>>Hi, buddy. Welcome back to the keeps coverage of AWS 2021. Re-invent you're watching the cube and I'm really excited. We're going to go outside the storage box. I like to say with my lawn Thompson Bukovac, who's the vice-president of block and object storage and Wayne Duso was a VP of storage edge and data governance guys. Great to see you again, we saw you at storage day, the 15 year anniversary of AWS, of course, the first product service ever. So awesome to be here. Isn't it. Wow. >>So much energy in the room. It's so great to see customers learning from each other, learning from AWS, learning from the things that you're observing as well. >>A lot of companies decided not to do physical events. I think you guys are on the right side of history. We're going to show you, you weren't exactly positive. How many people are going to show up. Everybody showed. I mean, it's packed house here, so >>Number 10. Yeah. >>All right. So let's get right into it. Uh, news of the week. >>So much to say, when you want to kick this off, >>We had a, we had a great set of announcements that Milan, uh, talked about yesterday, uh, in her talk and, and a couple of them in the file space, specifically a new, uh, member of the FSX family. And if you remember that the FSA, Amazon FSX is, uh, for customers who want to run fully managed versions of third party and open source file systems on AWS. And so yesterday we announced a new member it's FSX for open ZFS. >>Okay, cool. And there's more, >>Well, there's more, I mean, one of the great things about the new match file service world and CFS is it's powered by gravity. >>It is taught by Gravatar and all of the capabilities that AWS brings in terms of networking, storage, and compute, uh, to our customers. >>So this is really important. I want the audience to understand this. So I I've talked on the cube about how a large proportion let's call it. 30% of the CPU cycles are kind of wasted really on things like offloads, and we could be much more efficient, so graviton much more efficient, lower power and better price performance, lower cost. Amazon is now on a new curve, uh, cycles are faster for processors, and you can take advantage of that in storage it's storage users, compute >>That's right? In fact, you have that big launch as well for luster, with gravity. >>We did in fact, uh, so with, with, uh, Yasmin of open CFS, we also announced the next gen Lustre offering. And both of these offerings, uh, provide a five X improvement in performance. For example, now with luster, uh, customers can drive up to one terabyte per second of throughput, which is simply amazing. And with open CFS, right out of, right out of the box at GA a million IOPS at sub-millisecond latencies taking advantage of gravitas, taking advantage of our storage and networking capabilities. >>Well, I guess it's for HPC workloads, but what's the difference between these days HPC, big data, data intensive, a lot of AI stuff, >>All right. You to just, there's a lot of intersection between all of those different types of workloads they have, as you said, and you know, it all, it all depends on it all matters. And this is the reason why having the suite of capabilities that the, if you would, the members of the family is so important to our guests. >>We've talked a lot about, it's really can't think about traditional storage as a traditional storage anymore. And certainly your world's not a box. It's really a data platform, but maybe you could give us your point of view on that. >>Yeah, I think, you know, if, if we look, if we take a step back and we think about how does AWS do storage? Uh, we think along multiple dimensions, we have the dimension that Wayne's talking about, where you bring together the power of compute and storage for these managed file services that are so popular. You and I talked about, um, NetApp ONTAP. Uh, we went into some detail on that with you as well, and that's been enormously popular. And so that whole dimension of these managed file services is all about where is the customer today and how can we help them get to the cloud? But then you think about the other things that we're also imagining, and we're, re-imagining how customers want to grow those applications and scale them. And so a great example here at reinvent is let's just take the concept of archive. >>So many people, when they think about archive, they think about taking that piece of data and putting it away on tape, putting it away in a closet somewhere, never pulling it out. We don't think about archive like that archive just happens to be data that you just aren't using at the moment, but when you need it, you need it right away. And that's why we built a new storage class that we launched just yesterday, Dave, and it's called glacier instead of retrieval, it has retrieval and milliseconds, just like an Esri storage class has the same pricing of four tenths of a cent as glacier archive. >>So what's interesting at the analyst event today, Adam got a question about, and somebody was poking at him, you know, analysts can be snarky sometimes about, you know, price, declines and so forth. And he said, you know, one of the, one of the things that's not always shown up and we don't always get credit for lowering prices, but we might lower costs. And there's the archive and deep archive is an example of that. Maybe you could explain that point of view. >>Yeah. The way we look at it is that our customers, when they talk to us about the cost of storage, they talked to us about the total cost of the storage, and it's not just storing the data, it's retrieving it and using it. And so we have done an amazing amount across all the portfolio around reducing costs. We have glacier answer retrieval, which is 68% cheaper than standard infrequent access. That's a big cost reduction. We have EBS snapshots archive, which we introduced yesterday, 75% cheaper to archive a snapshot. And these are the types of that just transform the total cost. And in some cases we just eliminate costs. And so the glacier storage class, all bulk retrievals of data from the glacier storage class five to 12 hours, it's now free of charge. If you don't even have to think about, we didn't even reduce it. We just eliminated the cost of that data retrieval >>And additive to what Milan said around, uh, archiving. If you look at what we've done throughout the entire year, you know, a interesting statistic that was brought up yesterday is over the course of 2021, between our respective teams, we've launched over 105 capabilities for our customers throughout this year. And in some of them, for instance, on the file side for EFS, we launched one zone which reduced, uh, customer costs by 47%. Uh, you can now achieve on EFS, uh, cost of roughly 4.30 cents per gigabyte month on, uh, FSX, we've reduced costs up to 92%, uh, on Lustre and FSX for windows and with the introduction of ONTAP and open CFS, we continue those forward, including customers ability to compress and Dedoose against those costs. So they ended up seeing a considerable savings, even over what our standard low prices are. >>100 plus, what can I call them releases? And how can you categorize those? Are they features of eight? Do they fall into, >>Because they range for major services, like what we've launched with open ZFS to major features and really 95 of those were launched before re-invent. And so really what you have between the different teams that work in storage is you have this relentless drive to improve all the storage platforms. And we do it all across the course of the year, all across the course of the year. And in some cases, the benefit shows up at no cost at all to a customer. >>Uh, how, how did this, it seems like you're on an accelerated pace, a S3 EBS, and then like hundreds of services. I guess the question is how come it took so long and how is it accelerating now? Is it just like, there was so much focus on compute before you had to get that in place, or, but now it's just rapidly accessing, >>I I'll tell you, Dave, we took the time to count this year. And so we came to you with this number of 106, uh, that acceleration has been in place for many years. We just didn't take the time to couch. Correct. So this has been happening for years and years. Wayne and I have been with AWS for, for a long time now for 10 plus years. And really that velocity that we're talking about right now that has been happening every single year, which is where you have storage today. And I got to tell you, innovation is in our DNA and we are not going to stop now >>So 10 years. Okay. So it was really, the first five years was kind of slow. And then >>I think that's true at all. I don't think that try, you know, if you, if you look at, uh, the services that we have, we have the most complete portfolio of any cloud provider when it comes to storage and data. And so over the years, we've added to the foundation, which is S3 and the foundation, which is EBS. We've come out with a number of storage services in the, in the file space. Now you have an entire suite of persistent data stores within AWS and the teams behind those that are able to accelerate that pace. Just to give you an example, when I joined 10 years ago, AWS launched within that year, roughly a hundred and twenty, a hundred and twenty eight services or features our teams together this year have launched almost that many, just in those in, just in this space. So AWS continues to accelerate the storage teams continue to accelerate. And as my line said, we just started counting >>The thing. And if you think about those first five years, that was laying the baseline to launch us three, to launch EBS, to get that foundation in place, get lifecycle policies in place. But really, I think you're just going to see an even faster acceleration that number's going up. >>No, I that's what I'm saying. It does appear that way. And you had to build a team and put teams in place. And so that's, you know, part of the equation. But again, I come back to, it's not even, I don't even think of it as storage anymore. It's it's data. People are data lake is here to stay. You might not like the term. We always use the joke about a data ocean, but data lake is here to say 200,000 data lakes. Now we heard Adam talk about, uh, this morning. I think it was Adam. No, it was Swami. Do you want a thousand data lakes in your customer base now? And people are adding value to that data in new ways, injecting machine intelligence, you know, SageMaker is a big piece of that. Tying it in. I know a lot of customers are using glue as catalogs and which I'm like, wow, is glue a catalog or, I mean, it's just so flexible. So what are you seeing customers do with that base of data now and driving new business value? Because I've said last decade plus has been about it transformation. And now we're seeing business transformation. Maybe you could talk about that a little bit. >>Well, the base of every data lake is going to be as three yesterday has over 200 trillion objects. Now, Dave, and if you think about that, if you took every person on the planet, each of those people would have 26,000 S3 objects. It's gotten that big. And you know, if you think about the base of data with 200 trillion plus objects, really the opportunity for innovation is limitless. And you know, a great example for that is it's not just business value. It's really the new customer experiences that our customers are inventing the NFL. Uh, they, you know, they have that application called digital athlete where, you know, they started off with 10,000 labeled images or up to 20,000 labeled images now. And they're all using it to drive machine learning models that help predict and support the players on the field when they start to see things unfold that might cause injury. That is a brand new experience. And it's only possible with vast amounts of data >>Additive to when my line said, we're, we're in you talk about business transformation. We are in the age of data and we represent storage services. But what we really represent is what our customers hold one of their most valuable assets, which is their data. And that set of data is only growing. And the ability to use that data, to leverage that data for value, whether it's ML training, whether it's analytics, that's only accelerated, this is the feedback we get from our customers. This is where these features and new capabilities come from. So that's, what's really accelerating our pace >>Guys. I wish we had more time. I'd have to have you back because we're on a tight clock here, but, um, so great to see you both especially live. I hope we get to do more of this in 2022. I'm an optimist. Okay. And keep it right there, everybody. This is Dave Volante for the cube you're leader in live tech coverage, right back.

