be able to say, here, take care of my data for me. And that's what we do. And that's actually the differentiator. We just take care of it for you. >> Take care of it for you, I like that. >> So they download the open source. They could do it on their own. So all the different projects are out there. >> Yeah, absolutely. >> What do you guys bringing to the table? You said the managed service, can you explain that. >> Yeah, the managed service aspect of it is, really, you could install the software yourself. You can use Postgres or Apache Kafka or any one of the products that we support. Absolutely you can do it yourself. But is that really what you do for a living, or do you develop software, or do you sell a product? So we take and do the hard work of running the systems, running the equipment. We take care of backups, high availability, all the security and compliance things around access and certifications, all of those things that are logging, all of that stuff that's actually difficult to do, well and consistently, that's all we do. >> Talk about the momentum, I see you guys were founded in what? 2016? >> Yes. >> Just in May of '22, raised $210 million in series D funding. >> Yes. >> Talk about the momentum and also from your perspective, all of the massive changes in security. >> It's very interesting to work for a company where you're building more than 100% growth year over year. It's a powers of two thing. Going from one to two, not so scary, two to four, not so scary. 512 to 1024, it's getting scary. (Lisa chuckles) 1024 to 2048, oh crap! I've been with Aiven for just almost two years now, and we are less than 70 when I started, and we're near 500 now. So, explosive growth is very interesting, but it's also that, you're growing within a reasonable burn rate boundary as well. And what that does from a security perspective, is it leaves you in the position that I had. I walked in and I was the first actual CISO. I had a team of four, I now have a team of 40. Because it turns out that like a lot of things in life, as you start unpacking problems, they're kind of fractal. You unpack the problem, you're like oh, well I did deal with that problem, but now I got another problem that I got to deal with. And so there's, it's not turtles all the way down. >> There's a lot of things going on and other authors, survive change. >> And there's fundamental problems that are still not fixed. And yet we treat them like they're fixed. And so we're doing a lot of hard work to make it so that we don't have to do hard work ongoing. >> And that's the value of the managed service. >> Yes. >> Okay, so talk about competition. Obviously, we had ETR on which is Enterprise Research Firm that we trust, we like. And we were looking at the data with the headwinds in the market, looking at the different players like got Amazon has Redshift, Snowflake, and you got Azure Sequence. I think it's called one of those products. The money that's being shifted from on premise data where the old school data warehouse like terra data and whatnot, is going first to Snowflake, then to Azure, then to AWS. Yes, so that points to snowflake being kind of like the bell of the ball if you will, in terms of from a data cloud. >> Absolutely. >> How do you compete with them? What's the pitch 'Cause that seemed to be a knee-jerk reaction from the industry. 'Cause snowflake is hot. They have a good value product. They have a smart team, Databrick is out there too. >> Yeah I mean... >> how do you guys compete against all that. >> So this is that point where you're balancing the value of a specific technology, or a specific technology vendor. And am I going to be stuck with them? So I'm tying my future to their future. With open source, I'm tying my future to the common good right. The internet runs on open source. It doesn't run on anything closed. And so I'm not hitching my wagon to something that I don't control. I'm hitching it to something where, any one of our customers could decide. I'm not getting the value I need from Aiven anymore. I need to go. And we provide you with the tools necessary, to move from our open source managed service to your own. Whether you go on-prem or you run it yourself, on a cloud service provider, move your data to you because it's your data. It's not ours. How can I hold your data? It's like weird extortion ransoming thing. >> Actually speaking, I mean enterprise, it's a big land grab 'cause with cloud you're horizontally scalable. It's a beautiful thing, open source is booming. It's going in Aiven, every day it's just escalating higher and higher. >> Absolutely. >> It is the software business. So open is open. Integration and scale seems to be the competitive advantage. >> Yeah. >> Right. So, how do you guys compete with that? Because now you got open source. How do you offer the same benefits without the lock in, or what's the switching costs? How do you guys maintain that position of not saying the same thing in Snowflake? >> Because all of the biggest data users and consumers tend to give away their data products. LinkedIn gave away their data product. Uber gave away their data product, Facebook gave away their data product. And we now use those as community solutions. So, if the product works for something the scale of LinkedIn, or something the scale of Uber. It will probably work for you too. And scale is just... >> Well Facebook and LinkedIn, they gave away the product to own the data to use against you. >> But it's the product that counts because you need to be able to manipulate data the way they manipulate data, but with yours. >> So low latency needs to work. So horizontally, scalable, fees, machine learning. That's what we're seeing. How do you make that available? Customers want on architecture? What do you recommend? Control plane, data plane, how do you think about that? >> It's interesting. There's architectural reasons to think about it in terms like that. And there's other good architectural reasons to not think about it. There's sort of this dividing line in the cloud, where your cloud service provider, takes over and provides you with the opportunity to say, I don't know. And I don't care >> As long as it's secure >> As long as it's secure absolutely. But there's sort of that water line idea, where if it's below the water line, let somebody else deal. >> What is in the table stakes? 'Cause I like that approach. I think that's a good value proposition. Store it, what boxes have to be checked? Compliance, secure, what are some of the boxes? >> You need to make sure that you've taken care of all of the same basics if you are still running it. Remember you can't absolve yourself of your duty to your customer. You're still on the hook. So, you have to have backups. You have to have access control. You have to understand who's administering it, and how and what they're doing. Good logging, good comprehension there. You have to have anomaly detection, secure operations. You have to have all those compliance check boxes. Especially if you're dealing with regulated data type like PCI data or HIPAA health data or you know what there's other countries besides the United States, there's other kinds of of compliance obligations there. So you have to make sure that you've got all that taken into account. And remember that, like I said, you can't absolve yourself with those things. You can share responsibilities. But you can't walk away from that responsibility. So you still have to make sure that you validate that your vendor knows what they're talking about. >> I wanted to ask you about the cybersecurity skills gap. So I'm kind of giving a little segue here, because you mentioned you've been with Aiven for about two years. >> Almost. >> Almost two years. You've started with a team of four. You've grown at 10X in less than two years. How have you accomplished that, considering we're seeing one of the biggest skills shortages in cyber in history. >> It's amazing, you see this show up in a lot of job Ads, where they ask for 10 years of experience in something that's existed for three years. (John Furrier laughs) And it's like okay, well if I just be logical about this I can hire somebody at less than the skill level that I need today, and bring them up to that skill level. Or I can spend the same amount of time, hoping that I'll find the magical person that has that set of skills that I need. So I can solve the problem of the skills gap by up-skilling the people that I hire. Which is strangely contrary to how this thing works. >> The other thing too, is the market's evolving so fast that, that carry up and pulling someone along, or building and growing your own so to speak is workable. >> It also really helps us with a bunch of sustainability goals. It really helps with anything that has to do with diversity and inclusion, because I can bring forward people who are never given a chance. And say, you know what? You don't have that magical ticket in life, but damn you know what you're talking about? >> It's a classic pedigree. I went to this school, I studied this degree. There's no degree if have to stop a hacker using state of the art malware. (John Furrier laughs) >> Exactly. What I do today as a job, didn't exist when I was in post-secondary at all. >> So when you hire, what do you look for? I mean obviously problem solving. What's your kind of algorithm for hiring? >> Oh, that's a really interesting question. The quickest sort of summary of it is, I'm looking for not a jerk. >> Not a jerk. >> Yeah. >> Okay. >> Because it turns out that the quality that I can't fix in a candidate, is I can't fix whether or not they're a jerk, but I can up-skill them, I can educate them. I can teach them of a part of the world that they've not had any interaction with. But if they're not going to work with the team, if they're going to be, look at me, look at me. If they're going to not have that moment of, I have this great job, and I get to work today. And that's awesome. (Lisa Martin laughs) That's what I'm trying to hire for. >> The essence of this teamwork is fundamental. >> Collaboration. >> Cooperation. >> Curiosity. >> That's the thing yeah, absolutely. >> And everybody? >> Those things, oh absolutely. Those things are really, really hard to interview for. And they're impossible to fix after the fact. So that's where you really want to put the effort. 'Cause I can teach you how to use a computer. I mean it's hard, but it's not that hard. >> Yeah, yeah, yeah. >> Well I love the current state of data management. Good overview, you guys are in the good position. We love open source. Been covering it for, since theCUBE started. It continues to redefine more and more the industry. It is the software industry. Now there's no debate about that. If people want to have that debate, that's kind of waste of time, but there are other ways that are happening. So I have to ask you. As things are going forward with innovation. Okay, if opensource is going to be the software industry. Where's the value? >> That's a fun question wow? >> Is it going to be in the community? Is it the integration? Is it the scale? If you're open and you have low switching costs... >> Yeah so, when you look at Aiven's commitment to open source, a huge part of that is our open source project office, where we contribute back to those core products, whether it's parts of the Apache Foundation, or Postgres, or whatever. We contribute to those, because we have staff who work on those products. They don't work on our stuff. They work on those. And it's like the opposite of a zero sum game. It's more like Nash equilibrium. If you ever watch that movie, "A beautiful mind." That great idea of, you don't have to have winners and losers. You can have everybody loses a little bit but everybody wins a little bit. >> Yeah and that's the open the ethos. >> And that's where it gets tied up. >> Another follow up on that. The other thing I want to get your reaction on is that, now in this modern era of open source, almost all corporations are part of projects. I mean if you're an entrepreneur and you want to get funding it's pretty simple. You start open source project. How many stars you get on GitHub guarantees it's a series C round, pretty much. So open source now has got this new thing going on, where it's not just open source folks who believe in it It's an operating model. What's the dynamic of corporations being part of the system. It used to be, oh what's the balance between corporate and influence, now it's standard. What's your reaction? >> They can do good and they can do harm. And it really comes down to why are you in it? So if you look at the example of open search, which is one of the data products that we operate in the Aiven system. That's a collaboration between Aiven. Hey we're an awesome company, but we're nowhere near the size of AWS. And AWS where we're working together on it. And I just had this conversation with one of the attendees here, where he said, "Well AWS is going to eat your story there. "You're contributing all of this "to the open search platform. "And then AWS is going to go and sell it "and they're going to make more money." And I'm like yep, they are. And I've got staff who work for the organization, who are more fulfilled because they got to deliver something that's used by millions of people. And you think about your jobs. That moment of, (sighs) I did a cool thing today. That's got a lot of value in it. >> And part of something. >> Exactly. >> As a group. >> 100%. >> Exactly. >> And we end up with a product that's used by millions. Some of it we'll capture, because we do a better job running than the AWS does, but everybody ends up winning out of the backend. Again, everybody lost a little, but everybody also won. And that's better than that whole, you have to lose so that I can win. At zero something, that doesn't work. >> I think the silo conversations are coming, what's the balance between siloing something and why that happens. And then what's going to be freely accessible for data. Because the real time information is based upon what you can access. "Hey Siri, what's the weather. "We had a guest on earlier." It says, oh that's a data query. Well, if the weather is, the data weathers stored in a database that's out here and it can't get to the response on the app. Yeah, that's not good, but the data is available. It just didn't get delivered. >> Yeah >> Exactly. >> This is an example of what people are realizing now the consequences of this data, collateral damage or economy value. >> Yeah, and it's understanding how data fits in your environment. And I don't want to get on the accountants too hard, but the accounting organizations, AICPA and ISAE and others, they haven't really done a good job of helping you understand data as an asset, or data as a liability. I hold a lot of customer data. That's a liability to me. It's going to blow up in my face. We don't talk about the income that we get from data, Google. We don't talk about the expense of regenerating that data. We talk about, well what happens if you lose it? I don't know. And we're circling the drain around fiduciary responsibility, and we know how to do this. If you own a manufacturing plant, or if you own a fleet of vehicles you understand the fiduciary duty of managing your asset. But because we can't touch it, we don't do a good job of it. >> How far do you think are people getting into the point where they actually see that asset? Because I think it's out of sight out of mind. Now there's consequences, there's now it's public companies might have to do filings. It's not like sustainability and data. Like, wait a minute, I got to deal with these things. >> It's interesting, we got this great benefit of the move to cloud computing, and the move to utility style computing. But we took away that. I got to walk around and pet my computers. Like oh! This is my good database. I'm very proud of you. Like we're missing that piece now. And when you think about the size of data centers, we become detached from that, you don't really think about, Aiven operates tens of thousands of machines. It would take entire buildings to hold them all. You don't think about it. So how do you recreate that visceral connection to your data? Well, you need to start actually thinking about it. And you need to do some of that tokenization. When was the last time you printed something out, like you get a report and happens to me all the time with security reports. Look at a security report and it's like 150 page PDF. Scroll, scroll, scroll, scroll. Print it out, stump it on the table in front of you. Oh, there's gravitas here. There's something here. Start thinking about those records, count them up, and then try to compare that to something in the real world. My wife is a school teacher, kindergarten to grade three, and tokenizing math is how they teach math to little kids. You want to count something? Here's 10 things, count them. Well, you've got 60,000 customer records, or you have 2 billion data points in your IOT database, tokenize that, what does 2 billion look like? What does $1 million look like in the form of $100 dollars bills on a pallet? >> Wow. >> Right. Tokenize that data, create that visceral connection with it, and then talk about it. >> So when you say tokenized, you mean like token as in decentralization token? >> No, I mean create like a totem or an icon of it. >> Okay, got it. >> A thing you can hold holy. If you're a token company. >> Not token as in Token economics and Crypto. >> If you're a mortgage company, take that customer record for one of your customers, print it out and hold the file. Like in a Manila folder, like it's 1963. Hold that file, and then say yes. And you're explaining to somebody and say yes, and we have 3 million of these. If we printed them all out, it would take up a room this size. >> It shows the scale. >> Right. >> Right. >> Exactly, create that connection back to the human level of interaction with data. How do you interact with a terabyte of data, but you do. >> Right. >> But once she hits upgrade from Google drive. (team laughs) >> What's a terabyte right? We don't hold that anymore. >> Right, right. >> Great conversation. >> Recreate that connection. Talk about data that way. >> The visceral connection with data. >> Follow up after this event. We'd love to dig more and love the approach. Love open source, love what you're doing there. That's a very unique approach. And it's also an alternative to some of the other vast growing plus your valuations are very high too. So you're not like a... You're not too far away from these big valuations. So congratulations. >> Absolutely. >> Yeah excellent, I'm sure there's lots of work to do, lots of strategic work to do with that round of funding. But also lots of opportunity, that it's going to open up, and we know you don't hire jerks. >> I don't >> You have a whole team of non jerks. That's pretty awesome. Especially 40 of 'em. That's impressive James.| >> It is. >> Congratulations to you on what you've accomplished in the course of the team. And thank you for sharing your insights with John and me today, we appreciate it. >> Awesome. >> Thanks very much, it's been great. >> Awesome, for John furrier, I'm Lisa Martin and you're watching theCube, live in New York city at AWS Summit NYC 22, John and I will be right back with our next segment, stick around. (upbeat music)

>>Hey everyone. Welcome back to the queue of Lisa Martin with Dave Valante and we're live in Vegas. This is snowflake summit, 22, their fourth annual event. A lot of people here, a lot of news, a lot to unpack so far, and this is only day, day one. We've got two guests here with us to talk about, uh, cyber security, a very important topic, please welcome Omar singer the head of cyber security strategy at snowflake and Julie Chilo VP of security at Guild education. Welcome. Thank >>You. Thank you >>For having all of >>Our favorite topics. Yeah. Oh >>One. It's not boring. >>You know this much and you have so much more to learn now. So here >>We go. Cybersecurity is, is not to say it's boring. Not boring is an understatement. Yeah. Omar, I wanna start with you so much news coming out today. Talk to us about what's new with cybersecurity. Workload is snowflakes. Flywheel of innovation just seems to be getting bigger and faster. >>Yeah. Yeah. Well, well, I'll tell you it's been a long road to get to where we are today. Um, my initial role at snowflake was to lead security engineering. So I've actually been using snowflake as the home for security data, basically from day one. And we saw that it worked, it worked really well. And we started hearing from customers that they were dealing with some of the same challenges that we faced as an internal security team. And we decided as snowflake that we wanna bring the benefits of the data cloud to cyber security teams at all of our customers. And that's what the workload is all about. >>Talk to us about the, the voice of the customer. Obviously we saw a lot of customer stories heard your customer. We're gonna be talking about Guild education in a minute, but in the voice of the customer, in terms of being influential, obviously you were an internal customer drinking that champagne like this tastes really good. This is better of the Flaco <laugh>, but how is the voice of the customer influential in terms of the, the cybersecurity workload, as we've seen the threat landscape change so much in the last two years alone? >>Sure, sure. And you know, security, it's a really hard problem. We like to think of it as a data problem. And when you start thinking about it, that way snowflake is re very relevant for it. But many security teams don't yet think about their challenge as a data challenge. And so they're struggling with a very fragmented data landscape. The facts are all over the place and they're not able to ask the kind of questions that they need to understand. Where are my risks? How are the bad guys gonna try to get into my network? And they can't reflect that to leadership to everybody that really cares about cyber security. This is a board level concern today without the unified data and without the analytics. Um, they really can't do any of that. And, and yeah, representing the customer is, is a big part of what I do. And we have great customers like, like Julie, who's been kind of with us on this journey. She's, she's a part of the movement. I mean, Julie, what, what has it been like, uh, for, for you? >>Oh, it's been, uh, it's been game changer for, for Guild for sure. When we first, uh, started, I didn't one, I didn't know this was a concept <laugh> so when I first started talking O me and, um, snowflake, uh, I had just heard through the grapevine that, that you could do, like, this was a thing you could use the data, you could get everything you needed in one place. And, um, it's been game changing for my team. Uh, we, we were in many different security tools. They were all isolated, siloed, and we're now able to move everything into one, uh, one area, uh, and get we're getting close to the one pane of glass, which I, um, I just heard was a mythical concept for >>Security for >>A long time. Yeah. For a long time. Um, so it's, uh, it's just been amazing and it's, uh, brought us closer to our data ops team. So I'm here this week, uh, with somebody from data ops, actually, that's awesome to help us out. >>So can you describe that further? I'm I'm, I'm, I'm amazed and skeptical the, the, the I'm imagining, you know, the Optiv chart that says eight, 8 million security tools on there, are you actually able, uh, describe how you're able to consolidate your tooling? >>So, one of, one of the biggest problem, one of the biggest problems we were facing initially was our SIM, um, the security incident and event management tool could not take anything from our DevSecOps tools. And so any security that we had in a developer pipeline was really isolated to that tool, and we could never get it into a SIM Sims just aren't meant they're not built to handle that they're built to handle, um, not, not really old school networks and, and data center traffic and everything I have is in the cloud. And so we were really, I, everything was isolated. So with snowflake, what we do is we, um, worked with our data ops team. We can move things from, um, like our, our scanning tools for, for the developer pipelines into snowflake. We can use then correlate different things such as, from like eight year ADP. Like if a, do you have somebody pushing code to production who's out on vacation, you can actually do that correlation with snowflake that was never available before. These are things we could never do before. And we're able to, um, just do correlations. You could not get in that you cannot get in a SIM. >>Why couldn't I just throw those into any old, you know, run of the mill cloud data warehouse? >>Well, you know, it's not just the scale, it's the complexity of the data. I think snowflake how we have the, the sche on read and then all of the kind of things that make snowflake really good for other departments turns out, works really well for security. And it's the ecosystem too. Nobody else has this ecosystem approach. You know, you heard on the keynote today that snowflake is the, this disrupting, um, the, the software application development, right? All, all that kind of focus. The tool consolidation doesn't need to mean that you only have one tool you can actually have best of breed, choose the tool you want. As long as the data's consolidated, you're not building more silos. And that's what our partners are doing. They're separating the application from the data. They're bringing the work to the data, and that's what you hear here. So Julie's team can still choose to use a variety of tools that get the job done, but all those tools are working off of the single source of truth. And that, that is unique to what snowflake >>Can enable. So we, we are Reiss. Uh, we should have asked you about Guild education, explain your, your, your organization. >>Oh, what does Guild do? Uh, so we're a late stage startup. Uh, we manage education as a benefit for, for large companies. So we, we house data from very large organizations with like their workforce and, and help students help, help their workforce go back to school. >>Okay. So unpacking some of the things you said, schema on Reed, but not necessarily no schema on, right. It's a little different, right. Because you're ingesting. Yeah. And then you're determining the scheme on read that's right. Right. Okay. So that makes it simple and fast for zoom, but you get data in and then you figure it out, bringing work to data. Can we just double click on that a little bit? Cuz I think when I think about that, we've heard terms like over the years bring compute to the data. That's what Hadoop was supposed to do. And it didn't, you know, it was like, everything was mm-hmm <affirmative> shoved. So what do you mean by that? How, how, what, what actually does that >>Mean? Yeah. So if you think about the traditional SAS solution, the vendor needed to invest in a data center and to have a data platform that would be scalable and robust because their service dependent on it and they couldn't trust that the customer would have that kind of data platform on the customer's side. What Snowflake's data cloud has done has democratized the data platform. So now you have startups to fortune 500 S the vendors, the customers, they're all uneven footing when it comes to the data platform. So now the vendors can say, bring your own snowflake. Why not? You know, and they can focus on building the best application to solve the real challenges that security teams have. But by the way, not only cybersecurity, we see this and for example, the, um, customer data space as well. So we're seeing more and more kind of SaaS industries seeing this approach and the applications are gonna come yeah. To the data platform of choice, uh, for the practitioner. >>Julie, can we talk about some of the outcomes that Guild education has achieved so far by working with this solution in terms of, we look at the threat landscape and how it's changed so much the last couple of years and how it's a matter of if, or sorry, when not, if I get hit with an attack, how, what are some of the key outcomes that a snowflake partnership and technology has enabled you to achieve? >>So the, the biggest one, again, it's around the Def sec ops program, um, where you see so many attacks these days happening in the code base. So you really have to be careful with your, your pipeline where the code's getting moved through, who has access, who can move code into production. Um, and these are so the, like if you're using GitHub or, um, like using a scanning tool called snake, they're, they're separate, like they're completely separate the only way that we can see who's moving code into production, or if there was a vulnerability or somebody turned off, the security tool is to move these logs, this data into snowflake, uh, and our engineering teams were already using snowflake. Uh, so that made it, that was an easy transition for us. I didn't have to go out and convince another team to support us somewhere else, but a great example where we were, we're seeing great, um, savings, not only in people time, but, but for security, um, we were having problems or the security or the <laugh>, the engineers were turning off our secure codes scanner. >>And we didn't find out until a little bit later. Uh, oh yeah. Yeah. So found out we, my team, we had a team, we spent about 160 hours going through a thousand pole requests manually. And I said, no, no more go find the go figure out where this data exists. We put it in a snowflake and we can create an automatic, uh, ping to the security team saying, Hey, they turned off the, the scanner, go check and see what, why did the scanner get turned off? So it's an immediate response from my team instead of finding out two months later. And this is just, isn't something you can do right now. That's you can't set it up. So, um, makes it so easy. Ping goes to slack. We can go to the, immediately to the engineering team and say, why did you >>Using using automation? >>Yeah. Did you, did you turn this off? Why did you turn it off? Get an exception in so one, it like helps with compliance, so we're not messing up our SOC two audit. Uh, and then two, from a security perspective, we are able to, to trust, but verify, um, which is a big part of the DevSecOps landscape, where they need code to move into production. They need a scan to run in under five minutes. My team can't be there to scan, you know, 10, like 10 times a day or a hundred times a day. So we have to automate all of that and then just get information as it comes in. >>Is it accurate to say that, um, you're not like shutting off your tools, you're just taking advantage of them and compressing the time to get value out of them or are you actually reducing the tool sets? >>No, we don't. Well, no, we, our goal wasn't to reduce the tool set. I mean, we did actually get rid of the SIM we were using. Uh, so we were partnering with one of, um, uh, snowflakes partners, um, >>Because yeah, but you still have a SIM, >>We still have it. It's just minimized what goes to the SIM, because most of what I care about, isn't actually going to a SIM. Yeah. It's all the other pieces that are in a cloud because we use all like, we're, we're a hundred percent in the cloud. I don't have servers, I don't have firewalls. We don't have routes routers or switches. So all the things I care about live in a cloud somewhere. And, and I want that information. And so a lot of times, um, especially when it comes to the engineering tools, they were already sending the information to snowflake or they're also interested. And so we're partnering like it's, we're doubling up on the use of the >>Data. Okay. And you couldn't get that outta your SIM. Maybe you're asking your SIM to do too much, or it just didn't deliver. >>No systems are built on search engines. You know, they don't, >>They, they can't do it. >>You kind of knew what you were looking for and you say, Hey, where did I see this? Where did I see that? Very different from data analytics and the kinds of question that security teams really want to ask. These are emergent properties. You need context, you need sequel, you need Python. That's how you ask the questions that security teams really want to ask the legacy Sims. They don't let you ask that kind of question. They weren't built with that in mind. And they're so expensive that by moving off of them, to this approach, you kind of pay for all these other solutions that, that then you can bring on. >>That seems to make the, what you just said. There was brilliant. It seems to make the customer conversation quite easy if they're saying, well, why should I replace my SIM? It's doing just fine. You just nailed it with, with what you said there. >>So, yeah. And we're, and we're seeing that happen extensively. And I'm excited that we have customers here at summit talking about their experience, moving off of a legacy SIM where the security team was off to the side, away from the rest of the company to a unified approach, the SIM and the other security solutions working on top of the snowflake and a collaboration between security and the data >>Team. So what does your security ecosystem look like? You've got SIM partners. Do you have identity access partners, endpoint partner. Absolutely. >>Describe that compliance automation ass. Yeah. We hear about companies really struggling to meet all the compliance requirements. Well, if all the data's already centralized, then I can kind of prove to my auditors and not just once a quarter, but once a day, I can make sure that all the environment is in compliance with whatever standard I have. So we see a lot of that cloud security is another big one because there's just 10 times more things happening in the cloud environment than in the data center. Everything is so heavily instrumented. And so we see cloud security solutions as significant as well. And the identity space, the list goes on and on. We do see the future being the entire security program uses connected applications with a single source of truth in the company's snowflake. And >>Would you say centralized, you, you it's logically centralized, right? I mean, it's virtually centralized, right? It's not, >>Well, that's >>Not shoved into one container, right? >>I mean, it's right. Well, that's the beauty of the data cloud, right? We, everybody that's on the data cloud is able to collaborate. And so whether it's in the same account or table or database, you know, that's really besides the point because all of the platform investments that snowflake is making on cross region, cross cloud collaboration means that once it's in snowflake, then it is unified and can be used together. But >>I think people misunderstand that sometimes. And BEWA made this point, uh, as the Christian about the global nature of, of snowflake and it's globally distributed, but it's logically a data cloud. >>Yeah. I like to call it one big database in the sky. You know, that's how I explain to security teams that are kind of new to the concept, but >>It's not, it's could be a lot of little databases, but it, but having the same framework, the same governance structure, the same security >>You're right. I think that's how it's achieved is what you're describing. You know, I think from the outcome, what the security team needs to know is that when there's some breach hitting the headline and they need to go to their leadership and say, I can assure you, we were not affected. They can be confident in that answer because they have access to the data, wherever it is in the world, they have access to ask you the questions they need to ask. >>And that confidence is critical. These days as that threat landscape just continues to change. Thank you both so much for joining us. Thank you. Talking about from a cyber security perspective, some of the things that are new, new at snowflake, what you guys are doing at Guild education and how you're really transforming the organization with the data cloud, we appreciate your insights. Thank you for having us. Thank you. Thanks you guys for our guests and Dave ante. I'm Lisa Martin. You're watching the queue live from Las Vegas on the show floor of snowflake summit 22. We'll be right back with our next guest.

