>>from around the globe. It's the Cube presenting Cuban cloud brought to you by silicon angle. Okay, >>we're now going to explore the vision of the future of cloud computing From the perspective of one of the leaders in the field, J G >>Share >>a pure off is the vice president of As Your Data ai and Edge at Microsoft G. Welcome to the Cuban cloud. Thanks so much for participating. >>Well, thank you, Dave, and it's a real pleasure to be here with you. And I just wanna welcome the audience as well. >>Well, jg judging from your title, we have a lot of ground to cover, and our audience is definitely interested in all the topics that are implied there. So let's get right into it. You know, we've said many times in the Cube that the new innovation cocktail comprises machine intelligence or a I applied to troves of data. With the scale of the cloud. It's it's no longer, you know, we're driven by Moore's law. It's really those three factors, and those ingredients are gonna power the next wave of value creation and the economy. So, first, do you buy into that premise? >>Yes, absolutely. we do buy into it. And I think, you know, one of the reasons why we put Data Analytics and Ai together is because all of that really begins with the collection of data and managing it and governing it, unlocking analytics in it. And we tend to see things like AI, the value creation that comes from a I as being on that continues off, having started off with really things like analytics and proceeding toe. You know, machine learning and the use of data. Interesting breaks. Yes. >>I'd like to get some more thoughts around a data and how you see the future data and the role of cloud and maybe how >>Microsoft, you >>know, strategy fits in there. I mean, you, your portfolio, you got you got sequel server, Azure, Azure sequel. You got arc, which is kinda azure everywhere for people that aren't familiar with that. You've got synapse. Which course that's all the integration a data warehouse, and get things ready for B I and consumption by the business and and the whole data pipeline and a lot of other services as your data bricks you got You got cosmos in their, uh, Blockchain. You've got open source services like Post Dress and my sequel. So lots of choices there. And I'm wondering, you know, how do you think about the future of Of of Cloud data platforms? It looks like your strategies, right tool for the right job? Is that fair? >>It is fair, but it's also just to step back and look at it. It's fundamentally what we see in this market today is that customer was the Sikh really a comprehensive proposition? And when I say a comprehensive proposition, it is sometimes not just about saying that. Hey, listen way No, you're a sequel server company. We absolutely trust that you have the best Azure sequel database in the cloud, but tell us more. We've got data that's sitting in her group systems. We've got data that's sitting in Post Press in things like mongo DB, right? So that open source proposition today and data and data management and database management has become front and center, so are really sort of push. There is when it comes to migration management, modernization of data to present the broadest possible choice to our customers so we can meet them where they are. However, when it comes to analytics. One of the things they asked for is give us a lot more convergence use. You know it, really, it isn't about having 50 different services. It's really about having that one comprehensive service that is converged. That's where things like synapse Fitzer, where in just land any kind of data in the leg and then use any compute engine on top of it to drive insights from it. So, fundamentally, you know, it is that flexibility that we really sort of focus on to meet our customers where they are and really not pushing our dogma and our beliefs on it. But to meet our customers according to the way they have deployed stuff like this. >>So that's great. I want to stick on this for a minute because, you know, I know when when I have guests on like yourself, do you never want to talk about you know, the competition? But that's all we ever talk about. That's all your customers ever talk about, because because the counter to that right tool for the right job and that I would say, is really kind of Amazon's approach is is that you got the single unified data platform, the mega database that does it all. And that's kind of Oracle's approach. It sounds like you wanna have your cake and eat it, too, so you you got the right tool for the right job approach. But you've got an integration layer that allows you to have that converge database. I wonder if you could add color to that and you confirm or deny what I just said. >>No, that's a That's a very fair observation, but I I say there's a nuance in what I sort of describe when it comes to data management. When it comes to APS, we have them customers with the broadest choice. Even in that, even in that perspective, we also offer convergence. So, case in point, when you think about Cosmos TV under that one sort of service, you get multiple engines, but with the same properties, right global distribution, the five nines availability. It gives customers the ability to basically choose when they have to build that new cloud native AB toe, adopt cosmos Davey and adopted in a way that it's and choose an engine that is most flexible. Tow them, however you know when it comes to say, you know, writing a sequel server, for example from organizing it you know you want. Sometimes you just want to lift and shift it into things. Like I asked In other cases, you want to completely rewrite it, so you need to have the flexibility of choice there that is presented by a legacy off What's its on premises? When it moved into things like analytics, we absolutely believe in convergence, right? So we don't believe that look, you need to have a relation of data warehouse that is separate from a loop system that is separate from, say, a B I system. That is just, you know, it's a bolt on for us. We