(pensive music) >> Thank you, Jenna, it's great to see you guys and thank you for watching theCUBE's continuous coverage of AWS Storage Day. We're here at The Spheres, it's amazing venue. My name is Dave Vellante. I'm here with Mai-Lan Tomsen Bukovec who's Vice President of Block and Object Storage. Mai-Lan, always a pleasure to see you. Thanks for coming on. >> Nice to see you, Dave. >> It's pretty crazy, you know, this is kind of a hybrid event. We were in Barcelona a while ago, big hybrid event. And now it's, you know, it's hard to tell. It's almost like day-to-day what's happening with COVID and some things are permanent. I think a lot of things are becoming permanent. What are you seeing out there in terms of when you talk to customers, how are they thinking about their business, building resiliency and agility into their business in the context of COVID and beyond? >> Well, Dave, I think what we've learned today is that this is a new normal. These fluctuations that companies are having and supply and demand, in all industries all over the world. That's the new normal. And that has what, is what has driven so much more adoption of cloud in the last 12 to 18 months. And we're going to continue to see that rapid migration to the cloud because companies now know that in the course of days and months, you're, the whole world of your expectations of where your business is going and where, what your customers are going to do, that can change. And that can change not just for a year, but maybe longer than that. That's the new normal. And I think companies are realizing it and our AWS customers are seeing how important it is to accelerate moving everything to the cloud, to continue to adapt to this new normal. >> So storage historically has been, I'm going to drop a box off at the loading dock and, you know, have a nice day. And then maybe the services team is involved in, in a more intimate way, but you're involved every day. So I'm curious as to what that permanence, that new normal, some people call it the new abnormal, but it's the new normal now, what does that mean for storage? >> Dave, in the course of us sitting here over the next few minutes, we're going to have dozens of deployments go out all across our AWS storage services. That means our customers that are using our file services, our transfer services, block and object services, they're all getting improvements as we sit here and talk. That is such a fundamentally different model than the one that you talked about, which is the appliance gets dropped off at the loading dock. It takes a couple months for it to get scheduled for setup and then you have to do data migration to get the data on the new appliance. Meanwhile, we're sitting here and customers storage is just improving, under the hood and in major announcements, like what we're doing today. >> So take us through the sort of, let's go back, 'cause I remember vividly when, when S3 was announced that launched this cloud era and people would, you know, they would do a lot of experimentation of, we were storing, you know, maybe gigabytes, maybe even some terabytes back then. And, and that's evolved. What are you seeing in terms of how people are using data? What are the patterns that you're seeing today? How is that different than maybe 10 years ago? >> I think what's really unique about AWS is that we are the only provider that has been operating at scale for 15 years. And what that means is that we have customers of all sizes, terabytes, petabytes, exabytes, that are running their storage on AWS and running their applications using that storage. And so we have this really unique position of being able to observe and work with customers to develop what they need for storage. And it really breaks down to three main patterns. The first one is what I call the crown jewels, the crown jewels in the cloud. And that pattern is adopted by customers who are looking at the core mission of their business and they're saying to themselves, I actually can't scale this core mission on on-premises. And they're choosing to go to the cloud on the most important thing that their business does because they must, they have to. And so, a great example of that is FINRA, the regulatory body of the US stock exchanges, where, you know, a number of years ago, they took a look at all the data silos that were popping up across their data centers. They were looking at the rate of stock transactions going up and they're saying, we just can't keep up. Not if we want to follow the mission of being the watchdog for consumers, for transactions, for stock transactions. And so they moved that crown jewel of their application to AWS. And what's really interesting Dave, is, as you know, 'cause you've talked to many different companies, it's not technology that stops people from moving to the cloud as quick as they want to, it's culture, it's people, it's processes, it's how businesses work. And when you move the crown jewels into the cloud, you are accelerating that cultural change and that's certainly what FINRA saw. Second thing we see, is where a company will pick a few cloud pilots. We'll take a couple of applications, maybe one or a several across the organization and they'll move that as sort of a reference implementation to the cloud. And then the goal is to try to get the people who did that to generalize all the learning across the company. That is actually a really slow way to change culture. Because, as many of us know, in large organizations, you know, you have, you have some resistance to other organizations changing culture. And so that cloud pilot, while it seems like it would work, it seems logical, it's actually counter-productive to a lot of companies that want to move quickly to the cloud. And the third example is what I think of as new applications or cloud first, net new. And that pattern is where a company or a startup says all new technology initiatives are on the cloud. And we see that for companies like McDonald's, which has transformed their drive up experience by dynamically looking at location orders and providing recommendations. And we see it for the Digital Athlete, which is what the NFL has put together to dynamically take data sources and build these models that help them programmatically simulate risks to player health and put in place some ways to predict and prevent that. But those are the three patterns that we see so many customers falling into depending on what their business wants. >> I like that term, Digital Athlete, my business partner, John Furrier, coined the term tech athlete, you know, years ago on theCUBE. That third pattern seems to me, because you're right, you almost have to shock the system. If you just put your toe in the water, it's going to take too long. But it seems like that third pattern really actually de-risks it in a lot of cases, it's so it's said, people, who's going to argue, oh, the new stuff should be in the cloud. And so, that seems to me to be a very sensible way to approach that, that blocker, if you will, what are your thoughts on that? >> I think you're right, Dave. I think what it does is it allows a company to be able to see the ideas and the technology and the cultural change of cloud in different parts of the organization. And so rather than having a, one group that's supposed to generalize it across an organization, you get it decentralized and adopted by different groups and the culture change just goes faster. >> So you, you bring up decentralization and there's a, there's an emerging trend referred to as a data mesh. It was, it was coined, the term coined by Zhamak Dehghani, a very thought-provoking individual. And the concept is basically the, you know, data is decentralized, and yet we have this tendency to sort of shove it all into, you know, one box or one container, or you could say one cloud, well, the cloud is expanding, it's the cloud is, is decentralizing in many ways. So how do you see data mesh fitting in to those patterns? >> We have customers today that are taking the data mesh architectures and implementing them with AWS services. And Dave, I want to go back to the start of Amazon, when Amazon first began, we grew because the Amazon technologies were built in microservices. Fundamentally, a data mesh is about separation or abstraction of what individual components do. And so if I look at data mesh, really, you're talking about two things, you're talking about separating the data storage and the characteristics of data from the data services that interact and operate on that storage. And with data mesh, it's all about making sure that the businesses, the decentralized business model can work with that data. Now our AWS customers are putting their storage in a centralized place because it's easier to track, it's easier to view compliance and it's easier to predict growth and control costs. But, we started with building blocks and we deliberately built our storage services separate from our data services. So we have data services like Lake Formation and Glue. We have a number of these data services that our customers are using to build that customized data mesh on top of that centralized storage. So really, it's about at the end of the day, speed, it's about innovation. It's about making sure that you can decentralize and separate your data services from your storage so businesses can go faster. >> But that centralized storage is logically centralized. It might not be physically centralized, I mean, we put storage all over the world, >> Mai-Lan: That's correct. >> right? But, but we, to the developer, it looks like it's in one place. >> Mai-Lan: That's right. >> Right? And so, so that's not antithetical to the concept of a data mesh. In fact, it fits in perfectly to the point you were making. I wonder if we could talk a little bit about AWS's storage strategy and it started of course, with, with S3, and that was the focus for years and now of course EBS as well. But now we're seeing, we heard from Wayne this morning, the portfolio is expanding. The innovation is, is accelerating that flywheel that we always talk about. How would you characterize and how do you think about AWS's storage strategy per se? >> We are a dynamically and constantly evolving our AWS storage services based on what the application and the customer want. That is fundamentally what we do every day. We talked a little bit about those deployments that are happening right now, Dave. That is something, that idea of constant dynamic evolution just can't be replicated by on-premises where you buy a box and it sits in your data center for three or more years. And what's unique about us among the cloud services, is again that perspective of the 15 years where we are building applications in ways that are unique because we have more customers and we have more customers doing more things. So, you know, I've said this before. It's all about speed of innovation Dave, time and change wait for no one. And if you're a business and you're trying to transform your business and base it on a set of technologies that change rapidly, you have to use AWS services. Let's, I mean, if you look at some of the launches that we talk about today, and you think about S3's multi-region access points, that's a fundamental change for customers that want to store copies of their data in any number of different regions and get a 60% performance improvement by leveraging the technology that we've built up over, over time, leveraging the, the ability for us to route, to intelligently route a request across our network. That, and FSx for NetApp ONTAP, nobody else has these capabilities today. And it's because we are at the forefront of talking to different customers and that dynamic evolution of storage, that's the core of our strategy. >> So Andy Jassy used to say, oftentimes, AWS is misunderstood and you, you comfortable with that. So help me square this circle 'cause you talked about things you couldn't do on on-prem, and yet you mentioned the relationship with NetApp. You think, look at things like Outposts and Local Zones. So you're actually moving the cloud out to the edge, including on-prem data centers. So, so how do you think about hybrid in that context? >> For us, Dave, it always comes back to what the customer's asking for. And we were talking to customers and they were talking about their edge and what they wanted to do with it. We said, how are we going to help? And so if I just take S3 for Outposts, as an example, or EBS and Outposts, you know, we have customers like Morningstar and Morningstar wants Outposts because they are using it as a step in their journey to being on the cloud. If you take a customer like First Abu Dhabi Bank, they're using Outposts because they need data residency for their compliance requirements. And then we have other customers that are using Outposts to help, like Dish, Dish Networks, as an example, to place the storage as close as account to the applications for low latency. All of those are customer driven requirements for their architecture. For us, Dave, we think in the fullness of time, every customer and all applications are going to be on the cloud, because it makes sense and those businesses need that speed of innovation. But when we build things like our announcement today of FSx for NetApp ONTAP, we build them because customers asked us to help them with their journey to the cloud, just like we built S3 and EBS for Outposts for the same reason. >> Well, when you say over time, you're, you believe that all workloads will be on the cloud, but the cloud is, it's like the universe. I mean, it's expanding. So what's not cloud in the future? When you say on the cloud, you mean wherever you meet customers with that cloud, that includes Outposts, just the programming, it's the programmability of that model, is that correct? That's it, >> That's right. that's what you're talking about? >> In fact, our S3 and EBS Outposts customers, the way that they look at how they use Outposts, it's either as part of developing applications where they'll eventually go the cloud or taking applications that are in the cloud today in AWS regions and running them locally. And so, as you say, this definition of the cloud, you know, it, it's going to evolve over time. But the one thing that we know for sure, is that AWS storage and AWS in general is going to be there one or two steps ahead of where customers are, and deliver on what they need. >> I want to talk about block storage for a moment, if I can, you know, you guys are making some moves in that space. We heard some announcements earlier today. Some of the hardest stuff to move, whether it's cultural or maybe it's just hardened tops, maybe it's, you know, governance edicts, or those really hardcore mission critical apps and workloads, whether it's SAP stuff, Oracle, Microsoft, et cetera. You're clearly seeing that as an opportunity for your customers and in storage in some respects was a blocker previously because of whatever, latency, et cetera, then there's still some, some considerations there. How do you see those workloads eventually moving to the cloud? >> Well, they can move now. With io2 Block Express, we have the performance that those high-end applications need and it's available today. We have customers using them and they're very excited about that technology. And, you know, again, it goes back to what I just said, Dave, we had customers saying, I would like to move my highest performing applications to the cloud and this is what I need from the, from the, the storage underneath them. And that's why we built io2 Block Express and that's how we'll continue to evolve io2 Block Express. It is the first SAN technology in the cloud, but it's built on those core principles that we talked about a few minutes ago, which is dynamically evolving and capabilities that we can add on the fly and customers just get the benefit of it without the cost of migration. >> I want to ask you about, about just the storage, how you think about storage in general, because typically it's been a bucket, you know, it's a container, but it seems, I always say the next 10 years aren't going to be like the last, it seems like, you're really in the data business and you're bringing in machine intelligence, you're bringing in other database technology, this rich set of other services to apply to the data. That's now, there's a lot of data in the cloud and so we can now, whether it's build data products, build