(bright music) >> Okay, we're back in theCUBE. We said we were signing off for the night, but during the hallway track, we ran into old friend Stu Miniman who was the Director of Market Insights at Red Hat. Stu, friend of theCUBE done the thousands of CUBE interviews. >> Dave, it's great to be here. Thanks for pulling me on, you and I hosted Red Hat Summit before. It's great to see Paul here. I was actually, I was talking to some of the Red Hatters walking around Boston. It's great to have an event here. Boston's got strong presence and I understand, I think was either first or second year, they had it over... What's the building they're tearing down right down the road here. Was that the World Trade Center? I think that's where they actually held it, the first time they were here. We hosted theCUBE >> So they moved up. >> at the Hines Convention Center. We did theCUBE for summit at the BCEC next door. And of course, with the pandemic being what it was, we're a little smaller, nice intimate event here. It's great to be able to room the hall, see a whole bunch of people and lots watching online. >> It's great, it's around the same size as those, remember those Vertica Big Data events that we used to have here. And I like that you were commenting out at the theater and the around this morning for the keynotes, that was good. And the keynotes being compressed, I think, is real value for the attendees, you know? 'Cause people come to these events, they want to see each other, you know? They want to... It's like the band getting back together. And so when you're stuck in the keynote room, it's like, "Oh, it's okay, it's time to go." >> I don't know that any of us used to sitting at home where I could just click to another tab or pause it or run for, do something for the family, or a quick bio break. It's the three-hour keynote I hope has been retired. >> But it's an interesting point though, that the virtual event really is driving the physical and this, the way Red Hat marketed this event was very much around the virtual attendee. Physical was almost an afterthought, so. >> Right, this is an invite only for in-person. So you're absolutely right. It's optimizing the things that are being streamed, the online audience is the big audience. And we just happy to be in here to clap and do some things see around what you're doing. >> Wonderful see that becoming the norm. >> I think like virtual Stu, you know this well when virtual first came in, nobody had a clue with what they were doing. It was really hard. They tried different things, they tried to take the physical and just jam it into the virtual. That didn't work, they tried doing fun things. They would bring in a famous person or a comedian. And that kind of worked, I guess, but everybody showed up for that and then left. And I think they're trying to figure it out what this hybrid thing is. I've seen it both ways. I've seen situations like this, where they're really sensitive to the virtual. I've seen others where that's the FOMO of the physical, people want physical. So, yeah, I think it depends. I mean, reinvent last year was heavy physical. >> Yeah, with 15,000 people there. >> Pretty long keynotes, you know? So maybe Amazon can get away with it, but I think most companies aren't going to be able to. So what is the market telling you? What are these insights? >> So Dave just talking about Amazon, obviously, the world I live in cloud and that discussion of cloud, the journey that customers are going on is where we're spending a lot of the discussions. So, it was great to hear in the keynote, talked about our deep partnerships with the cloud providers and what we're doing to help people with, you like to call it super cloud, some call it hybrid, or multi-cloud... >> New name. (crosstalk) Meta-Cloud, come on. >> All right, you know if Che's my executive, so it's wonderful. >> Love it. >> But we'll see, if I could put on my VR Goggles and that will help me move things. But I love like the partnership announcement with General Motors today because not every company has the needs of software driven electric vehicles all over the place. But the technology that we build for them actually has ramifications everywhere. We've working to take Kubernetes and make it smaller over time. So things that we do at the edge benefit the cloud, benefit what we do in the data center, it's that advancement of science and technology just lifts all boats. >> So what's your take on all this? The EV and software on wheels. I mean, Tesla obviously has a huge lead. It's kind of like the Amazon of vehicles, right? It's sort of inspired a whole new wave of innovation. Now you've got every automobile manufacturer kind of go and after. That is the future of vehicles is something you followed or something you have an opinion on Stu? >> Absolutely. It's driving innovation in some ways, the way the DOS drove innovation on the desktop, if you remember the 64K DOS limit, for years, that was... The software developers came up with some amazing ways to work within that 64K limit. Then when it was gone, we got bloatware, but it actually does enforce a level of discipline on you to try to figure out how to make software run better, run more efficiently. And that has upstream impacts on the enterprise products. >> Well, right. So following your analogy, you talk about the enablement to the desktop, Linux was a huge influence on allowing the individual person to write code and write software, and what's happening in the EV, it's software platform. All of these innovations that we're seeing across industries, it's how is software transforming things. We go back to the mark end reasons, software's eating the world, open source is the way that software is developed. Who's at the intersection of all those? We think we have a nice part to play in that. I loved tha- Dave, I don't know if you caught at the end of the keynote, Matt Hicks basically said, "Our mission isn't just to write enterprise software. "Our mission is based off of open source because open source unlocks innovation for the world." And that's one of the things that drew me to Red Hat, it's not just tech in good places, but allowing underrepresented, different countries to participate in what's happening with software. And we can all move that ball forward. >> Well, can we declare victory for open source because it's not just open source products, but everything that's developed today, whether proprietary or open has open source in it. >> Paul, I agree. Open source is the development model period, today. Are there some places that there's proprietary? Absolutely. But I had a discussion with Deepak Singh who's been on theCUBE many times. He said like, our default is, we start with open source code. I mean, even Amazon when you start talking about that. >> I said this, the $70 billion business on open source. >> Exactly. >> Necessarily give it back, but that say, Hey, this is... All's fair in tech and more. >> It is interesting how the managed service model has sort of rescued open source, open source companies, that were trying to do the Red Hat model. No one's ever really successfully duplicated the Red Hat model. A lot of companies were floundering and failing. And then the managed service option came along. And so now they're all cloud service providers. >> So the only thing I'd say is that there are some other peers we have in the industry that are built off open source they're doing okay. The recent example, GitLab and Hashicorp, both went public. Hashi is doing some managed services, but it's not the majority of their product. Look at a company like Mongo, they've heavily pivoted toward the managed service. It is where we see the largest growth in our area. The products that we have again with Amazon, with Microsoft, huge growth, lots of interest. It's one of the things I spend most of my time talking on. >> I think Databricks is another interesting example 'cause Cloudera was the now company and they had the sort of open core, and then they had the proprietary piece, and they've obviously didn't work. Databricks when they developed Spark out of Berkeley, everybody thought they were going to do kind of a similar model. Instead, they went for all in managed services. And it's really worked well, I think they were ahead of that curve and you're seeing it now is it's what customers want. >> Well, I mean, Dave, you cover the database market pretty heavily. How many different open source database options are there today? And that's one of the things we're solving. When you look at what is Red Hat doing in the cloud? Okay, I've got lots of databases. Well, we have something called, it's Red Hat Open Database Access, which is from a developer, I don't want to have to think about, I've got six different databases, which one, where's the repository? How does all that happen? We give that consistency, it's tied into OpenShift, so it can help abstract some of those pieces. we've got same Kafka streaming and we've got APIs. So it's frameworks and enablers to help bridge that gap between the complexity that's out there, in the cloud and for the developer tool chain. >> That's really important role you guys play though because you had this proliferation, you mentioned Mongo. So many others, Presto and Starbursts, et cetera, so many other open source options out there now. And companies, developers want to work with multiple databases within the same application. And you have a role in making that easy. >> Yeah, so and that is, if you talk about the question I get all the time is, what's next for Kubernetes? Dave, you and I did a preview for KubeCon and it's automation and simplicity that we need to be. It's not enough to just say, "Hey, we've got APIs." It's like Dave, we used to say, "We've got standards? Great." Everybody's implementation was a little bit different. So we have API Sprawl today. So it's building that ecosystem. You've been talking to a number of our partners. We are very active in the community and trying to do things that can lift up the community, help the developers, help that cloud native ecosystem, help our customers move faster. >> Yeah API's better than scripts, but they got to be managed, right? So, and that's really what you guys are doing that's different. You're not trying to own everything, right? It's sort of antithetical to how billions and trillions are made in the IT industry. >> I remember a few years ago we talked here, and you look at the size that Red Hat is. And the question is, could Red Hat have monetized more if the model was a little different? It's like, well maybe, but that's not the why. I love that they actually had Simon Sinek come in and work with Red Hat and that open, unlocks the world. Like that's the core, it's the why. When I join, they're like, here's a book of Red Hat, you can get it online and that why of what we do, so we never have to think of how do we get there. We did an acquisition in the security space a year ago, StackRox, took us a year, it's open source. Stackrox.io, it's community driven, open source project there because we could have said, "Oh, well, yeah, it's kind of open source and there's pieces that are open source, but we want it to be fully open source." You just talked to Gunnar about how he's RHEL nine, based off CentOS stream, and now developing out in the open with that model, so. >> Well, you were always a big fan of Whitehurst culture book, right? It makes a difference. >> The open organization and right, Red Hat? That culture is special. It's definitely interesting. So first of all, most companies are built with the hierarchy in mind. Had a friend of mine that when he joined Red Hat, he's like, I don't understand, it's almost like you have like lots of individual contractors, all doing their things 'cause Red Hat works on thousands of projects. But I remember talking to Rackspace years ago when OpenStack was a thing and they're like, "How do you figure out what to work on?" "Oh, well we hired great people and they work on what's important to them." And I'm like, "That doesn't sound like a business." And he is like, "Well, we struggle sometimes to that balance." Red Hat has found that balance because we work on a lot of different projects and there are people inside Red Hat that are, you know, they care more about the project than they do the business, but there's the overall view as to where we participate and where we productize because we're not creating IP because it's all an open source. So it's the monetizations, the relationships we have our customers, the ecosystems that we build. And so that is special. And I'll tell you that my line has been Red Hat on the inside is even more Red Hat. The debates and the discussions are brutal. I mean, technical people tearing things apart, questioning things and you can't be thin skinned. And the other thing is, what's great is new people. I've talked to so many people that started at Red Hat as interns and will stay for seven, eight years. And they come there and they have as much of a seat at the table, and when I talk to new people, your job, is if you don't understand something or you think we might be able to do it differently, you better speak up because we want your opinion and we'll take that, everybody takes that into consideration. It's not like, does the decision go all the way up to this executive? And it's like, no, it's done more at the team. >> The cultural contrast between that and your parent, IBM, couldn't be more dramatic. And we talked earlier with Paul Cormier about has IBM really walked the walk when it comes to leaving Red Hat alone. Naturally he said, "Yes." Well what's your perspective. >> Yeah, are there some big blue people across the street or something I heard that did this event, but look, do we interact with IBM? Of course. One of the reasons that IBM and IBM Services, both products and services should be able to help get us breadth in the marketplace. There are times that we go arm and arm into customer meetings and there are times that customers tell us, "I like Red Hat, I don't like IBM." And there's other ones that have been like, "Well, I'm a long time IBM, I'm not sure about Red Hat." And we have to be able to meet all of those customers where they are. But from my standpoint, I've got a Red Hat badge, I've got a Red Hat email, I've got Red Hat benefits. So we are fiercely independent. And you know, Paul, we've done blogs and there's lots of articles been written is, Red Hat will stay Red Hat. I didn't happen to catch Arvin I know was on CNBC today and talking at their event, but I'm sure Red Hat got mentioned, but... >> Well, he talks about Red Hat all time. >> But in his call he's talking backwards. >> It's interesting that he's not here, greeting this audience, right? It's again, almost by design, right? >> But maybe that's supposed to be... >> Hundreds of yards away. >> And one of the questions being in the cloud group is I'm not out pitching IBM Cloud, you know? If a customer comes to me and asks about, we have a deep partnership and IBM will be happy to tell you about our integrations, as opposed to, I'm happy to go into a deep discussion of what we're doing with Google, Amazon, and Microsoft. So that's how we do it. It's very different Dave, from you and I watch really closely the VMware-EMC, VMware-Dell, and how that relationship. This one is different. We are owned by IBM, but we mostly, it does IBM fund initiatives and have certain strategic things that are done, absolutely. But we maintain Red Hat. >> But there are similarities. I mean, VMware crowd didn't want to talk about EMC, but they had to, they were kind of forced to. Whereas, you're not being forced to. >> And then once Dell came in there, it was joint product development. >> I always thought a spin in. Would've been the more effective, of course, Michael Dell and Egon wouldn't have gotten their $40 billion out. But I think a spin in was more natural based on where they were going. And it would've been, I think, a more dominant position in the marketplace. They would've had more software, but again, financially it wouldn't have made as much sense, but that whole dynamic is different. I mean, but people said they were going to look at VMware as a model and it's been largely different because remember, VMware of course was a separate company, now is a fully separate company. Red Hat was integrated, we thought, okay, are they going to get blue washed? We're watching and watching, and watching, you had said, well, if the Red Hat culture isn't permeating IBM, then it's a failure. And I don't know if that's happening, but it's definitely... >> I think a long time for that. >> It's definitely been preserved. >> I mean, Dave, I know I read one article at the beginning of the year is, can Arvin make IBM, Microsoft Junior? Follow the same turnaround that Satya Nadella drove over there. IBM I think making some progress, I mean, I read and watch what you and the team are all writing about it. And I'll withhold judgment on IBM. Obviously, there's certain financial things that we'd love to see IBM succeed. We worry about our business. We do our thing and IBM shares our results and they've been solid, so. >> Microsoft had such massive cash flow that even bomber couldn't screw it up. Well, I mean, this is true, right? I mean, you think about how were relevant Microsoft was in the conversation during his tenure and yet they never got really... They maintained a position so that when the Nadella came in, they were able to reascend and now are becoming that dominant player. I mean, IBM just doesn't have that cash flow and that luxury, but I mean, if he pulls it off, he'll be the CEO of the decade. >> You mentioned partners earlier, big concern when the acquisition was first announced, was that the Dells and the HP's and the such wouldn't want to work with Red Hat anymore, you've sort of been here through that transition. Is that an issue? >> Not that I've seen, no. I mean, the hardware suppliers, the ISVs, the GSIs are all very important. It was great to see, I think you had Accenture on theCUBE today, obviously very important partner as we go to the cloud. IBM's another important partner, not only for IBM Cloud, but IBM Services, deep partnership with Azure and AWS. So those partners and from a technology standpoint, the cloud native ecosystem, we talked about, it's not just a Red Hat product. I constantly have to talk about, look, we have a lot of pieces, but your developers are going to have other tools that they're going to use and the security space. There is no such thing as a silver bullet. So I've been having some great conversations here already this week with some of our partners that are helping us to round out that whole solution, help our customers because it has to be, it's an ecosystem. And we're one of the drivers to help that move forward. >> Well, I mean, we were at Dell Tech World last week, and there's a lot of talk about DevSecOps and DevOps and Dell being more developer friendly. Obviously they got a long way to go, but you can't have that take that posture and not have a relationship with Red Hat. If all you got is Pivotal and VMware, and Tansu >> I was thrilled to hear the OpenShift mention in the keynote when they talked about what they were doing. >> How could you not, how could you have any credibility if you're just like, Oh, Pivotal, Pivotal, Pivotal, Tansu, Tansu. Tansu is doing its thing. And they smart strategy. >> VMware is also a partner of ours, but that we would hope that with VMware being independent, that does open the door for us to do more with them. >> Yeah, because you guys have had a weird relationship with them, under ownership of EMC and then Dell, right? And then the whole IBM thing. But it's just a different world now. Ecosystems are forming and reforming, and Dell's building out its own cloud and it's got to have... Look at Amazon, I wrote about this. I said, "Can you envision the day where Dell actually offers competitive products in its suite, in its service offering?" I mean, it's hard to see, they're not there yet. They're not even close. And they have this high say/do ratio, or really it's a low say/do, they say high say/do, but look at what they did with Nutanix. You look over- (chuckles) would tell if it's the Cisco relationship. So it's got to get better at that. And it will, I really do believe. That's new thinking and same thing with HPE. And, I don't know about Lenovo that not as much of an ecosystem play, but certainly Dell and HPE. >> Absolutely. Michael Dell would always love to poke at HPE and HP really went very far down the path of their own products. They went away from their services organization that used to be more like IBM, that would offer lots of different offerings and very much, it was HP Invent. Well, if we didn't invent it, you're not getting it from us. So Dell, we'll see, as you said, the ecosystems are definitely forming, converging and going in lots of different directions. >> But your position is, Hey, we're here, we're here to help. >> Yeah, we're here. We have customers, one of the best proof points I have is the solution that we have with Amazon. Amazon doesn't do the engineering work to make us a native offering if they didn't have the customer demand because Amazon's driven off of data. So they came to us, they worked with us. It's a lot of work to be able to make that happen, but you want to make it frictionless for customers so that they can adopt that. That's a long path. >> All right, so evening event, there's a customer event this evening upstairs in the lobby. Microsoft is having a little shin dig, and then serves a lot of customer dinners going on. So Stu, we'll see you out there tonight. >> All right, thanks you. >> Were watching a brewing somewhere. >> Keynotes tomorrow, a lot of good sessions and enablement, and yeah, it's great to be in person to be able to bump some people, meet some people and, Hey, I'm still a year and a half in still meeting a lot of my peers in person for the first time. >> Yeah, and that's kind of weird, isn't it? Imagine. And then we kick off tomorrow at 10:00 AM. Actually, Stephanie Chiras is coming on. There she is in the background. She's always a great guest and maybe do a little kickoff and have some fun tomorrow. So this is Dave Vellante for Stu Miniman, Paul Gillin, who's my co-host. You're watching theCUBEs coverage of Red Hat Summit 2022. We'll see you tomorrow. (bright music)

>>Hi, everyone. Welcome to the cubes coverage of Avis reinvent 2021 we're onsite in person. It's a virtual event, also hybrid events. I'm Jennifer and my host, David Dante ninth year, Dave, we've been doing Avis reinvent the cube and it's 11th season. We've seen a lot. Yeah, I'll say. >>And the show is pretty packed, John. I mean, I think it's surprised some folks over 25,000 people here. I mean, obviously a lot of sponsors, but >>Customers to a bad event for AWS in terms of attendance is like record-breaking for any other company, people are standing in line for sessions. It's definitely happening. People are here to learn. They're not just all employees. So definitely a successful event in person as well in the live stream. But so much news to talk about. Andy Jassy is now the CEO of Amazon. That's the top story Adam's Lipsky's taking over as CEO of AWS time, Amazonian who left Amazon to take the CEO job of Tableau sold that company to Salesforce under mark Benioff. Now back to take the helm from Andy Jassy and quite the pressure cooker here as he takes the stage, a lot of people are asking, is will he do well? Will he fumble on stage? Will he do the right things? And does he have what it takes to take the cloud to the next generation with AWS as their number one clear far and away, then the second competitor in Microsoft and then a look distant third and Google. So Amazon's are under a ton of competitive pressure. At least from an industry standpoint, everyone's still trying to catch up. It's the same theme, Dave, every year Amazon is out front and the lead just gets extended and extended. And again, here, no exception. Well, the Uber >>Of course there's you mentioned is Andy Jassy is now taking over a CEO of Amazon. And you know, history would suggest that a lot of times that companies falter when there's a CEO transition, but it feels like it's different this time. Andy Jassy was here since the beginning launched AWS versus a profit engine of Amazon brought back Adam sill Lipski who has a deep understand. He's not as technical as Andy, but obviously as a deep understanding of the business, yeah, he was comfortable up in the keynote. It wasn't John, a typical firehose of announcements. Even those, a lot of announcements, they didn't shove them down our throat and they didn't in the analyst session as well. Usually in the analyst session, it's hours and hours and hours of firehose Kool-Aid injection, not this year. Why do you think that is, is that a COVID thing? Is that a change in now? >>I think Adam's Leschi wants to be his own guy. As, as leader here, a lot of things were eliminated from the keynote that Andy Jasmine did, for instance, Andy Jesse loves music. So we always had the music walk up music like you see in sports, uh, which is very cool. That's an Andy Jassy kind of tweak. Andy is all about announcements and he was just, uh, pushing the envelope. Adam was much more laid back. He sees, I think, more of a holistic picture being more of an app guy being more of a data guy, less of a, I would say under the covers nerd like Jassy was, Andy was very deep on, on a lot of the tech stuff as is Adam. But I think Andy a little bit more proactive on that. So Adam was very much more about the impact of 80 of us culturally, as a society, as a company and kind of brought in this kind of think different apple vibe, which is, you know, the people who are Pathfinders, um, as he takes that Jassy kind of, um, approach of leaders, but be a builder, be a change agent, be a game changer. >>Adam took it to another level by saying, Hey, it's okay to be a Pathfinder because it's net new disruption with the cloud. And I think that's the story that I see coming out of this where, uh, in talking to Adam one-on-one Amazon absolutely has a secret weapon in it's chips, custom Silicon. They're absolutely crushing it with how they're thinking about SAS and platforms and they have a huge ecosystem. And I think at the end of the day, and we talked about this in our story on Silicon angle, Amazon could actually wipe out Microsoft. And I think Microsoft's core competitive advantage has always been their ecosystem and their developers. I think right now in the next few years, if Microsoft doesn't match Amazon, they will be decimated anyway, you know? >>Yeah, hold on. Okay. Amazon's not going to wipe out Microsoft. Microsoft has too much of a cash cow. Look at the hanging on to windows. Couldn't, you know, the mistake and missing mobile event initially missing the cloud. Didn't wipe out Microsoft. So they've just got too much of a software cashflow. That's not gonna happen maybe a little bit over the top. >>I thought, but Microsoft has done a great job and it's not going to tell it to kind of stay in the game and do more. But if you look at the major inflection points, Dave where's digital equipment corporation, where's prime computer. Well, >>I think this is the point is again, history would show that those companies, when they handed the reigns over to a new CEO failed, they faltered, it was self-inflicted wounds. It almost happened. You thought it would happen with Microsoft, whether it became irrelevant under bomber, but when Nadella came in, he reinvigorated because specifically they had the cashflow to be able to do that. Now. So the big question is, okay, w what's going to happen. We ran a survey to our community to see what could disrupt Amazon. You know, that the us government wants to break them apart or wants to regulate them. But our survey respondents said there's a 60% plus probability that Amazon will be disrupted by other factors. And that's what I was self-inflicted wound that's Jesse's that's right. And that's, Jessie's big challenge is how to not make those disruptions, how to fight those disruptions. >>The number one, uh, reason why they could be disrupted was self-inflicted wounds, which again, history would show what happened. But one of the things we talked about is that normally happens when companies stop innovating when they rest on their laurels. Right. And you kind of saw that with those companies that you mentioned, but you mentioned their secret weapon. We wrote about that in our article, the chips. So we heard no secret. Everybody knew graviton three was coming, right? And so that is Amazon secret up. And you know, I've been thinking about this. John Amazon makes a lot of money on x86 instances that they've deployed years ago and they charge a lot for, I was wondering, you know, is the, or the old X 86 instances actually more profitable than graviton, maybe at this point in time, but long-term graviton. They control their own destiny because they control the hardware and software stack. And I bet you allows them to get better negotiating leverage with >>M D and it's of course, I mean, pat, Kelsey, we should talk about this all the time, but as bad as Jason Intel, you, if you're not out in the next wave, your driftwood, I think Intel and AMD and others, they have purpose-built general purpose chips. They're probably going to be for the lift and shift stuff when you, but if you're actually seriously writing software as an owner on the cloud, and you want specific advantages of speed and performance, you're going to want the custom Silicon that's purpose-built for your application and write code to that stack. So, so I think there's a whole nother level of platform as a service. Dave, that's kind of coming out of this re-invent that I think could be a multi generational trend, which is, Hey, the cloud is of super cloud or platform. Look at the riser, snowflake and Databricks. Those guys are on Amazon. Like they're super clouds in and of themselves they're platforms. They're not appoint SAS solution. I think Microsoft in my, my analysis is, yeah, they got office 365, okay. Word processing stuff. But what other SAS apps do they have besides SQL server and other things that are actually being built on there? And if, if I'm a developer you're going to want to go to the platform. That's the highest performance for office 365. It's a cash cow. But how long is that going to last >>A long time? I mean, major momentum. We argue about that later, but I wanna, I want to touch on graviton three because I think that was the big announcement of the day 25% faster than graviton to at least twice the floating point performance twice the crypto graphic performance in three times for machine learning, learning workloads, and very importantly, 60% less power. So at Amazon scale, uh, Adam said this in our meeting, he said, the economics really favor us because of our scale. And so, and they've also announced new training them instances and, and, and what, what having custom Silicon allows Amazon to do is release on a much, much faster cadence than traditional x86. And they could do, and they could do really cool things. Nitro is there, Nick they're smart NEC, which it says the basis, their new hypervisor, if you will. So it allows them to bring in x86, uh, Nvidia NPUs some of their own or Nvidia GPU, some of their own Silicon. So optionality is really the key there. You heard them announce, uh, an SAP instance. So that's a memory intensive instance. They can dial things up, dial things down. They've got full control of the stack. And by the way, copying them Google's copy of Microsoft is copying them. And who's leading this charge in custom Silicon, AWS, obviously Tesla, apple. I mean, these are leading companies that I don't think they all got it wrong. I think >>The Silicon angle is to have your own custom Silicon. And that's the, that is the clearly the advantage as it's vertically integrated. But the other thing that's coming out of this reinvents, the purpose built software concept where, you know, they're not copying Microsoft playbook as the wall street journal was saying, and some are saying Microsoft copying Amazon, Amazon has always been this horizontally scalable resource that's cloud, but with machine learning and AI, you now have this purpose-built kind of capability from software into the app itself where data has to be addressable. And I think the people in the data business kind of know this, but as the rest of the world comes out, architecturally having that horizontal observation space and data that's vertically tied to machine learning is a huge architectural shift. This is a complete rethinking of how software is built and that's going to be a game changer. I think Amazon's well out on front of that. And I think that's going to be a huge architectural shift. >>Well, let's quantify this a little bit because you know, you're, you're making the point that Amazon is the number one cloud, which I would agree with. We're talking here about IAS infrastructure as a service in the past layer that sits on top of that. Microsoft defines the cloud is we'll put in an office 365, Google we'll put in its Google apps, Amazon pure infrastructure as a service. And if you just look at that space, that's about $120 billion business. When you add up AWS, Azure, Alibaba and GCP, which I would contend are the only four hyperscalers out there. I don't include Oracle as a hyperscale. I don't include IBM. I get a lot of crap for that sometimes. Yeah, but we're talking big scaler, $120 billion. So actually relatively small compared to the trillion dollar opportunity that they have, but it's growing at 35% a year. Amazon will do more than 60 billion this year, 62 billion, just to quantify it in that ISS space. Microsoft will be about 38, 30 9 billion. Okay. So pretty substantial. Those two are far ahead of the others. Everybody else's, you know, Google is still in, you know, under 10 billion, Alibaba is right around there. So those two, it's really a two horse race. And I asked Microsoft using its software estate. Amazon's gotta be the innovator and has to have the best cloud to win. And it does well >>Also a platform. Let's go back to the little history lesson for the younger folks out there. When Microsoft was had a monopoly, they had windows operating system, which has had DAS under the covers, but windows was the operating system. And office was a suite of applications. They encourage software developers to build on top of windows and they had other servers off SQL server all came out of that small history. So their bread and butter was to have developers build on top of windows. Hence the monopoly, of course they had the application and the system software, hence the monopoly, hence the Microsoft breakup by the government in 1997. Now today cloud is essentially one big kind of PC concept. It's like windows, it's windows equivalent. So cloud is essentially an environment platform that has apps that run on top of it. Okay. In that world, Amazon by far is the number one windows model at Amazon's. >>I mean, Microsoft is used to is okay, I got Azure and I got office 365 that keeps them in business that keeps them from losing. So it's a placeholder. So that what I'm looking at is what is Amazon? I mean, Amazon versus Azure, doing relative to ISV and uptake for developers. And I'm suggesting that this trend of Amazon will go, if it goes uncontested by Azure, they'll wipe the table on ISV and suffer developers. If you're an owner of a software, you're not gonna write software, that's gonna be sub-optimized for a platform. That's not going to be before, >>Unless you're, unless you're a Microsoft developer, nearly all.net days. And there are a lot of those. And that's what, that's what Microsoft is doing. They're they're, they're, they've, they've shifted to cloud, they've gone everything into cloud. So Azure is their platform for innovation and acceleration. >>So those developers are going to build a sub application versus going over here on AWS. >>Well, that's the, that's the story with Microsoft. Good enough. I know >>Again, this is we're speculating, but we're going to watch that, but that is, to me, will be the battlefield of what will determine Azure versus AWS. And I think everything else is smoke and mirrors Amazon Webster way ahead of Azure, but the TeleSign is going to be does 80 bus attract those developers on their cloud with the custom Silicon, with the integrated stack and with the purpose-built software. I mean, it's looking really good. I think they've got a really compelling story. >>I think it's less about Azure versus AWS. I mean, that's an interesting storyline and I love to talk about it, but I think they'll go back to 120 billion out of 4 trillion. That's really the, the larger opportunity for, for both Microsoft and AWS to continue to grow. Because you look at, you look at Dell with apex, you look at HPE with GreenLake, Lenovo, Cisco, they've all got their own clouds. One of the things that didn't get into our article, but Adam Lipski when, when you asked him about hybrid is that hybrid cloud. When we were talking about some of the stuff they're doing, he S he said, look, that's not cloud what those guys are doing. That's not what we did. And he talked today about edge has to be AWS, not like AWS. That was the quote to use. Talk about, you know, private 5g, bringing out posts. And he gave some examples of that. The point is they, AWS is bringing its system, its architecture to the edge it's programming model infrastructure as code to the edge. Now, Kubernetes, Kubernetes does moderate that a little bit, but his point was, that's not AWS. That's not the cloud. >>Yeah. I think in summary, Dave had to wrap up what's the big trend this week is that Amazon web services is a, is a heaven environment for a developer, for the elite people who want to roll their own for the folks in it. In these other environments, you can have prefabricated purpose-built software platform to build on top of. And I think that isn't going to address the whole ease of ease of rollout. So if I'm a SAS developer, I don't, I want, I don't want to rebuild that over again. I don't want to roll my own. I'll take what you got and connects a good example. If you want to call shedder, you can take it and use it and then build on top of it and iterate on it. So I think it's more of here's a platform for you and take it. So I think that to me is the big story and that's not and think about it. How many people out there, a role in their own Amazon, you've got to be pretty strong at Amazon, uh, familiar ups to roll your own gut >>Of other quick points that he barely emphasized the primitives, the API APIs, that multiple databases, right tool for the right job, took a shot at Oracle without mentioning Oracle because they had sort of one database, but I will say this is mission critical. Oracle still owns that. Uh, they talked about a mainframe migration, tooling and runtime from mainframe compatible runtime. That's going to allow them to nip at the edges of those mainframe workloads and Oracle workloads. It, they're not going to get to the core anytime soon. They also talked about role level and cell level security. We think that's the squirrel acquisition from years ago. And then he made a statement. We have three X with Redshift price performance better than any cloud data warehouse sort of interesting shot at, at, at, at a snowflake and Databricks Databricks. So, um, anyway, yeah, >>I mean, I think, I think overall, I thought Adam did a good job. I think he didn't, uh, he didn't disappoint. Okay. But that's comfortable. I think his goal was to get through this and not have people go well, it's not Andy Jassy. I thought he did an awesome job and he did a good job. And he, he got, he got what he needed to do >>Comfortable. And he obviously leaned on some of his Pathfinder customers. NASDAQ, I thought was very impressive. United airlines dish. So, >>Okay. Cutie coverage, ninth year of the cube here at ADP reinvent, uh, 2021 is the cube. You're watching the leader in high-tech coverage. The cube.