love the proposition off, really building things that are so integrated that once you land data, once you prep it inside the lake, you can use it for analytics. You can use it for being. You can use it for machine learning. So I think you know, are sort of differentiated. Approach speaks for itself there. Well, >>that's that's interesting, because essentially, again, you're not saying it's an either or, and you're seeing a lot of that in the marketplace. You got some companies say no, it's the Data Lake and others saying No, no put in the data warehouse and that causes confusion and complexity around the data pipeline and a lot of calls. And I'd love to get your thoughts on this. Ah, lot of customers struggled to get value out of data and and specifically data product builders of frustrated that it takes too long to go from. You know, this idea of Hey, I have an idea for a data service and it could drive monetization, but to get there, you gotta go through this complex data lifecycle on pipeline and beg people to add new data sources. And do you do you feel like we have to rethink the way that we approach data architectures? >>Look, I think we do in the cloud, and I think what's happening today and I think the place where I see the most amount of rethink the most amount of push from our customers to really rethink is the area of analytics in a I. It's almost as if what worked in the past will not work going forward. Right? So when you think about analytics on in the Enterprise today, you have relational systems, you have produced systems. You've got data marts. You've got data warehouses. You've got enterprise data warehouses. You know, those large honking databases that you use, uh, to close your books with right? But when you start to modernize it, what deep you are saying is that we don't want to simply take all of that complexity that we've built over say, you know, 34 decades and simply migrated on mass exactly as they are into the cloud. What they really want is a completely different way of looking at things. And I think this is where services like synapse completely provide a differentiated proposition to our customers. What we say there is land the data in any way you see shape or form inside the lake. Once you landed inside the lake, you can essentially use a synapse studio toe. Prep it in the way that you like, use any compute engine of your choice and and operate on this data in any way that you see fit. So, case in point, if you want to hydrate relation all data warehouse, you can do so if you want to do ad hoc analytics using something like spark. You can do so if you want to invoke power. Bi I on that data or b i on that data you can do so if you want to bring in a machine learning model on this breath data you can do so, so inherently. So when customers buy into this proposition, what it solves for them and what it gives them is complete simplicity, right? One way to land the data, multiple ways to use it. And it's all eso. >>Should we think of synapse as an abstraction layer that abstracts away the complexity of the underlying technology? Is that a fair way toe? Think about it. >>Yeah, you can think of it that way. It abstracts away, Dave a couple of things. It takes away the type of data, you know, sort of the complexities related to the type of data. It takes away the complexity related to the size of data. It takes away the complexity related to creating pipelines around all these different types of data and fundamentally puts it in a place where it can be now consumed by any sort of entity inside the actual proposition. And by that token, even data breaks. You know, you can, in fact, use data breaks in in sort off an integrated way with a synapse, Right, >>Well, so that leads me to this notion of and then wonder if you buy into it s Oh, my inference is that a data warehouse or a data lake >>could >>just be a node in inside of a global data >>mesh on. >>Then it's synapses sort of managing, uh, that technology on top. Do you buy into that that global data mesh concept >>we do. And we actually do see our customers using synapse and the value proposition that it brings together in that way. Now it's not where they start. Often times when a customer comes and says, Look, I've got an enterprise data warehouse, I want to migrate it or I have a group system. I want to migrate it. But from there, the evolution is absolutely interesting to see. I give you an example. You know, one of the customers that we're very proud off his FedEx And what FedEx is doing is it's completely reimagining its's logistics system that basically the system that delivers What is it? The three million packages a day on in doing so in this covert times, with the view of basically delivering our covert vaccines. One of the ways they're doing it is basically using synapse. Synapse is essentially that analytic hub where they can get complete view into their logistic processes. Way things are moving, understand things like delays and really put all that together in a way that they can essentially get our packages and these vaccines delivered as quickly as possible. Another example, you know, is one of my favorite, uh, we see once customers buy into it, they essentially can do other things with it. So an example of this is, uh is really my favorite story is Peace Parks Initiative. It is the premier Air White Rhino Conservancy in the world. They essentially are using data that has landed in azure images in particular. So, basically, you know, use drones over the vast area that they patrol and use machine learning on this data to really figure out where is an issue and where there isn't an issue so that this part with about 200 rangers can scramble surgically versus having to read range across the last area that they cover. So What do you see here is you know, the importance is really getting your data in order. Landed consistently. Whatever the kind of data ideas build the right pipelines and then the possibilities of transformation are just endless. >>Yeah, that's very nice how you worked