data services. So how do you think about the business in that sense? It's no longer just a place to store stuff. It's actually a place to accelerate innovation and build and monetize for your customers. How do you think about that? >> Our customers use the word foundational. Every time they talk about storage, they say for us, it's foundational, and Dave, that's because every business is a data business. Every business is making decisions now on this changing landscape in a world where the new normal means you cannot predict what's going to happen in six months, in a year. And the way that they're making those smart decisions is through data. And so they're taking the data that they have in our storage services and they're using SageMaker to build models. They're, they're using all kinds of different applications like Lake Formation and Glue to build some of the services that you're talking about around authorization and data discovery, to sit on top of the data. And they're able to leverage the data in a way that they have never been able to do before, because they have to. That's what the business world demands today, and that's what we need in the new normal. We need the flexibility and the dynamic foundational storage that we provide in AWS. >> And you think about the great data companies, those were the, you know, trillions in the market cap, their data companies, they put data at their core, but that doesn't mean they shove all the data into a centralized location. It means they have the identity access capabilities, the governance capabilities to, to enable data to be used wherever it needs to be used and, and build that future. That, exciting times we're entering here, Mai-Lan. >> We're just set the start, Dave, we're just at the start. >> Really, what ending do you think we have? So, how do you think about Amazon? It was, it's not a baby anymore. It's not even an adolescent, right? You guys are obviously major player, early adulthood, day one, day zero? (chuckles) >> Dave, we don't age ourself. I think if I look at where we're going for AWS, we are just at the start. So many companies are moving to the cloud, but we're really just at the start. And what's really exciting for us who work on AWS storage, is that when we build these storage services and these data services, we are seeing customers do things that they never thought they could do before. And it's just the beginning. >> I think the potential is unlimited. You mentioned Dish before, I mean, I see what they're doing in the cloud for Telco. I mean, Telco Transformation, that's an industry, every industry, there's a transformation scenario, a disruption scenario. Healthcare has been so reluctant for years and that's happening so quickly, I mean, COVID's certainly accelerating that. Obviously financial services have been super tech savvy, but they're looking at the Fintech saying, okay, how do we play? I mean, there isn't manufacturing with EV. >> Mai-Lan: Government. >> Government, totally. >> It's everywhere, oil and gas. >> There isn't a single industry that's not a digital industry. >> That's right. >> And there's implications for everyone. And it's not just bits and atoms anymore, the old Negroponte, although Nicholas, I think was prescient because he's, he saw this coming, it really is fundamental. Data is fundamental to every business. >> And I think you want, for all of those in different industries, you want to pick the provider where innovation and invention is in our DNA. And that is true, not just for storage, but AWS, and that is driving a lot of the changes you have today, but really what's coming in the future. >> You're right. It's the common editorial factors. It's not just the, the storage of the data. It's the ability to apply other technologies that map into your business process, that map into your organizational skill sets that drive innovation in whatever industry you're in. It's great Mai-Lan, awesome to see you. Thanks so much for coming on theCUBE. >> Great seeing you Dave, take care. >> All right, you too. And keep it right there for more action. We're going to now toss it back to Jenna, Canal and Darko in the studio. Guys, over to you. (pensive music)

>>from around the globe. It's the Cube presenting Cuban cloud brought to you by silicon angle. >>We continue >>with Cuban Cloud. We're here with Milan Thompson Bukovec, who's the vice president? Block and object storage at A W s, which comprise comprises elastic block storage, AWS s three and Amazon Glacier. Milan. Great to see you again. Thanks so much for coming on the program. >>Nice to be here. Thanks for having me, David. >>You're very welcome it So here we are. We're unpacking the future of cloud. And we'd love to get your perspectives on how customers should think about the future of infrastructure, things like applying machine intelligence to their data. But just to set the stage when we look back at the history of storage in the Cloud is obviously started with us three. And then a couple years later was introduced CBS for block storage. And those are the most well known services in the portfolio. But there's there's Mawr, this cold storage and new capabilities that you announced recently. It reinvent around, you know, super duper block storage and in tearing is another example. But it looks like AWS is really starting to accelerate and pick up the pace of customer >>options in >>storage. So my first question is, how should we think about this expanding portfolio? >>Well, I think you have to go all the way back to what customers air trying to do with their data. Dave, The path to innovation is paved by data. If you don't have data, you don't have machine learning. You don't have the next generation of analytics applications. That helps you chart a path forward into a world that seems to be changing every week. And so in orderto have that insight in orderto have that predictive forecasting that every company needs, regardless of what industry that you're in today. It all starts from data, and I think the key shift that I've seen is how customers are thinking about that data about being instantly usable, whereas in the past it might have been a backup. Now it's part of a data lake, and if you could bring that data into a data lake, you can have not just analytics or machine learning or auditing applications. It's really what does your application do for your business, and how can it take advantage of that vast amount of shared data set in your business. Awesome. >>So thank you. So I wanna I wanna make sure we're hitting on the big trends that you're seeing in the market. That kind of informing your strategy around the portfolio and what you're seeing with customers Instant usability. You you bring in machine learning into the equation. I think, um, people have really started to understand the benefits of of of cloud storage as a service on the pay paid by the drink and that whole whole model, obviously co vid has accelerated that cloud migration has accelerated. Anything else we're missing there. What are the other big trends that you see if any? >>Well, Dave, you did a good job of capturing a lot of the drivers. The one thing I would say that just sits underneath All of it is the massive growth of digital data year over year I. D. C. Says digital data is growing at a rate of 40% year over year, and that has been true for a while. And it's not going to stop. It's gonna keep on growing because the sources of that data acquisition keeps on expanding and whether it's coyote devices whether it is content created by users. That data is going to grow, and everything you're talking about depends on the ability to not just capture it and store it. But as you say, use it well, >>you know, and we talk about data growth a lot, and sometimes it becomes bromide. But I think the interesting thing that I've observed over the last a couple of decades really is that the growth is nonlinear on. It's really the curve is starting. Thio used to shape exponentially. You guys always talk about that flywheel. Effect it. It's really hard to believe, You know, people say trees don't grow to the moon. It seems like data does. >>It does. And what's interesting about working in the world of AWS storage Dave is that it's counterintuitive. But our goal without data growth is to make it cost effective. And so year over year, how could we make it cheaper and cheaper? Just have customers store more and more data so they can use it. But it's also to think about the definition of usage. And what kind of data is that? Eyes being tapped by businesses for their insights and make that easier than it's ever been before. Let me ask >>you a follow up question on that my life could I get asked this a lot? Or guy here comments a lot that yes, A W s continuously and rigorously reduces pricing. But it's just >>kind of >>following the natural curve of Moore's law or, you know, whatever. How >>do you >>respond to that? And there are other factors involved. Obviously, labor is another cost reducing factor. But what's the trend line say, >>Well, cost efficiencies in our DNA, Dave. We come to work every day and aws across all of our services, and we ask ourselves, How can we lower our costs and be able to pass that along to customers? As you say, there are many different aspects to cost. There's the cost of the storage itself is the cost of the data center. And that's really what we've seen impact a lot of customers that were slower or just getting started with removed. The cloud is they entered 2020 and then they found out exactly how expensive that data center was to maintain because they had to put in safety equipment and they had to do all the things that you have to do in a pandemic in a data center. And so sometimes that cost is a little bit hidden or won't show up until you really don't need to have it land. But the cost of managing that explosive growth of data is very riel. And when we're thinking about cost, we're thinking about cost in terms of how can I lower it on a per gigabyte per month basis? But we're also building into the product itself adaptive discounts like we have a storage class in S three that's called intelligent hearing. And in intelligence hearing, we have built in monitoring where, if particular objects aren't frequently accessed in a given month, ah, customer will automatically get a discounted price for that storage or a customer Can you know, as of late last year, say that they wanna automatically move storage in the storage class that has been stored, for example, longer than 100 and 80 days and saves 95% by moving it into archive storage, deep archives storage? And so it's not just, you know, relentlessly going after and lowering the cost of storage. It's also building into the products these new ways where we can adaptive Lee discount storage based on what a customer's storage is actually doing >>well. And I would, I would add to our audience, is the other thing that does has done is it's really forced transparency almost the same way that Amazon has done on retail. And now my mom, When we talked last I mentioned that s three was an object store. And of course, that's technically technically correct. But your comment to me was Dave. It's more than that. And you started to talk about sage Maker and AI and bringing in machine learning. And I wonder if you could talk a little bit about the future of how storage is gonna be leveraged in the cloud that's may be different than what we've been, you know, used to in the early days of s three and how your customers should be thinking about infrastructure not as bespoke services but as a suite of capabilities and maybe some of those adjacent adjacent services that you see as most leverage a ble for customers And why? >>Well, to tell this story, dude, we're gonna have to go a little bit back in time all the way back to the 19 nineties. Or before then, when all you had waas, a set of hardware appliance vendors that sold you appliances that you put in your data center and inherently created a data silo because those hardware appliances were hardwired to your application. And so an individual application that was dealing with auditing as an example wouldn't really be able to access the storage for another application. Because you know, the architecture er of that legacy world is tied to a data silo and s tree came out launched in 2000 and six and introduced very low cost storage. That is an object. And I'll tell you, Dave, you know, over the last 10 plus years, we have seen all kinds of data come into us three, whereas before it might have been backups or it might have been images and videos. Now a pretty substantial data set is our parquet files and orc files. Thes files are there for business analytics for more real time type of processing. And that has really been the trend of the future. Is taking these different files putting them in a shared file layer, So any application today or in the future can tap into that data. And so this idea of the shared file layer is a major trend that has been taking off for the last. I would say five or six years, and I expect that to not only keep on going, but to really open up the type of services that you can then do on that shared file layer and whether that sage maker or some of the machine learning introduced by our connect service, it's bringing together the data as a starting point. And then the applications can evolve very rapidly. On top of that, I want to >>ask your opinion about big data architectures. One of our guests, Jim Octagon E. She's amazing, uh, data architect, and she's put forth this notion of a distributed global mesh, and I picked him picking up on some of the comments. Andy Jassy made it at reinvent How essentially Hey, we're bringing a W s to the edge. We see the data center is just another edge. Notes. You're seeing this massive distributed system evolving. You guys have talked about that for a while, and data by its very nature is distributed. But we've had this tendency to put into it monolithic Data Lake or a data warehouse on bits sort of antithetical to that distributed nature. So how >>do >>you see that playing out? What do you see customers in the future doing in terms of their big data architectures? And what does that mean for storage? >>It comes down to the nature of the data and again, the usage and Dave. That's where I see the biggest difference in these modern data architectures from the legacy of 20 years ago is the idea that the data need drives the data storage. So let's taken example of the type of data that you always wanna have on the edge. We have customers today that need tohave storage in the field and whether the field of scientific research or oftentimes, it's content creation in the in the film industry or if it's for military operations. There's a lot of data that needs to be captured and analyzed in the field and for us, what that means is that you know we have a suite of products called Snowball and whether it's snowball or snow cone, take your pick. That whole portfolio of AWS services is targeted at customers that need to do work with storage at the edge. And so it you know, if you think about the need for multiple applications acting on the same data set, that's when you keep it in an AWS region. And what we've done in AWS storage is we've recognized that depending on the need of usage, where you put your data and how you interactive, it may vary. But we've built a whole set of services like data transfer to help make sure that we can connect data from, for example, that new snow cone into a region automatically. And so our goal Dave, is to make sure that when customers air operating at the edge or they're operating in the region, they have the same quality of storage service, and they have easy ways to go between them. You shouldn't have to pick. You should be able to do it all. >>So in the spirit of do it all, this is sort of age old dynamic in the tech business, where you've got the friction between the the best of breed and the integrated suite, and my question is around what you're optimizing for for customers. And can you have your cake and eat it too? In other words, why A W S storage does what makes a compelling? Is it because it's kind of a best of breed storage service? Or is it because it's integrated with a W S? Would you ever sub optimize one in in order to get an advantage to the other? Or can you actually, >>you >>know, have your cake and eat it, too? >>The way that we build storage