[upbeat electronic music] >> Hi everyone, welcome back to theCUBE's coverage of AnsibleFest 2021. I'm John Furrier, your host of theCUBE. We're here with Eric Pennington, Director of Solutions Engineering, and Mike Todaro, Senior Epic Cache Consultant at Sapphire Health. Gentlemen, thank you for coming on theCUBE and chatting about the wave of Cloud, cloud-native, Sapphire Health and Ansible. Thanks for coming on. >> Thanks for having us. >> Thank you. >> So, let's get started. Can you guys just briefly describe Sapphire Health and what you guys are doing there. The consulting services, the trends that you're seeing. Just take a step, a minute to describe the environment at Sapphire Health and what you guys are doing. >> For sure, yeah. So, Sapphire Health was a consultancy that was founded by the CEO back in 2016, Austin Park, who also serves as a CTO for some healthcare organizations, because he was having difficulty finding an organization that really specialized in Epic infrastructure. So you might be familiar with some of the large players in Epic consultancies, but they are typically focused more on the application side, so configuring like the ambulatory clinical system or something like that. And there really wasn't a solution that he could find in the market for an organization that was focused on Epic infrastructure and some of the more technical components of managing an Epic technical ecosystem. So, Austin founded a team. Mike was one of the early folks to join. I joined a little bit later. But he put a team together to, again, really focus on the technical components of an Epic implementation. And since then, we've been providing managed services for Epic infrastructure for a number of organizations. We've been focusing on platform migrations from, for example, AIX to REL for Epic organizations, and we've been focusing on some growth areas as well in the Cloud. Epic systems is now able to be hosted on the public Cloud, that's a relatively recent occurrence. So, we're working with some organizations in that space as well. Mike, anything you'd add there? >> No, I think that pretty much covers it. We've spent a large fraction of our effort making sure that we're engineering solutions for these clients that move them in the directions towards Cloud readiness, towards containerization, automation, and those sorts of things. I think Eric's description's spot on. >> So, you guys must be busy. I mean, I can only imagine the action happening right now as people realized, with the pandemic specifically, two areas that we've reported aggressive growth on was public sector and healthcare. Both were under massive strains of pressure to get faster. (chuckles) Can you guys just weigh in real quickly on what you guys are seeing and how that's impacted your consulting services, but also the customer. What's going on in their minds? >> Absolutely, we had some customers very early on in the beginning of the pandemic where we were given the cadence of updates coming from Epic, the needs for growth for those customers where both in ICU surge capability as well as just general admittance. There was a flurry of hardware purchasing, provisioning, set up. An increased cadence around patching for various pieces of the Epic environment including Epic code directly. All of those things. The tempo of all of that increased once the pandemic began, and we spent a significant fraction of time trying to find better ways, faster ways to engineer what we were already doing for clients, simply so that we could continue to keep up with the surge in demand without requiring an additional surge in investment in people, where it wasn't necessary. Obviously, some growth was necessary, but we wanted to help our clients get the most out of what they already had so that they could spend that money where it was needed to help patients. >> Yeah, awesome, great stuff. So, we're here at AnsibleFest getting into the action. It's all about automation. So I have to ask you guys, what led you to start exploring automation solutions at Sapphire Health? >> Yeah, so there's quite a few reasons. I would say the most critical is that we've been providing managed services to organizations around infrastructure management for some time. And as you can imagine, infrastructure management has some repetitive tasks, and I'm quoting my colleague, Mike, here, but a good administrator is a lazy administrator. And what we mean when we say that is, if there's a repetitive task that's being performed over and over again, if there's an opportunity to automate it, that's going to save us time. But more importantly, that's going to... Paul, these lights here. Let me move around a little bit, should come back, there we go. But it's going to provide an opportunity for us to focus on more value-add services for the client. It's going to reduce costs for the client in terms of the services that we're providing. And I think most importantly, it's removing the possibility for human error or the possibility for error overall. So it's a natural evolution of us observing the time that we're spending with our client partners, and again, it really provides a lot of value to Sapphire as an organization and our customer partners as well. >> Mike, you want to weigh in on this automation trend. How do you see it evolving? I mean, obviously sounds good when you want to automate things that you do repetitive tasks, but is there more going on that you see in automation that goes beyond just, okay, if you do it three times-automated kind of vibe. >> Sure. Automating repetitive tasks is the kiddie end of the pool. That's how we get... That's how we sell the idea to people who just don't get the concept yet. But there are workflows that really aren't feasible outside of automation. We tend to think of automation, in some cases in this sort of limited way, but automation is really... What we really are targeting with automation is more about workflow. It's less about individual tasks, and it's more about an idea of workflow or a business requirement from its origin all the way through its implementation. So, I've got just the simplest case that jumps immediately to mind, is I have a new hire, I've got to provision them an account. I need to provision it across multiple systems. I've got to do it in our single sign on. They need home directories. They might need access. They need building accesses we need to generate. You got to generate badges for these people. And these are all workflows that are normally disparate. You know, you have to take your sheet to this guy, take your sheet to this guy, here's my new hire form. Really, what you really want is, we got a new hire, everything's checked out, put it in this basket here and let the automation move it through all of these systems all the way across. And that's the sort of thing, like I said, that's a very limited, very simple idea, but that's the kind of thing we really want. We want to get in the door with automation with simple things and then we want to teach... We want clients and ourselves to be challenged, to be creative, to find new ways to apply it that aren't immediately obvious. >> Yeah, I was smiling because I love the example of the kiddie end of the pool because automation is going mainstream, and it used to be kind of, you know, for the geeks who were doing the hardcore stuff who got the whole big picture. Now you're seeing with AI automation moving in and with Cloud, a lot more automation happening. So, I can almost see in my mind mental image of people wearing bubbles in the pool, kind of like going in the deep end, get back over here. Stay in your lane. Yeah, but this is the trend, and I want to get into this because you guys are involved in this Epic migration that's been talked about. So for the folks that aren't in, say the health care space, put a little context around Epic and then I want to get into this whole migration discussion. I think that kind of points to some real value propositions. So, what is Epic for the folks outside healthcare? >> Sure, so Epic is one of the leading EHRs or electronic health records software in the world. It is by far the most deployed in the United States. What's involved in building an Epic, or performing an Epic migration. Epic is hundreds of systems. When you think about Epic as an umbrella concept, it is servers and end-user workstations and all of these things. When we talk about platform migration, what we're usually talking about is the transactional database. They call it the ODB or whichever term I think you feel applies best. When we perform all those migrations, we're usually talking about... When we perform one of those migrations, we're usually talking about an AIX to Red Hat migration, although you can just do hardware to hardware. Involved in that is a number of things. You're building new VMs. You're setting up patch cycles, setting up the patching server. Installing the various administration scripts that Epic provides. Installing the software that runs the DB, which at the moment is either InterSystems Cache or Iris. There's the provisioning of the local security users. There's the configuration of the OS. If you're moving from AIX to Red Hat, you're talking generally about a bit endians conversions, so, big endian to little endian, there's a tool for that. There's a lot of these little stats. And the thing is, is that, they're all very, very well defined and very similar, and so, they look identical in many of these cases from one implementation of Epic to the next. And that's not true for the entire Epic stack necessarily, but at the ODB level, this stuff is all very similar, and this is a very right place to automate. This screams automate, and we do this because, I mean, who wants to make mistakes. If you write and build your script and debug it, the script runs, it doesn't make mistakes. I make mistakes, the script doesn't. So, we do that, and we end up spending less time on these repetitive, unnecessary tasks. We guarantee the correctness of them, or we do a better job of guaranteeing the correctness of them, and all of that ends up saving money in the long run. >> That's awesome, and thanks for the context. I was going to get there on the automation piece. It really sets the table for the automation. Real quick clarification. How much or what kind of software work is involved in a migration? >> Oh, so there's the installation of... You have from the installation of the OS and the configuration of the OS, the building in the patch server, the implementation, testing, and patch cycling. There's those data conversions I talked about. There's environment refreshes where we copy an existing environment on a regular basis to another environment for things like testing, for troubleshooting purposes or for other reasons. There's more than one database for Epic. There's one big production database. You have training databases, and you have playground databases for people to work in so they can learn to use the system better, and then there are, I mean, there's a galaxy. >> Oh man, so it's a huge system. Okay, so I got to ask the security question. >> Sure. >> Is security element as important when selecting automation or how has that factored in? I mean, right now that's super important, obviously, records are key, but honestly, where does that fit into the automation piece of security? >> Yeah, I think that's a very important question, and as you alluded to, security is incredibly important. It's very important in healthcare in particular. And in fact, with healthcare, there's a lot of regulatory requirements. There's a lot of requirements that individual healthcare institutions have that we as a partner to that institution need to follow. So, as we were evaluating automation vendors and automation solutions, a highly secure system was not a nice to have or like a value add, it was something that was absolutely critical and paramount to being able to successfully automate any of the things that we're doing. So I'll turn it over to Mike to talk about some of the specifics, but as we evaluated Ansible, we saw that it really supported robust security. So, Mike, can you comment a little bit more on that? >> Sure. There's a number of ways that we use Ansible to help improve the security posture for clients. One of the ways is Ansible playbooks are written to be runnable against the server and nothing will change unless something is set incorrectly. And this lets us assure that the configuration is where we expect it to be so we don't get drift on these servers. Now, remember I said an Epic environment is a lot of servers. If one or two of these... >> John: Mike, if you don't mind, I need to interrupt. What is, when you say drift, what are you referring to? >> So when I say drift, what I mean is, if there's a bunch of different servers and I as an administrator have to work on one or two of these servers just for little things during the day, I might make a change on one of these servers advertently or inadvertently, and then that server's configuration is now slightly out of phase with the other servers, which could be benign, but it could also be a security hole. Having Ansible able to run nightly and continue to adjust these servers back to the expected baseline, and in the case of things like tower, be able to report that these things were out of position. Let us know, hey, it lets us reduce the attack surface, first of all. It lets us multiply it, like a force multiply our attention across this farm of servers, and it gives us that sort of clarity that we know we're doing what we have to do to make sure these servers continue to be safe. >> That's an awesome service. That right there is, I mean, just going in manually trying to figure all this stuff out, it's just a nightmare. I mean, what a great relief that is. I mean, just the alternative is what, you know, more pain and suffering human wise, that's the labor, and then risk on attack because people go to bed. >> I'm a patient. The thing is, on a personal note, I'm a patient too, all of us are. We all have doctors. We have to go to the hospital for things occasionally. And if we fail when we perform these security audits, if we fail when we perform these security checks, patient data can get lost. It can get sent to people who shouldn't have it. And I'm a patient, I have no desire for my medical information to be available anywhere but in the hands of my doctor or myself. And that's the thought I try to stay with when I'm working on these systems. I'm a patient. It's not that I'm doing this because... I mean, the knock-on effects of reducing liability for the customers cannot be ignored or overstated, and they're critical, but, ultimately, my eyesight is on the patient. >> Yeah and having that stability is huge. Okay, this brings up the whole automation thing as it becomes more mainstream for you guys, specifically, is critical. The system's there, you have to watch farms, all the action happening, it's a huge system. Complex automation is key. How are you guys continuing to push the automation envelope into the Sapphire Health's consulting practice? >> Well, as you mentioned, John, yeah, we're really taking a look at the entire technical infrastructure when we're working with our clients. And we are offering fully outsourced managed services for organizations, not just around the Epic infrastructure but things like networking devices, security and other third party systems. So with that, we're seeing a lot of these things that are going on, and we're always evaluating opportunities for automation. There's actually two areas in particular that we're seeing gain a lot of momentum with our customers, and we're seeing a lot of opportunity for automation. The first is business continuity and disaster recovery, specifically within Epic. So, Epic has very stringent requirements for resiliency, as you can imagine. When the system goes down, a hospital can't really do what it needs to do from a billing standpoint, a clinical standpoint, so very robust disaster recovery and resiliency standards and solutions are very important. However, there's not a lot of automation that's available either from Epic or, as far as I know, other consultancies, so what we did is we built a script that provides failover automation. So some of the tasks that would be very manual in terms of failing over to your DR solution, we've automated that, and that again, removes a lot of the opportunity for human error, really speeds up the failover process. And so with the customers that we work with, that's something that we provide. Another big area that we're seeing is environment refreshes. So within Epic, there are different environments that are, basically, all their data is copied over on a recurring basis from the production environment, and the refreshes can have a lot of manual steps involved, so we found an opportunity and have implemented some automation around environment refreshes for some of our managed services clients. And as we continue to go throughout, you know, building our Cloud practice in some other areas, I'm very confident that we're going to see, you know, infrastructure is code more opportunities for automation around areas like that. >> I mean, you guys got to love the DevOps vibe going on now. Mike, I mean, you guys have seen the movie before in the old legacy going back to the mainframes, so you probably still run into a lot of older systems that still do a purpose. I mean, I have a lot of friends and clients that are working in the big banks, and they still have all the old school that does their job well, but containerization and Cloud kind of give life to these systems because now we're living in this system architecture called distributed computing again with the Cloud. It's the same game, different, different stuff though. >> Absolutely. Years ago, almost every Epic client was running on AIX, and maybe not mainframe but more mini computer. The migration path for almost all of the clients has been to move from those AIX mini computers down to VMs running Red Hat, or running Linux, and the natural evolution of that path is to move at least disaster recovery data centers into the Cloud, and then for some clients, the economics say the whole data center to the Cloud. So, absolutely that path is, it's well forged, it's there. I suspect that we'll see a lot more of clients, even larger hospitals, beginning to move down that road in the near future. >> And for the folks watching who may not have the scar tissue that we have, AIX was IBM's old Unix, a kind of mid-range mini computer. It was kind of client server, it was client server going now again being modernized. So obviously Red Hat is now part of IBM, but it speaks not just to IBM, this is about Ansible, right. So this is like, there is action happening here, so this is a case study of pretty much all migrations. It's not just the fact that it's AIX to Red Hat, it's system to the new thing that has benefits. >> Absolutely. >> What's your take, Mike, on that that kind of paradigm, because a lot of people going through similar situations just change AIX to something else. You have a lot of this migration re-platforming going on with the opportunity to kind of tweak it and add stuff to it. What's your advice and what's your reaction to this big trend? >> My advice for this trend, honestly, my advice is when you're planning these migrations, you know they're coming. Even if you're not in the cycle yet, you know it's coming. My advice is start brainstorming your implementation of the automation now. Get your automation into the system as you platform into your new platform, because it is far easier to build that entire platform with automation as a critical component than it is to bolt it on later, and you will get much more out of your investment and time and effort if you've integrated it from the very beginning. I would say anyone that was looking to perform a platform migration now and hadn't already begun serious consideration of running automation or had no plans for an automation, was setting themselves up for a very long and very difficult road to hell, and I would advise against it at this point. >> Great, great insight, Mike and Eric. Thanks for coming on, appreciate your insight here. You guys want to give a quick plug for the company? What you guys are looking to do, hiring, any update you want to share because great, great content you guys just shared here. Thanks for doing that. Take a minute to put a plug for the company. >> Yeah, I think a quick plug here. Yeah, if you're a talented cache admin, there's not too many Mikes out there, so we're definitely looking for more Mikes. But more broadly, we're really looking to expand into the Cloud space. We're rapidly expanding our managed services opportunities, and what we're seeing is a lot of organizations have like one ODB admin or one client systems ECSA admin. And what they run into is that person will leave, that person will retire, that person needs to get married and go on their honeymoon. It's kind of a problem, so we're working with a lot of organizations to not just fully outsource their environment but to provide a hybrid-managed service to provide overflow, to provide capabilities, to scale up with upgrades and projects like that. So, talk to us, we're pretty darn good at it, as you heard from Mike. We've got a couple of Mikes, again, we could use more, so if you are a Mike, please reach out. >> I think we virtualized him, we just virtualized Mike, you know, virtualization is a huge trend. >> If data writes Mike, we need to do that, yeah. >> Are you a body, are you the real Mike? >> (laughing) As far as I know, my wife would appreciate it if you guys would clone me a few times. >> You know, I've heard horror stories, Eric, around root passwords, like, who has the root password, oh, she left two years ago, kind of situations, this happens. I mean, this is not... it sounds like crazy but people leave. >> Yeah, I mean, nobody works anywhere forever, right? >> Don't be that company where you lose the root password, and never mind the ransomware action. Oh my God, must be brutal. Anyway, we can go another segment on that. Eric, thank you for coming on. Mike, thank you for your insight, really appreciate it, thanks for coming on. Appreciate it. >> Absolutely. >> Absolutely, it was our pleasure. >> Stay right here for continued coverage of AnsibleFest 2021. This is theCUBE, I'm John Furrier. Thanks for watching. (slow tempo electronic music)

>>Hello and welcome today's cube presentation of eight of us startup showcase. I'm john for your host highlighting the hottest companies and devops data analytics and cloud management lisa martin and David want are here to kick it off. We've got a great program for you again. This is our, our new community event model where we're doing every quarter, we have every new episode, this is quarter three this year or episode three, season one of the hottest cloud startups and we're gonna be featured. Then we're gonna do a keynote package and then 15 countries will present their story, Go check them out and then have a closing keynote with a practitioner and we've got some great lineups, lisa Dave, great to see you. Thanks for joining me. >>Hey guys, >>great to be here. So David got to ask you, you know, back in events last night we're at the 14 it's event where they had the golf PGA championship with the cube Now we got the hybrid model, This is the new normal. We're in, we got these great companies were showcasing them. What's your take? >>Well, you're right. I mean, I think there's a combination of things. We're seeing some live shows. We saw what we did with at mobile world Congress. We did the show with AWS storage day where it was, we were at the spheres, there was no, there was a live audience, but they weren't there physically. It was just virtual and yeah, so, and I just got pained about reinvent. Hey Dave, you gotta make your flights. So I'm making my flights >>were gonna be at the amazon web services, public sector summit next week. At least a lot, a lot of cloud convergence going on here. We got many companies being featured here that we spoke with the Ceo and their top people cloud management, devops data, nelson security. Really cutting edge companies, >>yes, cutting edge companies who are all focused on acceleration. We've talked about the acceleration of digital transformation the last 18 months and we've seen a tremendous amount of acceleration in innovation with what these startups are doing. We've talked to like you said, there's, there's C suite, we've also talked to their customers about how they are innovating so quickly with this hybrid environment, this remote work and we've talked a lot about security in the last week or so. You mentioned that we were at Fortinet cybersecurity skills gap. What some of these companies are doing with automation for example, to help shorten that gap, which is a big opportunity >>for the job market. Great stuff. Dave so the format of this event, you're going to have a fireside chat with the practitioner, we'd like to end these programs with a great experienced practitioner cutting edge in data february. The beginning lisa are gonna be kicking off with of course Jeff bar to give us the update on what's going on AWS and then a special presentation from Emily Freeman who is the author of devops for dummies, she's introducing new content. The revolution in devops devops two point oh and of course jerry Chen from Greylock cube alumni is going to come on and talk about his new thesis castles in the cloud creating moats at cloud scale. We've got a great lineup of people and so the front ends can be great. Dave give us a little preview of what people can expect at the end of the fireside chat. >>Well at the highest level john I've always said we're entering that sort of third great wave of cloud. First wave was experimentation. The second big wave was migration. The third wave of integration, Deep business integration and what you're >>going to hear from >>Hello Fresh today is how they like many companies that started early last decade. They started with an on prem Hadoop system and then of course we all know what happened is S three essentially took the knees out from, from the on prem Hadoop market lowered costs, brought things into the cloud and what Hello Fresh is doing is they're transforming from that legacy Hadoop system into its running on AWS but into a data mess, you know, it's a passionate topic of mine. Hello Fresh was scaling they realized that they couldn't keep up so they had to rethink their entire data architecture and they built it around data mesh Clements key and christoph Soewandi gonna explain how they actually did that are on a journey or decentralized data >>measure it and your posts have been awesome on data measure. We get a lot of traction. Certainly you're breaking analysis for the folks watching check out David Landes, Breaking analysis every week, highlighting the cutting edge trends in tech Dave. We're gonna see you later, lisa and I are gonna be here in the morning talking about with Emily. We got Jeff Barr teed up. Dave. Thanks for coming on. Looking forward to fireside chat lisa. We'll see you when Emily comes back on. But we're gonna go to Jeff bar right now for Dave and I are gonna interview Jeff. Mm >>Hey Jeff, >>here he is. Hey, how are you? How's it going really well. So I gotta ask you, the reinvent is on, everyone wants to know that's happening right. We're good with Reinvent. >>Reinvent is happening. I've got my hotel and actually listening today, if I just remembered, I still need to actually book my flights. I've got my to do list on my desk and I do need to get my >>flights. Uh, >>really looking forward >>to it. I can't wait to see the all the announcements and blog posts. We're gonna, we're gonna hear from jerry Chen later. I love the after on our next event. Get your reaction to this castle and castles in the cloud where competitive advantages can be built in the cloud. We're seeing examples of that. But first I gotta ask you give us an update of what's going on. The ap and ecosystem has been an incredible uh, celebration these past couple weeks, >>so, so a lot of different things happening and the interesting thing to me is that as part of my job, I often think that I'm effectively living in the future because I get to see all this really cool stuff that we're building just a little bit before our customers get to, and so I'm always thinking okay, here I am now, and what's the world going to be like in a couple of weeks to a month or two when these launches? I'm working on actually get out the door and that, that's always really, really fun, just kind of getting that, that little edge into where we're going, but this year was a little interesting because we had to really significant birthdays, we had the 15 year anniversary of both EC two and S three and we're so focused on innovating and moving forward, that it's actually pretty rare for us at Aws to look back and say, wow, we've actually done all these amazing things in in the last 15 years, >>you know, it's kind of cool Jeff, if I may is is, you know, of course in the early days everybody said, well, a place for startup is a W. S and now the great thing about the startup showcases, we're seeing the startups that >>are >>very near, or some of them have even reached escape velocity, so they're not, they're not tiny little companies anymore, they're in their transforming their respective industries, >>they really are and I think that as they start ups grow, they really start to lean into the power of the cloud. They as they start to think, okay, we've we've got our basic infrastructure in place, we've got, we were serving data, we're serving up a few customers, everything is actually working pretty well for us. We've got our fundamental model proven out now, we can invest in publicity and marketing and scaling and but they don't have to think about what's happening behind the scenes. They just if they've got their auto scaling or if they're survivalists, the infrastructure simply grows to meet their demand and it's it's just a lot less things that they have to worry about. They can focus on the fun part of their business which is actually listening to customers and building up an awesome business >>Jeff as you guys are putting together all the big pre reinvented, knows a lot of stuff that goes on prior as well and they say all the big good stuff to reinvent. But you start to see some themes emerged this year. One of them is modernization of applications, the speed of application development in the cloud with the cloud scale devops personas, whatever persona you want to talk about but basically speed the speed of of the app developers where other departments have been slowing things down, I won't say name names, but security group and I t I mean I shouldn't have said that but only kidding but no but seriously people want in minutes and seconds now not days or weeks. You know whether it's policy. What are some of the trends that you're seeing around this this year as we get into some of the new stuff coming out >>So Dave customers really do want speed and for we've actually encapsulate this for a long time in amazon in what we call the bias for action leadership principle >>where >>we just need to jump in and move forward and and make things happen. A lot of customers look at that and they say yes this is great. We need to have the same bias fraction. Some do. Some are still trying to figure out exactly how to put it into play. And they absolutely for sure need to pay attention to security. They need to respect the past and make sure that whatever they're doing is in line with I. T. But they do want to move forward. And the interesting thing that I see time and time again is it's not simply about let's adopt a new technology. It's how do we >>how do we keep our workforce >>engaged? How do we make sure that they've got the right training? How do we bring our our I. T. Team along for this. Hopefully new and fun and exciting journey where they get to learn some interesting new technologies they've got all this very much accumulated business knowledge they still want to put to use, maybe they're a little bit apprehensive about something brand new and they hear about the cloud, but there by and large, they really want to move forward. They just need a little bit of >>help to make it happen >>real good guys. One of the things you're gonna hear today, we're talking about speed traditionally going fast. Oftentimes you meant you have to sacrifice some things on quality and what you're going to hear from some of the startups today is how they're addressing that to automation and modern devoPS technologies and sort of rethinking that whole application development approach. That's something I'm really excited to see organization is beginning to adopt so they don't have to make that tradeoff anymore. >>Yeah, I would >>never want to see someone >>sacrifice quality, >>but I do think that iterating very quickly and using the best of devoPS principles to be able to iterate incredibly quickly and get that first launch out there and then listen with both ears just >>as much >>as you can, Everything. You hear iterate really quickly to meet those needs in, in hours and days, not months, quarters or years. >>Great stuff. Chef and a lot of the companies were featuring here in the startup showcase represent that new kind of thinking, um, systems thinking as well as you know, the cloud scale and again and it's finally here, the revolution of deVOps is going to the next generation and uh, we're excited to have Emily Freeman who's going to come on and give a little preview for her new talk on this revolution. So Jeff, thank you for coming on, appreciate you sharing the update here on the cube. Happy >>to be. I'm actually really looking forward to hearing from Emily. >>Yeah, it's great. Great. Looking forward to the talk. Brand new Premier, Okay, uh, lisa martin, Emily Freeman is here. She's ready to come in and we're going to preview her lightning talk Emily. Um, thanks for coming on, we really appreciate you coming on really, this is about to talk around deVOPS next gen and I think lisa this is one of those things we've been, we've been discussing with all the companies. It's a new kind of thinking it's a revolution, it's a systems mindset, you're starting to see the connections there she is. Emily, Thanks for coming. I appreciate it. >>Thank you for having me. So your teaser video >>was amazing. Um, you know, that little secret radical idea, something completely different. Um, you gotta talk coming up, what's the premise behind this revolution, you know, these tying together architecture, development, automation deployment, operating altogether. >>Yes, well, we have traditionally always used the sclc, which is the software delivery life cycle. Um, and it is a straight linear process that has actually been around since the sixties, which is wild to me um, and really originated in manufacturing. Um, and as much as I love the Toyota production system and how much it has shown up in devops as a sort of inspiration on how to run things better. We are not making cars, we are making software and I think we have to use different approaches and create a sort of model that better reflects our modern software development process. >>It's a bold idea and looking forward to the talk and as motivation. I went into my basement and dusted off all my books from college in the 80s and the sea estimates it was waterfall. It was software development life cycle. They trained us to think this way and it came from the mainframe people. It was like, it's old school, like really, really old and it really hasn't been updated. Where's the motivation? I actually cloud is kind of converging everything together. We see that, but you kind of hit on this persona thing. Where did that come from this persona? Because you know, people want to put people in buckets release engineer. I mean, where's that motivation coming from? >>Yes, you're absolutely right that it came from the mainframes. I think, you know, waterfall is necessary when you're using a punch card or mag tape to load things onto a mainframe, but we don't exist in that world anymore. Thank goodness. And um, yes, so we, we use personas all the time in tech, you know, even to register, well not actually to register for this event, but a lot events. A lot of events, you have to click that drop down. Right. Are you a developer? Are you a manager, whatever? And the thing is personas are immutable in my opinion. I was a developer. I will always identify as a developer despite playing a lot of different roles and doing a lot of different jobs. Uh, and this can vary throughout the day. Right. You might have someone who has a title of software architect who ends up helping someone pair program or develop or test or deploy. Um, and so we wear a lot of hats day to day and I think our discussions around roles would be a better, um, certainly a better approach than personas >>lease. And I've been discussing with many of these companies around the roles and we're hearing from them directly and they're finding out that people have, they're mixing and matching on teams. So you're, you're an S R E on one team and you're doing something on another team where the workflows and the workloads defined the team formation. So this is a cultural discussion. >>It absolutely is. Yes. I think it is a cultural discussion and it really comes to the heart of devops, right? It's people process. And then tools deVOps has always been about culture and making sure that developers have all the tools they need to be productive and honestly happy. What good is all of this? If developing software isn't a joyful experience. Well, >>I got to ask you, I got you here obviously with server list and functions just starting to see this kind of this next gen. And we're gonna hear from jerry Chen, who's a Greylock VC who's going to talk about castles in the clouds, where he's discussing the moats that could be created with a competitive advantage in cloud scale. And I think he points to the snowflakes of the world. You're starting to see this new thing happening. This is devops 2.0, this is the revolution. Is this kind of where you see the same vision of your talk? >>Yes, so DeVOps created 2000 and 8, 2000 and nine, totally different ecosystem in the world we were living in, you know, we didn't have things like surveillance and containers, we didn't have this sort of default distributed nature, certainly not the cloud. Uh and so I'm very excited for jerry's talk. I'm curious to hear more about these moz. I think it's fascinating. Um but yeah, you're seeing different companies use different tools and processes to accelerate their delivery and that is the competitive advantage. How can we figure out how to utilize these tools in the most efficient way possible. >>Thank you for coming and giving us a preview. Let's now go to your lightning keynote talk. Fresh content. Premier of this revolution in Devops and the Freemans Talk, we'll go there now. >>Hi, I'm Emily Freeman, I'm the author of devops for dummies and the curator of 97 things every cloud engineer should know. I am thrilled to be here with you all today. I am really excited to share with you a kind of a wild idea, a complete re imagining of the S DLC and I want to be clear, I need your feedback. I want to know what you think of this. You can always find me on twitter at editing. Emily, most of my work centers around deVOps and I really can't overstate what an impact the concept of deVOPS has had on this industry in many ways it built on the foundation of Agile to become a default a standard we all reach for in our everyday work. When devops surfaced as an idea in 2008, the tech industry was in a vastly different space. AWS was an infancy offering only a handful of services. Azure and G C P didn't exist yet. The majority's majority of companies maintained their own infrastructure. Developers wrote code and relied on sys admins to deploy new code at scheduled intervals. Sometimes months apart, container technology hadn't been invented applications adhered to a monolithic architecture, databases were almost exclusively relational and serverless wasn't even a concept. Everything from the application to the engineers was centralized. Our current ecosystem couldn't be more different. Software is still hard, don't get me wrong, but we continue to find novel solutions to consistently difficult, persistent problems. Now, some of these end up being a sort of rebranding of old ideas, but others are a unique and clever take to abstracting complexity or automating toil or perhaps most important, rethinking challenging the very premises we have accepted as Cannon for years, if not decades. In the years since deVOps attempted to answer the critical conflict between developers and operations, engineers, deVOps has become a catch all term and there have been a number of derivative works. Devops has come to mean 5000 different things to 5000 different people. For some, it can be distilled to continuous integration and continuous delivery or C I C D. For others, it's simply deploying code more frequently, perhaps adding a smattering of tests for others. Still, its organizational, they've added a platform team, perhaps even a questionably named DEVOPS team or have created an engineering structure that focuses on a separation of concerns. Leaving feature teams to manage the development, deployment, security and maintenance of their siloed services, say, whatever the interpretation, what's important is that there isn't a universally accepted standard. Well, what deVOPS is or what it looks like an execution, it's a philosophy more than anything else. A framework people can utilize to configure and customize their specific circumstances to modern development practices. The characteristic of deVOPS that I think we can all agree on though, is that an attempted to capture the challenges of the entire software development process. It's that broad umbrella, that holistic view that I think we need to breathe life into again, The challenge we face is that DeVOps isn't increasingly outmoded solution to a previous problem developers now face. Cultural and technical challenge is far greater than how to more quickly deploy a monolithic application. Cloud native is the future the next collection of default development decisions and one the deVOPS story can't absorb in its current form. I believe the era of deVOPS is waning and in this moment as the sun sets on deVOPS, we have a unique opportunity to rethink rebuild free platform. Even now, I don't have a crystal ball. That would be very handy. I'm not completely certain with the next decade of tech looks like and I can't write this story alone. I need you but I have some ideas that can get the conversation started, I believe to build on what was we have to throw away assumptions that we've taken for granted all this time in order to move forward. We must first step back. Mhm. The software or systems development life cycle, what we call the S. D. L. C. has been in use since the 1960s and it's remained more or less the same since before color television and the touch tone phone. Over the last 60 or so odd years we've made tweaks, slight adjustments, massaged it. The stages or steps are always a little different with agile and deVOps we sort of looped it into a circle and then an infinity loop we've added pretty colors. But the sclc is more or less the same and it has become an assumption. We don't even think about it anymore, universally adopted constructs like the sclc have an unspoken permanence. They feel as if they have always been and always will be. I think the impact of that is even more potent. If you were born after a construct was popularized. Nearly everything around us is a construct, a model, an artifact of a human idea. The chair you're sitting in the desk, you work at the mug from which you drink coffee or sometimes wine, buildings, toilets, plumbing, roads, cars, art, computers, everything. The sclc is a remnant an artifact of a previous era and I think we should throw it away or perhaps more accurately replace it, replace it with something that better reflects the actual nature of our work. A linear, single threaded model designed for the manufacturer of material goods cannot possibly capture the distributed complexity of modern socio technical systems. It just can't. Mhm. And these two ideas aren't mutually exclusive that the sclc was industry changing, valuable and extraordinarily impactful and that it's time for something new. I believe we are strong enough to hold these two ideas at the same time, showing respect for the past while envisioning the future. Now, I don't know about you, I've never had a software project goes smoothly in one go. No matter how small. Even if I'm the only person working on it and committing directly to master software development is chaos. It's a study and entropy and it is not getting any more simple. The model with which we think and talk about software development must capture the multithreaded, non sequential nature of our work. It should embody the roles engineers take on and the considerations they make along the way. It should build on the foundations of agile and devops and represent the iterative nature of continuous innovation. Now, when I was thinking about this, I was inspired by ideas like extreme programming and the spiral model. I I wanted something that would have layers, threads, even a way of visually representing multiple processes happening in parallel. And what I settled on is the revolution model. I believe the visualization of revolution is capable of capturing the pivotal moments of any software scenario. And I'm going to dive into all the discrete elements. But I want to give you a moment to have a first impression, to absorb my idea. I call it revolution because well for one it revolves, it's circular shape reflects the continuous and iterative nature of our work, but also because it is revolutionary. I am challenging a 60 year old model that is embedded into our daily language. I don't expect Gartner to build a magic quadrant around this tomorrow, but that would be super cool. And you should call me my mission with. This is to challenge the status quo to create a model that I think more accurately reflects the complexity of modern cloud native software development. The revolution model is constructed of five concentric circles describing the critical roles of software development architect. Ng development, automating, deploying and operating intersecting each loop are six spokes that describe the production considerations every engineer has to consider throughout any engineering work and that's test, ability, secure ability, reliability, observe ability, flexibility and scalability. The considerations listed are not all encompassing. There are of course things not explicitly included. I figured if I put 20 spokes, some of us, including myself, might feel a little overwhelmed. So let's dive into each element in this model. We have long used personas as the default way to do divide audiences and tailor messages to group people. Every company in the world right now is repeating the mantra of developers, developers, developers but personas have always bugged me a bit because this approach typically either oversimplifies someone's career are needlessly complicated. Few people fit cleanly and completely into persona based buckets like developers and operations anymore. The lines have gotten fuzzy on the other hand, I don't think we need to specifically tailor messages as to call out the difference between a devops engineer and a release engineer or a security administrator versus a security engineer but perhaps most critically, I believe personas are immutable. A persona is wholly dependent on how someone identifies themselves. It's intrinsic not extrinsic. Their titles may change their jobs may differ, but they're probably still selecting the same persona on that ubiquitous drop down. We all have to choose from when registering for an event. Probably this one too. I I was a developer and I will always identify as a developer despite doing a ton of work in areas like devops and Ai Ops and Deverell in my heart. I'm a developer I think about problems from that perspective. First it influences my thinking and my approach roles are very different. Roles are temporary, inconsistent, constantly fluctuating. If I were an actress, the parts I would play would be lengthy and varied, but the persona I would identify as would remain an actress and artist lesbian. Your work isn't confined to a single set of skills. It may have been a decade ago, but it is not today in any given week or sprint, you may play the role of an architect. Thinking about how to design a feature or service, developer building out code or fixing a bug and on automation engineer, looking at how to improve manual processes. We often refer to as soil release engineer, deploying code to different environments or releasing it to customers or in operations. Engineer ensuring an application functions inconsistent expected ways and no matter what role we play. We have to consider a number of issues. The first is test ability. All software systems require testing to assure architects that designs work developers, the code works operators, that infrastructure is running as expected and engineers of all disciplines that code changes won't bring down the whole system testing in its many forms is what enables systems to be durable and have longevity. It's what reassures engineers that changes won't impact current functionality. A system without tests is a disaster waiting to happen, which is why test ability is first among equals at this particular roundtable. Security is everyone's responsibility. But if you understand how to design and execute secure systems, I struggle with this security incidents for the most part are high impact, low probability events. The really big disasters, the one that the ones that end up on the news and get us all free credit reporting for a year. They don't happen super frequently and then goodness because you know that there are endless small vulnerabilities lurking in our systems. Security is something we all know we should dedicate time to but often don't make time for. And let's be honest, it's hard and complicated and a little scary def sec apps. The first derivative of deVOPS asked engineers to move security left this approach. Mint security was a consideration early in the process, not something that would block release at the last moment. This is also the consideration under which I'm putting compliance and governance well not perfectly aligned. I figure all the things you have to call lawyers for should just live together. I'm kidding. But in all seriousness, these three concepts are really about risk management, identity, data, authorization. It doesn't really matter what specific issue you're speaking about, the question is who has access to what win and how and that is everyone's responsibility at every stage site reliability engineering or sorry, is a discipline job and approach for good reason. It is absolutely critical that applications and services work as expected. Most of the time. That said, availability is often mistakenly treated as a synonym for reliability. Instead, it's a single aspect of the concept if a system is available but customer data is inaccurate or out of sync. The system is not reliable, reliability has five key components, availability, latency, throughput. Fidelity and durability, reliability is the end result. But resiliency for me is the journey the action engineers can take to improve reliability, observe ability is the ability to have insight into an application or system. It's the combination of telemetry and monitoring and alerting available to engineers and leadership. There's an aspect of observe ability that overlaps with reliability, but the purpose of observe ability isn't just to maintain a reliable system though, that is of course important. It is the capacity for engineers working on a system to have visibility into the inner workings of that system. The concept of observe ability actually originates and linear dynamic systems. It's defined as how well internal states of a system can be understood based on information about its external outputs. If it is critical when companies move systems to the cloud or utilize managed services that they don't lose visibility and confidence in their systems. The shared responsibility model of cloud storage compute and managed services require that engineering teams be able to quickly be alerted to identify and remediate issues as they arise. Flexible systems are capable of adapting to meet the ever changing needs of the customer and the market segment, flexible code bases absorb new code smoothly. Embody a clean separation of concerns. Are partitioned into small components or classes and architected to enable the now as well as the next inflexible systems. Change dependencies are reduced or eliminated. Database schemas accommodate change well components, communicate via a standardized and well documented A. P. I. The only thing constant in our industry is change and every role we play, creating flexibility and solutions that can be flexible that will grow as the applications grow is absolutely critical. Finally, scalability scalability refers to more than a system's ability to scale for additional load. It implies growth scalability and the revolution model carries the continuous innovation of a team and the byproducts of that growth within a system. For me, scalability is the most human of the considerations. It requires each of us in our various roles to consider everyone around us, our customers who use the system or rely on its services, our colleagues current and future with whom we collaborate and even our future selves. Mhm. Software development isn't a straight line, nor is it a perfect loop. It is an ever changing complex dance. There are twirls and pivots and difficult spins forward and backward. Engineers move in parallel, creating truly magnificent pieces of art. We need a modern model for this modern era and I believe this is just the revolution to get us started. Thank you so much for having me. >>Hey, we're back here. Live in the keynote studio. I'm john for your host here with lisa martin. David lot is getting ready for the fireside chat ending keynote with the practitioner. Hello! Fresh without data mesh lisa Emily is amazing. The funky artwork there. She's amazing with the talk. I was mesmerized. It was impressive. >>The revolution of devops and the creative element was a really nice surprise there. But I love what she's doing. She's challenging the status quo. If we've learned nothing in the last year and a half, We need to challenge the status quo. A model from the 1960s that is no longer linear. What she's doing is revolutionary. >>And we hear this all the time. All the cube interviews we do is that you're seeing the leaders, the SVP's of engineering or these departments where there's new new people coming in that are engineering or developers, they're playing multiple roles. It's almost a multidisciplinary aspect where you know, it's like going into in and out burger in the fryer later and then you're doing the grill, you're doing the cashier, people are changing roles or an architect, their test release all in one no longer departmental, slow siloed groups. >>She brought up a great point about persona is that we no longer fit into these buckets. That the changing roles. It's really the driver of how we should be looking at this. >>I think I'm really impressed, really bold idea, no brainer as far as I'm concerned, I think one of the things and then the comments were off the charts in a lot of young people come from discord servers. We had a good traction over there but they're all like learning. Then you have the experience, people saying this is definitely has happened and happening. The dominoes are falling and they're falling in the direction of modernization. That's the key trend speed. >>Absolutely with speed. But the way that Emily is presenting it is not in a brash bold, but it's in a way that makes great sense. The way that she creatively visually lined out what she was talking about Is amenable to the folks that have been doing this for since the 60s and the new folks now to really look at this from a different >>lens and I think she's a great setup on that lightning top of the 15 companies we got because you think about sis dig harness. I white sourced flamingo hacker one send out, I oh, okay. Thought spot rock set Sarah Ops ramp and Ops Monte cloud apps, sani all are doing modern stuff and we talked to them and they're all on this new wave, this monster wave coming. What's your observation when you talk to these companies? >>They are, it was great. I got to talk with eight of the 15 and the amount of acceleration of innovation that they've done in the last 18 months is phenomenal obviously with the power and the fuel and the brand reputation of aws but really what they're all facilitating cultural shift when we think of devoPS and the security folks. Um, there's a lot of work going on with ai to an automation to really kind of enabled to develop the develops folks to be in control of the process and not have to be security experts but ensuring that the security is baked in shifting >>left. We saw that the chat room was really active on the security side and one of the things I noticed was not just shift left but the other groups, the security groups and the theme of cultural, I won't say war but collision cultural shift that's happening between the groups is interesting because you have this new devops persona has been around Emily put it out for a while. But now it's going to the next level. There's new revolutions about a mindset, a systems mindset. It's a thinking and you start to see the new young companies coming out being funded by the gray locks of the world who are now like not going to be given the we lost the top three clouds one, everything. there's new business models and new technical architecture in the cloud and that's gonna be jerry Chen talk coming up next is going to be castles in the clouds because jerry chant always talked about moats, competitive advantage and how moats are key to success to guard the castle. And then we always joke, there's no more moz because the cloud has killed all the boats. But now the motor in the cloud, the castles are in the cloud, not on the ground. So very interesting thought provoking. But he's got data and if you look at the successful companies like the snowflakes of the world, you're starting to see these new formations of this new layer of innovation where companies are growing rapidly, 98 unicorns now in the cloud. Unbelievable, >>wow, that's a lot. One of the things you mentioned, there's competitive advantage and these startups are all fueled by that they know that there are other companies in the rear view mirror right behind them. If they're not able to work as quickly and as flexibly as a competitor, they have to have that speed that time to market that time to value. It was absolutely critical. And that's one of the things I think thematically that I saw along the eighth sort of that I talked to is that time to value is absolutely table stakes. >>Well, I'm looking forward to talking to jerry chan because we've talked on the queue before about this whole idea of What happens when winner takes most would mean the top 3, 4 cloud players. What happens? And we were talking about that and saying, if you have a model where an ecosystem can develop, what does that look like and back in 2013, 2014, 2015, no one really had an answer. Jerry was the only BC. He really nailed it with this castles in the cloud. He nailed the idea that this is going to happen. And so I think, you know, we'll look back at the tape or the videos from the cube, we'll find those cuts. But we were talking about this then we were pontificating and riffing on the fact that there's going to be new winners and they're gonna look different as Andy Jassy always says in the cube you have to be misunderstood if you're really going to make something happen. Most of the most successful companies are misunderstood. Not anymore. The cloud scales there. And that's what's exciting about all this. >>It is exciting that the scale is there, the appetite is there the appetite to challenge the status quo, which is right now in this economic and dynamic market that we're living in is there's nothing better. >>One of the things that's come up and and that's just real quick before we bring jerry in is automation has been insecurity, absolutely security's been in every conversation, but automation is now so hot in the sense of it's real and it's becoming part of all the design decisions. How can we automate can we automate faster where the keys to automation? Is that having the right data, What data is available? So I think the idea of automation and Ai are driving all the change and that's to me is what these new companies represent this modern error where AI is built into the outcome and the apps and all that infrastructure. So it's super exciting. Um, let's check in, we got jerry Chen line at least a great. We're gonna come back after jerry and then kick off the day. Let's bring in jerry Chen from Greylock is he here? Let's bring him in there. He is. >>Hey john good to see you. >>Hey, congratulations on an amazing talk and thesis on the castles on the cloud. Thanks for coming on. >>All right, Well thanks for reading it. Um, always were being put a piece of workout out either. Not sure what the responses, but it seemed to resonate with a bunch of developers, founders, investors and folks like yourself. So smart people seem to gravitate to us. So thank you very much. >>Well, one of the benefits of doing the Cube for 11 years, Jerry's we have videotape of many, many people talking about what the future will hold. You kind of are on this early, it wasn't called castles in the cloud, but you were all I was, we had many conversations were kind of connecting the dots in real time. But you've been on this for a while. It's great to see the work. I really think you nailed this. I think you're absolutely on point here. So let's get into it. What is castles in the cloud? New research to come out from Greylock that you spearheaded? It's collaborative effort, but you've got data behind it. Give a quick overview of what is castle the cloud, the new modes of competitive advantage for companies. >>Yeah, it's as a group project that our team put together but basically john the question is, how do you win in the cloud? Remember the conversation we had eight years ago when amazon re event was holy cow, Like can you compete with them? Like is it a winner? Take all? Winner take most And if it is winner take most, where are the white spaces for Some starts to to emerge and clearly the past eight years in the cloud this journey, we've seen big companies, data breaks, snowflakes, elastic Mongo data robot. And so um they spotted the question is, you know, why are the castles in the cloud? The big three cloud providers, Amazon google and Azure winning. You know, what advantage do they have? And then given their modes of scale network effects, how can you as a startup win? And so look, there are 500 plus services between all three cloud vendors, but there are like 500 plus um startups competing gets a cloud vendors and there's like almost 100 unicorn of private companies competing successfully against the cloud vendors, including public companies. So like Alaska, Mongo Snowflake. No data breaks. Not public yet. Hashtag or not public yet. These are some examples of the names that I think are winning and watch this space because you see more of these guys storm the castle if you will. >>Yeah. And you know one of the things that's a funny metaphor because it has many different implications. One, as we talk about security, the perimeter of the gates, the moats being on land. But now you're in the cloud, you have also different security paradigm. You have a different um, new kinds of services that are coming on board faster than ever before. Not just from the cloud players but From companies contributing into the ecosystem. So the combination of the big three making the market the main markets you, I think you call 31 markets that we know of that probably maybe more. And then you have this notion of a sub market, which means that there's like we used to call it white space back in the day, remember how many whites? Where's the white space? I mean if you're in the cloud, there's like a zillion white spaces. So talk about this sub market dynamic between markets and that are being enabled by the cloud players and how these sub markets play into it. >>Sure. So first, the first problem was what we did. We downloaded all the services for the big three clowns. Right? And you know what as recalls a database or database service like a document DB and amazon is like Cosmo dB and Azure. So first thing first is we had to like look at all three cloud providers and you? Re categorize all the services almost 500 Apples, Apples, Apples # one number two is you look at all these markets or sub markets and said, okay, how can we cluster these services into things that you know you and I can rock right. That's what amazon Azure and google think about. It is very different and the beauty of the cloud is this kind of fat long tail of services for developers. So instead of like oracle is a single database for all your needs. They're like 20 or 30 different databases from time series um analytics, databases. We're talking rocks at later today. Right. Um uh, document databases like Mongo search database like elastic. And so what happens is there's not one giant market like databases, there's a database market And 30, 40 sub markets that serve the needs developers. So the Great News is cloud has reduced the cost and create something that new for developers. Um also the good news is for a start up you can find plenty of white speeds solving a pain point, very specific to a different type of problem >>and you can sequence up to power law to this. I love the power of a metaphor, you know, used to be a very thin neck note no torso and then a long tail. But now as you're pointing out this expansion of the fat tail of services, but also there's big tam's and markets available at the top of the power law where you see coming like snowflake essentially take on the data warehousing market by basically sitting on amazon re factoring with new services and then getting a flywheel completely changing the economic unit economics completely changing the consumption model completely changing the value proposition >>literally you >>get Snowflake has created like a storm, create a hole, that mode or that castle wall against red shift. Then companies like rock set do your real time analytics is Russian right behind snowflakes saying, hey snowflake is great for data warehouse but it's not fast enough for real time analytics. Let me give you something new to your, to your parallel argument. Even the big optic snowflake have created kind of a wake behind them that created even more white space for Gaza rock set. So that's exciting for guys like me and >>you. And then also as we were talking about our last episode two or quarter two of our showcase. Um, from a VC came on, it's like the old shelf where you didn't know if a company's successful until they had to return the inventory now with cloud you if you're not successful, you know it right away. It's like there's no debate. Like, I mean you're either winning or not. This is like that's so instrumented so a company can have a good better mousetrap and win and fill the white space and then move up. >>It goes both ways. The cloud vendor, the big three amazon google and Azure for sure. They instrument their own class. They know john which ecosystem partners doing well in which ecosystems doing poorly and they hear from the customers exactly what they want. So it goes both ways they can weaponize that. And just as well as you started to weaponize that info >>and that's the big argument of do that snowflake still pays the amazon bills. They're still there. So again, repatriation comes back, That's a big conversation that's come up. What's your quick take on that? Because if you're gonna have a castle in the cloud, then you're gonna bring it back to land. I mean, what's that dynamic? Where do you see that compete? Because on one hand is innovation. The other ones maybe cost efficiency. Is that a growth indicator slow down? What's your view on the movement from and to the cloud? >>I think there's probably three forces you're finding here. One is the cost advantage in the scale advantage of cloud so that I think has been going for the past eight years, there's a repatriation movement for a certain subset of customers, I think for cost purposes makes sense. I think that's a tiny handful that believe they can actually run things better than a cloud. The third thing we're seeing around repatriation is not necessary against cloud, but you're gonna see more decentralized clouds and things pushed to the edge. Right? So you look at companies like Cloudflare Fastly or a company that we're investing in Cato networks. All ideas focus on secure access at the edge. And so I think that's not the repatriation of my own data center, which is kind of a disaggregated of cloud from one giant monolithic cloud, like AWS east or like a google region in europe to multiple smaller clouds for governance purposes, security purposes or legacy purposes. >>So I'm looking at my notes here, looking down on the screen here for this to read this because it's uh to cut and paste from your thesis on the cloud. The excellent cloud. The of the $38 billion invested this quarter. Um Ai and ml number one, um analytics. Number two, security number three. Actually, security number one. But you can see the bubbles here. So all those are data problems I need to ask you. I see data is hot data as intellectual property. How do you look at that? Because we've been reporting on this and we just started the cube conversation around workflows as intellectual property. If you have scale and your motives in the cloud. You could argue that data and the workflows around those data streams is intellectual property. It's a protocol >>I believe both are. And they just kind of go hand in hand like peanut butter and jelly. Right? So data for sure. I. P. So if you know people talk about days in the oil, the new resource. That's largely true because of powers a bunch. But the workflow to your point john is sticky because every company is a unique snowflake right? Like the process used to run the cube and your business different how we run our business. So if you can build a workflow that leverages the data, that's super sticky. So in terms of switching costs, if my work is very bespoke to your business, then I think that's competitive advantage. >>Well certainly your workflow is a lot different than the cube. You guys just a lot of billions of dollars in capital. We're talking to all the people out here jerry. Great to have you on final thought on your thesis. Where does it go from here? What's been the reaction? Uh No, you put it out there. Great love the restart. Think you're on point on this one. Where did we go from here? >>We have to follow pieces um in the near term one around, you know, deep diver on open source. So look out for that pretty soon and how that's been a powerful strategy a second. Is this kind of just aggregation of the cloud be a Blockchain and you know, decentralized apps, be edge applications. So that's in the near term two more pieces of, of deep dive we're doing. And then the goal here is to update this on a quarterly and annual basis. So we're getting submissions from founders that wanted to say, hey, you missed us or he screwed up here. We got the big cloud vendors saying, Hey jerry, we just lost his new things. So our goal here is to update this every single year and then probably do look back saying, okay, uh, where were we wrong? We're right. And then let's say the castle clouds 2022. We'll see the difference were the more unicorns were there more services were the IPO's happening. So look for some short term work from us on analytics, like around open source and clouds. And then next year we hope that all of this forward saying, Hey, you have two year, what's happening? What's changing? >>Great stuff and, and congratulations on the southern news. You guys put another half a billion dollars into early, early stage, which is your roots. Are you still doing a lot of great investments in a lot of unicorns. Congratulations that. Great luck on the team. Thanks for coming on and congratulations you nailed this one. I think I'm gonna look back and say that this is a pretty seminal piece of work here. Thanks for sharing. >>Thanks john thanks for having us. >>Okay. Okay. This is the cube here and 81 startup showcase. We're about to get going in on all the hot companies closing out the kino lisa uh, see jerry Chen cube alumni. He was right from day one. We've been riffing on this, but he nails it here. I think Greylock is lucky to have him as a general partner. He's done great deals, but I think he's hitting the next wave big. This is, this is huge. >>I was listening to you guys talking thinking if if you had a crystal ball back in 2013, some of the things Jerry saying now his narrative now, what did he have a crystal >>ball? He did. I mean he could be a cuBA host and I could be a venture capital. We were both right. I think so. We could have been, you know, doing that together now and all serious now. He was right. I mean, we talked off camera about who's the next amazon who's going to challenge amazon and Andy Jassy was quoted many times in the queue by saying, you know, he was surprised that it took so long for people to figure out what they were doing. Okay, jerry was that VM where he had visibility into the cloud. He saw amazon right away like we did like this is a winning formula and so he was really out front on this one. >>Well in the investments that they're making in these unicorns is exciting. They have this, this lens that they're able to see the opportunities there almost before anybody else can. And finding more white space where we didn't even know there was any. >>Yeah. And what's interesting about the report I'm gonna dig into and I want to get to him while he's on camera because it's a great report, but He says it's like 500 services I think Amazon has 5000. So how you define services as an interesting thing and a lot of amazon services that they have as your doesn't have and vice versa, they do call that out. So I find the report interesting. It's gonna be a feature game in the future between clouds the big three. They're gonna say we do this, you're starting to see the formation, Google's much more developer oriented. Amazon is much more stronger in the governance area with data obviously as he pointed out, they have such experience Microsoft, not so much their developer cloud and more office, not so much on the government's side. So that that's an indicator of my, my opinion of kind of where they rank. So including the number one is still amazon web services as your long second place, way behind google, right behind Azure. So we'll see how the horses come in, >>right. And it's also kind of speaks to the hybrid world in which we're living the hybrid multi cloud world in which many companies are living as companies to not just survive in the last year and a half, but to thrive and really have to become data companies and leverage that data as a competitive advantage to be able to unlock the value of it. And a lot of these startups that we talked to in the showcase are talking about how they're helping organizations unlock that data value. As jerry said, it is the new oil, it's the new gold. Not unless you can unlock that value faster than your competition. >>Yeah, well, I'm just super excited. We got a great day ahead of us with with all the cots startups. And then at the end day, Volonte is gonna interview, hello, fresh practitioners, We're gonna close it out every episode now, we're going to do with the closing practitioner. We try to get jpmorgan chase data measures. The hottest area right now in the enterprise data is new competitive advantage. We know that data workflows are now intellectual property. You're starting to see data really factoring into these applications now as a key aspect of the competitive advantage and the value creation. So companies that are smart are investing heavily in that and the ones that are kind of slow on the uptake are lagging the market and just trying to figure it out. So you start to see that transition and you're starting to see people fall away now from the fact that they're not gonna make it right, You're starting to, you know, you can look at look at any happens saying how much ai is really in there. Real ai what's their data strategy and you almost squint through that and go, okay, that's gonna be losing application. >>Well the winners are making it a board level conversation >>And security isn't built in. Great to have you on this morning kicking it off. Thanks John Okay, we're going to go into the next set of the program at 10:00 we're going to move into the breakouts. Check out the companies is three tracks in there. We have an awesome track on devops pure devops. We've got the data and analytics and we got the cloud management and just to run down real quick check out the sis dig harness. Io system is doing great, securing devops harness. IO modern software delivery platform, White Source. They're preventing and remediating the rest of the internet for them for the company's that's a really interesting and lumbago, effortless acres land and monitoring functions, server list super hot. And of course hacker one is always great doing a lot of great missions and and bounties you see those success continue to send i O there in Palo alto changing the game on data engineering and data pipe lining. Okay. Data driven another new platform, horizontally scalable and of course thought spot ai driven kind of a search paradigm and of course rock set jerry Chen's companies here and press are all doing great in the analytics and then the cloud management cost side 80 operations day to operate. Ops ramps and ops multi cloud are all there and sunny, all all going to present. So check them out. This is the Cubes Adria's startup showcase episode three.