in some of the customer examples. I appreciate that. I wanna ask you, though, that that some people might say that putting in that layer while it clearly adds simplification and e think a great thing that they're begins over time to be be a gap, if you will, between the ability of that layer to integrate all the primitives and all the peace parts on that, that you lose some of that fine grain control and it slows you down. What would you say to that? >>Look, I think that's what we excel at, and that's what we completely sort of buy into on. It's our job to basically provide that level off integration that granularity in the way that so it's an art, absolutely admit it's an art. There are areas where people create simplicity and not a lot of you know, sort of knobs and dials and things like that. But there are areas where customers want flexibility, right? So I think just to give you an example of both of them in landing the data inconsistency in building pipelines, they want simplicity. They don't want complexity. They don't want 50 different places to do this. Just 100 to do it. When it comes to computing and reducing this data analyzing this data, they want flexibility. This is one of the reasons why we say, Hey, listen, you want to use data breaks? If you're you're buying into that proposition and you're absolutely happy with them, you can plug plug it into it. You want to use B I and no, essentially do a small data mart. You can use B I If you say that. Look, I've landed in the lake. I really only want to use em melt, bringing your animal models and party on. So that's where the flexibility comes in. So that's sort of really sort of think about it. Well, >>I like the strategy because, you know, my one of our guest, Jim Octagon, e E. I think one of the foremost thinkers on this notion of off the data mesh and her premises that that that data builders, data product and service builders air frustrated because the the big data system is generic to context. There's no context in there. But by having context in the big data architecture and system, you could get products to market much, much, much faster. So but that seems to be your philosophy. But I'm gonna jump ahead to do my ecosystem question. You've mentioned data breaks a couple of times. There's another partner that you have, which is snowflake. They're kind of trying to build out their own, uh, data cloud, if you will, on global mesh in and the one hand, their partner. On the other hand, there are competitors. How do you sort of balance and square that circle? >>Look, when I see snowflake, I actually see a partner. You know that when we essentially you know, we are. When you think about as you know, this is where I sort of step back and look at Azure as a whole and in azure as a whole. Companies like snowflakes are vital in our ecosystem, right? I mean, there are places we compete, but you know, effectively by helping them build the best snowflake service on Asia. We essentially are able toe, you know, differentiate and offer a differentiated value proposition compared to, say, a Google or on AWS. In fact, that's being our approach with data breaks as well, where you know they are effectively on multiple club, and our opportunity with data breaks is toe essentially integrate them in a way where we offer the best experience. The best integrations on Azure Barna That's always been a focus. >>That's hard to argue with. Strategy. Our data with our data partner eat er, shows Microsoft is both pervasive and impressively having a lot of momentum spending velocity within the budget cycles. I wanna come back thio ai a little bit. It's obviously one of the fastest growing areas in our in our survey data. As I said, clearly, Microsoft is a leader in this space. What's your what's your vision of the future of machine intelligence and how Microsoft will will participate in that opportunity? >>Yeah, so fundamentally, you know, we've built on decades of research around, you know, around, you know, essentially, you know, vision, speech and language that's being the three core building blocks and for the for a really focused period of time we focused on essentially ensuring human parody. So if you ever wondered what the keys to the kingdom are it, czar, it's the most we built in ensuring that the research posture that we've taken there, what we then done is essentially a couple of things we focused on, essentially looking at the spectrum. That is a I both from saying that, Hollis and you know it's gotta work for data. Analysts were looking toe basically use machine learning techniques, toe developers who are essentially, you know, coding and building a machine learning models from scratch. So for that select proposition manifesto us, as you know, really a. I focused on all skill levels. The other court thing we've done is that we've also said, Look, it will only work as long as people trust their data and they can trust their AI models. So there's a tremendous body of work and research we do in things like responsibility. So if you ask me where we sort of push on is fundamentally to make sure that we never lose sight of the fact that the spectrum off a I, and you can sort of come together for any skill level, and we keep that responsibly. I proposition. Absolutely strong now against that canvas, Dave. I'll also tell you that you know, as edge devices get way more capable, right where they can input on the edge, see a camera or a mike or something like that, you will see us pushing a lot more of that capability onto the edge as well. But to me, that's sort of a modality. But the core really is all skill levels and that responsible denia. >>Yeah, So that that brings me to this notion of wanna bring an edge and and hybrid cloud Understand how you're thinking about hybrid cloud multi cloud. Obviously one of your competitors, Amazon won't even say the word multi cloud you guys have, Ah, you know, different approach there. But what's the strategy with regard? Toe, toe hybrid. You know, Do you see the cloud you bringing azure to the edge? Maybe you could talk about that and talk about how you're different from the competition. >>Yeah, I think in the edge from Annette, you know, I live in I'll be the first one to say that the word nge itself is conflated. Okay, It's, uh but I will tell you, just focusing on hybrid. This is one of the places where you know I would say the 2020 if I would have looked back from a corporate perspective. In particular, it has Bean the most informative because we absolutely saw customers digitizing moving to the cloud. And we really saw hybrid in action. 