is to focus on being both the breath of capabilities on the depth of capabilities. And so where we identify ah, particular need where we think that it takes a whole new service to deliver, we'll go build that service and example for that is FTP, our AWS sftp service, which you know there's a lot of sftp usage out there and there will be for a while because of the you know, the Legacy B two b type of architectures that still live in the business world today. And so we looked at that problem. We said, How are we gonna build that in the best depth way and the best focus? And we launched a separate service for them. And so our goal is to take the individual building blocks of CBS and Glacier and s three and make the best of class and the most comprehensive in the capabilities of what we can dio and where we identify very specific need. We'll go build a service for. But, Dave, you know, as an example for that idea of both depths and breath s three storage lands is a great example of that s three storage lands is a new capability that we launched last year. And what it does is it lets you look across all your regions and all your accounts and get a summary view of all your s three storage and whether that's buckets or, you know, the most active prefixes that you have and be able to drill down from that and that is built in to the S three service and available for any customer that wants to turn it on in the AWS Management Council. >>Right? And we we saw just recently made I called it super duper block storage. But you made some, you know, improvements and really addressing the highest performance. Um, I want to ask you So we've all learned about an experience the benefits of cloud over the last several years, and especially in the last 10 months during the pandemic. But one >>of >>the challenges, and it's particularly acute with bio is, of course, Leighton see and moving data around and accessing data remotely. It's It's a challenge for customers, you know, due to speed of light, etcetera. So my question is, how was a W s thinking about all that data that still resides on premises? I think we heard that reinvent. That's still 90% of the opportunities or or the workloads. They're still on Prem that live inside a customer's data center. So how do you tap into those and help customers innovate with on Prem data, particularly from a storage >>angle? Well, we always want to provide the best of class solution for those little Leighton see workloads, and that's why we launched Block Express just late last year. It reinvent and Black expresses a new capability and preview on top of our Iot to provisioned eye ops volume type, and what's really interesting about Block Express Dave, is that the way that we're able to deliver the performance of Block Express, which is sound performance with cloud elasticity, is that we went all the way down to the network layer and we customize the hardware software. And at the network Lehrer, we built a Block Express on something called SRD, which stands for a scalable, reliable diagrams. And basically, what is letting us to do is offload all of our EBS operations for Block Express on the Nitro card on hardware. And so that type of innovation where we're able Thio, you know, take advantage of modern cop commodity, multi tenant data center networks where we're sending in this new network protocol across a large number of network paths, and that that type of innovation all the way down to that protocol level helps us innovate in a way that's hard. In fact, I would say impossible for for other sound providers to kind of really catch up and keep up. And so we feel that the amount of innovation that we have for delivering those low latency workloads in our AWS cloud storage is is unlimited, really, Because of that ability to customize software, hardware and network protocols as we go along without requiring upgrades from a customer it just gets better and the customer benefits. Now if you want to stay in your data center, that's why we built outposts. And for outpost, we have EBS and we have s three for outposts. And our goal there is that some customers will have workloads where they want to keep them resident in the data center And for those customers, we want to give them that AWS storage opportunities as well. So >>thank you for coming back to block Express. So you call it in sand in the cloud eso Is that essentially you've you've comprises a custom built, essentially storage storage network. Is that is that right? What kind of what you just described? SRD? I think you call it. >>Yeah, it's SRT is used by other AWS services as well, but it is a custom network protocol that we designed to deliver the lowest latency experience on We're taking advantage of it with Block Express >>sticking with traditional data centers for a moment, I'm interested in your thoughts on the importance of the cloud you know, pricing approach I e. The consumption model to paid by the drink. Obviously, it's one of the most attractive features But But And I ask that because we're seeing what Andy Jassy first, who is the old Guard Institute? Flexible pricing models. Two of the biggest storage companies HP with Green Lake and Dell has this thing called Apex. They've announced such models for on Prem and and presumably, Cross Cloud. How >>do you think >>this is going to impact your customers Leverage of AWS cloud storage? Is it something that you have ah, opinion on? >>Yeah, I think it all comes down to again that usage of the storage And this is where I think there is an inherent advantage for our cloud storage. So there might be an attempt by the old guard toe lower prices or add flexibility. But the end of the day it comes down to what the customer actually needs to to. And if you think about gp three, which is the new E. B s volume, the idea with GP three is we're gonna pass along savings to the customer by making the storage 20% cheaper than GP two. And we're gonna make the product better by giving a great, reliable baseline performance. But we're also going to let customers who want to run work clothes like Cassandra on TBS tune their throughput separately, for example, from their capacity. So if you're running Cassandra, sometimes you don't need to change your capacity. Your storage capacity works just fine, but what happens with for example, Cassandra were quote is that you may need more throughput. And if you're buying hardware appliance, you just have to buy for your peak. You have to buy for the max of what you think, your throughput in the max of what your storage is and this inherent flexibility that we have for AWS storage and being able to tune throughput separate from IOP, separate from capacity like you do for GP three. That is really where the future is for customers having control over costs and control over customer experience without compromising or trading off either one. >>Awesome. Thank you for that. So another time we have remaining my line. I want to talk about the topic of diversity. Uh, social impact on Daz. Ah, woman leader, women executive on. I really wanna get your perspectives on this, and I've shared with the audience previously. One of my breaking analysis segments your your boxing video, which is awesome and eso so you've got a lot of unique, non traditional aspects to your to your life, and and I love it. But I >>want to >>ask you this. So it's obviously, you know, certainly politically and socially correct to talk about diversity, the importance of diversity. There's data that suggests that that that diversity is good both economically, not just socially. And of course, it's the right thing to do. But there are those. Peter Thiel is probably the most prominent, but there are others who say, You know what, >>But >>get that. Just hire people just like you will be able to go faster, ramp up more quickly, hit escape velocity. It's natural. And that's what you should dio. Why is that not the right approach? Why is diversity both course socially responsible, but also good for business? >>For Amazon, we think about diversity as something that is essential toe how we think about innovation. And so, Dave, you know, as you know, from listening to some of the announcements I reinvent, we launched a lot of new ideas, new concepts and new services in AWS and just bringing that lends down to storage U. S. Tree has been reinventing itself every year since we launched in 2000 and six. PBS introduced the first Son on the Cloud late last year and continues to reinvent how customers think about block storage. We would not be able Thio. Look at a product in a different way and think to ourselves Not just what is the legacy system dio in a data center today. But how do we want to build this new distributed system in a way that helps customers achieve not just what they're doing today, but what they want to do in five and 10 years? You can't get that innovative mindset without bringing different perspectives to the table. And so we strongly believe in hiring people who are from underrepresented groups and whether that's gender or it's related racial equality or if its geographic, uh, diversity and bringing them in tow have the conversation. Because those divers viewpoints inform how we can innovate at all levels in a W s >>right. And so I really appreciate the perspectives on that, and we've had a zoo. You probably know the Cube has been, you know, a very big advocate of diversity, you know, generally, but women in tech Specifically, we participated a lot. And you know, I often ask this question is, you know, as a smaller company, uh, I and some of my other colleagues in in small business Sometimes we struggle. Um and so my question is, how >>how do >>you go beyond What's your advice for going beyond, you know, the good old boys network? I think its large companies like AWS and the big players you've got a responsibility to that. You can put somebody in charge and make it you know, their full time job. How should smaller companies, um, that are largely white, male dominated? How should they become more diverse? What should they do? Thio increase that diversity? >>Well, I think the place to start his voice. A lot of what we try to dio is make sure that the underrepresented voice is heard. And so, Dave, any small business owner of any industry can encourage voice for your under represented or your unheard populations. And honestly, it is a simple as being in a meeting and looking around that table, we're on your screen as it were and asking yourself Who hasn't talked? Who hasn't weighed in particularly if the debate is contentious or even animated. And you will see, particularly if you note this. Over time you will see that there may be somebody and whether it's an underrepresented, a group or its ah woman whose early career or it's it's not. It's just a member of your team who happens to be a white male to who's not being hurt. And you can ask that person for their perspective. And that is a step that every one of us can and should do, which is asked toe, have everyone's voice at the table, toe listen and to weigh in on it. So I think that is something everyone should dio. I think if you are a member of an underrepresented groups, as for example, I'm Vietnamese American and I'm the female in Tech. I think it z something to think about how you can make sure that you're always taking that bold step forward. And it's one of the topics that we covered it at reinvent. We had a great discussion with a group of women CEOs, and a lot of it we talked about is being bolt, taking the challenge of being bold in tough situations, and that is an important thing, I think, for anybody to keep in mind, but especially for members of underrepresented groups, because sometimes Dave, that bold step that you kind of think of is like, Oh, I don't know if I should ask for that promotion or I don't know if I should volunteer for that project It's not. It's not a big ask, but it's big in your head. And so if you can internalize as a member of some, you know, a group that maybe hasn't heard or seen as much how you can take those bold challenges and step forward and learn, maybe fell also because that's how you learn. Then that is a way toe. Also have people learn and develop and become leaders in whatever industry it ISS. It's >>great advice, and I reminds me of, I mean, I think most of us can relate to that my land, because when we started in the industry, we may be timid. You didn't want to necessarily speak up, and I think it's incumbent upon those in a position of power. And by the way, power might just be running a meeting agenda to maybe calling those folks that are. Maybe it's not diversity of gender or, you know, our or race. And maybe it's just the underrepresented. Maybe that's a good way to start building muscle memory. So that's unique advice that I hadn't heard before. So thank you very much for that. Appreciate it. And, uh hey, listen, thanks so much for coming on the Cuban cloud. Uh, we're out of time and and really, always appreciate your perspectives. And you're doing a great job, and thank you. >>Great. Thank you, Dave. Thanks for having me and have a great day. >>All right? And keep it right, everybody. You're watching the cube on cloud right back.

>> We continue with cube on cloud. We here with Mai-Lan Tomsen Bukovec who's the vice president of block and object storage at AWS which comprises elastic block storage, AWS S3 and Amazon glacier. Mai-Lan Great to see you again. Thanks so much for coming on the program. >> Nice to be here. Thanks for having me, Dave. >> You're very welcome. So here we're unpacking the future of cloud and we'd love to get your perspectives on how customers should think about the future of infrastructure things like applying machine intelligence to their data but just to set the stage, when we look back at the history of storage and the cloud has obviously started with S3 and then a couple of years later AWS introduced EBS for block storage and those are the most well-known services in the portfolio but there's more of this cold storage and new capabilities that you announced recently at reinvent around, you know, super-duper block storage and in tiering is another example. But it looks like AWS is really starting to accelerate and pick up the pace of customer options in storage. So my first question is how should we think about this expanding portfolio? >> Well, I think you have to go all the way back to what customers are trying to do with their data Dave. The path to innovation is paved by data. If you don't have data, you don't have machine learning. You don't have the next generation of analytics applications that helps you chart a path forward into a world that seems to be changing every week. And so in order to have that insight in order to have that predictive forecasting that every company needs, regardless of what industry that you're in today, it all starts from data. And I think the key shift that I've seen is how customers are thinking about that data, about being instantly usable. Whereas in the past, it might've been a backup. Now it's part of a data lake. And if you can bring that data into a data lake you can have not just analytics or machine learning or auditing applications, it's really what does your application do for your business and how can it take advantage of that vast amount of shared data set in your business? >> Awesome, so thank you. So I want to make sure we're hitting on the big trends that you're seeing in the market that kind of are informing your strategy around the portfolio, and what you're seeing with customers. Instant usability, you know, you bring in machine learning into the equation. I think people have really started to understand the benefits of cloud storage as a service and the pay by the drink. and that whole model. Obviously COVID has accelerated that, you know, cloud migration is accelerated. Anything else we're missing there? What are the other big trends that you see? If any. >> Well, Dave, you did a good job of capturing a lot of the drivers. The one thing I would say that just sits underneath all of it is the massive growth of digital data year over year. IDC says digital data is growing at a rate of 40% year over year. And that has been true for a while and it's not going to stop. It's going to keep on growing because the sources of that data acquisition keeps on expanding and whether it's IOT devices whether it is a content created by users, that data is going to grow and everything you're