(upbeat music) >> From around the globe, it's theCUBE with digital coverage of Postgres vision 2021 brought to you by EDB. >> Hello everybody. Welcome back to Postgres Vision 21. My name is Dave Vellante and we're super excited to have Josh Berkus on. He's joining us, he's a leader in the Kubernetes community, extremely well-versed in containerized applications, application development, containerizing databases all things Open-source, CUBE alum, Josh Berkus welcome back to theCUBE. Great to see you again. >> Thank you. I'm glad to be here. >> Just recently, you're coming off KuberCon, we heard some of the themes from that event. There was a lot of focus on inclusion and diversity, which of course, you know, that's the Open-source ethos and a lot of discussion around designing security in, the whole conversation about shift left. That's great to see larger companies giving back, to obviously a lot of the pressure over the years on the big companies that there's a one-way street, they're actually giving back, making some investments. So we love to see that. And just Open-source continues to be the main spring of innovation. I got to say, I got to call-out and a recent Red Hat survey the state of the enterprise Open-source in 2021, 90% of technology leaders said that they're adopting Open-source and made a joke that the other 10% they're doing it they just don't know it. But so what were some of your takeaways from the event and some of the trends you're seeing but specifically as it relates to containers. >> So, I mean, you're right, one thing is this sort of return to security, the security topic again because we've had like a couple of things happen. One was, when we initially got, started doing containers or platform with Docker and with early Kubernetes and that sort of thing we got a lot of container image scan, right? So you have like Clare and Docker has a scanning thing and Amazon and Azure have their own scanning things. And people felt that was kind of good enough for a while but then we both had the solar winds hack. And the thing is like, in the meantime, we've gone from a stage where people were mostly using Kubernetes in dev to people using Kubernetes in production. And there's a lot of extra security issues and vulnerabilities that come up in an actual production environment that people just didn't necessarily think about before. And so now we're looking at adding more pieces to the security stack and making those more standard for everyone who uses Kubernetes. And I've had the chance to work with the StackRox folks since they became part of Red Hat. So it's been very exciting to look at the whole thing and look at things like container supply chain because the solar winds showed us obviously, it's not enough to necessarily just trust the vendor. You need to trust their whole supply chain. And it helps to be able to examine that supply chain. >> Yeah, it's very scary when you look at that you're absolutely right. Multiple components of malware coming into an organization through the supply chain cell forming, different signatures. And so it's great to see the community spending time on that and an emphasis on that. Now I got to cut right to the chase here, in 2018, you wrote a two-part blog series it's called Should I run Postgres in Kubernetes? Obviously it's highly relevant for this community. So I want to talk about your perspective, well, first of all, the thing I love about you is you're tactical and you can go deep, but at the same time, you can speak to a business audience. >> Thanks. >> You're welcome and thank you for writing this and communicating the way you do, but talk about when it makes sense and when it doesn't, I mean, that's kind of... My big three takeaways on the pros were simplify, simplify, simplify, especially if you're running application components and other services on Kubernetes but give us the update three years later, why should you, why shouldn't? >> You know let's actually, why don't we zoom out to an even bigger picture? Which is just honestly like every new platform that we've got, right? So when virtualization and VMware became a thing we had the same sort of decisions about when do I move my database to this, when AWS and the public cloud became a thing. I could have like, like if I had written that 12 years ago I could have written it about AWS and it would have had a lot of the same decision tree 'cause what it really sort of comes down to is the more commodifiable a particular database instance is the better candidate it is to move to an advanced infrastructure platform, and the most advanced, currently being Kubernetes. To the extent that you can describe this particular database, what it does, who needs to use it, what's in it in and a simple one pager then that's probably a really good candidate for hosting on Kubernetes. Whereas if you have a database where it's like, Hey, the entire company uses it and it's so complicated we can't describe it's inputs and outputs. That's possibly the last thing in your company that you're going to migrate to Kubernetes, because both in terms of there's less gain to be made there, because the real advantage of moving stuff to Kubernetes is your ability to automate things. The whole way I got into Kubernetes in the first place was I started out way down the line not using containers at all. I was just looking to solve the problem of how do we automate Postgres high availability. That's what I was looking for. And it started out with something I built using SaltStack called handy rep, that Casey and I built. And mostly that was a problem discovery exercise, we discovered what the hard problems were there. And then we moved from that, and then we moved from that to Docker because containers offered an encapsulation strategy because one of the problems you run into when automating high availability is the database actually down or not. And so the first thing that containers offered us was not packaging, what people usually talk about but instead of encapsulation, right, because it's a lot easier to determine is the container running or not, than is the database down or not? Because an actual Postgres database has multiple components and multiple processes that make it up. And some of those can be down without the others being down which can then make you think a database is down that's not actually shut down. And being able to put that in a container, it gives me more of a binary up or down. And then from there, I got into, okay, well but I need to automate a lot of other components. I need to automate the storage and everything else. And that led to Kubernetes. And so if you look at it in terms of deciding when you're going to migrate the database to Kubernetes you look at, can I take advantage of that automation? Is this something that my application workflow and my team organization allows me to do? And if the answer is yes, particularly, if you're in a company that's doing the full dev ops thing where you have a unified development and infra team that owns the entire stack then those people are going to be a really good candidate for moving that stack to Kubernetes. >> Got it. Okay, so let me ask you, in database especially in critical apps, your recovery's everything, when something goes wrong, you got to recover. So if I understand it correctly, just in reading and listening to you, if you've got Kubernetes expertise and you're building applications in that environment then the application components are in there. And am I inferring correctly that you're going to be able to automate and facilitate high quality recovery with certainty? >> Yeah, there's a bunch of infrastructure involved, and this is why, what enterprises do is they move things like the web front-end to Kubernetes first and is what they should do, right? That is absolutely the right order of things to do because the minute that you're looking at bringing databases in, you're now looking at your whole storage infrastructure. So that direct attack storage that was attached physically to one machine is not going to work once you've moved to a container-based cloud. You suddenly need a way to be able to attach that storage to any of the nodes in your cluster so that you can move the database around and you can have fail-over. But once you build those things up, you can't. I mean, some of the stuff that I've done, I work in the office of the CTO now at Red Hat. So I'm not in production support. So the only Postgres instance I'm supporting are ones for some Open-source projects we support like the Python project. And in those cases, it's not a high criticality database, but I'm not support, I'm not on call on the weekend. I want something where it doesn't require need to be on call in order for it to stay up. And so putting that on open shift with the Patroni fail-over driver was the answer for that. And it has failed over in the Red Hat IT team contacts me and says, "Hey, we need to move those servers. And then we'll just add a node to the cluster and delete the old node and it'll do the right thing." And I don't have to worry about it, which is really what you're going for there. >> The other thing I took away from your writing was that you suggested that a lot of the successes in areas where the Postgres databases were rather small and there were a lots of them. And so to the extent that you can automate that you're going to save yourself a lot of problems. Whereas in the flip side if you're running extremely large databases or there may be performance constraint that might be an area to be a little bit more circumspect. >> Yeah and that's absolutely true because like the other side of this, like I've worked with the dev ops people and the people who are on Heroku and that sort of thing that have one database per application, right. And those people are great candidates for migrating. But then I've also worked with the people who have a one big database for the company, where the database is three terabytes in size, it powers their reporting system and their customer's system and the web portal and everything else in one database. That's the one that's really going to be a hard call and that you might in fact, never physically migrate to Kubernetes because even if it's on Kubernetes you are going to mess with the hardware policy to give it its own dedicated machine. So in that case, what I would honestly tend to do is there's a feature in Kubernetes called service catalog that allows you to expose an external service within Kubernetes as if it were a Kubernetes service. And that's what I tend to do with those kinds of databases because it's, there's not a huge advantage in actually physically moving the database to a container. There's a bunch of steps involved and going via service catalog is a lot easier. >> But essentially you're you're speaking the same language in that example that you just gave. >> Yeah. >> Now, the other thing you pointed out at the time that you wrote this article is there's a lot of pre 1.0 kind of alpha in the Kubernetes stack and it might be prudent to if, not putting your HIPAA compliant, since it evolved. >> Yeah, if I was to update two things in the article I guess that would be one of them the other one I'll get to in a minute. So the first one is that, Kubernetes has progressed along that maturity timeline. Like we recently added the production readiness reviews as part of our feature review process. We've really improved tested adherence, so that we're not releasing with known broken tests, and a bunch of other things to make it more stable. But part of it depends on who I'm talking to because there's still degrees here. So if I'm talking to the context of the world of software then Kubernetes has reached the point of maturity that it is as stable as anything else. And if you use a release, you can assume that any sort of major issues have been worked out. The one difference with it and some other platforms people may have used is it's still young enough that backwards compatibility can be an issue. As in Kubernetes releases now three times a year, we've stepped down from four and within three releases you can find yourself needing to change API calls which means needing to refactor parts of your application. So if you compare that with some other things, like a JVM platform, when's the last time you had a major API change with a JVM platform. But you know the Kubernetes is only six years old, so that's part of that. The other thing is the question is I'm talking to the Postgres community, right? Which is within Postgres, people run the daily Postgres snapshot in production. I would not do that with Kubernetes, I would wait for release. So there's still kind of a difference there if people are coming from the Postgres community, right. Is we're used to this really extreme level of stability that we have with Postgres and Kubernetes as a much younger project isn't quite there yet. >> So that's a process, a change that you would have to be aware of if you want to take the benefits of containers with Postgres, you just have to really understand that and make that process part of your change management. >> The other thing I would say has changed is there are new opportunities in running your data warehouse, your big data databases on Kubernetes. A number of platforms, the one I'm most familiar with is Citus, because I worked with those folks that have taken advantage of Kubernetes as a deployment and management platform for their database, their big data database infrastructure, which makes sense because if you look at a lot of modern data analysis and data mining platforms that are built on top of Postgres part of how they do their work is they actually run a bunch of little Postgres instances that they federate together. And then Kubernetes becomes the tool that allows you to manage all of those little Postgres instances. So that's the sort of exception to the, should I migrate this really big database? That can be a yes, if you are migrating it to a big data platform that supports Kubernetes, then it can be a huge advantage. >> Obviously you've got the practitioner knowledge and you were working in the community. I'm wondering if you can share just thinking about sort of the motivation to move to a container environment if you're one of the Postgres folks in the audience could you share any, either anecdotal or other data on business impact, benchmarks that you've seen, some of the things that you've seen some positives there? >> If you actually look at my history when you talk about performance is one, right? And if you actually look at my history, I actually did, and for that matter of some of the folks from Percona and some of our other folks in the database field did a bunch of benchmarks of running Postgres in MySQL, on Kubernetes versus running it not on Kubernetes. And one of the advantages of containers over VMS is that there isn't any intrinsic, there's not any intrinsic sort of layer gap or virtualization that modifies your performance. In other words, if a container is using storage that's present on the node where the container is running it is using that storage through Linux. And therefore the performance is, with some caveats, performance is going to be identical to if you were running that on the host system. Now, where performance differences creep in is that you might not be able to use the same kind of storage. In that Kubernetes and containers systems in general are organized around the idea that no service is using a majority of the resources on the system, so again, if you're planning on user running a larger Postgres database that really needs all the RAM that a system has you're going to have to do a lot of tinkering with Kubernetes configuration to get the same performance, you would have a running it on a dedicated hardware now. >> Okay, but fundamentally you're saying that overhead is less with caveats, like you said, you just mentioned in the story, right? >> Yeah, well, the overhead is not any different from if you were running under the host system. So a really good example of that was, if you go back to on my lightning talking in, (indistinct) Austin, I think. I showed running a benchmark with Postgres on an AWS instance using EBS storage, both not in Kubernetes and in Kubernetes. And there was no perceptible performance difference between the two of them because it was all metered by how fast was EBS for me. >> Right, and I said less, but I should've been more specific less than say you would expect with virtualization. >> Right, and then it just comes down to a business decision, which is that if you're already on some sort of cloud storage or network storage, and again you have databases that can share hardware systems then you shouldn't really expect substantial performance differences by moving to Kubernetes. That's something that you can eliminate inside of words, but if you're going in the process going to be migrating from direct attached storage to network storage then you are going to see a performance difference but that's caused by the change in storage. Or if you're going to be moving from systems that are not shared to systems that aren't shared again you're going to see a difference from them, but it wouldn't be any different than if you did that without Kubernetes containers being involved. >> If you're using any world-class shared storage device from whatever name of big vendor, you're going to accommodate if you're racking and stacking your own flash drives or worse yet spinning disk drives that's in direct attached, that's maybe a different story, so, okay. That's good. Where would you advise people to get started with Postgres and Kubernetes? >> The nice thing is there are a number of advanced systems now, and advanced systems that are supported by the various Postgres vendors. And that can actually be a great place to get started because the systems are Open-source so you can try them out. This is, as far as I know, they're Open-source you can try them out but then if you decide you like them, you can get support. And so that would include Crunchy data. Enterprise DB has a system, and honestly, I have to admit less familiar with than the ones that Crunchy runs. StackRox is another one out of Europe that has their own system for running cloud native Postgres. And there's one I'm forgetting, and what a lot of these have to do with is taking advantage of the automation. 'Cause you can obviously can put Postgres and container play around, right? But your whole point of moving to Kubernetes in general is going to be take advantage of the automation, so you want to look at the various automation platforms and you can go ahead and do that and the one I'm most familiar with because I develop it as Patroni, is the component for automating Postgres. You do Patroni plus you do operators, it's another word that comes in here. But if you're looking at this as a business you're probably going to want something that supported or that at least there's a potential to buy support and a bunch of the different companies in the Postgres space package up these components for you into a platform. Like I know the Crunchy platform uses Patroni plus some proxy stuff, plus PG back rest plus a couple of other things to give you a sort of full automation platform for running Postgres on Kubernetes. >> Awesome, last question. Where are we in the whole container adoption, we started out kind of you've mentioned this stateless and now you're building stateful applications but still you look at the, we look at spending data with our data partners ETR and containers and container orchestration. It's it's right up there with RPA, with cloud, with AI just in terms of the attention and resource that's going in. So it's exploding. It feels like it's still early days. There's a lot of legs left, what do you see? >> Yeah, well, a lot of it is, I mean you're talking about migrating IT infrastructure, right? So where we are with Kubernetes is we have the early adopters, right? We have all the people who were at the point of building their new infrastructure when Kubernetes came out, right. And people who had major unsolved problems which is a big reason for adopting a new platform was just was no old platform for you. and so we sort of have those people and those people are already on Kubernetes and running their stuff there. And so now we're looking at the really long path of people who are not in one of those camps moving, right. And in a lot of cases, that's a matter of coinciding with other reasons why they have to look at an upgrade because even if, whether it's the gradual replacement of old applications by new ones, where you gradually all the legacy applications get offline and the new applications run in Kubernetes or sometimes it's a, "Hey we're waiting for replacement cycle." We're waiting for, we already had plans to move from on-prem to public cloud, and so we're going to move from on-prem to public cloud on Kubernetes, to make it part of the migration. And that'll be years. I still like, I have fingers into other areas, like I still know a lot of people in the nonprofit space and a lot of nonprofits just got around to adopting virtualization, right? Like they're not even at public cloud yet. I don't even talk to them about Kubernetes. There's this huge long tail in terms of adoption. The nice thing is we don't show any signs of stopping, is that one of the things that we kind of learned from earlier stuff particularly learned from our friends at OpenStack was to really really focus on the APIs, to look at who Kubernetes more as the hub of a system of an infrastructure idea with potentially unbounded growth. If you have a new concept that comes in like service mesh, service mesh is not a successor to Kubernetes. It's not an alternative to Kubernetes. It is a thing you layer on top of Kubernetes because we didn't make it exclusive. >> Right. Great, great example going back to OpenStack and thank you for bringing that in because there's lessons learned. And so Josh, we've got to leave it there. Thanks so much for coming back in theCUBE, great conversation, you're awesome. >> Okay, good to talk to you. >> All right, and thank you for watching everybody, keep it right there for more content from Postgres Vision 21. My name is Dave Vellante, you're watching theCUBE. (upbeat music)