2020 was the year that hybrid sort of really became really from a cloud computing perspective and an example of this is we understood it's not all or nothing. So sometimes customers want azure consistency in their data centers. This is where things like Azure stack comes in. Sometimes they basically come to us and say, We want the flexibility of adopting flexible pattern, you know, platforms like, say, containers orchestra, Cuban Pettis, so that we can essentially deployed wherever you want. And so when we design things like art, it was built for that flexibility in mind. So here is the beauty of what's something like our can do for you. If you have a kubernetes endpoint anywhere we can deploy and as your service onto it, that is the promise, which means if for some reason, the customer says that. Hey, I've got this kubernetes endpoint in AWS and I love as your sequel. You will be able to run as your sequel inside AWS. There's nothing that stops you from doing it so inherently you remember. Our first principle is always to meet our customers where they are. So from that perspective, multi cloud is here to stay. You know, we're never going to be the people that says, I'm sorry, we will never see a But it is a reality for our customers. >>So I wonder if we could close. Thank you for that by looking, looking back and then and then ahead. And I wanna e wanna put forth. Maybe it's, Ah criticism, but maybe not. Maybe it's an art of Microsoft, but But first you know, you get Microsoft an incredible job of transitioning. It's business as your nominee president Azzawi said. Our data shows that so two part question First, Microsoft got there by investing in the cloud, really changing its mind set, I think, in leveraging its huge software state and customer base to put Azure at the center of its strategy, and many have said me included that you got there by creating products that air Good enough. You know, we do a 1.0, it's not that great. And the two Dato, and maybe not the best, but acceptable for your customers. And that's allowed you to grow very rapidly expanding market. >>How >>do you respond to that? Is that is that a fair comment? Ume or than good enough? I wonder if you could share your >>thoughts, gave you? You hurt my feelings with that question. I don't hate me, g getting >>it out there. >>So there was. First of all, thank you for asking me that. You know, I am absolutely the biggest cheerleader. You'll find a Microsoft. I absolutely believe you know that I represent the work off almost 9000 engineers and we wake up every day worrying about our customer and worrying about the customer condition and toe. Absolutely. Make sure we deliver the best in the first time that we do. So when you take the platter off products we've delivered in nausea, be it as your sequel, be it as your cosmos TV synapse as your data breaks, which we did in partnership with data breaks, a za machine learning and recently when we prevail, we sort off, you know, sort of offered the world's first comprehensive data government solution in azure purview. I would humbly submit to you that we're leading the way and we're essentially showing how the future off data ai and the actual work in the cloud. >>I'd be disappointed if you if you had If you didn't, if you capitulated in any way J g So so thank you for that. And the kind of last question is, is looking forward and how you're thinking about the future of cloud last decade. A lot about your cloud migration simplifying infrastructure management, deployment SAS if eyeing my enterprise, lot of simplification and cost savings. And, of course, the redeployment of resource is toward digital transformation. Other other other valuable activities. How >>do >>you think this coming decade will will be defined? Will it be sort of more of the same? Or is there Is there something else out there? >>I think I think that the coming decade will be one where customers start one law outside value out of this. You know what happened in the last decade when people leave the foundation and people essentially looked at the world and said, Look, we've got to make the move, you know, the largely hybrid, but we're going to start making steps to basically digitize and modernize our platforms. I would tell you that with the amount of data that people are moving to the cloud just as an example, you're going to see use of analytics ai for business outcomes explode. You're also going to see a huge sort of focus on things like governance. You know, people need to know where the data is, what the data catalog continues, how to govern it, how to trust this data and given all other privacy and compliance regulations out there. Essentially, they're complying this posture. So I think the unlocking of outcomes versus simply Hey, I've saved money Second, really putting this comprehensive sort off, you know, governance, regime in place. And then, finally, security and trust. It's going to be more paramount than ever before. Yeah, >>nobody's gonna use the data if they don't trust it. I'm glad you brought up your security. It's It's a topic that hits number one on the CEO list. J G. Great conversation. Obviously the strategy is working, and thanks so much for participating in Cuba on cloud. >>Thank you. Thank you, David. I appreciate it and thank you to. Everybody was tuning in today. >>All right? And keep it right there. I'll be back with our next guest right after this short break.

>>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.