talking about depends on the ability to not just capture it and store it. But as you say, use it. >> Well, you know, and we talk about data growth a lot and sometimes it can, it becomes bromide. But I think the interesting thing that I've observed over the last couple of decades really is that the growth is non-linear and it's really the curve is starting to shape exponentially. You guys always talk about that flywheel effect it's really hard to believe, you know people say trees don't grow to the moon. It seems like data does. >> It does and what's interesting about working in a world of AWS storage Dave is that it's counter-intuitive but our goal with a data growth is to make it cost effective. And so year over year how can we make it cheaper and cheaper? It is have customers store more and more data so they can use it. But it's also to think about the definition of usage and what kind of data is being tapped by businesses for their insights and make that easier than it's ever been before. >> Let me ask you a follow up question on that Mai-Lan. Cause I get asked this a lot, or I hear comments a lot that yes AWS continuously and rigorously reduces pricing but it's just kind of following the natural curve of Moore's law or whatever. How do you respond to that? Are there other factors involved? Obviously labor is another, you know, cost reducing factor, but what's the trend line say? >> Well, cost efficiency is in our DNA, Dave we come to work every day in AWS across all of our services and we ask ourselves, how can we lower our costs and be able to pass that along to customers. As you say, there are many different aspects to costs. There's a cost to the storage itself There's a cost to the data center. And that's really what we've seen impact a lot of customers that were slower or just getting started with a move to the cloud, is they entered 2020 and then they found out exactly how expensive that data center was to maintain because they had to put in safety equipment and they had to do all the things that you have to do in a pandemic, in a data center. And so sometimes that cost is a little bit hidden or it won't show up until you really don't need to have it land. But the costs of managing that explosive growth of data is very real. And when we're thinking about costs, we're thinking about costs in terms of how can I lower it on a per gigabyte per month basis, but we're also building into the product itself, adaptive discounts. Like we have a storage class in S3 that's called intelligent tiering. And in intelligent tiering we have built-in monitoring where if particular objects aren't frequently accessed in a given month, a customer will automatically get a discounted price for that storage or a customer can, you know, as of late last year say that they want to automatically move storage in the storage class that has been stored for example longer than 180 days and saves 95% by moving it into deep archive storage. And so it's not just, you know relentlessly going after and lowering the cost of storage. It's also building into the products these new ways where we can adaptively discount storage based on what a customer's storage is actually doing. >> Right, and I would add to already is the other thing Gatos has done is it's really forced transparency almost the same way that Amazon has done on retail. And now Mai-Lan when we talked last I mentioned that S3 was an object store. And of course that's technically correct but your comment to me was Dave, it's more than that. And you started to talk about SageMaker and AI and bringing in machine learning. And I wonder if you could talk a little bit about the future of how storage is going to be leveraged in the cloud. That's maybe different than what we've been used to in the early days of S3. And how your customers should be thinking about infrastructure, not as bespoke services, but as a suite of capabilities and maybe some of those adjacent services that you see as most leverageable for customers and why? >> Well, to tell this story, Dave, we're going to have to go a little bit back in time, all the way back to the 1990s or before then. When all you had was a set of hardware appliance vendors that sold you appliances that you put in your data center and inherently created a data silo because those hardware appliances were hardwired to your application. And so an individual application that was dealing with auditing as an example wouldn't really be able to access the storage for another application, because you know, the architecture of that legacy world is tied to a data silo and S3 came out launched in 2006 and introduced very low cost storage. That is an object. And I'll tell you, Dave, you know, over the last 10 plus years we have seen all kinds of data coming to S3. Whereas before it might've been backups or it might've been images and videos. Now a pretty substantial data set is our parquet files and work files. These files are there for business analytics for more real-time type of processing. And that has really been the trend of the future, is taking these different files putting them in a shared file layer, so any application today or in the future can tap into that data. And so this idea of the shared file layer is a major trend that has been taking off for the last I would say five or six years. And I expect that to not only keep on going but to really open up the type of services that you can then do on that shared file layer. And whether that's Sage maker or some of the machine learning introduced by our connect service, it's bringing together the data as a starting point and then the applications can evolve very rapidly on top of that. >> I want to ask your opinion about big data architectures. One of our guests Chamakh Tigani, she's amazing data architect. And she's put forth this notion of a distributed global mesh. And picking up on some of the comments, Andy Jassy made it at re-invent how essentially, "Hey we're bringing AWS to the edge. "We see the data center is just another edge node." So you're seeing this massive distributed system evolving. You guys have talked about that for a while and data by its very nature is distributed but we've had this tendency to put it into a monolithic data Lake or a data warehouse and it's sort of antithetical to that distributed nature. So how do you see that playing out? What do you see customers in the future doing in terms of their big data architectures and what does that mean for storage? >> It comes down to the nature of the data and again the usage and Dave that's where I see the biggest difference in these modern data architectures from the legacy of 20 years ago, is the idea that the data need drives the data storage. So let's take an example of the type of data that you always want to have on the edge. We have customers today that need to have storage in the field and whether the field of scientific research or oftentimes it's content creation in the film industry, or if it's for military operations there's a lot of data that needs to be captured and analyzed in the field. And for us, what that means is that, you know we have a suite of products called snow ball and whether it's snow ball or snow cone, take your pick. That whole portfolio of AWS services is targeted at customers that need to do work with storage at the edge. And so, you know, if you think about the need for multiple applications acting on the same data set that's when you keep it in an AWS region. And what we've done in AWS storage is we've recognized that depending on the need of usage where you put your data and how you interact with it may vary. But we've built a whole set of services like data transfer to help make sure that we can connect data from, for example that new snow cone into a region automatically. And so our goal Dave is to make sure that when customers are operating at the edge or they're operating in the region they have the same quality of storage service and they have easy ways to go between them. You shouldn't have to pick, you should be able to do it all. >> So in the spirit of do it all there's this sort of age old dynamic in the tech business where you've got the friction between the best of breed and the integrated suite. And my question is around what you're optimizing for customers. And can you have your cake and eat it too? In other words, why AWS storage? What makes it compelling? Is it because it's kind of a best of breed storage service or is it because it's integrated with AWS? Would you ever sub optimize one in order to get an advantage to the other? Or can you actually, you know have your cake and eat it too? >> The way that we build storage is to focus on being both the breadth of capabilities and the depth of capabilities. And so where we identify a particular need where we think that it takes a whole new service to deliver we'll go build that service. And an example for that as FTP our AWS SFTP service, which, you know, there's a lot of SFTP usage out there and there will be for a while because of the, you know, the legacy B2B type of architectures that still live in the business world today. And so we looked at that problem. We said, how are we going to build that in the best depth way, in the best focus? And we launched a separate service for that. And so our goal is to take the individual building blocks of EBS and glacier and S3 and make the best of class and the most comprehensive in the capabilities of what we can do and where we identify a very specific need. We'll go build a service for it. But Dave, you know as an example for that idea of both depth and breadth, S3 Storage Lens is a great example of that. S3 Storage Lens is a new capability that we launched late last year. And what it does is it lets you look across all your regions and all your accounts and get a summary view of all your S3 storage and whether that's buckets or the most active prefixes that you have and be able to drill down from that. And that is built in to the S3 service and available for any customer that wants to turn it on in the AWS management console. >> Right, and we saw just recently made, I called it super-duper block storage but you can make some improvements in really addressing the highest performance. I want to ask you, so we've all learned about an experience that benefits of cloud over the last several years and especially in the last 10 months during the pandemic but one of the challenges and it's particularly acute with IO is of course latency and moving data around and accessing data remotely. It's a challenge for customers, you know, due to speed of light, et cetera. So my question is how was AWS thinking about all that data that's still resides on premises? I think we heard at reinvent, that's still on 90% of the opportunity is, or the the workloads are still on prem that live inside a customer's data centers. So how do you tap into those and help customers innovate with on-prem data, particularly from a storage angle? >> Well, we always want to provide the best of class solution for those little latency workloads. And that's why we launched Block Express just late last year at reinvent. And Block Express has a new capability in preview on top of our IO to provisioned IOPS volume type. And what's really interesting about block express Dave is that the way that we're able to deliver the performance of Block Express, which is sound performance with cloud elasticity is that we went all the way down to the network layer and we customize the hardware software. And at the network layer we built Block Express on something called SRD which stands for a scalable reliable diagrams. And basically what it's letting us do is offload all of our EBS operations for Block Express on the nitrile card on hardware. And so that type of innovation where we're able to, you know, take advantage of modern cop commodity, multi-tenant data center networks, where we're sending in this new network protocol across a large number of network paths. And that type of innovation all the way down to that protocol level helps us innovate in a way that's hard. In fact, I would say impossible for other sound providers to kind of really catch up and keep up. And so we feel that the amount of innovation that we have for delivering those low latency workloads in our AWS cloud storage is unlimited really because of that ability to customize software hardware and network protocols as we go along without requiring upgrades from a customer it just gets better. And the customer benefits. Now, if you want to stay in your data center that's why we build outposts. And for outposts, we have UVS and we have S3 for outposts and our goal there is that some customers will have workloads where they want to keep them resident in the data center. And for those customers we want to give them that AWS storage opportunities as well. >> So thank you for coming back to Block Express. So you call it, you know, sand in the cloud. So is that essentially it comprises a custom built essentially storage network. Is that right? What you just described SRD? I think you called it. >> Yeah, it's a SRD is used by other AWS services as well but it is a custom network protocol that we designed to deliver the lowest latency experience and we're taking advantage of it with Block Express. >> So sticking with traditional data centers for a moment I'm interested in your thoughts on the importance of the cloud pricing approach, I.e the consumption model to pay by the drink. Obviously it's one of the most attractive features, and I asked that because we're seeing what Andy Jassy refers to as the old guard Institute, flexible pricing models two of the biggest storage companies, HP with GreenLake and Dell has this thing called apex. They've announced such models for on-prem and presumably cross cloud. How do you think this is going to impact your customers leverage of AWS cloud storage? Is it something that you have an opinion on? >> Yeah, I think it all comes down to, again that usage of the storage, and this is where I think there's an inherent advantage for our cloud storage. So there might be an attempt by the old guard to lower prices or add flexibility but at the end of the day it comes down to what the customer actually needs to tune. And if you think about gp3 which is the new EBS volume. The idea with gp3 is we're going to pass a long savings to the customer by making the storage 20% cheaper than gp2. And we're going to make the product better by giving a great, reliable baseline performance. But we're also going to let customers who want to run workloads like Cassandra on EBS tune their throughput separately, for example from their capacity. So if you're running Cassandra sometimes you don't need to change your capacity. Your storage capacity works just fine. But what happens with, for example Cassandra workload is that you may need more throughput. And if you're buying hardware appliance you just have to buy for your peak. You have to buy for the max of what you think your throughput and the max of what your storage is. And this inherent flexibility that we have for AWS storage and being able to tune throughput separate from up separate from capacity like you do for gp3 that is really where the future is for customers having control over costs and control over customer experience without compromising or trading off either one. >> Awesome, thank you for that. So in the time we have remaining Mai-Lan, I want to talk about the topic of diversity social impact, and as a woman leader, women executive, and I really want to get your perspectives on this. And I've shared with the audience previously, one of my breaking analysis segments, your boxing video which is awesome. And so, you've got a lot of unique non-traditional aspects to your life and I love it, but I want to ask you this. So it's obviously, you know, certainly politically and socially correct to talk about diversity, the importance of diversity, there's data that suggests that diversity is good both economically, not just socially, and of course it's the right thing to do. But there are those, you know, Peter teal is probably the most prominent but there are others that say, "You know what? "Forget that, just hire people, just like you'll be able "to go faster, ramp up more quickly, hit escape "velocity it's natural." And that's what you should do. Why is that not the right approach? Why is diversity both, of course, socially, you know responsible, but also, you