(upbeat music) >> The innovation around databases has exploded over the last few years. Not only do organizations continue to rely on database technology to manage their most mission critical business data. But new use cases have emerged that process and analyze unstructured data. They share data at scale, protect data, provide greater heterogeneity. New technologies are being injected into the database equation. Not just cloud which has been a huge force in the space, but also AI to drive better insights and automation, blockchain to protect data and provide better auditability, new file formats to expand the utility of database technology and more. Debates are bound as to who's the best number one, the fastest, the most cloudy, the least expensive, et cetera. But there is no debate, when it comes to leadership and mission critical database technologies. That status goes to Oracle. And with me to talk about the developments of database technology in the market is cube alum Juan Loaiza, who's executive vice president of Mission Critical Database Technology at Oracle. Juan always great to see you, thanks for making some time. >> Thanks, great to see you Dave, always a pleasure to join you. >> Yeah and I hope you have some time because they've got a lot of questions for you. (chuckles) I want to start with- >> All right I love questions. >> Good I want to start and we'll go deep if you're up for it. I want to start with the GoldenGate announcement. We're covering that recent announcement, the service on OCI. GoldenGate it's part of this your super high availability capabilities that Oracle is so well known for. What do we need to know about the new service and what it brings for your customers? >> Yeah, so first of all, GoldenGate is all about creating real time data throughout an enterprise. So it does replication, data integration, moving data into analytic workloads, streaming analytics of data, migrating of databases and making databases highly available. All those are use cases for real-time data movement. And GoldenGate is really the leading product in the market, has been for many years. We have about 80% of the global fortune 500 running GoldenGate today, in addition to thousands and thousands of smaller customers. So it is the premier data integration, replication, high availability, anything involving moving data in real time, GoldenGate is the premier platform. And so we've had that available as a product for many years. And what we just recently done is we've released it as a cloud service, as a fully managed and automated cloud service. So that's kind of the big new thing that's happening right now. >> So is that what's unique about this, is it's now a service, or there are other attributes that are unique to Oracle? >> Yeah, so the service is kind of the most basic part to it. But the big thing about the service is it makes this product dramatically easier to use. So traditionally the data integration, replication products, although very powerful, also are very complex to use. And one of the big benefits of the service is we've made a dramatically simpler. So not just super experts can use it, but anyone can use it. And also as part of releasing it as a cloud service, we've done a number of unique things including making it completely elastically scalable, pay per use and dynamic scalability. So just in time, real time scalability. So as your workload increases we automatically increase the throughput of GoldenGate. So previously you had to figure all this stuff out ahead of time. It was very static. All these products have been very static. Now it's completely dynamic a native cloud product and that's very unique in the market. >> So, I mean, from an availability standpoint, I guess IBM sort of has this with Db2 but it doesn't offer the heterogeneity that GoldenGate has. But at what about like AWS, Microsoft, Google, do they provide services like, like GoldenGate? >> There's really nothing like the GoldenGate service. When you're talking about people like Google and Azure, they really have do it yourself third-party products. So there'll be a third party data integration replication product, and it's kind of available in their marketplace and customers have to do everything. So it's basically a put it together, your own kit. And it's very complicated. I mean these data integration products have always been complicated, and they're even more complicated in the cloud, if you have to do everything yourself. Amazon has a product but it's really focused on basic data migration to their cloud. It doesn't have the same capabilities as Oracle has. It doesn't have the elasticity, it doesn't have pay peruse, so it's really not very clavy at all. >> Well, so I mean the biggest customers have always glommed onto GoldenGate because they need that super ultra high availability. And they're capable of do it yourself. So, tell us how this compares to two DIY. >> Yeah, so you have mentioned the big customers so you're absolutely right. The big customers have been big users of GoldenGate. Smaller customers or users as well, however, it's been challenging because it's complicated. Data integration has been a complicated area of data management. More and most complicated. And so one of the things this does, is that it expands the market. Makes it much dramatically easier for smaller companies that don't have as many it resources to use the product. Also, smaller companies obviously don't have as much data as the really large giants. So they don't have as much data throughput. So traditionally the price has been high for a small customer. But now, with pay per use in the cloud, it eliminates the two big blockers for smaller enterprises. Which are the costs, the high fixed costs and the complexity of the products. So in which, by the way, it's helpful for everyone also. And for big customers they've also struggled with elasticity. So sometimes a huge batch job will kick in, the rate of change increases and suddenly the replication product doesn't keep up. Because on-prem products aren't really very elastic. So it helps large customers as well. Everybody loves these reviews but the elasticity pay per use, on demand nature of it's really helpful for everybody. >> Well, and because it's delivered as a service I would imagine for the large customers that you're giving them more granularity, so they can apply it maybe for a single application, as opposed to trying to have to justify it across a whole suite. And because the cost is higher, but now if you're allowing me to pay by the drink, is that right? I could just sort of apply it in a more granular level. >> Yes, that's exactly right. It's really pay per use. You can use it as much or as little as you want. You just pay for what you use. And as I mentioned, it's not a static payment either. So if you have a lot of data loads going on and right now you pay a little more, at night when you have less going on, you pay a lot less. So you really just paying for what use. It's very easy to set it up for a single application or all your applications. >> How about for things like continuous replication or real-time analytics, is the service designed to support that? >> Yes, so that's the heritage of GoldenGate. GoldenGate has been around for decades and we've worked with some of the most demanding customers in the world on exactly those things. So real time data all over the enterprise is really the goal that everyone wants. Real-time data from OTP and to analytics, from one system to another system, and for availability. That is the key benefit of GoldenGate. And that's the key technology that we've been working on for decades. And now we have it very easy to use in the cloud. >> Well what would be the overheads associated with that? I mean, for instance, you've go it, you need a second copy. You need the other database copies, and where does it make sense to incur that overhead? Obviously the super high availability apps that can exploit real time. Think like fraud detection is the obvious one, but what else can you add there? >> Well, GoldenGate itself doesn't require any extra copies of anything. However, it does enable customers that want to create for example, an analytics system, a data warehouse, to feed data from all their systems in real time into that data warehouse for example. And it also enables the real-time capabilities, enable high availability and you can get high availability within the cloud with it, between on premises in the cloud, between clouds. Also, you can migrate data. Migrate databases without having to take them down. So all these capabilities are available now and they're very easy to use. >> Okay. Thanks for that clarification. What about autonomous? Is that on the roadmap or what you thinking? >> Yeah, the GoldenGate is essentially an autonomous service. And it works with the Oracle Autonomous Database. So you can both use it as a source for data and as a sink for data, as a place you're writing data. So for example, you can have an autonomous OTP database, that's replicating to another autonomous OTP database in real time. And both of them are replicating changes to the autonomous data warehouse. But it doesn't all have to be autonomous. You can have any mix of, autonomous not autonomous, on-prem in cloud, in anybody's cloud. So that's the beauty of GoldenGate, It's extremely flexible. >> Well, you mentioned the plasticity a couple of times. I mean, why is that so important that that GoldenGate on OCI gives you that elastic, whatever billing the auto-scaling talk, talk to me in terms of what that does for the customer. >> Yeah, there's really two big benefits. One benefit is it's very difficult to predict workloads. So normally on an on-prem configuration, you have to say, okay what is the max possible workload that's going to happen here? And then you have to buy the product, configure the product, get hardware, basically size, everything for that. And then if you guess wrong, you're either spending too much because you oversized it or you have a big data real-time problem. The data can't keep up with the real-time because you've undersized the configuration. So that's hard to do. So the beauty of elasticity and the dynamic elasticity, the pay per use, is you don't have to figure all this stuff out. So if you have more workload, we grow it automatically. If you have less workload, we shrink it automatically. And you don't have to guess ahead of time. You don't have to price ahead of time. So you, you just use what, what you use, right? You don't pay for something that you're not using. So it's a very big change in the whole model of how you use these data, replication, integration, high availability technologies. >> Well, I think I'm correct to say GoldenGate primarily has been for big companies. You mentioned that small companies can now take advantage of this service. We talked about the granularity. And I could definitely see, can they afford it? I guess this is part one and then, and then the other part of the question is, I can see GoldenGate really satisfying your on-prem customers and them taking advantage of it, but do you think this will attract new customers beyond your core? So two part question there. >> Yeah, absolutely. So small customers have been challenged by the complexity of data integration. And that's one of the great things about the cloud services is it's dramatically simpler. So Oracle manages everything. Oracle does the patching, the upgrades. Oracle does the monitoring. It takes care of the high availability of the product. So all that management, complexity, all the configuration set up, everything like that, that's all automated, that's owned by Oracle. So small customers were always challenged by the complexity of product, along with everything else that they had to do. And then the other of course benefit is small customers were challenged by the large fixed price. So now with pay per use, they pay only for what they use. It's really usable by easily by small customers also. So it really expands the market and makes it more broadly applicable. >> So kind of same answer for beyond your existing customer base, beyond the on-prem that that's kind of... You answered >> Right. >> my two part question with one answer, so that was pretty efficient, (chuckles) pun intended. So the bottom line for me and squinting through this announcement is you've got the heterogeneity piece with GoldenGate OCI and as such it's going to give you the capability to create what I'll call an architecturally coherent decentralized data mesh. Big on this data mesh these days, could have decentralized data. With the proviso then I going to be able to connect to OCI, which of course you can do with Azure or I guess you could bring cloud to a customer on prem, first of all, is this correct? And can we expect you over time to do this with AWS or other cloud providers? >> It can move data from Amazon or to Amazon. It can actually handle, any data wherever it lives. So, yeah, it's very flexible and it's really just the automation of all the management, that we're running in our public cloud But the data can be from anywhere to anywhere. >> Cool, all right, let's switch topics here a little bit. Just talk about some of the things that you've been working on, some of the innovation. I sat through your blockchain announcement, it was very cool. Of course I love anything blockchain and crypto, NFTs are exploding, so that Coinbase IPO. It's just really an exciting time out there. I think a lot of people don't really appreciate the innovation that's occurring. So you've been making a lot of big announcements last several months. You've been taking your R and D bringing it into product, So that's great, we love to always see that because that's where really the rubber meets the road. Just for the database side of the house, you announced 21c the next generation of the self-driving data warehouse, ADW, blockchain tables, now you got GoldenGate running on OCI. Take us inside the development organizations. What are the underlying drivers other than your boss. >> When we talk about our autonomous database, it is the mission critical Oracle database, but it's dramatically easier to do. So Oracle does all the management all on automation, but also we use machine learning to tune, and to make it highly available, and to make it highly secure. So that that's been one of our biggest products we've been working on for many years. And recently we enhanced our autonomous data warehouse taking it beyond being a data warehouse to complete a data analytics platform. So it includes things like ETL. So we built ETL into the autonomous data warehouse. We're building our GoldenGate replication into autonomous data warehousing. We built machine learning directly natively into the database. So now, if someone wants to run some machine learning they just run a machine learning queries. They no longer have to stand up a separate system. So a big move that we've been making is, taking it beyond just a database to a full analytic platform. And this goes beyond what anyone else in the industry is doing, because we have a lot more technology. So for example, the ML machine learning directly in the database, the ETL directly in the database. The data replication is directly in the database. All these things are very unique to Oracle. And they dramatically simplify for customers how they manage data. In addition to that, we've also been working in our database product. We've enhanced it tremendously. So our big goal there is to provide what we call it converged database. So everything you need, all the data types. Whether it's JSON, relational, spatial, graph, all that different kinds of data types, all the different kinds of workloads. Analytics, OTP, things like blockchain, microservices events, all built into the Oracle database, making it dramatically easier to both develop and deploy new applications. So those are some of our big, big goals. Make it simple, make it integrated. Take the complexity, we'll take on the complexity. So developers and customers find it easy to develop an easy to use. And we've made huge strides in all these areas in the last couple of years. >> That's awesome. I wonder if we could land on blockchain again for now it's kind of jogging, but sort of on crypto. Though you're not about crypto but you are about applying blockchain. Maybe you can help our audience understand what are some of the real use cases where blockchain tech can be used with Oracle database. >> Yeah, so that's a very interesting topic. As you mentioned, blockchain is very currently, we see a lot of cryptocurrencies. I distributed applications for blockchain. So in general, in the past, we've had two worlds. We've had the enterprise data management world and we've had the blockchain world. And these are very distinct, right? And on the blockchain side the applications have mostly centered around, distributed multi-party applications, right? So where you have multiple parties that all want to reach consensus and then that consensus is stored in a blockchain. So that's kind of been the focus of blockchain. And what we've done is very innovative. We're the first company to ever do this. Is we've taken the core architecture, ideas. And really a lot of it has to do with the cryptography of blockchain. And we've built, we've engineered that natively into the mainstream Oracle database. So now in mainstream Oracle database, we have blockchain technology built in. And it's very dramatically simpler to use. And the use cases, you asked about the use case, that's what we've done. And it's taken us about five years to do this. Now it's been released into the market in our mainstream 19c Oracle database. So the use case is different from the conventional blockchain use case. Which I mentioned was really multi-party consensus based apps. We're trying to make blockchain useful for mainstream, enterprise and government applications. So any kind of mainstream government application, or enterprise application. And that idea of blockchain, the core concept of blockchain, is it addresses a different kind of security problem. So when you look at conventional security, it's really trying to keep people out. So we have things like firewalls, passwords, networking cryption, data encryption. It's all about keeping bad people out of the data. And there's really two big problems that it doesn't address well. One problem is that there's always new security exploits being published. So you have hackers out there that are working overtime. Sometimes they're nation States that are trying to attack data providers. And every week, every month there's a new security exploit that's discovered and this happens all the time. So that's one big problem. So we're building up these elaborate walls of protection around our core data assets. And in the meantime, we have basically barbarians attacking on every side.(chuckles) And every once in a while, they get over the walls and this is just what's happening. So that's one big problem. And the second big problem is elicit changes made by people with credentials. So sometimes you have an insider in your, in your company. Whether it's an administrator or a sales person, a support person, that has valid credentials, but then uses those valid credentials in some illicit way. They go out and change somebody's data for their own gain. And even more common than that cause there's not that many bad guys inside the company to they exist, is stolen credentials. So what's happened in many cases is hackers or nation States will steal for example, administrative credentials and then use those administrative credentials to come into a system and steal data. So that's the kind of problem that is not well addressed by security mechanism. So if you have privileges security mechanism says, yeah you're fine. If somebody steals your privileges, again you get the pass through the gate. And so what we've done with blockchain is we've taken the cryptography elements of blockchain. We call it crypto secure data management. And we've built those into the Oracle database. So think of it this way. If someone actually makes it through over the walls that we built, and in into the core data, what we've done with that cryptographic technology of blockchain, is we've made that immutable. So you can't change it. So even if you make it over the gate you can't get into the core data assets and change those assets. And that's not built into Oracle databases is super easy to adopt. And I think it's going to really enhance and expand the community of people that can actually use that blockchain technology. >> I mean, that's awesome. I could talk all day about blockchain. And I mean, when you think about hackers, it's all there. They're all about ROI, value over cost. And if you can increase the denominator they're going to go somewhere else, right? Because the value will will decline. And this is really the intersection of software engineering cryptography. And I guess even when you bring crypto currency into it, it's like sort of the game theory. That's really kind of not what you're all about, but the first two pieces are really critical in terms of just next generation of raising that security hurdle. Love it. Now, go ahead. >> Yeah it's a different approach. I was just going to say, it's a different approach. Because think about trying to keep people out with things like passwords and firewalls, you can have basically bugs in that software that allow people to exploit and get in. When you're talking about cryptography, that's math, it's very difficult. I mean, you really can't fight pass math. Once the data is cryptographically protected on a blockchain, a hacker can't really do anything with that. It's just, math is math. There's nothing you can do to break it, right. It's very different from trying to get through some algorithm. That's really trying to keep you out. >> Awesome. I said, I could talk forever on this topic. But let me, let me go into some competitive dynamics. You recently announced Autonomous Data Warehouse. You've got service capabilities that are really trying to appeal to the line of business. I want to get your take on that announcement and specifically how you think it compares name names. I'm going to name names you don't have to. But Snowflake, obviously a lot of momentum in the marketplace. AWS with Redshift is doing very, very well. Obviously there are others. But those are two prominent ones that we've tracked in our data shows that have momentum. How do you compare? >> Yeah, so there's a number of different ways to look at the comparison. So the most simplest and straightforward is there's a lot more functionality in Oracle data warehousing. Oracle has been doing this for decades. We have a lot of built-in functionality. For example, machine learning natively built into the database makes it super easy to use. We have mixed workloads, we have spatial capabilities. We have graph capabilities. We have JSON capabilities. We have a microservice capabilities. We have-- So there's a lot more capabilities. So that's number one. Number two, our cloud service is dramatically more elastic. So with our cloud service all you really do, is you basically move the slide. You say hey, I want more resources, I want less resources. In fact, we'll do that automatically, that's called auto-scaling. In contrast when you look at people like Snowflake or Redshift they want you to stand up a new cluster. Hey you have some more workload on Monday, stand up another cluster and then we'll have two sets of clusters or maybe you'd want a third cluster, maybe you want a fourth cluster. So you end up with all these different systems which is how they scale. They say, hey, I can have multiple sets of servers access the same data. With Oracle you don't have to even think about those things. We auto scale, you get more workload. We just give it more resources. You don't even have to think about that. And then the other thing is we're looking at the whole data management end to end problem. So starting with capturing the data, moving the data in real time, transforming the data, loading the data, running machine learning and analytics on the data. Putting all kinds of data in a single place that you can do analytics on all of it together. And then having very rich screen capabilities for viewing the data, graphing the data, modeling the data, all those things. So it's all integrated. It makes it super easy to use. So a much easier, much more functionality and much more elastic than any of our competitors in the market. >> Interesting, thank you for those comments. I mean, it's a different world, right? I mean, you guys got all the market share, they got all the growth, those things over time, you've been around, you see it, they come together and you fight it out and may the best approach wins. >> So we'll be watching >> Yeah also I forgot to mention the obvious thing, which is Oracle runs everywhere. So you can run Oracle on premises. You can run Oracle on the public cloud. You can run what we call cloud at customer. Our competitors really are just public cloud only. So you customers don't get the choice of where they want to run their data warehouse. >> Now Juan a while ago I sat down with David foyer and Mark steamer. We reviewed how Gartner looks at the marketplace and it wasn't surprise that when it came to operational workloads, Oracle stood out. I mean, that's kind of an understatement relative to the major competitors. Most of our viewers, I don't think expected for instance Microsoft or AWS to be that far away from you. But at the same time, the database magic quadrant maybe didn't reflect that gap as widely. So there's some dissonance there with the detailed workload drill downs were dramatic. And I wonder what your take on the results. I mean, obviously you're happy with them. You came out leading in virtually every category or you will one and two, and some of that sort of not even non-mission critical operational stuff. But what can you add to my narrative there? >> Yeah, so Gartner, first of all, we're talking about cloud databases. >> Right. >> Right, so this is not on premises databases this is pure cloud databases. And what they did is they did two things. One is, the main thing was a technical rating of the databases, of the cloud databases. And, there's other vendors that have been had database in the cloud for longer than we have. But in the most recent Gartner analysis report, as you mentioned, Oracle came out on top for cloud database technology, in almost every single operational use case including things like Internet of Things, things like JSON data, variable data, analytics as well as a traditional OTP and mixed workloads. So Oracle was rated the highest technology which isn't a big surprise. We've been doing this for decades. Over 90% of the global fortune 500 run Oracle. And there's a reason, because this is what we're good at. This our core strength. Our availability, our security, our scalability, our functionality, both for OTP and analytics. All the capabilities, built-in machine learning, graph analytics, everything. So even when we compare narrowly things like Internet of Things or variable data against niche competitors that that's what all they do. We came up dramatically ahead. But what surprised a lot of people is how far ahead of some of the other cloud vendors like Amazon, like Azure, like Google, Oracle came out ahead in the cloud database category. So a lot of people think, well, some of these other pure cloud vendors must be ahead of Oracle in cloud database. But actually not. I mean, if you look at the Gartner analyst report, it was very clear. It was Oracle was dramatically ahead of their cloud database technologies with our cloud database. >> So I'm pretty much out of time but last question. I've had some interesting discussions lately and we've pointed out for years in our research that of course you're delivering the entire stack, the database, part of the infrastructure the applications, you have the whole engineered system strategy. And for the most part you're kind of unique in this regard. I mean, Dell just announced that it's spinning off VMware and it could have gone the other direction. And become more integrated hardware and software player, for the data center. But look, it's working for Dell based on the reaction, from the street post announcement. Cisco they got a hardware and software model that's sort of integrated but the company's value that peaked back in the .com boom, it's been very slow to bounce back. But my point is for these companies the street doesn't value, the integrated model. Oracle is kind of the exception. You know, it's at trading at all time highs, I know you're not going to comment on the stock price, but I guess in SAP until it missed it guided conservatively, was kind of on the good trajectory. But so I'm wondering, why do you think Oracle strategy resonates with investors, but not so much those companies? Is it, because you have the applications piece? I mean, maybe that's kind of my premise for, for SAP but what's your take? Why is it working for you? >> Well, okay. I think it's pretty simple, which is some of our competitors, for example, they might have a software product and a hardware product. But mostly those are acquired in their separate products that just happen to be in a portfolio. They are not a single company with a single vision and joint engineering going on. It's really, hey, I got the software on over here. I got the hardware over there, but they don't really talk to each other, they don't really work together. They're not trying to develop something where the stack is actually not just integrated but engineered together. And that is really the key. Oracle focuses on data management top to bottom. So we have everything from our ERP, CRM applications talking to our database, talking to our engineered systems, running in our cloud. And it's all completely engineered together. So Oracle doesn't just acquire these things and kind of glue them together. We actually engineer them and that's fundamentally the difference. You can buy two things and have them as two separate divisions in your company but it doesn't really get you a whole lot. >> Juan it's always a pleasure, I love these conversations and hope we can do more in the future. Really appreciate your time. Thanks for coming to the CUBE >> Pleasure, Dave nice to talk to you. >> All right keep it right there, everybody. This is Dave Vellante for theCUBE, we'll see you next time. (upbeat musiC)