know, good for business >> For Amazon we think about diversity as something that is essential to how we think about innovation. And so, Dave, as you know, from listening to some of the announcements at reinvent, we launch a lot of new ideas, like new concepts and new services in AWS. And just bringing that lens down to storage. Astri has been reinventing itself every year since we launched in 2006. EBS introduced the first sun on the cloud late last year, and continues to reinvent how customers think about block storage. We would not be able to look at a product in a different way and think to ourselves, not just what is the legacy system do in a data center today but how do we want to build this new distributed system in a way that helps customers achieve not just what they're doing today, but what they want to do in five and 10 years. You can't get that innovative mindset without bringing different perspectives to the table. And so we strongly believe in hiring people who are from under represented groups and whether that's gender or it's related to racial equality or if it's geographic diversity and bringing them in to have the conversation because those diverse viewpoints inform how we can innovate at all levels in AWS. >> Right, and so I really appreciate their perspectives on that. And we've had, as you probably know the cube has been, you know a very big advocate of diversity, you know, generally but women in tech specifically, we participated a lot. And I often ask this question is, you know, as a smaller company, I, and some of my other colleagues in small business, sometimes we struggle. And so my question is how do you go beyond what's your advice for going beyond, you know the good old boys network? I think it's large companies like AWS and, you know, the big players, you've got responsibility too that you can put somebody in charge and make it their full-time job. How should smaller companies that are largely white male dominated, how should they become more diverse? What should they do to increase that diversity? >> I think the place to start is voice. A lot of what we try to do is make sure that the under represented voice is heard. And so Dave, any small business owner of any industry can encourage voice for your under represented or your unheard populations. And honestly, it is as simple as being in a meeting and looking around that table or on your screen, as it were and asking yourself, who hasn't talked? Who hasn't weighed in? Particularly if the debate is contentious or even animated. And you will see, particularly if you note this over time you will see that there may be somebody and whether it's an under represented group or it's a woman who's early career, or it's not it's just a member of your team who happens to be a white male too, who's not being heard. And you can ask that person for their perspective. And that is a step that every one of us can and should do which is ask to have everyone's voice at the table to listen and to weigh in on it. So I think that is something everyone should do. I think if you are a member of an under represented group as for example, I'm Vietnamese American and I'm a female in tech, I think, it's something to think about how you can make sure that you're always taking that bold step forward. And it's one of the topics that we covered at re-invent. We had a great discussion with a group of women CEOs and a lot of it we talked about is being bold taking the challenge of being bold in tough situations. And that is an important thing, I think for anybody to keep in mind, but especially for members of under represented groups, because sometimes Dave that bold step that you kind of think of as like, "Oh I don't know if I should ask for that promotion." or "I don't know if I should volunteer for that project." It's not a big ask, but it's big in your head. And so if you can internalize as a member of some, you know, a group that maybe isn't heard as or seen as much how you can take those bold challenges and step forward and learn, maybe fail also cause that's how you learn. Then that is a way to also have people learn and develop and become leaders in whatever industry it is. >> That's great advice. It reminds me of, I think most of us can relate to that Mai-Lan, because when we started in the industry, we may be timid. You didn't want to necessarily speak up. And I think it's incumbent upon those in a position of power. And by the way power might just be running a meeting agenda to maybe call on those folks that are, maybe it's not diversity of gender or, you know, or race. Maybe it's just the under represented. Maybe that's a good way to start building muscle memory. So that's unique advice that I hadn't heard before. So thank you very much for that. I appreciate it. And Hey, listen. Thanks so much for coming on the Cube On Cloud. We're out of time and really always appreciate your perspectives and you're doing a great job. And thank you. >> Great, thank you Dave. Thanks for having me and have a great day. >> All right, and Keep it right there buddy. You're watching the Cube On Cloud. Right back. (gentle upbeat music)

>>from around the globe. It's the Cube with digital coverage of AWS reinvent 2020 sponsored by Intel and AWS. Yeah, hello, everyone, and welcome back to the Cubes Walter Wall coverage of AWS reinvent 2020. We've gone virtual along with reinvent and we heard in Andy Jassy is hours long. Keynote a number of new innovations in the area of storage. And with me to talk about that is Milan Thompson Bukovec. She's the vice president of Block and Object Storage and AWS. That's everything. Elastic block storage s three Glacier, the whole portfolio Milon. Thanks for coming on. >>Great to see you. >>Great to see you too. So you heard Andy. We all heard Andy talk a lot about reinventing different parts of the platform, reinventing industries and a really kind of exciting and visionary put talk that he put forth. Let's >>talk >>about storage, though. How is storage reinventing itself? >>Well, as you know, cloud storage was essentially invented by a W s a number of years ago. And whether that's in 2000 and six, when US three was launched, or 2000 and eight when CBS was launched and we first came up with this model of pay as you go for durable, attached storage. Too easy to instances. And so we haven't stopped and we haven't slowed down. If anything, we've picked up the rate of reinvention that we've done across the portfolio for storage. I think, as Andy called out, speed matters. And it matters for how customers air thinking about how do they pivot and move to the cloud as quickly as they can, particularly this year. And it matters a lot in storage as well, because the changing access patterns of what customers air doing with their new cloud applications, you know they're they're transforming their businesses and their applications, and they need a modern storage platform underneath it. And that's what you have with AWS Storage. And he talked about some of the key releases, particularly in block storage. It's actually kind of amazing. What's what's been done with CBS is here. We launched GP three GP two was the previous generation general purpose volume type. We launched that in 2000 and 14 again thief, first type of general purpose volume that had this great combination of simplicity and price, and just about everybody uses it for a boot or often a data volume. And with GP three, which was available yesterday with Andy's announcement, we added four times peak throughput on top of GP two, and it's a 20% lower storage price per gigabyte per month. And we took the feedback. The number one feedback we got on GP to which was how can I separate buying throughput and I ops from storage capacity? And that is really important. That goes back to the promise of the cloud. And it goes back to being able to pick what aspect do you want to scale your storage on? And so, with GP three, you could buy a certain amount of capacity. And if you're good with that capacity, but you need more throughput, more eye ops, you can buy those independently. And that is that fine grained customization for those changing data patterns that I just talked about. And it's available for GP three today. >>Yeah, that was I looked at that, like my life is a knob that you could turn Okay, juice my eye ops. And don't touch my capacity. I'm happy there. I don't wanna pay for more of it. >>And thio add to that it's a knob you could turn if you need it. We have more throughput, more eye ops as a baseline capacity for your storage capacity than we did for GP to. But then you can tune it based on whatever you need, not just now, but in the future. >>So so given the pandemic, I mean, how has that affected E? Everybody is talking about going to the cloud, because where else you gonna go? But But how has that affected what customers are doing this year, and does it change your roadmap at all? Does it change your thinking? >>Well, I have to say, there's two main things that we've seen. One is it's really accelerated customers thinking about getting off of on premises and into the club. It's done that because nobody really wants to manage the data center. And if there's ever a year you don't want to manage the data center, it's 2020 and it's because, particularly with storage appliances, it takes a long time to acquire. Let's just take storage area networks or sense super expensive. You get a fixed amount of capacity you have to acquire. It takes months to come in you gotta rack and stack. Then you gotta change all your networking and maintain it. Ah, lot of customers don't want to do that. And so what it's done for us is it's really, uh, you know, accelerated our thinking and you saw yesterday and Andy's keynote as well. Of how do we build the first san in the cloud? And we launched Io two. In August of this year, we introduced the first nines of durability, again reinventing how people think about durability and their block storage. But just this week we now have a Iot to block Express with 2 56 K ai ops, four K megabytes of throughput in 64 terabytes of capacity, that sand level performance. And it's available for preview because I 02 is going to be your son in the cloud. And that is a direct correlation to what we hear from customers, which is how can I get away from these expensive on premises purchases like Sands and combine the performance with the elasticity that I need? So that's the first thing. How can we accelerate getting off of these very rigid procurement cycles that we have and having to manage a data center. It's not just for EBS, its for S. Trias. Well, the second thing we're hearing from customers is how can I have the agility? So you talk to customers as well. He talked to CEOs and C. T. O s. It's been a crazy year in 2020. It was one thing that a company has to do its pivot. It's really figure out. How are you going to adjust and adjust quickly? And so we have customers like Ontario Telehealth Network up in Canada, where they went from 8000 to 30,000 users because they're doing virtual health for Ontario. And we have other customers who, you know, that's a pivot. That's an increase. And we have other customers, like APS Flyer, where their goal is to just save money without changing their application. And they also did a pivot. They used the intelligence hearing storage class, which is the most popular storage class, as three offers for data lakes, and they were able to make that change save 18% on their storage cost, no change of their application, just using the capabilities of AWS. And so his ability to pivot helped you know really make us think and accelerate what we're building as well. And so one of the things that we launched just recently for intelligent hearing is we added two new archival tears to intelligent hearing. And those are archival tears, you know, just like intelligence hearing automatically watches every object industry storage and your data lake and gives you dynamic pricing based on if it's frequently accessed in a month or inflict infrequently accessed, you can turn on archival tear. And if your object your pork a file, for example, isn't access or your backup isn't access for 90 days, intelligence hearing will automatically move it to glacier characteristics of archival or too deep archive and give you the same price. A dollar, a terabyte per month. If your data is an access to 180 days, it's done automatically, and it means you save up to 90% 95% and cost on that storage. And so, if you if you think about those two trends, how can I get away from getting locked into those on premises Hardware cycles? How can I get away from it faster for sands and other hardware appliances and then the other trend is how can I pivot and use the innovation and the reinvention in our storage services to just save money and be more agile in these changing conditions? >>So I gotta ask you follow up question on staying in the cloud, because when you think of sand, you think of switches. You think of complexity, but I get that you're connecting to the performance of a sand. But you guys are all about simplicity. So how did you What's behind there? Can you take us under the covers? Just you guys build your own little storage network because it's cloud. It's gotta be fast and simple. >>That's right. When we're thinking about performance and cost, we go down to the metal for this stuff. We think about Unicosta a very fine grained level, and when we're building new technology that we know is gonna be the foundation for everything we're doing for that high performance, we went down to the protocol level. We're using something called Us RD. It's all rolled up under the hood for Block Express, and it's the foundation of that super super high performance. As you know, there's a lot of engineering behind the scenes in the cloud and for for what we've done this year, as part of that reinvention we've reinvented all the way down to the protocol way. >>Let me ask you that the two things that come up in our survey when you talk to CEOs, they say two priorities. Security is actually second cloud migration actually popped up to the top. So where does storage fit in that whole notion about cloud migration, >>Storage eyes, usually where a lot of people start, you know, Luckily, with a W s, you don't have to choose between security or cloud of migration. Security is job one for every AWS service. And so when customers air thinking about how do I move an application, they gotta move the data first. And so they start from the from the data. What storage do I use? What is the best fit for the storage and how do I best secure that's storage? And so the innovation that we dio on storage always comes with that. That combination of, you know, migration, the set of tools that we provide for getting data from on premises into the cloud. We have tools like aws data sync which do a great job of this on. Then we also look at things like how do we continue to take the profile of security forward? And one example of that is something we launched just this week called Bucket keys s three bucket keys. And it drops the cost of using kms for service side encryption with us three by over 90%. And the way it does it is that we've integrated those two services super closely together so that you can minimize the amount of costs that you make for very, very frequent request. Because in data lakes you have millions and billions of objects and our goal is to make security so cost effective people don't even think about it. That also goes for other parts of the platform. We have guard duty for us three now, and what that does is security anomaly detection automatically to track your access patterns across as three and flag when something is not quite what it should be. And so this idea of like how do I not only get my data into the cloud? But then how do I take advantage of the breath of the storage portfolio, but also the breath of the AWS services to really maximize that security profile as well as the access patterns that I want from my application. >>Well, my way hit the major announcements and unfortunately, out of time. But I really would love to have you back and go deeper and have you share your vision of what the cloud storage piece looks like going forward. Thanks so much for coming in. The Cube is great to have you. >>Great to be here. Thanks, Dave. CIA. >>See you later and keep it right, everybody. You're watching the cubes. Coverage of aws reinvent 2020 right back.