>>From around the globe. It's the cube with digital coverage of AWS reinvent 2020 sponsored by Intel, AWS, and our community partners. >>Hi everyone. Welcome back to the cubes. Virtual coverage of AWS reinvent 2020 virtual. We are the cube virtual I'm John ferry, your host with my coach, Dave Alante for keynote analysis from Swami's machine learning, all things, data huge. Instead of announcements, the first ever machine learning keynote at a re-invent Dave. Great to see you. Thanks Johnny. And from Boston, I'm here in Palo Alto. We're doing the cube remote cube virtual. Great to see you. >>Yeah, good to be here, John, as always. Wall-to-wall love it. So, so, John, um, how about I give you my, my key highlights from the, uh, from the keynote today, I had, I had four kind of curated takeaways. So the first is that AWS is, is really trying to simplify machine learning and use machine intelligence into all applications. And if you think about it, it's good news for organizations because they're not the become machine learning experts have invent machine learning. They can buy it from Amazon. I think the second is they're trying to simplify the data pipeline. The data pipeline today is characterized by a series of hyper specialized individuals. It engineers, data scientists, quality engineers, analysts, developers. These are folks that are largely live in their own swim lane. Uh, and while they collaborate, uh, there's still a fairly linear and complicated data pipeline, uh, that, that a business person or a data product builder has to go through Amazon making some moves to the front of simplify that they're expanding data access to the line of business. I think that's a key point. Is there, there increasingly as people build data products and data services that can monetize, you know, for their business, either cut costs or generate revenue, they can expand that into line of business where there's there's domain context. And I think the last thing is this theme that we talked about the other day, John of extending Amazon, AWS to the edge that we saw that as well in a number of machine learning tools that, uh, Swami talked about. >>Yeah, it was great by the way, we're live here, uh, in Palo Alto in Boston covering the analysis, tons of content on the cube, check out the cube.net and also check out at reinvent. There's a cube section as there's some links to so on demand videos with all the content we've had. Dave, I got to say one of the things that's apparent to me, and this came out of my one-on-one with Andy Jassy and Andy Jassy talked about in his keynote is he kind of teased out this idea of training versus a more value add machine learning. And you saw that today in today's announcement. To me, the big revelation was that the training aspect of machine learning, um, is what can be automated away. And it's under a lot of controversy around it. Recently, a Google paper came out and the person was essentially kind of, kind of let go for this. >>But the idea of doing these training algorithms, some are saying is causes more harm to the environment than it does good because of all the compute power it takes. So you start to see the positioning of training, which can be automated away and served up with, you know, high powered ships and that's, they consider that undifferentiated heavy lifting. In my opinion, they didn't say that, but that's clearly what I see coming out of this announcement. The other thing that I saw Dave that's notable is you saw them clearly taking a three lane approach to this machine, learning the advanced builders, the advanced coders and the developers, and then database and data analysts, three swim lanes of personas of target audience. Clearly that is in line with SageMaker and the embedded stuff. So two big revelations, more horsepower required to process training and modeling. Okay. And to the expansion of the personas that are going to be using machine learning. So clearly this is a, to me, a big trend wave that we're seeing that validates some of the startups and I'll see their SageMaker and some of their products. >>Well, as I was saying at the top, I think Amazon's really trying, working hard on simplifying the whole process. And you mentioned training and, and a lot of times people are starting from scratch when they have to train models and retrain models. And so what they're doing is they're trying to create reusable components, uh, and allow people to, as you pointed out to automate and streamline some of that heavy lifting, uh, and as well, they talked a lot about, uh, doing, doing AI inferencing at the edge. And you're seeing, you know, they, they, uh, Swami talked about several foundational premises and the first being a foundation of frameworks. And you think about that at the, at the lowest level of their S their ML stack. They've got, you know, GPU's different processors, inferential, all these alternative processes, processors, not just the, the Xav six. And so these are very expensive resources and Swami talked a lot about, uh, and his colleagues talked a lot about, well, a lot of times the alternative processor is sitting there, you know, waiting, waiting, waiting. And so they're really trying to drive efficiency and speed. They talked a lot about compressing the time that it takes to, to run these, these models, uh, from, from sometimes weeks down to days, sometimes days down to hours and minutes. >>Yeah. Let's, let's unpack these four areas. Let's stay on the firm foundation because that's their core competency infrastructure as a service. Clearly they're laying that down. You put the processors, but what's interesting is the TensorFlow 92% of tensor flows on Amazon. The other thing is that pie torch surprisingly is back up there, um, with massive adoption and the numbers on pie torch literally is on fire. I was coming in and joke on Twitter. Um, we, a PI torch is telling because that means that TensorFlow is originally part of Google is getting, is getting a little bit diluted with other frameworks, and then you've got MX net, some other things out there. So the fact that you've got PI torch 91% and then TensorFlow 92% on 80 bucks is a huge validation. That means that the majority of most machine learning development and deep learning is happening on AWS. Um, >>Yeah, cloud-based, by the way, just to clarify, that's the 90% of cloud-based cloud, uh, TensorFlow runs on and 91% of cloud-based PI torch runs on ADM is amazingly massive numbers. >>Yeah. And I think that the, the processor has to show that it's not trivial to do the machine learning, but, you know, that's where the infrared internship came in. That's kind of where they want to go lay down that foundation. And they had Tanium, they had trainee, um, they had, um, infrared chow was the chip. And then, you know, just true, you know, distributed training training on SageMaker. So you got the chip and then you've got Sage makers, the middleware games, almost like a machine learning stack. That's what they're putting out there >>And how bad a Gowdy, which was, which is, which is a patrol also for training, which is an Intel based chip. Uh, so that was kind of interesting. So a lot of new chips and, and specialized just, we've been talking about this for awhile, particularly as you get to the edge and do AI inferencing, you need, uh, you know, a different approach than we're used to with the general purpose microbes. >>So what gets your take on tenant? Number two? So tenant number one, clearly infrastructure, a lot of announcements we'll go through those, review them at the end, but tenant number two, that Swami put out there was creating the shortest path to success for builders or machine learning builders. And I think here you lays out the complexity, Dave butts, mostly around methodology, and, you know, the value activities required to execute. And again, this points to the complexity problem that they have. What's your take on this? >>Yeah. Well you think about, again, I'm talking about the pipeline, you collect data, you just data, you prepare that data, you analyze that data. You, you, you make sure that it's it's high quality and then you start the training and then you're iterating. And so they really trying to automate as much as possible and simplify as much as possible. What I really liked about that segment of foundation, number two, if you will, is the example, the customer example of the speaker from the NFL, you know, talked about, uh, you know, the AWS stats that we see in the commercials, uh, next gen stats. Uh, and, and she talked about the ways in which they've, well, we all know they've, they've rearchitected helmets. Uh, they've been, it's really a very much database. It was interesting to see they had the spectrum of the helmets that were, you know, the safest, most safe to the least safe and how they've migrated everybody in the NFL to those that they, she started a 24%. >>It was interesting how she wanted a 24% reduction in reported concussions. You know, you got to give the benefit of the doubt and assume some of that's through, through the data. But you know, some of that could be like, you know, Julian Edelman popping up off the ground. When, you know, we had a concussion, he doesn't want to come out of the game with the new protocol, but no doubt, they're collecting more data on this stuff, and it's not just head injuries. And she talked about ankle injuries, knee injuries. So all this comes from training models and reducing the time it takes to actually go from raw data to insights. >>Yeah. I mean, I think the NFL is a great example. You and I both know how hard it is to get the NFL to come on and do an interview. They're very coy. They don't really put their name on anything much because of the value of the NFL, this a meaningful partnership. You had the, the person onstage virtually really going into some real detail around the depth of the partnership. So to me, it's real, first of all, I love stat cast 11, anything to do with what they do with the stats is phenomenal at this point. So the real world example, Dave, that you starting to see sports as one metaphor, healthcare, and others are going to see those coming in to me, totally a tale sign that Amazon's continued to lead. The thing that got my attention was is that it is an IOT problem, and there's no reason why they shouldn't get to it. I mean, some say that, Oh, concussion, NFL is just covering their butt. They don't have to, this is actually really working. So you got the tech, why not use it? And they are. So that, to me, that's impressive. And I think that's, again, a digital transformation sign that, that, you know, in the NFL is doing it. It's real. Um, because it's just easier. >>I think, look, I think, I think it's easy to criticize the NFL, but the re the reality is, is there anything old days? It was like, Hey, you get your bell rung and get back out there. That's just the way it was a football players, you know, but Ted Johnson was one of the first and, you know, bill Bellacheck was, was, you know, the guy who sent him back out there with a concussion, but, but he was very much outspoken. You've got to give the NFL credit. Uh, it didn't just ignore the problem. Yeah. Maybe it, it took a little while, but you know, these things take some time because, you know, it's generally was generally accepted, you know, back in the day that, okay, Hey, you'd get right back out there, but, but the NFL has made big investments there. And you can say, you got to give him, give him props for that. And especially given that they're collecting all this data. That to me is the most interesting angle here is letting the data inform the actions. >>And next step, after the NFL, they had this data prep data Wrangler news, that they're now integrating snowflakes, Databricks, Mongo DB, into SageMaker, which is a theme there of Redshift S3 and Lake formation into not the other way around. So again, you've been following this pretty closely, uh, specifically the snowflake recent IPO and their success. Um, this is an ecosystem play for Amazon. What does it mean? >>Well, a couple of things, as we, as you well know, John, when you first called me up, I was in Dallas and I flew into New York and an ice storm to get to the one of the early Duke worlds. You know, and back then it was all batch. The big data was this big batch job. And today you want to combine that batch. There's still a lot of need for batch, but when people want real time inferencing and AWS is bringing that together and they're bringing in multiple data sources, you mentioned Databricks and snowflake Mongo. These are three platforms that are doing very well in the market and holding a lot of data in AWS and saying, okay, Hey, we want to be the brain in the middle. You can import data from any of those sources. And I'm sure they're going to add more over time. Uh, and so they talked about 300 pre-configured data transformations, uh, that now come with stage maker of SageMaker studio with essentially, I've talked about this a lot. It's essentially abstracting away the, it complexity, the whole it operations piece. I mean, it's the same old theme that AWS is just pointing. It's its platform and its cloud at non undifferentiated, heavy lifting. And it's moving it up the stack now into the data life cycle and data pipeline, which is one of the biggest blockers to monetizing data. >>Expand on that more. What does that actually mean? I'm an it person translate that into it. Speak. Yeah. >>So today, if you're, if you're a business person and you want, you want the answers, right, and you want say to adjust a new data source, so let's say you want to build a new, new product. Um, let me give an example. Let's say you're like a Spotify, make it up. And, and you do music today, but let's say you want to add, you know, movies, or you want to add podcasts and you want to start monetizing that you want to, you want to identify, who's watching what you want to create new metadata. Well, you need new data sources. So what you do as a business person that wants to create that new data product, let's say for podcasts, you have to knock on the door, get to the front of the data pipeline line and say, okay, Hey, can you please add this data source? >>And then everybody else down the line has to get in line and Hey, this becomes a new data source. And it's this linear process where very specialized individuals have to do their part. And then at the other end, you know, it comes to self-serve capability that somebody can use to either build dashboards or build a data product. In a lot of that middle part is our operational details around deploying infrastructure, deploying, you know, training machine learning models that a lot of Python coding. Yeah. There's SQL queries that have to be done. So a lot of very highly specialized activities, what Amazon is doing, my takeaway is they're really streamlining a lot of those activities, removing what they always call the non undifferentiated, heavy lifting abstracting away that it complexity to me, this is a real positive sign, because it's all about the technology serving the business, as opposed to historically, it's the business begging the technology department to please help me. The technology department obviously evolving from, you know, the, the glass house, if you will, to this new data, data pipeline data, life cycle. >>Yeah. I mean, it's classic agility to take down those. I mean, it's undifferentiated, I guess, but if it actually works, just create a differentiated product. So, but it's just log it's that it's, you can debate that kind of aspect of it, but I hear what you're saying, just get rid of it and make it simpler. Um, the impact of machine learning is Dave is one came out clear on this, uh, SageMaker clarify announcement, which is a bias decision algorithm. They had an expert, uh, nationally CFUs presented essentially how they're dealing with the, the, the bias piece of it. I thought that was very interesting. What'd you think? >>Well, so humans are biased and so humans build models or models are inherently biased. And so I thought it was, you know, this is a huge problem to big problems in artificial intelligence. One is the inherent bias in the models. And the second is the lack of transparency that, you know, they call it the black box problem, like, okay, I know there was an answer there, but how did it get to that answer and how do I trace it back? Uh, and so Amazon is really trying to attack those, uh, with, with, with clarify. I wasn't sure if it was clarity or clarified, I think it's clarity clarify, um, a lot of entirely certain how it works. So we really have to dig more into that, but it's essentially identifying situations where there is bias flagging those, and then, you know, I believe making recommendations as to how it can be stamped. >>Nope. Yeah. And also some other news deep profiling for debugger. So you could make a debugger, which is a deep profile on neural network training, um, which is very cool again on that same theme of profiling. The other thing that I found >>That remind me, John, if I may interrupt there reminded me of like grammar corrections and, you know, when you're typing, it's like, you know, bug code corrections and automated debugging, try this. >>It wasn't like a better debugger come on. We, first of all, it should be bug free code, but, um, you know, there's always biases of the data is critical. Um, the other news I thought was interesting and then Amazon's claiming this is the first SageMaker pipelines for purpose-built CIC D uh, for machine learning, bringing machine learning into a developer construct. And I think this started bringing in this idea of the edge manager where you have, you know, and they call it the about machine, uh, uh, SageMaker store storing your functions of this idea of managing and monitoring machine learning modules effectively is on the edge. And, and through the development process is interesting and really targeting that developer, Dave, >>Yeah, applying CIC D to the machine learning and machine intelligence has always been very challenging because again, there's so many piece parts. And so, you know, I said it the other day, it's like a lot of the innovations that Amazon comes out with are things that have problems that have come up given the pace of innovation that they're putting forth. And, and it's like the customers drinking from a fire hose. We've talked about this at previous reinvents and the, and the customers keep up with the pace of Amazon. So I see this as Amazon trying to reduce friction, you know, across its entire stack. Most, for example, >>Let me lay it out. A slide ahead, build machine learning, gurus developers, and then database and data analysts, clearly database developers and data analysts are on their radar. This is not the first time we've heard that. But we, as the kind of it is the first time we're starting to see products materialized where you have machine learning for databases, data warehouse, and data lakes, and then BI tools. So again, three different segments, the databases, the data warehouse and data lakes, and then the BI tools, three areas of machine learning, innovation, where you're seeing some product news, your, your take on this natural evolution. >>Well, well, it's what I'm saying up front is that the good news for, for, for our customers is you don't have to be a Google or Amazon or Facebook to be a super expert at AI. Uh, companies like Amazon are going to be providing products that you can then apply to your business. And, and it's allowed you to infuse AI across your entire application portfolio. Amazon Redshift ML was another, um, example of them, abstracting complexity. They're taking, they're taking S3 Redshift and SageMaker complexity and abstracting that and presenting it to the data analysts. So that, that, that individual can worry about, you know, again, getting to the insights, it's injecting ML into the database much in the same way, frankly, the big query has done that. And so that's a huge, huge positive. When you talk to customers, they, they love the fact that when, when ML can be embedded into the, into the database and it simplifies, uh, that, that all that, uh, uh, uh, complexity, they absolutely love it because they can focus on more important things. >>Clearly I'm this tenant, and this is part of the keynote. They were laying out all their announcements, quick excitement and ML insights out of the box, quick, quick site cue available in preview all the announcements. And then they moved on to the next, the fourth tenant day solving real problems end to end, kind of reminds me of the theme we heard at Dell technology worlds last year end to end it. So we are starting to see the, the, the land grab my opinion, Amazon really going after, beyond I, as in pass, they talked about contact content, contact centers, Kendra, uh, lookout for metrics, and that'll maintain men. Then Matt would came on, talk about all the massive disruption on the, in the industries. And he said, literally machine learning will disrupt every industry. They spent a lot of time on that and they went into the computer vision at the edge, which I'm a big fan of. I just loved that product. Clearly, every innovation, I mean, every vertical Dave is up for grabs. That's the key. Dr. Matt would message. >>Yeah. I mean, I totally agree. I mean, I see that machine intelligence as a top layer of, you know, the S the stack. And as I said, it's going to be infused into all areas. It's not some kind of separate thing, you know, like, Coobernetti's, we think it's some separate thing. It's not, it's going to be embedded everywhere. And I really like Amazon's edge strategy. It's this, you, you are the first to sort of write about it and your keynote preview, Andy Jassy said, we see, we see, we want to bring AWS to the edge. And we see data center as just another edge node. And so what they're doing is they're bringing SDKs. They've got a package of sensors. They're bringing appliances. I've said many, many times the developers are going to be, you know, the linchpin to the edge. And so Amazon is bringing its entire, you know, data plane is control plane, it's API APIs to the edge and giving builders or slash developers, the ability to innovate. And I really liked the strategy versus, Hey, here's a box it's, it's got an x86 processor inside on a, throw it over the edge, give it a cool name that has edge in it. And here you go, >>That sounds call it hyper edge. You know, I mean, the thing that's true is the data aspect at the edge. I mean, everything's got a database data warehouse and data lakes are involved in everything. And then, and some sort of BI or tools to get the data and work with the data or the data analyst, data feeds, machine learning, critical piece to all this, Dave, I mean, this is like databases used to be boring, like boring field. Like, you know, if you were a database, I have a degree in a database design, one of my degrees who do science degrees back then no one really cared. If you were a database person. Now it's like, man data, everything. This is a whole new field. This is an opportunity. But also, I mean, are there enough people out there to do all this? >>Well, it's a great point. And I think this is why Amazon is trying to extract some of the abstract. Some of the complexity I sat in on a private session around databases today and listened to a number of customers. And I will say this, you know, some of it I think was NDA. So I can't, I can't say too much, but I will say this Amazon's philosophy of the database. And you address this in your conversation with Andy Jassy across its entire portfolio is to have really, really fine grain access to the deep level API APIs across all their services. And he said, he said this to you. We don't necessarily want to be the abstraction layer per se, because when the market changes, that's harder for us to change. We want to have that fine-grained access. And so you're seeing that with database, whether it's, you know, no sequel, sequel, you know, the, the Aurora the different flavors of Aurora dynamo, DV, uh, red shift, uh, you know, already S on and on and on. There's just a number of data stores. And you're seeing, for instance, Oracle take a completely different approach. Yes, they have my SQL cause they know got that with the sun acquisition. But, but this is they're really about put, is putting as much capability into a single database as possible. Oh, you only need one database only different philosophy. >>Yeah. And then obviously a health Lake. And then that was pretty much the end of the, the announcements big impact to health care. Again, the theme of horizontal data, vertical specialization with data science and software playing out in real time. >>Yeah. Well, so I have asked this question many times in the cube, when is it that machines will be able to make better diagnoses than doctors and you know, that day is coming. If it's not here, uh, you know, I think helped like is really interesting. I've got an interview later on with one of the practitioners in that space. And so, you know, healthcare is something that is an industry that's ripe for disruption. It really hasn't been disruption disrupted. It's a very high, high risk obviously industry. Uh, but look at healthcare as we all know, it's too expensive. It's too slow. It's too cumbersome. It's too long sometimes to get to a diagnosis or be seen, Amazon's trying to attack with its partners, all of those problems. >>Well, Dave, let's, let's summarize our take on Amazon keynote with machine learning, I'll say pretty historic in the sense that there was so much content in first keynote last year with Andy Jassy, he spent like 75 minutes. He told me on machine learning, they had to kind of create their own category Swami, who we interviewed many times on the cube was awesome. But a lot of still a lot more stuff, more, 215 announcements this year, machine learning more capabilities than ever before. Um, moving faster, solving real problems, targeting the builders, um, fraud platform set of things is the Amazon cadence. What's your analysis of the keynote? >>Well, so I think a couple of things, one is, you know, we've said for a while now that the new innovation cocktail is cloud plus data, plus AI, it's really data machine intelligence or AI applied to that data. And the scale at cloud Amazon Naylor obviously has nailed the cloud infrastructure. It's got the data. That's why database is so important and it's gotta be a leader in machine intelligence. And you're seeing this in the, in the spending data, you know, with our partner ETR, you see that, uh, that AI and ML in terms of spending momentum is, is at the highest or, or at the highest, along with automation, uh, and containers. And so in. Why is that? It's because everybody is trying to infuse AI into their application portfolios. They're trying to automate as much as possible. They're trying to get insights that, that the systems can take action on. >>And, and, and actually it's really augmented intelligence in a big way, but, but really driving insights, speeding that time to insight and Amazon, they have to be a leader there that it's Amazon it's, it's, it's Google, it's the Facebook's, it's obviously Microsoft, you know, IBM's Tron trying to get in there. They were kind of first with, with Watson, but with they're far behind, I think, uh, the, the hyper hyper scale guys. Uh, but, but I guess like the key point is you're going to be buying this. Most companies are going to be buying this, not building it. And that's good news for organizations. >>Yeah. I mean, you get 80% there with the product. Why not go that way? The alternative is try to find some machine learning people to build it. They're hard to find. Um, so the seeing the scale of kind of replicating machine learning expertise with SageMaker, then ultimately into databases and tools, and then ultimately built into applications. I think, you know, this is the thing that I think they, my opinion is that Amazon continues to move up the stack, uh, with their capabilities. And I think machine learning is interesting because it's a whole new set of it's kind of its own little monster building block. That's just not one thing it's going to be super important. I think it's going to have an impact on the startup scene and innovation is going, gonna have an impact on incumbent companies that are currently leaders that are under threat from new entrance entering the business. >>So I think it's going to be a very entrepreneurial opportunity. And I think it's going to be interesting to see is how machine learning plays that role. Is it a defining feature that's core to the intellectual property, or is it enabling new intellectual property? So to me, I just don't see how that's going to fall yet. I would bet that today intellectual property will be built on top of Amazon's machine learning, where the new algorithms and the new things will be built separately. If you compete head to head with that scale, you could be on the wrong side of history. Again, this is a bet that the startups and the venture capitals will have to make is who's going to end up being on the right wave here. Because if you make the wrong design choice, you can have a very complex environment with IOT or whatever your app serving. If you can narrow it down and get a wedge in the marketplace, if you're a company, um, I think that's going to be an advantage. This could be great just to see how the impact of the ecosystem this will be. >>Well, I think something you said just now it gives a clue. You talked about, you know, the, the difficulty of finding the skills. And I think that's a big part of what Amazon and others who were innovating in machine learning are trying to do is the gap between those that are qualified to actually do this stuff. The data scientists, the quality engineers, the data engineers, et cetera. And so companies, you know, the last 10 years went out and tried to hire these people. They couldn't find them, they tried to train them. So it's taking too long. And now that I think they're looking toward machine intelligence to really solve that problem, because that scales, as we, as we know, outsourcing to services companies and just, you know, hardcore heavy lifting, does it doesn't scale that well, >>Well, you know what, give me some machine learning, give it to me faster. I want to take the 80% there and allow us to build certainly on the media cloud and the cube virtual that we're doing. Again, every vertical is going to impact a Dave. Great to see you, uh, great stuff. So far week two. So, you know, we're cube live, we're live covering the keynotes tomorrow. We'll be covering the keynotes for the public sector day. That should be chock-full action. That environment is going to impact the most by COVID a lot of innovation, a lot of coverage. I'm John Ferrari. And with Dave Alante, thanks for watching.

>>from around the globe. It's the Cube with digital coverage of aws reinvent 2024 sponsored by Intel and AWS. Yeah. >>Welcome back here to our coverage here on the Cube of AWS reinvent 2020. It's now pleasure. Welcome. Sean. Vice to the program was the vice president of databases at AWS and Sean. Good day to you. How you doing, sir? >>I'm doing great. Thank you for having me. >>You bet. You bet. Thanks for carving out time. I know it was a very a busy couple of weeks for the A. W s team on DSO certainly was kicked off key notes today. We heard right away that there's some fairly significant announcements that I know certainly affect your world at AWS. Tell us a little bit about those announcements, and then we'll do a little deeper divers. You you go through >>sure, you know. And he made three big announcements this morning as it relates to databases, one of whom was around Aurora serverless V two on. Do you could just think of that as, uh um, no infrastructure whatsoever to manage and Aurora server list that can scale for, you know, from zero to hundreds of thousands of transactions in a fraction of a second, literally with no infrastructure to manage. So it's a really easy way to build applications in the cloud. Eso excited about that? Another big announcement WAAS related to a lot of our customers today are really they're using the right tool for the right job. In other words, they're not trying toe GM all of their data into one database management systems. They're breaking app down into smaller parts. They pick the right tool for the right job. And with that context, we announce glue elastic views, which just allows you to very easily write a sequel. Query most. There's a lot of developers that understand sequel. So if I could easily write a sequel query to reach out to the source databases and then materialize, um, that data into a different target, Um, that's a really simple way toe. Build new customer experiences and make the most of the databases you have. Aan den. The third big announcement remained today was called Babble Eso Babel. Babel Fish is really a a compatibility or a sequel server compatibility layer on Aurora post grass. So if you have ah sequel server application. You've been trying to migrate it to post grass, and you've been wishing for an easier way to get that done. Babel Fish allows you to take your T sequel or your Microsoft sequel server application connected to post grass. Using your same client drivers with little to no code change eso That's a big deal for those that are trying to migrate from commercial systems to open source. And then finally, we didn't stop there as we thought about Babel, Um, and talked to a lot of customers about it. We actually are open sourcing the technology, so it will be available later in 21. All the development will be done open transparently hosted on get hub and licensed under Apache 20 so those that's kind of one lap around the track, if you will, of the big announcements from today How big >>the open source announcement to me. I mean, that's fairly significant that that you're opening up this new opportunity thio the entire community, um, that you're willing to open it up, and I'm sure you're gonna have you know, I mean, this is this is gonna be I would imagine Ah, very popular destination for a lot of folks. >>Yeah, I think so, too. You know, I'm I'm personally, I'm a believer that every customer can use data to build a foundation for future innovation. And to me, a lot of things start and end with data. As we know, data really is a foundational component of at a swell A systems and, you know, and you know, what we found is not every customer can plan for every contingency that happens. But what they can do is build a strong foundation. So, you know, and with a strong foundation, you really stand the best chance to overcome whatever that next unexpected thing is or innovate new ways. And with that is a backdrop. We think this open source piece is a big deal. Why? I'll tell you, you know, it's just us right now. But if I told you the story behind the story, I have met so many customers over the last few years that you know, John, if you and I were sitting down with them, it kind of sounds like this. You sit down, you talk to somebody and they'll say things like, Hey, I've built, you know, we've built years and years and years of application development against sequel server. We really don't like the punitive commercial licensing and, you know, we're trying to get over Thio open source, but we need an easier way and, you know, and we thought about that long and hard and, you know, we came up with the team, came up with a wonderful solution for this, But to tell you the truth, as we were building Babel fish and talking to customers, what became really clear with the community enterprises in I S V s and s eyes is they all basically said, Hey, if there was a way where we could go and extend this, um for, you know, like it could be Boy, if this thing supported to more features, that would be awesome. But if it was open source, that would be even better, because then we could we could take things under our own control so that that's what truly motivated this decision to go open source and based on conversations we've had in the decisions we made, we actually think it's it's really big. It's really big for everybody who has been trying to move off of commercial systems and over toe open source. You. >>Let's talk about transforming your kind of your database mindset in general right now from a client's perspective, especially for somebody who was considering, you know, substantial moves, you know, a major reconfigurations off their processes. What's the process that you go through with them to evaluate their needs, to evaluate their capabilities, to evaluate their storage? All that, you know, that comes into play here and help them to get thio kind of the end of the rainbow >>because it z absolutely, you know, so it really depends on who you're talking Thio and no, at this stage of the game, the clouds been around now for 10, 14 years. I think it is something in that range, you know? So a lot of the early cloud adopters, you know, they've been here and they've been building in a certain way. Um and you know, you and I know early cloud adopters by way of watching streaming media, ordering rideshare, taking a selfie, you know, and you know, we have these great application experiences and we expect them to work all the time at Super Low. Leighton See, they should always be available. So you know, the single biggest thing we learned from Early Cloud builders was there's no such thing as one size football. There's one thing doesn't fit anything at all. Um, that's kind of the way data was, you know, 20 years ago. But today, if you take the learning from these early cloud builders, the journey that we go on with, let's say a mid to late stage cloud a doctor. We're all excited on, you know, sort of. If they can start now today, where Early Cloud Wilders have done a bunch of pioneering, they get excited. So So what happens is, um, there's usually to kind of conversations. One is how do we you know, we've got all these databases that we self managed on premise. How do we bring those into the cloud? And then how do we stop doing undifferentiated heavy lifting? In other words, what they're saying is, we don't want to do patching and back up and monitoring that Z instead, our precious resources should be working on innovations for the business. So in that context, you and I would end up talking to somebody about moving to fully managed services like an already s, for example, um and then the other conversation we have with customers is is the one about breaking free, which is hey, a burn on commercial. I wanna move for open source. And in that context, there are a lot of customers today that they'll move to the cloud. And then and then when they get there as a first step, their second step is to is to migrate over toe open source. And then that third piece is folks that are trying to build for the cloud, these modern APS. And in that context, they follow the playbook of these early cloud builders, which is what you take this big app. You break it into smaller parts and then they pick the right tool for the right job. So that's that's kind of the conversation that we go through there. And finally, what I would say is, most customers say that they'll say to me, What do you mean by picking the right tool for the right job? And the mindset is very different than the one that we all grew up in from 20 years ago. 20 years ago, you just bought a database platform. And then whatever the business was trying to do, you you you would try to support that access pattern on on that database choice. But today, the new world that we live in, it really is. Let's start with the business use case first, understand the access pattern and then pick the best optimized database storage for that. So that's that's kind of how those conversations go. >>You've got what, 15, 14, 15 different data based instruments, you know, like in your tool chest? Um, how how is that evolution occurred? Um because I'm sure, you know one, but got another big at another big at another, looking at different capabilities, different needs. So I mean, >>kind of walked me >>through that a little bit and how you've gotten to the point that you've got 15 >>Tonto eso. So one of the things that you know I'd start off with here, like the question is, Well, if there's 15 today, is there gonna be 100 tomorrow? The real answer is, I don't know, you know, And but what I do know is there's really a handful of categories around data models and access patterns that if you will kind of fill out the portfolio if you will. Um, the first one is around relation. Also, relational databases have been around for a long time. It has a certain set of characteristics that people have come to appreciate and understand and, you know, and we provide a set of services that provide fully managed relational services. Let it be for things like Oracle or sequel, server or open source, like Maria DB or my sequel or Post Press and even Aurora, which provides commercial grade performance availability and scale it about 1/10 the cost of commercial. So you know, there's a handful of different services in that context. But there's new services in this key value. And think of a key value access pattern along the lines of you. Imagine. We order you order a ride share and you're trying to track a vehicle every second. So on your phone you can see it moving across your phone. And now imagine if you were building that at our a million people going to do that all at the same time or 10. So in that kind of access pattern, a product like dynamodb is excellent because It's designed for basically unlimited scale, really high throughput. So developer doesn't have toe really worry about a million people. 10 million people are one. This thing can just scale inevitably. Yeah, it's just not an issue. And, you know, I'll give you one other example like, um, in Neptune, which is a graph database. So you and I would know graph databases by way of seeing a product recommendation, for example, Um, and you know, grab the beauty of a graph databases. It's optimized for highly connected data. In other words, as a developer, I can what I can do with a few lines of code and a graph database because it's optimized for all these different relationships. I might try to do that in a different system that I might write 1500 lines of codes and because it was never designed for something like highly connect the data like graph. So that's kind of the evolution of how things there's just these different categories that have to do with access patterns and data models. And our strategy is simple. In each category, we wanna have the very best AP is available for our customers. Let's >>talk about security here for a moment because you have, you know, these just these tremendous reservoirs now, right that you've built up in capabilities got, you know, new data centers going up every day. It seems like around around the country and around the world, security or securing data nevermore important on dnep ver mawr, I guess on the radar of the bad actors to at the same time because of the value of that data. So just if you would paint the picture in terms of security awareness three encryption devices that you're now deploying the stuff that's keeping you up at night, I would think probably falls into this category a little bit. Eso Let's just take it on security and the level of concern. And then what you at a w s are doing about that? >>Yeah. So, you know, when I talked to customers, I always remind people security is a shared responsibility on De So Amazon's piece of that is the infrastructure that we build the processes that we have, you know, from how people you know can enter a building toe, what they can do in an environment. The auditing to the encryption systems that rebuild. Um, there's there's three infrastructure responsibility, which, you know, we think about every second of every day. Um, Andi, it's, you know, yes, it's one of those things that keeps you up at night. But you have to kind of have this level of paranoia, if you will. There's bad actors everywhere. And, you know, that mindset is kind of, you know, kind of helps you stay focused on Ben. There's the customers responsibility to in in terms of how they think about security. So, you know, um and what that means is, uh, you know, best practices around how they how they integrate identity and access management into their solution. Um, you know how they use how they rotate encryption keys, how they apply encryption and all the safeguards that you would expect the customer do so together, you know, we work with our customers to ensure that our systems are are secure. Um, and the only other thing that I would add to this is that, you know, kind of in the old world. And I keep bringing up the old world because security in the old world was sort of one of those things. Like if you go back 20 years ago. You know, security sometimes is one of those things that you think about a little bit later in the cycle. And I've met a lot of customers that tryto bolt on security and it never works. It's just hard to just bolt it into an app. But the really nice thing about thes fully managed services in the cloud they have security built right in. So security, performance and availability is built right into these fully managed A p I s eso customer doesn't have to think about Well, how do I add this capability onto it? You know, in some sense, it could be a simple is turning a feature on or something like encryption being turned on by default, and they don't have to do anything. So, you know, there it's just a completely different world that we live in today, and we try to improve it every second of every day. >>Well, Sean, it's nice to know that you're experiencing the paranoia for all your customers. That Zaveri very gracious yesterday There. Hey, thanks for the time. I appreciate it. I know you're very busy the next couple of weeks with the number of leadership sessions and intermediate sessions as well with AWS reinvent. So thanks again for carving a little bit of time for us here today on the Cube. >>You bet, John. Thank you. I really appreciate it. >>Take care.

>> From theCUBE studios in Palo Alto and Boston, connecting with thought-leaders all around the world, this is a Cube Conversation. >> Hi everybody, this is Dave Vellante. Welcome to this Cube Conversation. We're really excited to have Wim Coekaerts in, he is the senior vice-president of software development at Oracle. Wim, it's great to have you on, and, you know I often say I wish we were face-to-face but if we were you'd have to cut off my tie, cause developers and ties just don't go together. >> No, I know, and this is my normal outfit, so this is me wherever I go. Hi again, good to see you. >> Yeah, great to see you. So, of course, you know a lot of people are confused about Oracle, and open-source, they say "Oracle? Open-source? What is that all about?" But I think you're misunderstood. People don't, first of all, realize you as the leader of the software-development community inside of Oracle, I mean, you've been involved in Linux since the early 90s. But you guys have a lot of committers, you do a lot. I want to talk about that. What is up with Oracle, and open-source? >> Ah, well, it's a broad question. So, you know, a couple of things. One is, we have many different areas within the company that are dealing with open-source. So we have the cloud team doing a lot of stuff around cloud SDKs and support for different languages like Python and Go, and of course Java and so forth, so they do a lot around ensuring that the Oracle ecosystem is integrated in the open-source tools that customers use, or developers use, Terraform companies and so forth. And then you have the Java team, and so forth. Java is open-source and then the Graal project, GraalVM which is a polyglot compiler that can run Java, and Python, and Javascript and so forth together in one. VM do really cool optimizations, that's an open-source project, also on GitHub. There's of course MySQL, which is along with Java, they're probably the two most popular and widely used open-source projects out there. There's VirtualBox which is of course also a very popular project that's open-source. There's all the work we do around Linux. And I think one of the things is that, when you have so many different areas, doing things that are for that area, then as a developer or as a customer, you typically just deal with that group. And what you see is, oh you're talking to the Java developers, so you know what's going on around Java. The Java developers might not necessarily say, "Oh well we also do MySQL, and we do Linux and VirtualBox and so forth," and so you get a rather myopic, narrow view of the larger company. When you add all these things up, and there will be one big slide that says "This is Oracle, these are all these open source projects," and there's multiple ways. One is, we have projects that we've open-sourced and all the code came from us and we made it publicly available, we're the main contributor and we get contributions back. There are other projects where we contribute to third-party in terms of enhancing things, like I said with the Cloud Team, and then in general something like Linux where we're part of an external project and we participate in development of that project at large. And so there's these three different ways, when you count up all the developers that we have that deal with open-source on a daily basis. And in terms of contributions, in terms of bug fixes, testing, and so forth, it's thousands, literally, full-time paid developers. And of course, all the projects are all either on GitHub or similar sites that are very popular. So yeah, I think the misunderstood is probably a lack of knowledge of the breadth of what we do. And, you know, our primary goal is to provide services and products to customers, and so the open-source part is sort of embedded in a development methodology. But that's not something we sell or market separately, we just work with customers and products and services, and so in some cases it's not well-understood. >> Yeah. Well, we're talking of course, we're talking about the state of the penguin, I think it's important for people to understand, Oracle got into the Linux game in the 90s, maybe the latter part of the 90s and Oracle, of course, wants to make Linux-- wants to make Oracle, it's applications and database run better on Linux, but as you're pointing out, your Linux distro, full support, end-to-end, thousands of people in your open-source community, and the contributions that you make to Linux, many if not most, they go upstream, everybody can benefit from those, but of course you want an Oracle distro that is going to make Oracle stuff run better, that's always kind of been the Oracle way. >> Well, so, yes, two things though. One is, so everything we do is upstream. So we have no Linux patches that are not contributed upstream; There's no proprietary code in Oracle Linux at all, it's all completely open, publicly available: the source code, the change log, all the commits, it's fully open and public, which sometimes is not well-understood, but it's completely open. And, everything we do in terms of feature development or functionality or bug fixes goes upstream to the Linux kernel mail-list. It's actually, it's the only way to be able to manage a Linux distribution and be a Linux vendor is to live in that eco-system. Otherwise, the cost of maintaining your own fork, so to speak, is very high and it doesn't really solve the problem. Now, the functionality we work on obviously is focused on making Oracle products run better, making Oracle Cloud run better, and so forth. However, again, what's important to understand, though, is an Oracle database is a program running on an operating system. It does IO, it does networking, it deals with memory management, lots of processing. So, for the most part, the things that we work on to improve that helps everyone out, right? It helps every other database run better, or helps every other language run better. So none of these changes are specific to Oracle, they're just things that we found doing performance benchmarks and testing and so forth, where we say "Hey, if Linux did the following, it would make boot-up faster. Now boot-up has nothing to do with the database. But our customers run on 1-terabyte, 4-terabyte, 8-terabyte systems, and so booting up, and Linux starting up, and cleaning up memory takes a long time. So we want to reduce that from an availability point of view. So here, we're now talking about just enterprise for you. So there's this broad set of things we work on that definitely help us, but they're actually really completely generic and help everyone out. >> Yeah, that's great. So I wanted to kind of get that out of the way and help our audience understand that. So let's get into it a little bit; What are you seeing, what's going on in IT, pick your observation space and your vision of what you see happening out there. >> Well, you know, it's very interesting, it's sort of, there's two... there's sort of two worlds, right, there's the cloud world and the move to cloud, and there's the on-premises world, where people run their systems on their own. And, one of the things that we've learned is, when you talk about machine-learning, obviously, is something that's very popular these days, and automation. And so in order to rely on machine-learning well, and have algorithms that are very effective, you need lots of data. And so being a cloud vendor, and having Linux in our cloud on tens of thousands, or hundreds of thousands of servers, or more, allows us to have a view of how an operating system works across an incredibly large scale. So we get lots of data. And so for us to figure out which algorithms work well in terms of how can we do network optimizations, how can we discover anomalies on the storage site, and deal with it and so forth, we can do that at scale. And what's interesting is, how do we then bring that on-prem? Well, if we can get the data and the learning done, the training done, in our cloud directly, then when we provide that service also for people running Oracle Linux on premises then that will work. The alternative is to have point solutions where you provide something to a customer, and he needs to learn something from small amounts of data. That doesn't work so well. So I think having both worlds, on-prem and cloud directly, allows us to kind of benefit from that. And I think that's important, because lots of customers are interested in going to cloud. Many of the enterprises have not yet. You know, they're starting, but there's still a huge on-premises space that's important. And so by being able to get them familiar with how these things work at scale, autonomy is again important, right, Autonomous Database is incredibly popular and so forth, that allows us to then say, "Here, try these things out here, it's a service. We can show you the benefits right away," and then as that improves we bring that, to a certain extent, on-premises as well. And then they can have it in both places. And that, I think, is something, again, that's relatively unique but also very important, is that we want to provide services and products that act similarly on-premises as well as in cloud, because at some point when people move we want to make that transition seamless. And what you have today for the most part is one world that's on-prem, and then the cloud world is completely different. And that is a big barrier of moving, and so we want to reduce that, we can run the same operating system local as well as cloud, you can the same functionality, and then that helps transition people over much easier. >> Yeah, well Oracle actually was one of the -- I think Oracle was the first company to actually market same-same, you actually used that term. Others put forth that concept, but Oracle was the first to announce products like Cloud at Customer, that were same-same, now it took some time to actually get it perfected, and get it to market, but the point is, and we've written about this, is Oracle, because of the ascendancy of cloud, flipped and has a cloud-first mentality, and you just kind of referenced that, you just said, "And you can bring that to on-prem." So I wonder if you could talk about that cloud-first mentality, and the impact on hybrid. >> So yeah, I think the cloud-first part is of course in cloud we work on services moreso than products that we deliver. And there's a number of things that are happening. So one is that we obviously continue to provide products to customers, you can download Oracle Linux, you can download the database and what not, you can install it on your own, you can do the traditional way of working. Then in the cloud-world, what typically happens is "Oh, I use a database service. I'm not installing anything, I push a button and I get an IP address and a SQL that connects extremely quickly to the database." And we take care of everything underneath that is on this database. Now, in order to do that, you need a whole infrastructure in place, you need log-in agents, you need a back-end that captures all that stuff, you need monitoring tools, you need all the automation scripts for bringing the service up and monitor it. And so, that takes a lot of time to do right, and we learn a lot by doing this. And so the cloud-first part of these services means that we get to experience this ourselves with direct access to everything. Now taking that service with all of the additional features like autonomy, and bringing that to an on-premises world, we have to make sure we can package that so that all these pieces around it go along with it. And that takes a little bit more time, so we can do everything at the same time. And so what we've done with Autonomous Database is we created everything in Oracle Cloud, we have the whole system running really well, and then we've been able to sort of package that and shrink it into something that can be installed on-premises, but then connected into Oracle Cloud again. And so that way we can get all the telemetry over the metric, and that allows us to scale. Because part of providing a cloud service that runs on-prem in the customer environment is that we need to be able to remotely manage that similar to how that runs in our own cloud. Right, otherwise it doesn't scale. And so that takes a little bit of time, but we've done all that work, and now with Cloud at Customer Database that's really in place. >> Yeah, you really want to have that same cloud experience, whether with on-prem, in the public cloud, hybrid, et cetera. So, I want to explore a little bit more who is using Oracle Linux, and what's the driver for using it. Can you describe maybe some of the types of customers and why they buy? >> Sure, so we started this fourteen years ago, in 2006, October 25th, 2006. I remember that day very well; Penguins on stage and a big launch for Oracle Linux in San Francisco Moscone Center. So, look, the initial driver for Oracle Linux was to ensure that Oracle database customers or Oracle product customers had a good operating system experience, and the ability to be able to handle critical issues when that occurs, because typically a database runs the company's critical data: the most essential stuff that a company has is typically in a database, an Oracle database. And so when that thing has issues with the operating system, you don't want just to talk to multiple vendors and have finger-pointing, and having to explain to an operating system vendor how the database works. In the Unix world, we had a good relationship with the OS vendors, and the hardware vendors, they were the same. And they knew our products really well, and in the Linux world, that was very different. The OS vendor basically did not want to understand or learn anything about the products living on top. And so while to a certain extent that makes sense, it's an enterprise world where time is of the essence, and downtime needs to be limited absolutely. We can't have these arguments and such. And that was the driver, initially, for doing Oracle Linux. It was to ensure there was a Linux distribution really backed by us, that we could fix, that we could fully support. That was completely the original intent. And so the early customer base was database customers. Database and middleware. Mostly database. But that has then evolved quickly, and so what happened was, people say "Look, I have a thousand servers, a hundred run Oracle, so we'll run Oracle Linux on those hundred, and we'll run something else on those other nine-hundred." Now after a year or so, they realize that our support is really good; We fix all these issues, and so then they're like "Why are we having two Linux distributions? This thing works really well, it runs any application, it's fully compatible, so we'll do a thousand with Oracle Linux." And so the early days, the first few years, was definitely Oracle Database as the core driver, and then it sort of expanded to the rest of the estate. And over the years, we've added lots of features and functionality, like Ksplice, and so forth. We have an attractive pricing model for running on servers, and so now lots of our customers have a very small Oracle percentage running and many other things running. So it's really become a all-or-nothing play in the Linux space, and we're well-known now, so it's actually very good. >> You just mentioned Ksplice. We've been talking about cloud, and on-prem, and hybrid. Let's talk about security, because security really is a differentiator, particularly if you're going to start to put stuff in the cloud. Talk about Ksplice specifically, but generally security and your policy there. >> So, "Security first" is sort of what you hear us say and do, in everything we do. The database obviously security, on the Linux site security matters. Ksplice as a technology is there to do critical bug-fixing and make sure that we can apply security vulnerability fixes without affecting the customer, and not have downtime. And if you look at most of the cases or many of the cases where you have security vulnerabilities and exploits, it tends to be because systems were not patched. Why were they not patched? Well not that our customer doesn't understand that it's important, but it's a whole train of events that needs to happen. You have to, you get notified that there's a security issue in your operating system or application. Then, well, an application typically means it's a multi-layered setup. So if you have to bring your database server down, then you first have to coordinate with the application users to bring the app server down, cause that talks to the database. So to patch one system, you basically have to bring down the whole application stack. You have to negotiate with the DBAs, you have to negotiate with the app admins, you have to negotiate with the user. It takes weeks to do that and find time. Well during that time, you're vulnerable. So the only way, really, to address security in a scalable and reducing that window of time is to do it without affecting the customer. And so Casewise is something that, it's a company we acquired in 2009, and have since evolved in terms of capabilities, and so it allows us to patch the Linux terminal without downtime. We lock the kernel for 8 microseconds. It's literally no downtime. You don't have to bring down applications, the user doesn't see it, there's no hang, there's no delay. And so by doing that, you can run a Linux operating system, or gLinux, and you can be fully patched on a system that hasn't rebooted for 3 years. You don't even know it. And so by doing that type of stuff, it makes customers more secure, and it avoids them-- It saves them a lot of money in terms of dealing with project management and so forth, but it really keeps them secure. And so we do that for the Linux kernel, we do that for some of the libraries on top that are critical like OpenSSL and 2 LVC, and, you know one example-- I can give you two examples. So one example is, Heartbleed was this bug in OpenSSL a number of years ago. And so everyone had to patch their SSH server. And that meant, basically, systems around the world had to reboot. Like a whole IT reboot across the world. With Ksplice today, if Heartbleed were to happen tomorrow, we would be able to patch this online for all the Oracle Linux customers without any downtime. No reboots, no restarting of applications, everything keeps running. The amount of money saved would be massive, and also, of course, the headache. Another example is, and this was in Oracle Cloud, when some of these CPU bugs that happened a few years ago that were rather damaging on the cloud side, where you could basically see memory potentially of other CPUs running, the cloud is incredibly critical. We were basically able to basically patch our entire cloud in four hours. And the customer didn't know, right, a hundred and twenty million patches, or something, that we applied within four hours, all online, without any downtime. And so that technology has been really helpful, both for us to run our cloud, but the exact same patches and same fixes go to customers on-premises as well. But this comes back to the whole, what we do in cloud we also do for customer. And I think that's a unique thing that we have at Oracle which is quite fascinating. The operating system we run for our customers, the operating system that's the host part of VMs, is the exact same binary and source code that we make available, just to be clear, the exact same binaries are the ones that you run as a customer on-premises. So if you run Oracle Linux with KVM, you run VMs, you're actually running the exact same stuff as we run underneath our customer's stuff. Nobody else does that, everyone else has a black box. So I think that helps a little bit with transparency as well. >> Yeah, and that homogeneity just creates an environment, you're talking about that sort of security mindset, it's critical, you're not just bolting it on, it's part of the culture. But you started your career, and then of course you were a Linux person when you came to Oracle, but then I think you spent some time in database, back in the day when there were serious database wars going on, before Oracle became the king of database. So now you've got, obviously, this great portfolio, and a lot of really sharp software developers; What should we expect going forward, from Oracle? What should we look for? >> You know, I was talking to some, I was welcoming some interns to the company, for their summer internship yesterday, and one of the things I mentioned to them was that -- so cloud obviously gives us a lot of opportunities, but there's a number of things. One is, we have such a breadth of applications and software and hardware together. We have the servers, we have the storage, we have the operating systems, we have the database layer and so forth, and we have the cloud side, and one of the great opportunities, and I think we've shown a lot of this happening with the ability to create something like Autonomous Database, is to combine all these things. Right, we have such a broad portfolio of really cool technology that by itself is okay, but if you combine the things it really becomes awesome. You cannot create autonomous database without having autonomous learning. You cannot create those two and make them really safe without also controlling the firmware on the hardware and so forth. So by being able to combine all these layers, and by having a really great relationship across the teams within the company, that opens up a lot of opportunities to do stuff really quickly. And having the scale for that. I think that has been, for the last few years, a really great thing, but I can see that being one of the advantages that we have going forward. We have Oracle Fusion Applications, which is incredibly popular, and has great growth, and then we have that running on Oracle Cloud, that talks to Oracle Autonomous Database, so we bring all these pieces together. And no other SaaS vendor can do that, because they don't have these other pieces. They have one area, we have all of them. And so that's the exciting part for me, it's not so much about making my own world better, and having Linux be better, and Casewise and so forth, which is important, but that becoming part of the bigger picture. And that's the exciting part. >> Well, Oracle's always invested in RND, we've made that point many, many times. Whether it's database, you know Fusion was a painful but worthy effort, the whole public cloud piece, obviously many acquisitions, but the investments that you've made in open-source as well, Wim, you're a great spokesperson, and a great representative of the open-source community generally, and then Oracle specifically, so thanks very much for coming on theCUBE and sharing with us the state of the penguin, and best of luck. >> You're welcome. Thank you, thanks for having me. >> Alright, and thank you for watching, everybody. This is Dave Vellante for theCUBE. We'll see you next time. (cheerful music).