>> Hello everyone, we're here at the Snowflake Data Cloud Summit. This is the Tech Titans panel. We're going to explore some of the trends that are shaping new data capabilities and specifically how organizations are transforming their companies, with data and insights. And with me are three amazing guest panelists. Christian Kleinerman is the senior vice president of product at Snowflake. He's joined by Mark Nelson, who's the EVP of product development at Salesforce/Tableau and Mai-Lan Thompson Bukovec, who's the vice president of Block and Object Storage at Amazon web services. Folks, thanks so much for coming on the program. Great to see you all. >> Thanks for having us. >> Nice to see you. >> Glad to be here. >> Excellent, so here in this session, you know, we have the confluence of the data cloud. We have simple and cost effective storage repositories and the visualization of data. These are three ingredients that are really critical for quickly analyzing and turning data into insights and telling stories with data. So, Christian, let me start with you. Of course, this is all enabled by the Cloud and Snowflake. You're extending that to this data cloud. One of the things that we can do today with data that we say weren't able to do maybe five years ago. >> Yeah, certainly I think there is lots of things that we can integrate specific actions but if you were to zoom out and look at the big picture, our ability to reason through data to inform our choices to date with data is bigger than ever before. There are still many companies that have to decide to sample data or to throw away older data, or they don't have the right data from external companies to put their decisions and actions in context. Now we have the technology and the platforms to bring all that data together, tear down silos and look a 360 of a customer or entire action. So I think it's reasoning through data that has increased the capability of organizations dramatically in the last few years. >> So Mai-Lan, when I was a young pup, at IDC, I started the storage program there, many, many moons ago. And so I always pay attention to what's going on in storage, back of my mind. And S3 people forget, sometimes, that was actually the very first cloud product announced by AWS, which really ushered in the cloud era. And that was 2006, it fundamentally changed the way we think about storing data. I wonder if you can explain how S3 specifically in an object storage generally, you know, with get put really transformed storage from a blocker to an enabler of some of these new workloads that we're seeing. >> Absolutely, I think it has been transformational for many companies in every industry. And the reason for that is because in S3, you can consolidate all the different data sets that today are scattered around so many companies, different data centers. And so if you about it, S3 gives the ability to put unstructured data which are video recordings and images. It puts semi structured data which is the CSV file, which every company has lots of. And that has also support for structured data types like parquet files, which drive a lot of the business decisions that every company has to make today. And so if you think about S3, which launched on Pi day in March of 2006, S3 started off as an object store, but it has evolved into so much more than that, where companies all over the world, and every industry are taking those different data sets, they're putting it in S3, they're growing their data and then they're growing the value that they capture on top of that data. And that is the separation we see that snowflake talks about and many of the pioneers across different industries talk about, which is a separation of the growth of storage and the growth of your computer applications. And what's happening is that when you have a place to put your data like S3, which is secure by default and has the availability and the durability and the operational profile you know, and can trust, then the innovation of the application developers really take over, and you know, one example of that is where we have a customer in the financial sector and they started to use S3 to put their customer care recordings. And they were just using it for storage because that obviously dataset grows very quickly. And then somebody in their fraud department got the idea of doing machine learning on top of those customer care recordings. And when they did that they found really interesting data that they could then feed into their fraud detection models. And so you get this kind of alchemy of innovation that happens when you take the datasets of today and yesterday and tomorrow you put them all in one place which is the history and the innovation of your application, developers just takes over and builds, not just what you need today but what you need in the future as well. >> Thank you for that. Mark, I want to bring you into this panel. It's great to have you here. So thank you. I mean, Tableau has been a game changer for organizations. I remember my first, Tableau conference, passionate customers and really bringing cloud-like agility and simplicity to visualization just totally changed the way people thought about data and met with massive data volumes and simplified access. And now we're seeing new workloads that are developing on top of data and Snowflake data and the cloud. Can you talk about how your customers are really telling stories and bringing to life those stories with data on top of things like S3, which Mai-Lan was just talking about? >> Yeah, for sure. Building on what Christian and Mai-Lan have already said our mission at Tableau has always been help people see and understand data. And you look at the amazing advances that are happening in storage and data processing. And now, the data that you can see and play with is so amazing, right? Like at this point in time, it's really nothing short of a new microscope or a new telescope that really lets you understand patterns. They were always there in the world, but you literally couldn't see them because of the limitations of the amount of data that you could bring into the picture, because of the amount of processing power and the amount of sharing of data that you could bring into the picture. And now like you said, these three things are coming together and this amazing ability to see and tell stories with your data combined with the fact that you've got so much more data at your fingertips, the fact that you can now process that data, look at that data share that data in ways that was never possible. Again, I'll go back to that analogy. It feels like the invention of a new microscope, a new telescope a new way to look at the world and tell stories and get to insights that were just, were never possible before. >> So thank you for that, and then Christian I want to come back to this notion of the data cloud and, you know, it's a very powerful concept and of course it's good marketing, but I wonder if you could add some additional color for the audience. I mean, what more can you tell us about the data cloud, how you're seeing it evolving and maybe building on some of the things that Mark was just talking about just in terms of, you know, bringing this vision into reality? >> Certainly, yeah. Data cloud for sure, is bigger and more concrete than just the marketing value of it. The big insight behind our vision for the data cloud is that just the technology, a capability, just a cloud data platform is not what gets organizations to be able to be a data driven, to be able to make great use of data or be highly capable in terms of data ability. The other element beyond technology is the access and availability of data to put their own data in context or enrich based on the knowledge or data from other third parties. So the data cloud, the way to think about it is, is a combination of both technology, which for Snowflake is our Cloud Data platform in all the workloads, the ability to do data warehousing and queries and speeds and feeds fit in there and data engineering, et cetera. But it's also, how do we make it easier for our customers to have access to the data that they need or they could benefit to improve the decisions for their own organizations. Think of the analogy of a set top box. I can give you a great technically set top box but if there's no content on the other side, it makes it difficult for you to get value out of it. That's how we should all be thinking about it, the data cloud, it's technology, but it's also seamless access to data. >> And Mai-Lan, can you give us a sense of the scope and what kind of scale are you seeing with Snowflake on AWS? >> Well, Snowflake has always driven as Christian as a very high transaction rate to S3. And in fact, when Christian and I were talking just yesterday, we were talking about some of the things that have really been remarkable about the long partnership that we've had over the years. And so I'll give you an example of how that evolution has really worked. So as you know, S3 has, is, you know, the first AWS services that is launched and we have customers who have petabytes, hundreds of petabytes and exabytes of storage on history. And so from the ground up S3 has been built for scale. And so when we have customers, like Snowflake that have very high transaction rates for requests, for S3 storage, we put our customer hat on and we ask customers like Snowflake, how do you think about performance? Not just what performance do you need but how do you think about performance? And you know, when Christian and his team were working through the demands of making requests to their S3 data, they were talking about some pretty high spikes over time and just a lot of volume. And so when we built improvements, into our performance over time, we put that hat on for work, you know, Snowflake was telling us what they needed. And then we built our performance model not around a bucket or an account. We built it around a request rate per prefix, because that's what Snowflake and other customers told us they needed. And so when you think about how we scale our performance, we scale it based on a prefix and not a bucket in our account, which other cloud providers do. We do it in this unique way because 90% of our customer roadmap across AWS comes from customer requests. And then that's what Snowflake and other customers were saying is that, "Hey, I think about my performance based on a prefix and of an object and not some, you know, arbitrary semantic of how I happened to organize my buckets." I think the other thing I would also throw out there for skill is, as you might imagine, S3 is a very large distributed system. And again, if I go back to how we architected for our performance improvements, we architected in such a way that a customer like Snowflake, could come in and they could take advantage of horizontally scaling. They can do parallel data retrievals and puts in gets for your data. And when they do that they can get tens of thousands of requests per second because they're taking advantage of the scale of S3. And so, you know, when we think about scale it's not just scale which is the growth of your storage, which every customer needs. IDC says that digital data is growing at 40% year over year. So every customer needs a place to put all of those storage sets that are growing. But the way we also have worked together for many years is this, how can we think about how Snowflake and other customers are driving these patterns of access on top of the data, not just the last history of the storage, but the access and then how can we architect often very uniquely as I talked about with our request rate in such a way that they can achieve what they need to do not just today, but in the future. >> I don't know, three companies here that don't often take their customer hats off. Mark, I wonder if we could come to you, you know, during the Data Cloud Summit, we've been exploring this notion that innovation in technology is really evolved from point products you know, the next generation of server or software tool to platforms that made infrastructure simpler or called functions and now it's evolving into leveraging ecosystems. You know, the power of many versus the resources of one. So my question is, you know, how are you all collaborating and creating innovations that your customers can leverage? >> Yeah, for sure, so certainly, you know Tableau and Snowflake, you know, kind of where were dropped at natural partners from the beginning, right? Like putting that visualization engine on top of Snowflake to, you know, combine that processing power and data and the ability to visualize it was obvious. As you talk about the larger ecosystem now of course, Tableau is part of Salesforce. And so there's a much more interesting story now to be told across the three companies, one in two and a half maybe as we talk about Tableau and Salesforce combined together of really having this full circle of Salesforce you know, with this amazing set of business apps that so much value for customers and getting the data that comes out of their Salesforce applications, putting it into Snowflake so that you can combine that, share that, you process it combine it with data, not just for across Salesforce, but from your other apps in a way that you want. And then put Tableau on top of it. Now you're talking about this amazing platform ecosystem of data, you know, coming from your most valuable business applications in the world with the most, you know, sales opportunity objects, marketing, service, all of that information flowing into this flexible data platform and then this amazing visualization platform on top of it. And there's really no end of the things that our customers can do with that combination >> Christian we're out of time, but I wonder if you could bring us home and I want to end with, you know let's say, you know, people, some people here maybe they don't, maybe they're still struggling with the cumbersome nature of let's say their on-prem data, warehouses. You know, the kids just unplugged them because they rely on them for certain things like reporting but let's say they to raise the bar on their data and analytics, what would you advise for a next step for them? >> Yeah I think the first part or first step to take is around embrace the cloud and the promise on the abilities of cloud technology. There's many studies where relative to peers, companies that are embracing data are coming out ahead and outperforming their peers. And with traditional technology on-prem technology, you ended up with a proliferation of silos and copies of data. And a lot of energy went into managing those on-prem systems and making copies and data governance and security and cloud technology and the type of platform that the Snowflake has brought to market enables organizations to focus on the data, the data model, the data insights, and not necessarily on managing the infrastructure. So I think that will be the first recommendation from our end. Embrace cloud, get onto a modern cloud data platform, make sure that you're spending your time on data, not managing infrastructure and seeing what the infrastructure lets you do. >> It makes a lot of sense, guys. Thanks, thanks so much. We'll have to end it there and thank you everybody for watching. Keep it right there. We'll be back, with the next segment, right after this short break.

>> From Cambridge, Massachusetts. It's theCUBE, covering MIT Chief Data Officer and Information Quality Symposium 2019. Brought to you by SiliconANGLE Media. >> Welcome back to Cambridge, Massachusetts, everybody. We're here at MIT, sweltering Cambridge, Massachusetts. You're watching theCUBE, the leader in live tech coverage, my name is Dave Vellante. I'm here with my co-host, Paul Gillin. Special coverage of the MITCDOIQ. The Chief Data Officer event, this is the 13th year of the event, we started seven years ago covering it, Mark Ramsey is here. He's the Chief Data and Analytics Officer Advisor at Ramsey International, LLC and former Chief Data Officer of GlaxoSmithKline. Big pharma, Mark, thanks for coming onto theCUBE. >> Thanks for having me. >> You're very welcome, fresh off the keynote. Fascinating keynote this evening, or this morning. Lot of interest here, tons of questions. And we have some as well, but let's start with your history in data. I sat down after 10 years, but I could have I could have stretched it to 20. I'll sit down with the young guns. But there was some folks in there with 30 plus year careers. How about you, what does your data journey look like? >> Well, my data journey, of course I was able to stand up for the whole time because I was in the front, but I actually started about 32, a little over 32 years ago and I was involved with building. What I always tell folks is that Data and Analytics has been a long journey, and the name has changed over the years, but we've been really trying to tackle the same problems of using data as a strategic asset. So when I started I was with an insurance and financial services company, building one of the first data warehouse environments in the insurance industry, and that was in the 87, 88 range, and then once I was able to deliver that, I ended up transitioning into being in consulting for IBM and basically spent 18 years with IBM in consulting and services. When I joined, the name had evolved from Data Warehousing to Business Intelligence and then over the years it was Master Data Management, Customer 360. Analytics and Optimization, Big Data. And then in 2013, I joined Samsung Mobile as their first Chief Data Officer. So, moving out of consulting, I really wanted to own the end-to-end delivery of advanced solutions in the Data Analytics space and so that made the transition to Samsung quite interesting, very much into consumer electronics, mobile phones, tablets and things of that nature, and then in 2015 I joined GSK as their first Chief Data Officer to deliver a Data Analytics solution. >> So you have long data history and Paul, Mark took us through. And you're right, Mark-o, it's a lot of the same narrative, same wine, new bottle but the technology's obviously changed. The opportunities are greater today. But you took us through Enterprise Data Warehouse which was ETL and then MAP and then Master Data Management which is kind of this mapping and abstraction layer, then an Enterprise Data Model, top-down. And then that all failed, so we turned to Governance which has been very very difficult and then you came up with another solution that we're going to dig into, but is it the same wine, new bottle from the industry? >> I think it has been over the last 20, 30 years, which is why I kind of did the experiment at the beginning of how long folks have been in the industry. I think that certainly, the technology has advanced, moving to reduction in the amount of schema that's required to move data so you can kind of move away from the map and move type of an approach of a data warehouse but it is tackling the same type of problems and like I said in the session it's a little bit like Einstein's phrase of doing the same thing over and over again and expecting a different answer is certainly the definition of insanity and what I really proposed at the session was let's come at this from a very different perspective. Let's actually use Data Analytics on the data to make it available for these purposes, and I do think I think it's a different wine now and so I think it's just now a matter of if folks can really take off and head that direction. >> What struck me about, you were ticking off some of the issues that have failed like Data Warehouses, I was surprised to hear you say Data Governance really hasn't worked because there's a lot of talk around that right now, but all of those are top-down initiatives, and what you did at GSK was really invert that model and go from the bottom up. What were some of the barriers that you had to face organizationally to get the cooperation of all these people in this different approach? >> Yeah, I think it's still key. It's not a complete bottoms up because then you do end up really just doing data for the sake of data, which is also something that's been tried and does not work. I think it has to be a balance and that's really striking that right balance of really tackling the data at full perspective but also making sure that you have very definitive use cases to deliver value for the organization and then striking the balance of how you do that and I think of the things that becomes a struggle is you're talking about very large breadth and any time you're covering multiple functions within a business it's getting the support of those different business functions and I think part of that is really around executive support and what that means, I did mention it in the session, that executive support to me is really stepping up and saying that the data across the organization is the organization's data. It isn't owned by a particular person or a particular scientist, and I think in a lot of organization, that gatekeeper mentality really does put barriers up to really tackling the full breadth of the data. >> So I had a question around digital initiatives. Everywhere you go, every C-level Executive is trying to get digital right, and a lot of this is top-down, a lot of it is big ideas and it's kind of the North Star. Do you think that that's the wrong approach? That maybe there should be a more tactical line of business alignment with that threaded leader as opposed to this big picture. We're going to change and transform our company, what are your thoughts? >> I think one of the struggles is just I'm not sure that organizations really have a good appreciation of what they mean when they talk about digital transformation. I think there's in most of the industries it is an initiative that's getting a lot of press within the organizations and folks want to go through digital transformation but in some cases that means having a more interactive experience with consumers and it's maybe through sensors or different ways to capture data but if they haven't solved the data problem it just becomes another source of data that we're going to mismanage and so I do think there's a risk that we're going to see the same outcome from digital that we have when folks have tried other approaches to integrate information, and if you don't solve the basic blocking and tackling having data that has higher velocity and more granularity, if you're not able to solve that because you haven't tackled the bigger problem, I'm not sure it's going to have the impact that folks really expect. >> You mentioned that at GSK you collected 15 petabytes of data of which only one petabyte was structured. So you had to make sense of all that unstructured data. What did you learn about that process? About how to unlock value from unstructured data as a result of that? >> Yeah, and I think this is something. I think it's extremely important in the unstructured data to apply advanced analytics against the data to go through a process of making sense of that information and a lot of folks talk about or have talked about historically around text mining of trying to extract an entity out of unstructured data and using that for the value. There's a few steps before you even get to that point, and first of all it's classifying the information to understand which documents do you care about and which documents do you not care about and I always use the story that in this vast amount of documents there's going to be, somebody has probably uploaded the cafeteria menu from 10 years ago. That has no scientific value, whereas a protocol document for a clinical trial has significant value, you don't want to look through manually a billion documents to separate those, so you have to apply the technology even in that first step of classification, and then there's a number of steps that ultimately lead you to understanding the relationship of the knowledge that's in the documents. >> Side question on that, so you had discussed okay, if it's a menu, get rid of it but there's certain restrictions where you got to keep data for decades. It struck me, what about work in process? Especially in the pharmaceutical industry. I mean, post Federal Rules of Civil Procedure was everybody looking for a smoking gun. So, how are organizations dealing with what to keep and what to get rid of? >> Yeah, and I think certainly the thinking has been to remove the excess and it's to your point, how do you draw the line as to what is excess, right, so you don't want to just keep every document because then if an organization is involved in any type of litigation and there's disclosure requirements, you don't want to have to have thousands of documents. At the same time, there are requirements and so it's like a lot of things. It's figuring out how do you abide by the requirements, but that is not an easy thing to do, and it really is another driver, certainly document retention has been a big thing over a number of years but I think people have not applied advanced analytics to the level that they can to really help support that. >> Another Einstein bro-mahd, you know. Keep everything you must but no more. So, you put forth a proposal where you basically had this sort of three approaches, well, combined three approaches. The crawlers to go, the spiders to go out and do the discovery and I presume that's where the classification is done? >> That's really the identification of all of the source information >> Okay, so find out what you got, okay. >> so that's kind of the start. Find out what you have. >> Step two is the data repository. Putting that in, I thought it was when I heard you I said okay it must be a logical data repository, but you said you basically told the CIO we're copying all the data and putting it into essentially one place. >> A physical location, yes. >> Okay, and then so I got another question about that and then use bots in the pipeline to move the data and then you sort of drew the diagram of the back end to all the databases. Unstructured, structured, and then all the fun stuff up front, visualization. >> Which people love to focus on the fun stuff, right? Especially, you can't tell how many articles are on you got to apply deep learning and machine learning and that's where the answers are, we have to have the data and that's the piece that people are missing. >> So, my question there is you had this tactical mindset, it seems like you picked a good workload, the clinical trials and you had at least conceptually a good chance of success. Is that a fair statement? >> Well, the clinical trials was one aspect. Again, we tackled the entire data landscape. So it was all of the data across all of R&D. It wasn't limited to just, that's that top down and bottom up, so the bottom up is tackle everything in the landscape. The top down is what's important to the organization for decision making. >> So, that's actually the entire R&D application portfolio. >> Both internal and external. >> So my follow up question there is so that largely was kind of an inside the four walls of GSK, workload or not necessarily. My question was what about, you hear about these emerging Edge applications, and that's got to be a nightmare for what you described. In other words, putting all the data into one physical place, so it must be like a snake swallowing a basketball. Thoughts on that? >> I think some of it really does depend on you're always going to have these, IOT is another example where it's a large amount of streaming information, and so I'm not proposing that all data in every format in every location needs to be centralized and homogenized, I think you have to add some intelligence on top of that but certainly from an edge perspective or an IOT perspective or sensors. The data that you want to then make decisions around, so you're probably going to have a filter level that will impact those things coming in, then you filter it down to where you're going to really want to make decisions on that and then that comes together with the other-- >> So it's a prioritization exercise, and that presumably can be automated. >> Right, but I think we always have these cases where we can say well what about this case, and you know I guess what I'm saying is I've not seen organizations tackle their own data landscape challenges and really do it in an aggressive way to get value out of the data that's within their four walls. It's always like I mentioned in the keynote. It's always let's do a very small proof of concept, let's take a very narrow chunk. And what ultimately ends up happening is that becomes the only solution they build and then they go to another area and they build another solution and that's why we end up with 15 or 25-- (all talk over each other) >> The conventional wisdom is you start small. >> And fail. >> And you go on from there, you fail and that's now how you get big things done. >> Well that's not how you support analytic algorithms like machine learning and deep learning. You can't feed those just fragmented data of one aspect of your business and expect it to learn intelligent things to then make recommendations, you've got to have a much broader perspective. >> I want to ask you about one statistic you shared. You found 26 thousand relational database schemas for capturing experimental data and you standardized those into one. How? >> Yeah, I mean we took advantage of the Tamr technology that Michael Stonebraker created here at MIT a number of years ago which is really, again, it's applying advanced analytics to the data and using the content of the data and the characteristics of the data to go from dispersed schemas into a unified schema. So if you look across 26 thousand schemas using machine learning, you then can understand what's the consolidated view that gives you one perspective across all of those different schemas, 'cause ultimately when you give people flexibility they love to take advantage of it but it doesn't mean that they're actually doing things in an extremely different way, 'cause ultimately they're capturing the same kind of data. They're just calling things different names and they might be using different formats but in that particular case we use Tamr very heavily, and that again is back to my example of using advanced analytics on the data to make it available to do the fun stuff. The visualization and the advanced analytics. >> So Mark, the last question is you well know that the CDO role emerged in these highly regulated industries and I guess in the case of pharma quasi-regulated industries but now it seems to be permeating all industries. We have Goka-lan from McDonald's and virtually every industry is at least thinking about this role or has some kind of de facto CDO, so if you were slotted in to a CDO role, let's make it generic. I know it depends on the industry but where do you start as a CDO for an organization large company that doesn't have a CDO. Even a mid-sized organization, where do you start? >> Yeah, I mean my approach is that a true CDO is maximizing the strategic value of data within the organization. It isn't a regulatory requirement. I know a lot of the banks started there 'cause they needed someone to be responsible for data quality and data privacy but for me the most critical thing is understanding the strategic objectives of the organization and how will data be used differently in the future to drive decisions and actions and the effectiveness of the business. In some cases, there was a lot of discussion around monetizing the value of data. People immediately took that to can we sell our data and make money as a different revenue stream, I'm not a proponent of that. It's internally monetizing your data. How do you triple the size of the business by using data as a strategic advantage and how do you change the executives so what is good enough today is not good enough tomorrow because they are really focused on using data as their decision making tool, and that to me is the difference that a CDO needs to make is really using data to drive those strategic decision points. >> And that nuance you mentioned I think is really important. Inderpal Bhandari, who is the Chief Data Officer of IBM often says how can you monetize the data and you're right, I don't think he means selling data, it's how does data contribute, if I could rephrase what you said, contribute to the value of the organization, that can be cutting costs, that can be driving new revenue streams, that could be saving lives if you're a hospital, improving productivity. >> Yeah, and I think what I've shared typically shared with executives when I've been in the CDO role is that they need to change their behavior, right? If a CDO comes in to an organization and a year later, the executives are still making decisions on the same data PowerPoints with spinning logos and they said ooh, we've got to have 'em. If they're still making decisions that way then the CDO has not been successful. The executives have to change what their level of expectation is in order to make a decision. >> Change agents, top down, bottom up, last question. >> Going back to GSK, now that they've completed this massive data consolidation project how are things different for that business? >> Yeah, I mean you look how Barron joined as the President of R&D about a year and a half ago and his primary focus is using data and analytics and machine learning to drive the decision making in the discovery of a new medicine and the environment that has been created is a key component to that strategic initiative and so they are actually completely changing the way they're selecting new targets for new medicines based on data and analytics. >> Mark, thanks so much for coming on theCUBE. >> Thanks for having me. >> Great keynote this morning, you're welcome. All right, keep it right there everybody. We'll be back with our next guest. This is theCUBE, Dave Vellante with Paul Gillin. Be right back from MIT. 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