>> From theCUBE studios in Palo Alto and Boston, connecting with thought-leaders all around the world, this is a Cube Conversation. >> Hi everybody, this is Dave Vellante. Welcome to this Cube Conversation. We're really excited to have Wim Coekaerts in, he is the senior vice-president of software development at Oracle. Wim, it's great to have you on, and, you know I often say I wish we were face-to-face but if we were you'd have to cut off my tie, cause developers and ties just don't go together. >> No, I know, and this is my normal outfit, so this is me wherever I go. Hi again, good to see you. >> Yeah, great to see you. So, of course, you know a lot of people are confused about Oracle, and open-source, they say "Oracle? Open-source? What is that all about?" But I think you're misunderstood. People don't, first of all, realize you as the leader of the software-development community inside of Oracle, I mean, you've been involved in Linux since the early 90s. But you guys have a lot of committers, you do a lot. I want to talk about that. What is up with Oracle, and open-source? >> Ah, well, it's a broad question. So, you know, a couple of things. One is, we have many different areas within the company that are dealing with open-source. So we have the cloud team doing a lot of stuff around cloud SDKs and support for different languages like Python and Go, and of course Java and so forth, so they do a lot around ensuring that the Oracle ecosystem is integrated in the open-source tools that customers use, or developers use, Terraform companies and so forth. And then you have the Java team, and so forth. Java is open-source and then the Graal project, GraalVM which is a polyglot compiler that can run Java, and Python, and Javascript and so forth together in one. VM do really cool optimizations, that's an open-source project, also on GitHub. There's of course MySQL, which is along with Java, they're probably the two most popular and widely used open-source projects out there. There's VirtualBox which is of course also a very popular project that's open-source. There's all the work we do around Linux. And I think one of the things is that, when you have so many different areas, doing things that are for that area, then as a developer or as a customer, you typically just deal with that group. And what you see is, oh you're talking to the Java developers, so you know what's going on around Java. The Java developers might not necessarily say, "Oh well we also do MySQL, and we do Linux and VirtualBox and so forth," and so you get a rather myopic, narrow view of the larger company. When you add all these things up, and there will be one big slide that says "This is Oracle, these are all these open source projects," and there's multiple ways. One is, we have projects that we've open-sourced and all the code came from us and we made it publicly available, we're the main contributor and we get contributions back. There are other projects where we contribute to third-party in terms of enhancing things, like I said with the Cloud Team, and then in general something like Linux where we're part of an external project and we participate in development of that project at large. And so there's these three different ways, when you count up all the developers that we have that deal with open-source on a daily basis. And in terms of contributions, in terms of bug fixes, testing, and so forth, it's thousands, literally, full-time paid developers. And of course, all the projects are all either on GitHub or similar sites that are very popular. So yeah, I think the misunderstood is probably a lack of knowledge of the breadth of what we do. And, you know, our primary goal is to provide services and products to customers, and so the open-source part is sort of embedded in a development methodology. But that's not something we sell or market separately, we just work with customers and products and services, and so in some cases it's not well-understood. >> Yeah. Well, we're talking of course, we're talking about the state of the penguin, I think it's important for people to understand, Oracle got into the Linux game in the 90s, maybe the latter part of the 90s and Oracle, of course, wants to make Linux-- wants to make Oracle, it's applications and database run better on Linux, but as you're pointing out, your Linux distro, full support, end-to-end, thousands of people in your open-source community, and the contributions that you make to Linux, many if not most, they go upstream, everybody can benefit from those, but of course you want an Oracle distro that is going to make Oracle stuff run better, that's always kind of been the Oracle way. >> Well, so, yes, two things though. One is, so everything we do is upstream. So we have no Linux patches that are not contributed upstream; There's no proprietary code in Oracle Linux at all, it's all completely open, publicly available: the source code, the change log, all the commits, it's fully open and public, which sometimes is not well-understood, but it's completely open. And, everything we do in terms of feature development or functionality or bug fixes goes upstream to the Linux kernel mail-list. It's actually, it's the only way to be able to manage a Linux distribution and be a Linux vendor is to live in that eco-system. Otherwise, the cost of maintaining your own fork, so to speak, is very high and it doesn't really solve the problem. Now, the functionality we work on obviously is focused on making Oracle products run better, making Oracle Cloud run better, and so forth. However, again, what's important to understand, though, is an Oracle database is a program running on an operating system. It does IO, it does networking, it deals with memory management, lots of processing. So, for the most part, the things that we work on to improve that helps everyone out, right? It helps every other database run better, or helps every other language run better. So none of these changes are specific to Oracle, they're just things that we found doing performance benchmarks and testing and so forth, where we say "Hey, if Linux did the following, it would make boot-up faster. Now boot-up has nothing to do with the database. But our customers run on 1-terabyte, 4-terabyte, 8-terabyte systems, and so booting up, and Linux starting up, and cleaning up memory takes a long time. So we want to reduce that from an availability point of view. So here, we're now talking about just enterprise for you. So there's this broad set of things we work on that definitely help us, but they're actually really completely generic and help everyone out. >> Yeah, that's great. So I wanted to kind of get that out of the way and help our audience understand that. So let's get into it a little bit; What are you seeing, what's going on in IT, pick your observation space and your vision of what you see happening out there. >> Well, you know, it's very interesting, it's sort of, there's two... there's sort of two worlds, right, there's the cloud world and the move to cloud, and there's the on-premises world, where people run their systems on their own. And, one of the things that we've learned is, when you talk about machine-learning, obviously, is something that's very popular these days, and automation. And so in order to rely on machine-learning well, and have algorithms that are very effective, you need lots of data. And so being a cloud vendor, and having Linux in our cloud on tens of thousands, or hundreds of thousands of servers, or more, allows us to have a view of how an operating system works across an incredibly large scale. So we get lots of data. And so for us to figure out which algorithms work well in terms of how can we do network optimizations, how can we discover anomalies on the storage site, and deal with it and so forth, we can do that at scale. And what's interesting is, how do we then bring that on-prem? Well, if we can get the data and the learning done, the training done, in our cloud directly, then when we provide that service also for people running Oracle Linux on premises then that will work. The alternative is to have point solutions where you provide something to a customer, and he needs to learn something from small amounts of data. That doesn't work so well. So I think having both worlds, on-prem and cloud directly, allows us to kind of benefit from that. And I think that's important, because lots of customers are interested in going to cloud. Many of the enterprises have not yet. You know, they're starting, but there's still a huge on-premises space that's important. And so by being able to get them familiar with how these things work at scale, autonomy is again important, right, Autonomous Database is incredibly popular and so forth, that allows us to then say, "Here, try these things out here, it's a service. We can show you the benefits right away," and then as that improves we bring that, to a certain extent, on-premises as well. And then they can have it in both places. And that, I think, is something, again, that's relatively unique but also very important, is that we want to provide services and products that act similarly on-premises as well as in cloud, because at some point when people move we want to make that transition seamless. And what you have today for the most part is one world that's on-prem, and then the cloud world is completely different. And that is a big barrier of moving, and so we want to reduce that, we can run the same operating system local as well as cloud, you can the same functionality, and then that helps transition people over much easier. >> Yeah, well Oracle actually was one of the -- I think Oracle was the first company to actually market same-same, you actually used that term. Others put forth that concept, but Oracle was the first to announce products like Cloud at Customer, that were same-same, now it took some time to actually get it perfected, and get it to market, but the point is, and we've written about this, is Oracle, because of the ascendancy of cloud, flipped and has a cloud-first mentality, and you just kind of referenced that, you just said, "And you can bring that to on-prem." So I wonder if you could talk about that cloud-first mentality, and the impact on hybrid. >> So yeah, I think the cloud-first part is of course in cloud we work on services moreso than products that we deliver. And there's a number of things that are happening. So one is that we obviously continue to provide products to customers, you can download Oracle Linux, you can download the database and what not, you can install it on your own, you can do the traditional way of working. Then in the cloud-world, what typically happens is "Oh, I use a database service. I'm not installing anything, I push a button and I get an IP address and a SQL that connects extremely quickly to the database." And we take care of everything underneath that is on this database. Now, in order to do that, you need a whole infrastructure in place, you need log-in agents, you need a back-end that captures all that stuff, you need monitoring tools, you need all the automation scripts for bringing the service up and monitor it. And so, that takes a lot of time to do right, and we learn a lot by doing this. And so the cloud-first part of these services means that we get to experience this ourselves with direct access to everything. Now taking that service with all of the additional features like autonomy, and bringing that to an on-premises world, we have to make sure we can package that so that all these pieces around it go along with it. And that takes a little bit more time, so we can do everything at the same time. And so what we've done with Autonomous Database is we created everything in Oracle Cloud, we have the whole system running really well, and then we've been able to sort of package that and shrink it into something that can be installed on-premises, but then connected into Oracle Cloud again. And so that way we can get all the telemetry over the metric, and that allows us to scale. Because part of providing a cloud service that runs on-prem in the customer environment is that we need to be able to remotely manage that similar to how that runs in our own cloud. Right, otherwise it doesn't scale. And so that takes a little bit of time, but we've done all that work, and now with Cloud at Customer Database that's really in place. >> Yeah, you really want to have that same cloud experience, whether with on-prem, in the public cloud, hybrid, et cetera. So, I want to explore a little bit more who is using Oracle Linux, and what's the driver for using it. Can you describe maybe some of the types of customers and why they buy? >> Sure, so we started this fourteen years ago, in 2006, October 25th, 2006. I remember that day very well; Penguins on stage and a big launch for Oracle Linux in San Francisco Moscone Center. So, look, the initial driver for Oracle Linux was to ensure that Oracle database customers or Oracle product customers had a good operating system experience, and the ability to be able to handle critical issues when that occurs, because typically a database runs the company's critical data: the most essential stuff that a company has is typically in a database, an Oracle database. And so when that thing has issues with the operating system, you don't want just to talk to multiple vendors and have finger-pointing, and having to explain to an operating system vendor how the database works. In the Unix world, we had a good relationship with the OS vendors, and the hardware vendors, they were the same. And they knew our products really well, and in the Linux world, that was very different. The OS vendor basically did not want to understand or learn anything about the products living on top. And so while to a certain extent that makes sense, it's an enterprise world where time is of the essence, and downtime needs to be limited absolutely. We can't have these arguments and such. And that was the driver, initially, for doing Oracle Linux. It was to ensure there was a Linux distribution really backed by us, that we could fix, that we could fully support. That was completely the original intent. And so the early customer base was database customers. Database and middleware. Mostly database. But that has then evolved quickly, and so what happened was, people say "Look, I have a thousand servers, a hundred run Oracle, so we'll run Oracle Linux on those hundred, and we'll run something else on those other nine-hundred." Now after a year or so, they realize that our support is really good; We fix all these issues, and so then they're like "Why are we having two Linux distributions? This thing works really well, it runs any application, it's fully compatible, so we'll do a thousand with Oracle Linux." And so the early days, the first few years, was definitely Oracle Database as the core driver, and then it sort of expanded to the rest of the estate. And over the years, we've added lots of features and functionality, like Ksplice, and so forth. We have an attractive pricing model for running on servers, and so now lots of our customers have a very small Oracle percentage running and many other things running. So it's really become a all-or-nothing play in the Linux space, and we're well-known now, so it's actually very good. >> You just mentioned Ksplice. We've been talking about cloud, and on-prem, and hybrid. Let's talk about security, because security really is a differentiator, particularly if you're going to start to put stuff in the cloud. Talk about Ksplice specifically, but generally security and your policy there. >> So, "Security first" is sort of what you hear us say and do, in everything we do. The database obviously security, on the Linux site security matters. Ksplice as a technology is there to do critical bug-fixing and make sure that we can apply security vulnerability fixes without affecting the customer, and not have downtime. And if you look at most of the cases or many of the cases where you have security vulnerabilities and exploits, it tends to be because systems were not patched. Why were they not patched? Well not that our customer doesn't understand that it's important, but it's a whole train of events that needs to happen. You have to, you get notified that there's a security issue in your operating system or application. Then, well, an application typically means it's a multi-layered setup. So if you have to bring your database server down, then you first have to coordinate with the application users to bring the app server down, cause that talks to the database. So to patch one system, you basically have to bring down the whole application stack. You have to negotiate with the DBAs, you have to negotiate with the app admins, you have to negotiate with the user. It takes weeks to do that and find time. Well during that time, you're vulnerable. So the only way, really, to address security in a scalable and reducing that window of time is to do it without affecting the customer. And so Casewise is something that, it's a company we acquired in 2009, and have since evolved in terms of capabilities, and so it allows us to patch the Linux terminal without downtime. We lock the kernel for 8 microseconds. It's literally no downtime. You don't have to bring down applications, the user doesn't see it, there's no hang, there's no delay. And so by doing that, you can run a Linux operating system, or gLinux, and you can be fully patched on a system that hasn't rebooted for 3 years. You don't even know it. And so by doing that type of stuff, it makes customers more secure, and it avoids them-- It saves them a lot of money in terms of dealing with project management and so forth, but it really keeps them secure. And so we do that for the Linux kernel, we do that for some of the libraries on top that are critical like OpenSSL and 2 LVC, and, you know one example-- I can give you two examples. So one example is, Heartbleed was this bug in OpenSSL a number of years ago. And so everyone had to patch their SSH server. And that meant, basically, systems around the world had to reboot. Like a whole IT reboot across the world. With Ksplice today, if Heartbleed were to happen tomorrow, we would be able to patch this online for all the Oracle Linux customers without any downtime. No reboots, no restarting of applications, everything keeps running. The amount of money saved would be massive, and also, of course, the headache. Another example is, and this was in Oracle Cloud, when some of these CPU bugs that happened a few years ago that were rather damaging on the cloud side, where you could basically see memory potentially of other CPUs running, the cloud is incredibly critical. We were basically able to basically patch our entire cloud in four hours. And the customer didn't know, right, a hundred and twenty million patches, or something, that we applied within four hours, all online, without any downtime. And so that technology has been really helpful, both for us to run our cloud, but the exact same patches and same fixes go to customers on-premises as well. But this comes back to the whole, what we do in cloud we also do for customer. And I think that's a unique thing that we have at Oracle which is quite fascinating. The operating system we run for our customers, the operating system that's the host part of VMs, is the exact same binary and source code that we make available, just to be clear, the exact same binaries are the ones that you run as a customer on-premises. So if you run Oracle Linux with KVM, you run VMs, you're actually running the exact same stuff as we run underneath our customer's stuff. Nobody else does that, everyone else has a black box. So I think that helps a little bit with transparency as well. >> Yeah, and that homogeneity just creates an environment, you're talking about that sort of security mindset, it's critical, you're not just bolting it on, it's part of the culture. But you started your career, and then of course you were a Linux person when you came to Oracle, but then I think you spent some time in database, back in the day when there were serious database wars going on, before Oracle became the king of database. So now you've got, obviously, this great portfolio, and a lot of really sharp software developers; What should we expect going forward, from Oracle? What should we look for? >> You know, I was talking to some, I was welcoming some interns to the company, for their summer internship yesterday, and one of the things I mentioned to them was that -- so cloud obviously gives us a lot of opportunities, but there's a number of things. One is, we have such a breadth of applications and software and hardware together. We have the servers, we have the storage, we have the operating systems, we have the database layer and so forth, and we have the cloud side, and one of the great opportunities, and I think we've shown a lot of this happening with the ability to create something like Autonomous Database, is to combine all these things. Right, we have such a broad portfolio of really cool technology that by itself is okay, but if you combine the things it really becomes awesome. You cannot create autonomous database without having autonomous learning. You cannot create those two and make them really safe without also controlling the firmware on the hardware and so forth. So by being able to combine all these layers, and by having a really great relationship across the teams within the company, that opens up a lot of opportunities to do stuff really quickly. And having the scale for that. I think that has been, for the last few years, a really great thing, but I can see that being one of the advantages that we have going forward. We have Oracle Fusion Applications, which is incredibly popular, and has great girth, and then we have that running on Oracle Cloud, that talks to Oracle Autonomous Database, so we bring all these pieces together. And no other SaaS vendor can do that, because they don't have these other pieces. They have one area, we have all of them. And so that's the exciting part for me, it's not so much about making my own world better, and having Linux be better, and Casewise and so forth, which is important, but that becoming part of the bigger picture. And that's the exciting part. >> Well, Oracle's always invested in RND, we've made that point many, many times. Whether it's database, you know Fusion was a painful but worthy effort, the whole public cloud piece, obviously many acquisitions, but the investments that you've made in open-source as well, Wim, you're a great spokesperson, and a great representative of the open-source community generally, and then Oracle specifically, so thanks very much for coming on theCUBE and sharing with us the state of the penguin, and best of luck. >> You're welcome. Thank you, thanks for having me. >> Alright, and thank you for watching, everybody. This is Dave Vellante for theCUBE. We'll see you next time. (cheerful music).

hello everybody and thank you for joining us today at the virtual Vertica BBC 2020 today's breakout session is entitled the road to autonomous database management how Domo is delivering SLA for less my name is su LeClair I'm the director of marketing at Vertica and I'll be your host for this webinar joining me is Ben white senior database engineer at Domo but before we begin I want to encourage you to submit questions or comments during the virtual session you don't have to wait just type your question or comment in the question box below the slides and click Submit there will be a Q&A session at the end of the presentation we'll answer as many questions as we're able to during that time any questions that we aren't able to address or drew our best to answer them offline alternatively you can visit vertical forums to post your questions there after the session our engineering team is planning to join the forum to keep the conversation going also as a reminder you can maximize your screen by clicking the double arrow button in the lower right corner of the slide and yes this virtual session is being recorded and will be available to view on demand this week we'll send you notification as soon as it's ready now let's get started then over to you greetings everyone and welcome to our virtual Vertica Big Data conference 2020 had we been in Boston the song you would have heard playing in the intro would have been Boogie Nights by heatwaves if you've never heard of it it's a great song to fully appreciate that song the way I do you have to believe that I am a genuine database whisperer then you have to picture me at 3 a.m. on my laptop tailing a vertical log getting myself all psyched up now as cool as they may sound 3 a.m. boogie nights are not sustainable they don't scale in fact today's discussion is really all about how Domo engineers the end of 3 a.m. boogie nights again well I am Ben white senior database engineer at Domo and as we heard the topic today the road to autonomous database management how Domo is delivering SLA for less the title is a mouthful in retrospect I probably could have come up with something snazzy er but it is I think honest for me the most honest word in that title is Road when I hear that word it evokes for me thoughts of the journey and how important it is to just enjoy it when you truly embrace the journey often you look up and wonder how did we get here where are we and of course what's next right now I don't intend to come across this too deep so I'll submit there's nothing particularly prescient and simply noticing the elephant in the room when it comes to database economy my opinion is then merely and perhaps more accurately my observation the office context imagine a place where thousands and thousands of users submit millions of ad-hoc queries every hour now imagine someone promised all these users that we could deliver bi leverage at cloud scale in record time I know what many of you should be thinking who in the world would do such a thing of course that news was well received and after the cheers from executives and business analysts everywhere and chance of Keep Calm and query on finally started to subside someone that turns an ass that's possible we can do that right except this is no imaginary place this is a very real challenge we face the demo through imaginative engineering demo continues to redefine what's possible the beautiful minds at Domo truly embrace the database engineering paradigm that one size does not fit all that little philosophical nugget is one I would pick up while reading the white papers and books of some guy named stone breaker so to understand how I and by extension Domo came to truly value analytic database administration look no further than that philosophy and what embracing it would mean it meant really that while others were engineering skyscrapers we would endeavor to build Datta neighborhoods with a diverse kapala G of database configuration this is where our journey at Domo really gets under way without any purposeful intent to define our destination not necessarily thinking about database as a service or anything like that we had planned this ecosystem of clusters capable of efficiently performing varied workloads we achieve this with custom configurations for node count resource pool configuration parameters etc but it also meant concerning ourselves with the unattended consequences of our ambition the impact of increased DDL activities on the catalog system overhead in general what would be the management requirements of an ever-evolving infrastructure we would be introducing multiple points of failure what are the advantages the disadvantages those types of discussions and considerations really help to define what would be the basic characteristics of our system the database itself needed to be trivial redundant potentially ephemeral customizable and above all scalable and we'll get more into that later with this knowledge of what we were getting into automation would have to be an integral part of development one might even say automation will become the first point of interest on our journey now using popular DevOps tools like saltstack terraform ServiceNow everything would be automated I mean it discluded everything from larger multi-step tasks like database designs database cluster creation and reboots to smaller routine tasks like license updates move-out and projection refreshes all of this cool automation certainly made it easier for us to respond to problems within the ecosystem these methods alone still if our database administration reactionary and reacting to an unpredictable stream of slow query complaints is not a good way to manage a database in fact that's exactly how three a.m. Boogie Nights happen and again I understand there was a certain appeal to them but ultimately managing that level of instability is not sustainable earlier I mentioned an elephant in the room which brings us to the second point of interest on our road to autonomy analytics more specifically analytic database administration why our analytics so important not just in this case but generally speaking I mean we have a whole conference set up to discuss it domo itself is self-service analytics the answer is curiosity analytics is the method in which we feed the insatiable human curiosity and that really is the impetus for analytic database administration analytics is also the part of the road I like to think of as a bridge the bridge if you will from automation to autonomy and with that in mind I say to you my fellow engineers developers administrators that as conductors of the symphony of data we call analytics we have proven to be capable producers of analytic capacity you take pride in that and rightfully so the challenge now is to become more conscientious consumers in some way shape or form many of you already employ some level of analytics to inform your decisions far too often we are using data that would be categorized as nagging perhaps you're monitoring slow queries in the management console better still maybe you consult the workflows analyzing how about a logging and alerting system like sumo logic if you're lucky you do have demo where you monitor and alert on query metrics like this all examples of analytics that help inform our decisions being a Domo the incorporation of analytics into database administration is very organic in other words pretty much company mandated as a company that provides BI leverage a cloud scale it makes sense that we would want to use our own product could be better at the business of doma adoption of stretches across the entire company and everyone uses demo to deliver insights into the hands of the people that need it when they need it most so it should come as no surprise that we have from the very beginning use our own product to make informed decisions as it relates to the application back engine in engineering we call it our internal system demo for Domo Domo for Domo in its current iteration uses a rules-based engine with elements through machine learning to identify and eliminate conditions that cause slow query performance pulling data from a number of sources including our own we could identify all sorts of issues like global query performance actual query count success rate for instance as a function of query count and of course environment timeout errors this was a foundation right this recognition that we should be using analytics to be better conductors of curiosity these types of real-time alerts were a legitimate step in the right direction for the engineering team though we saw ourselves in an interesting position as far as demo for demo we started exploring the dynamics of using the platform to not only monitor an alert of course but to also triage and remediate just how much economy could we give the application what were the pros and cons of that Trust is a big part of that equation trust in the decision-making process trust that we can mitigate any negative impacts and Trust in the very data itself still much of the data comes from systems that interacted directly and in some cases in directly with the database by its very nature much of the data was past tense and limited you know things that had already happened without any reference or correlation to the condition the mayor to those events fortunately the vertical platform holds a tremendous amount of information about the transaction it had performed its configurations the characteristics of its objects like tables projections containers resource pools etc this treasure trove of metadata is collected in the vertical system tables and the appropriately named data collector tables as a version 9 3 there are over 190 tables that define the system tables while the data collector is the collection of 215 components a rich collection can be found in the vertical system tables these tables provide a robust stable set of views that let you monitor information about your system resources background processes workload and performance allowing you to more efficiently profile diagnose and correlate historical data such as low streams query profiles to pool mover operations and more here you see a simple query to retrieve the names and descriptions of the system tables and an example of some of the tables you'll find the system tables are divided into two schemas the catalog schema contains information about persistent objects and the monitor schema tracks transient system States most of the tables you find there can be grouped into the following areas system information system resources background processes and workload and performance the Vertica data collector extends system table functionality by gathering and retaining aggregating information about your database collecting the data collector mixes information available in system table a moment ago I show you how you get a list of the system tables in their description but here we see how to get that information for the data collector tables with data from the data collecting tables in the system tables we now have enough data to analyze that we would describe as conditional or leading data that will allow us to be proactive in our system management this is a big deal for Domo and particularly Domo for demo because from here we took the critical next step where we analyze this data for conditions we know or suspect lead to poor performance and then we can suggest the recommended remediation really for the first time we were using conditional data to be proactive in a database management in record time we track many of the same conditions the Vertica support analyzes via scrutinize like tables with too many production or non partition fact tables which can negatively affect query performance and life in vertical in viral suggests if the table has a data a time step column you recommend the partitioning by the month we also can track catalog sizes percentage of total memory and alert thresholds and trigger remediations requests per hour is a very important metric in determining when a trigger are scaling solution tracking memory usage over time allows us to adjust resource pool parameters to achieve the optimal performance for the workload of course the workload analyzer is a great example of analytic database administration I mean from here one can easily see the logical next step where we were able to execute these recommendations manually or automatically be of some configuration parameter now when I started preparing for this discussion this slide made a lot of sense as far as the logical next iteration for the workload analyzing now I left it in because together with the next slide it really illustrates how firmly Vertica has its finger on the pulse of the database engineering community in 10 that OS management console tada we have the updated work lies will load analyzer we've added a column to show tuning commands the management console allows the user to select to run certain recommendations currently tuning commands that are louder and alive statistics but you can see where this is going for us using Domo with our vertical connector we were able to then pull the metadata from all of our clusters we constantly analyze that data for any number of known conditions we build these recommendations into script that we can then execute immediately the actions or we can save it to a later time for manual execution and as you would expect those actions are triggered by thresholds that we can set from the moment nyan mode was released to beta our team began working on a serviceable auto-scaling solution the elastic nature of AI mode separated store that compute clearly lent itself to our ecosystems requirement for scalability in building our system we worked hard to overcome many of the obstacles they came with the more rigid architecture of enterprise mode but with the introduction is CRM mode we now have a practical way of giving our ecosystem at Domo the architectural elasticity our model requires using analytics we can now scale our environment to match demand what we've built is a system that scales without adding management overhead or our necessary cost all the while maintaining optimal performance well we're really this is just our journey up to now and which begs the question what's next for us we expand the use of Domo for Domo within our own application stack maybe more importantly we continue to build logic into the tools we have by bringing machine learning and artificial intelligence to our analysis and decision making really do to further illustrate those priorities we announced the support for Amazon sage maker autopilot at our demo collusive conference just a couple of weeks ago for vertical the future must include in database economy the enhanced capabilities in the new management console to me are clear nod to that future in fact with a streamline and lightweight database design process all the pieces should be in place versions deliver economists database management itself we'll see well I would like to thank you for listening and now of course we will have a Q&A session hopefully very robust thank you [Applause]

>> Narrator: From theCUBE studios in Palo Alto in Boston, connecting with top leaders all around the world, this is theCUBE Conversation. >> Hi everybody, I'm Dave Vellante, and welcome to the Vertica Big Data Conference virtual. This is our digital presentation, wall to wall coverage actually, of the Vertica Big Data Conference. And with me is Jeff Healy, who directs product marketing at Vertica. Jeff, good to see you. >> Good to see you, Dave. Thanks for the opportunity to chat. >> You're very welcome Now I'm excited about the products that you guys announced and you're hardcore into product marketing, but we're going to talk about the Vertica Big Data Conference. It's been a while since you guys had this. Obviously, new owner, new company, some changes, but that new company Microfocus has announced that it's investing, I think the number was $70 million into two areas. One was security and the other, of course, was Vertica. So we're really excited to be back at the virtual Big Data Conference. And let's hear it from you, what are your thoughts? >> Yeah, Dave, thanks. And we love having theCUBE at all of these events. We're thrilled to have the next Vertica Big Data Conference. Actually it was a physical event, we're moving it online. We know it's going to be a big hit because we've been doing this for some time particularly with two of the webcast series we have every month. One is under the Hood Webcast Series, which is led by our engineers and the other is what we call a Data Disruptors Webcast Series, which is led by all customers. So we're really confident this is going to be a big hit we've seen the registration spike. We just hit 1,000 and we're planning on having about 1,000 at the physical event. It's growing and growing. We're going to see those big numbers and it's not going to be a one time thing. We're going to keep the conversation going, make sure there's plenty of best practices learning throughout the year. >> We've been at all the big BDCs and the first one's were really in the heart of the Big Data Movement, really exciting time and the interesting thing about this event is it was always sort of customers talking to customers. There wasn't a lot of commercials, an intimate event. Of course I loved it because it was in our hometown. But I think you're trying to carry that theme obviously into the digital sphere. Maybe you can talk about that a little bit. >> Yeah, Dave, absolutely right. Of course, nothing replaces face to face, but everything that you just mentioned that makes it special about the Big Data Conference, and you know, you guys have been there throughout and shown great support in talking to so many customers and leaders and what have you. We're doing the same thing all right. So we had about 40 plus sessions planned for the physical event. We're going to run half of those and we're not going to lose anything though, that's the key point. So what makes the Vertica Big Data Conference really special is that the only presenters that are allowed to present are either engineers, Vertica engineers, or best practices engineers and then customers. Customers that actually use the product. There's no sales or marketing pitches or anything like that. And I'll tell you as far as the customer line up that we have, we've got five or six already lined up as part of those 20 sessions, customers like Uber, customers like the Trade Desk, customers like Phillips talking about predictive maintenance, so list goes on and on. You won't want to miss it if you're on the fence or if you're trying to figure out if you want to register for this event. Best part about it, it's all free, and if you can't attend it live, it will be live Q&A chat on every single one of those sessions, we promise we'll answer every question if we don't get it live, as we always do. They'll all be available on demand. So no reason not to register and attend or watch later. >> Thinking about the content over the years, in the early days of the Big Data Conference, of course Vertica started before the whole Big Data Conference meme really took off and then as it took off, plugged right into it, but back then the discussion was a lot of what do I do with big data, Gartner's three Vs and how do I wrangle it all, and what's the best approach and this stuff is, Hadoop is really complicated. Of course Vertica was an alternative to RDBMS that really couldn't scale or give that type of performance for analytical databases so you had your foot in that door. But now the conversation that's interesting your theme, it's win big with data. Of course, the physical event was at the Encore, which is the new Casino in Boston. But my point is, the conversation is no longer about, how to wrangle all this data, you know how to lower the cost of storing this data, how to make it go faster, and actually make it work. It's really about how to turn data into insights and transform your organizations and quote and quote, win with big data. >> That's right. Yeah, that's great point, Dave. And that's why I mean, we chose the title really, because it's about our customers and what they're able to do with our platform. And it's we know, it's not just one platform, all of the ecosystem, all of our incredible partners. Yeah it's funny when I started with the organization about seven years ago, we were closing lots of deals, and I was following up on case studies and it was like, Okay, why did you choose Vertica? Well, the queries went fast. Okay, so what does that mean for your business? We knew we're kind of in the early adopter stage. And we were disrupting the data warehouse market. Now we're talking to our customers that their volumes are growing, growing and growing. And they really have these analytical use cases again, talk to the value at the entire organization is gaining from it. Like that's the difference between now and a few years ago, just like you were saying, when Vertica disrupted the database market, but also the data warehouse market, you can speak to our customers and they can tell you exactly what's happening, how it's moving the needle or really advancing the entire organization, regardless of the analytical use case, whether it's an internet of things around predictive maintenance, or customer behavior analytics, they can speak confidently of it more than just, hey, our queries went faster. >> You know, I've mentioned before the Micro Focus investment, I want to drill into that a bit because the Vertica brand stands alone. It's a Micro Focus company, but Vertica has its own sort of brand awareness. The reason I've mentioned that is because if you go back to the early days of MPP Database, there was a spate of companies, startups that formed. And many if not all of those got acquired, some lived on with the Codebase, going into the cloud, but generally speaking, many of those brands have gone away Vertica stays. And so my point is that we've seen Vertica have staying power throughout, I think it's a function of the architecture that Stonebraker originally envisioned, you guys were early on the market had a lot of good customer traction, and you've been very responsive to a lot of the trends. Colin Mahony will talk about how you adopted and really embrace cloud, for example, and different data formats. And so you've really been able to participate in a lot of the new emerging waves that have come out to the market. And I would imagine some of that's cultural. I wonder if you could just address that in the context of BDC. >> Oh, yeah, absolutely. You hit on all the key points here, Dave. So a lot of changes in the industry. We're in the hottest industry, the tech industry right now. There's lots of competition. But one of the things we'll say in terms of, Hey, who do you compete with? You compete with these players in the cloud, open source alternatives, traditional enterprise data warehouses. That's true, right. And one of the things we've stayed true within calling is really kind of led the charge for the organization is that we know who we are right. So we're an analytical database platform. And we're constantly just working on that one sole Source Code base, to make sure that we don't provide a bunch of different technologies and databases, and different types of technologies need to stitch together. This platform just has unbelievable universal capabilities from everything from running analytics at scale, to in Database Machine Learning with the different approach to all different types of deployment models that are supported, right. We don't go to our companies and we say, yeah, we take care of all your problems but you have to stitch together all these different types of technologies. It's all based on that core Vertica engine, and we've expanded it to meet all these market needs. So Colin knows and what he believes and what he tells the team what we lead with, is that it lead with that one core platform that can address all these analytical initiatives. So we know who we are, we continue to improve on it, regardless of the pivots and the drastic measures that some of the other competitors have taken. >> You know, I got to ask you, so we're in the middle of this global pandemic with Coronavirus and COVID-19, and things change daily by the hour sometimes by the minute. I mean, every day you get up to something new. So you see a lot of forecasts, you see a lot of probability models, best case worst case likely case even though nobody really knows what that likely case looks like, So there's a lot of analytics going on and a lot of data that people are crunching new data sources come in every day. Are you guys participating directly in that, specifically your customers? Are they using your technology? You can't use a traditional data warehouse for this. It's just you know, too slow to asynchronous, the process is cumbersome. What are you seeing in the customer base as it relates to this crisis? >> Sure, well, I mean naturally, we have a lot of customers that are healthcare technology companies, companies, like Cerner companies like Philips, right, that are kind of leading the charge here. And of course, our whole motto has always been, don't throw away any the data, there's value in that data, you don't have to with Vertica right. So you got petabyte scale types of analytics across many of our customers. Again, just a few years ago, we called the customers a petabyte club. Now a majority of our large enterprise software companies are approaching those petabyte volumes. So it's important to be able to run those analytics at that scale and that volume. The other thing we've been seeing from some of our partners is really putting that analytics to use with visualizations. So one of the customers that's going to be presenting as part of the Vertica Big Data conferences is Domo. Domo has a really nice stout demo around be able to track the Coronavirus the outbreak and how we're getting care and things like that in a visual manner you're seeing more of those. Well, Domo embeds Vertica, right. So that's another customer of ours. So think of Vertica is that embedded analytical engine to support those visualizations so that just anyone in the world can track this. And hopefully as we see over time, cases go down we overcome this. >> Talk a little bit more about that. Because again, the BDC has always been engineers presenting to audiences, you guys have a lot of you just mentioned the demo by Domo, you have a lot of brand names that we've interviewed on theCUBE before, but maybe you could talk a little bit more about some of the customers that are going to be speaking at the virtual event, and what people can expect. >> Sure, yeah, absolutely. So we've got Uber that's presenting just a quick fact around Uber. Really, the analytical data warehouse is all Vertica, right. And it works very closely with Open Source or what have you. Just to quick stat on on Uber, 14 million rides per day, what Uber is able to do is connect the riders with the drivers so that they can determine the appropriate pricing. So Uber is going to be a great session that everyone will want to tune in on that. Others like the Trade Desk, right massive Ad Tech company 10 billion ad auctions daily, it may even be per second or per minute, the amount of scale and analytical volume that they have, that they are running the queries across, it can really only be accomplished with a few platforms in the world and that's Vertica that's another a hot one is with the Trade Desk. Philips is going to be presenting IoT analytical workloads we're seeing more and more of those across not only telematics, which you would expect within automotive, but predictive maintenance that cuts across all the original manufacturers and Philips has got a long history of being able to handle sensor data to be able to apply to those business cases where you can improve customer satisfaction and lower costs related to services. So around their MRI machines and predictive maintenance initiative, again, Vertica is kind of that heartbeat, that analytical platform that's driving those initiatives So list goes on and on. Again, the conversation is going to continue with the Data Disruptors in the Under Hood webcast series. Any customers that weren't able to present and we had a few that just weren't able to do it, they've already signed up for future months. So we're already booked out six months out more and more customer stories you're going to hear from Vertica.com. >> Awesome, and we're going to be sharing some of those on theCUBE as well, the BDC it's always been intimate event, one of my favorites, a lot of substance and I'm sure the online version, the virtual digital version is going to be the same. Jeff Healey, thanks so much for coming on theCUBE and give us a little preview of what we can expect at the Vertica BDC 2020. >> You bet. >> Thank you. >> Yeah, Dave, thanks to you and the whole CUBE team. Appreciate it >> Alright, and thank you for watching everybody. Keep it right here for all the coverage of the virtual Big Data conference 2020. You're watching theCUBE. I'm Dave Vellante, we'll see you soon

>> Narrator: From Burlingame, California, it's theCUBE. Covering Sumo Logic Illuminate 2019. Brought to you by Sumo Logic. >> Hey, welcome back, everybody, Jeff Frick here with theCUBE. We're at Sumo Logic Illuminate 2019. It's at the Hyatt Regency San Francisco Airport. We're excited to be back. It's our second year, so third year of the show, and really, one of the key tenants of this whole event is the report. It's the fourth year of the report. It's The Continuous Intelligence Report, and here to tell us all about it is the VP of Product Marketing, Kalyan Ramanathan. He's, like I said, VP, Product Management of Sumo Logic. Great to see you again. >> All right, thank you, Jeff. >> What a beautiful report. >> Absolutely, I love the cover and I love the data in the report even more. >> Yeah, but you cheat, you cheat. >> How come? >> 'Cause it's not a survey. You guys actually take real data. >> Ah, that's exactly right, exactly right. >> No, I love them, let's jump into it. No, it's a pretty interesting fact, though, and it came out in the keynote that this is not a survey. Tell us how you get the data. >> Yeah, I mean, so as you already know, Sumo Logic is a continuous intelligence platform. And what we do is to help our customers manage the operations and security of the mission critical application. And the way we do that is by collecting machine data from our customers, and many of our customers, we have two thousand, our customers, they're all running modern applications in the cloud, and when we collect this machine data, we can grade insights into how are these customers building their applications, how are these customers running and securing their application, and that insight is what is reflected in this report. And so, you're exactly right, this is not a survey. This is data from our customers that we bring into our system and then what we do is really treat things once we get this data into our system. First and foremost, we completely anonymize this data. So, we don't-- >> I was going to say Let's make sure we have to get that out. >> Yes, absolutely, so we don't have any customer references in this data. Two, we genericize this data. So, we're not looking for anomalies. We are looking for broad patterns, broad trends that we can apply across all of our customers and all of these enterprises that are running modern mission critical applications in the cloud. And then three, we analyze ten weeks to Sunday. We look at these datas, we look at what stands out in terms of good sample sizes, and that's what we reflect in this report. >> Okay, and just to close a loop on that, are there some applications that you don't include? 'Cause they're just legacy applications that're running on the cloud that doesn't give you good information, or you're basically taking them all in? >> Yeah, it's a good point, I mean we collect all data and we collect all applications, so we don't opt-in applications or out applications for that matter because we don't care about it. But what we do look for is significant sample size because we want to make sure that we're not talking about onesie-twosie applications here or there. We're looking for applications that have significant eruption in the cloud and that's what gets reflected in this report. >> Okay, well, let's jump into it. We don't have time to go through the whole thing here now, but people can get it online. They can download their own version and go through it at their leisure. Biggest change from last year as the fourth year of the report. >> Yeah, I mean, look, there are three big insights that we see in this report. The first one is, while we continue to see AWS rule in the cloud and that's not surprising at all, we're starting to see pretty dramatic adoption of multi-cloud technologies. So, two years ago, we saw a smidgen of multi-cloud in this report. Now, we have seen almost a 50% growth year over year in terms of multi-cloud adoption amongst enterprises who are in the cloud, and that's a substantial jump albeit from a smaller baseline. >> Do you have visibility if those are new applications or are those existing ones that are migrating to different platforms? Are they splitting? Do you have any kind of visibility into that? >> Yeah, I mean, it's an interesting point, and part of this is very related to the growth of Kubernetes that we also see in this report. What ypu've seen is that, in AWS itself, Kubernetes adoption has gone up significantly, what's even more interesting is that, as you think about multi-cloud adoption, we see a lot of Kubernetes, Kubernetes as the platform that is driving this multi-cloud adoption. There is a very interesting chart in this report on page nine. Obviously, I think you guys can see this if they want to download the report. If you're looking at AWS only, we see one in five customers are adopting Kubernetes. If you're looking at AWS and GCP, Google Cloud Platform, we see almost 60% of our customers are adopting Kubernetes. Now, when you put in AWS-- >> One in five at AWS, 60% we got Google, so that means four out of five at GCP are using Kubernetes and bring that average up. >> And then, if you look at AWS, Azure, and GCP, now you're talking about the creme de la creme customers who want to adopt all three clouds, it's almost 80% adoption of Kubernetes, so what it tells you is that Kubernetes has almost become this new Linux in the cloud world. If I want to deploy my application across multiple clouds, guess what, Kubernetes is that platform that enables me to deploy my application and then port it and re-target it to any other cloud or, for that matter, even an on-prem environment. >> Now, I mean, you don't see motivation behind action, but I'm just curious how much of it is now that I have Kubernetes. I can do multi-cloud or I've been wanting to do multi-cloud, and now that I have Kubernetes, I have an avenue. >> Yeah, it started another question. What's the chicken and what's the egg right here? My general sense, and we've debated this endlessly in our company, our general sense has been that the initiative to go multi-cloud typically comes top down in an organization. It's usually the CIO or the CSO who says, you know what, we need to go multi-cloud. And there are various reasons to go multi-cloud, some of which you heard in our keynote today. It could be for more reliability, it could be for more choice that you may want, it could be because you don't want to get logged into any one cloud render, so that decision usually comes top down. But then, now, the engineering teams, the ops teams have to support that decision, and what these engineering teams and these ops teams have realized is that, if they deploy Kubernetes, they have a very good option available now to port their applications very easily across these various cloud platforms. So, Kubernetes, in some sense, is supporting the top down decision to go multi-cloud which is something that is shown in spades as a result of this report. >> So, another thing that jumped out at me, or is there another top trend you want to make sure we cover before we get in some of those specifics? >> I mean we can talk to-- >> Yeah, one of them, one of them that jumped out at me was Docker. The Docker adoption. So, Docker was the hottest thing since sliced bread about four years ago, and is the shade of Kubernetes, not that they're replacements for one another specifically, but it definitely put a little bit of appall in the buzz that was the Docker, yet here, the Docker utilization, Docker use is growing year over year. 30%! >> I'll be the first one to tell you that Docker adoption has not stalled at all. This is shown in the report. It's shown in customers that we talk to. I mean, everyone is down the path of containerizing their application. The value of Docker is indisputable. That I get better agility, that I get better portability with Docker cannot be questioned. Now, what is indeed happening is that everyone who is deploying Docker today is choosing a orchestration technology and that orchestration technology happens to be Kubernetes. Again, Kubernetes is the king of the hill. If I'm deploying Docker, I'm deploying Kubernetes along with it. >> Okay, another one that jumped out at me, which shouldn't be a big surprise, but I'm a huge fan of Andy Jassy, we do all the AWS shows, and one of always the shining moments is he throws up the slide, he's got the Customer slide. >> There you go. >> It's the Services slide which is, in like, 2.6 font across a 100-foot screen that fills Las Vegas, and yet, your guys' findings is that it's really: the top ten applications are the vast majority of the AWS offerings that are being consumed. >> Yep, not just that. It's that the top services in AWS are the infrastructure-as-a-service services. These are the core services that you need if you have to build an application in AWS. You need ECDO, I need Esri, I need identity access management. Otherwise, I can't even log into AWS. So, this again goes back to that first point that I was making was that multi-cloud adoption is top of mind for many, many customers right now. It's something that many enterprises think of, and so, if I want to indeed be able to port my application from AWS to any other environment, guess what I should be doing? I shouldn't be adopting every AWS service out there because if I frankly adopted all these AWS services, the tentacles of the cloud render are just so that I will not be able to port away from my cloud render to any other cloud service out there. So, to a certain extent, many of the data points that we have in this report support the story that enterprises are becoming more conscious of the cloud platform choices that they are making. They want to at least keep an option of adopting the second or the third cloud out there, and they're consciously, therefore choosing the services that they are building their applications with. >> So, another hot topic, right? Computer 101 is databases. We're just up the road from Oracle. Oracle OpenWorld's next week. A lot of verbal jabs between Oracle and some of the cloud providers on the databases, et cetera. So, what do the database findings come back as? >> I mean, look at the top four databases: Redis, MySQL, Postgres, Mongo. You know what's common across them? They're all open-source. They're all open-source database, so if you're building your application, find standard components that you can then build your application on, whether it's a community that you can then take and move to any other cloud that you want to. That's takeaway number one. Takeaway number two, look at where Oracle is in this report. I think they're the eighth database in the cloud. I actually talked to a few customers of ours today. >> Now, are you sampling from Oracle's cloud? Is that a dataset? >> No, this is-- >> Yes, right, okay. So, I thought I want to make sure. >> And, if AWS is almost the universe of cloud today, we can debate at some bids, but it is close enough, I'd say, it tells you where Oracle is in this cloud universe, so our friends at Redwood City may talk about cloud day in and day out, but it's very clear that they're not making much of intent in the cloud at this point. >> And then, is this the first year the rollup of the type of database that NoSQL exceeded relational database? >> No, I mean, we've been doing this for the last two years, and it's very clear that NoSQL is ahead of SQL in the cloud, and I think the way we think about it is primarily because, when you are re-architecting your applications in the cloud, the cloud gives you a timeline, it gives you an opportunity to reconsider how you build out your data layer, and many of our customers are saying NoSQL is the way to go. The scalability demands, the reliability demands, so if my application was such that I now have the opportunity to rethink and redo my data layer, and frankly, NoSQL is winning the game. >> Right, it's winning big time. Another big one: serverless, Lambda. Actually, I'm kind of surprised it took so long to get to Lambda 'cause we've been going to smaller atomic units of compute, store, and networking for so, so long, but it sounds like, looks like we're starting to hit some critical mass here. >> Yeah, I mean, look, Lambda's ready for primetime. I mean we have seen that tipping point out here. Almost one in three customers of ours are using Lambda in production environments. And then, if you cast a wider net, go beyond production and even look at dev tests, what we see is that almost 60% of Sumo Logic's customers, and if you look at 2,000 customers, that's a pretty big sample size. Almost 60% of enterprises are using Lambda in some way, shape, or form. So, I think it's not surprising that Lambda is getting used quite well in the enterprise. The question really is: what are these people doing with Lambda? What's the intent behind the use of Lambda? And that's where I think we have to do some more research. My general sense, and I think it's shared widely within Sumo Logic, is that Lambda's still at the edges of the application. It's not at the core of the application. People are not building your mission critical application on Lambda yet because I think that that paradigm of thinking about event-driven application is still a little foreign to many organizations, so I think it'll take a few more years for an entire application to be built on Lambda. >> But you would think, if it's variable demand applications, whether that's a marketing promotion around the Super Bowl or running the books at the end of the month, I guess it's easy enough to just fire up the servers versus doing a pure Lambda at this point in time, but it seems like a natural fit. >> If you're doing the utility type application and you want to start it and you want to kill it and not use it after an event has come and gone, absolutely, Lambda's the way to go. The economics of Lambda. Lambda absolutely makes sense. Having said that, I mean, if you're to build a true mission critical application that you're going to be keeping on for a while to come, I'm not seeing a lot of that in Lambda yet, but it's definitely getting there. I mean we have lots of customers who are building some serious stuff on Lambda. >> Well, a lot of great information. It's nice to have the longitudinal aspect as you do this year over year, and again, we're glad you're cheating 'cause you're getting good data. >> (chuckles) >> (laughs) You're not asking people questions. >> Yeah, I mean, I'd like to finish out by saying this is a report that Sumo Logic builds every year, not because we want to sell Sumo Logic. It's because we want to give back to our community. We want our community to build great apps. We want them to understand how their peers are building some amazing mission critical apps in the cloud and so, please download this report, learn from how your peers are doing things, and that's our only intent and goal from this report. >> Great, well, thanks for sharing the information and a great catch-up, nice event. >> All right, thank you very much, Jeff. >> All right, he's Kalyan, I'm Jeff. You're watching theCUBE. We're at Sumo Logic Illuminate 2019. Thanks for watching, we'll see you next time. (upbeat electronic music)

>> live from London, England. It's the queue covering a ws summat. London twenty nineteen Brought to you by Amazon Web services. >> Thiss really is huge, >> isn't it? David >> London is my co star today on the Cube. We're going to be extracting the signal from the noise and there is a lot of noise. Just trying to register. Here was an event in itself, and one guy in the queue with me earlier said, You know, this is like an army of young technologist backing one particular platform, and we've had the main keynote speeches already in the conference hall. There are breakout sessions going on as well as we speak. And in those keynote speeches, it really wants the focus again on Hey I and machine learning and a huge array of services that eight of us now provide. Because, of course, every tech company, every company is a tech company these days. Where do you work in transportation or defense or retail? Let's talk >> about Dave a little bit about a ws and the exponential growth that it's seen over the past two years because it just keeps on getting bigger and you could see testament really out there just so many people here. >> You know, Susannah, when a WS announced its first service in two thousand six, very quietly announced E C, too, which is a computer service. Nobody really paid much attention. But a devious has permanently changed the landscape of the of the technology business. And we're here in London twelve thousand people at a one day summit. I mean, that's his large as many or or larger than most U. S based three day conferences. >> And there are many thousands more watching the life streaming as well, >> right? And when you talk to the people here, they're a division. First of them has builders, and it was interesting to hear some of the key knows this morning talking about some of the innovations that occurred in the UK he obviously UK, very prideful country. The first lights in electric lights work the Savoy Theatre, the Colossus, you know, Code breaker and many, many others. Home computing originated in the UK It so a diverse are connecting that invention and that what they call reinvention. Eight of us talks about his differentiation. The number of regions that it has around the world believe they said twenty one regions, sixty for availability zones, which are little, many regions inside of the regions. In case there's a problem, you can fail over fourteen database services. You know what's happening is all the traditional tea, which is eighty percent of the market place, trying to sort of hang on to their legacy install basis. So they're trying to substantially mimic eight of us. The problem is, eight of us moves faster, has more services, and it's just growing at such a phenomenal rate. >> And it's really kind of bottom up. A CZ. Well, it's so got that head start. So it's learning from its current customers and those it's had in the past, really to find out what new services they want that has his wealth of data ofthe gods to build on it, doesn't it? So every it seems every month it's it's another step ahead. >> Well, the data is critical. Amazon. Is it a dogfight? I always say, for your data with Google and Microsoft and Oracle, they all want your data. Why? Because data is the most valuable resource today, right? People talk about data is the new oil. We think data is more valuable than oil. You could put oil in your car. You can put in your house, but you can't put it in. Both data is reusable in a way that we've never seen a natural resource before. So it's extremely powerful applying machine intelligence to data. So Amazon knows if it can get your data into the cloud and do so cost effectively and deliver services that make you happy and delight you that they have a perpetual business model that's really unbeatable. The company now is at a thirty billion dollars run rate, growing at a constant currency rate of forty two percent per year. No people will say, Well, well, Microsoft is going faster. Microsoft is growing at seventy two percent here, but it's a much, much smaller base we're talking about single digit, a few billion versus thirty billion. So Amazon each year is growing at a nine to ten billion dollars incremental rate. Even more importantly, the operating income is phenomenal. I mean, a WS is only twelve percent of Amazon's revenue, but it accounts for fifty percent of its operating income. Hey, Ws is operating income is is in the high twenties, twenty eight twenty nine percent higher than Cisco, higher than AMC when it when he had seen was a public company. And those air very profitable companies the only companies that are more profitable on a percentage basis that that Amazon a pure place, software companies like an oracle. So Amazon, who's an infrastructure company, is as profitable almost as a software company. It's astounding, >> really interesting to see some of the partners that were invited on. It's about the keynote speeches. For example, Saint spreads so real traditional retailer at a prompter state that they'd be in the business for one hundred fifty years and some would say in many ways a competitive toe. Amazon at marketplace because they sell a vast array of goods and services to the customers. But they talked about how they're using around eighty eight WS services. It's always like a kind of a pic, a mix sweet shop. Or, as you would say, a candy store isn't and I think that's that's some of the benefits that some customers view for A W. S. Some would say, actually, I would prefer all of my product be in one place or the car that access and services in one place. And so is this pick a mix idea that I think really is taking off, isn't it? >> I'm glad you brought up the state's very example because, essentially, in a way, they are in adjacent competitors Teo, eight, of us. And yet they've chosen to put their data. And there's in leverage Amazon services. It's like Netflix. Everybody uses Netflix as the example. I mean, they compete vigorously with with Amazon Prime Video, and yet they choose to run in the age of U. S code. Now this is one of the areas where you heard at the Google Cloud next show a lot of talk about retail companies, you know, considering using Google, because, of course, they're concerned about Amazon eating their lunch. And so it's a hard decision for retail companies to make. Sainsbury obviously has said OK, we can compete. We have a unique advantage with Amazon retail, you know, but it's something worth watching for sure, because, you know, Walmart obviously doesn't wantto run in the eight of us Cloud because it's it's fearful. Ah, at the same time, Amazon would tell you, Auntie Jessie offenses look. There's a brick wall between eight of us and the retail side. We don't share data, so it's just a matter of that. Trade off is the risk of running in a ws er and potentially running at a competitors sight worth the extra value that you get out of the services. And that's what the market has to decide, >> yet certainly does interesting as well. We had the Department of Justice on the UK Department of Justice because they're has beans real concerned about security, about putting all your eggs in one basket effectively put a your data into a club no operated by you. And it does, though seem is, though little by little, some of those security fears are being laid up. Play >> well, there was this. The seminal moment in a WS. His history was in two thousand thirteen, when it won the CIA CIA contract who was more security conscious than the CIA. And they beat Big Blue IBM for that contract way back in two thousand thirteen, and the analysis that came out of that because IBM contested that contract. What came out of that was information that suggested that eight of us said the far superior solution forced IBM to go spend two billion dollars on a company called Software to actually get into the public Cloud does. It couldn't really compete with its own sets of services, and since that, Amazon has only accelerated its lead. IBM, of course, has a public cloud, and it's competitive in its own right. But the point is that the CIA determined that security the cloud was better than it could do on Prem. Now you're seeing the big battle for the Jet I contract Joint Enterprise Defensive Initiative. It's the biggest story in DC Amazon is the front runner. It's down the Amazon and Microsoft. Not surprisingly, Oracle has contested that because the government uses these sources from multiple suppliers and there's contesting it, saying, Hey, that's not fair to use one cloud. When a vendor contests Abid, a lot of information comes out. The General Accountability Office and the D. O. D determined that a single cloud was more secure, more reliable, more cost effective and less complex to run. So this is big debate around multi cloud versus single cloud. And again, Amazon continues to lead in the marketplace and in many many instances, is winning >> on DH. There were a few comments made in certainly one of the key notes today, trying to kind of blow the competition out of the water again knows whether a few specific references, in fact, to Oracle and Microsoft >> were right. And so they called the database freedom they had hashtag database freedom again. As they say, Microsoft, IBM, Oracle, Amazon, they're in a fight for your data. That's why Oracle has launched fourteen database services. Now it's not trivial. So Sainsbury and the Ministry of Justice both talked about moving Oracle databases into the eight of us Cloud. It's not trivial. It's much easier for data warehouse and stateless applications for online transaction processing. Things like banking much, much more difficult to migrate into the clouds. So it's interesting. Sainsbury talked about racquets stands for a really application close. There's a very high end, complicated Oracle database that they migrated to Aurora. The Ministry of Justice talked about moving Oracle in tow. RGS, this is a battle I tweeted today earlier, Susana, you pick up the Wall Street Journal is a quarter page ad on the front page. Cut your Amazon bill in half now, of course, what? Oracle doesn't tell you is that they date to X the price when you're running on or on Amazon versus Oracle. So they're playing pricing games. Having said that organism very good database, the best database in the industry, the most reliable. So for mission critical applications, Oracle continues to be the leader. However, Oracle, strong arms people, they'LL, they'LL raise prices, they'LL get you in a headlock and do audits. And that's what Amazon was referring today about Microsoft and Oracle will do out. It's so they position. They tried a D position Oracle as an evil company. The Oracle, of course, so way add value. We have the best database, and they're trying to add value for the customers. Build their own cloud. So it's quite a battle that's going on, and you see the instance. Creation of that battle manifest itself in the general contract. >> Absolutely interesting is well, what we heard from really both states bruise on the Ministry of Justice, really talking about the end users and how they're so different. So for public sector organizations, this isn't about making more money making profit. It's about the experience for the user. But in fact, that came up from Sainsbury's as well, making sure that the right products are with the right part of the store. And that's how a I could help them do that and efficient, usable data they currently have. >> I think every enterprise really wants to have a consumer app like experience, and very few do. I mean, we all know used these enterprise APS from large, you know, brands, and they're often times not that great. So what, you're seeing a closing of the Gap? People see what's happening with Facebook and Instagram and Whatsapp and so forth and say we should be able to have apse that run that simply and so you're seeing that gap clothes. I don't see how you could do that without some kind of public cloud infrastructure because of the massive scale that's required. It's so companies like Saintsbury are moving in that direction. Mobile has been critical for the last decade, and so that's what the consumer wants. That's what the cloud can provide. >> Is that what every consumer wants? Because increasingly, we're hearing a lot more concerned about privacy, that people not wanting to give all of her data across to private companies and do you think this could be dist sticking point ready going forward and could actually hold back the growth all they ws and its competitors >> a great point because you have a problem. Wonder problems. You have this app creep. I can tell you have dozens and dozens and dozens of app on my phone. I don't know if I trust them with the data. So having said that, one way to simplify that is to eliminate the need to do heavy lifting and patching of your infrastructure. Let us take care of that and build value up the stack by focusing re shifting your resource is on on value added services. Could it be a problem? I think no question. When Snowden came out in the U. S. People in Europe for sure. As you know, we're concerned about putting their data in the cloud that seems to have attenuated. I don't hear much about that anymore, you know. But if the NSA can come in and demand access to my data, well, that could be problematic. That's why I ws is putting so much or one reason why they're putting so much emphasis on setting up regions. It not just eight of us, Amazon and Google and Microsoft as well for many reasons. Privacy. GPR compliance on of course, Leighton. See the laws of physics? >> Absolutely. Okay, Dave Melody, thank you very much for being with me here at the age of us. That summit here >> in London at the XL Center there is still so much going on here. Lots of breakout sessions, many more kind of individual keynotes taking place with the various different subsections. Although the A W s business and also its partners. So we will be keeping across all of those on the Cube. Thanks for watching.