>>Welcome back to the cubes, continuous coverage of HP es latest Green Lake announcement firehose of innovation. We're seeing a >>cadence >>that HP is delivering in cloud services. Daniel Newman is here, he's the principal analyst at the tour, um, extraordinary research company. Daniel great to see you how you doing man. >>Dave Great to, great to be in person again six ft and safe. But it's good to be back. >>Yeah, it really is uh, been a blur. Right? So we're gonna talk about the pivot to cloud based services. We're seeing that everybody is sort of leaning in HP es all in. I want to talk about value and what this all means to investors. We talk about data, but let me start with the whole as a service move. As I said, everybody's doing it. You see it virtually every companies. Hp was certainly the first to say we're all in, It communicated very well to Wall Street. Everybody's in a debate. No, we were first. No, we were first, but you gotta evaluate based upon the actions that they're taking. How do you look at the trends in this space and how do you look at H. P. S performance? >>Yeah, I admired and Antonio's early pivot, you know, when he got on stage and he said, We're gonna move everything to as a service. I believe that was about two years ago now and the ambition was to have it by 2022. It immediately stood out to me because the momentum, the momentum was behind public cloud, you would have believed three years ago that every workload was going to be in the public cloud and unfortunately guys like us knew that wasn't true. But what we did know was the customers, the enterprise, we're all becoming very comfortable and preference was starting to be shown with that consumption of it meaning subscription based, moving from Capex to apex. That to me was a signal that the timing was right now. Once they got the timing right, it was really about how does this all happened right? It's not necessarily just, we're gonna flip a switch and we're going to start to offer everything as a subscription as a service. There's a lot of standing up those services, putting all that compute all that network, all that storage into a data center, making sure that you have a way to accurately price it and make it quickly consumable, which is something by the way I've admired over the past couple of years, watching the evolution of the software that HP has been rolling. Whether that's Green Lake Central as moral, is that, you know, whether that's kubernetes in the orchestration of hybrid cloud using containers or that's just the ability to spin up a single compute workload in a timely fashion. That's the attraction to public cloud. So, you know, take H P E and its strategy aside and what we have now is you have all of the traditional big iron I T O E M all moving in this direction concurrently. They all understand from both evaluation standpoint meeting Wall Street and also meeting the customer where they are, they have to step up. They had to, uh, whether that was what I was doing with apex Cisco with plus iBMS acquisition of red hat. All these companies were going from, you know, public to private, private to public and then of course you gotta go horizontal from edge to cloud as well. It's a lot to undertake Dave but it's an exciting time and knowing that hybrid is the answer the data is proving that it puts a lot of these companies in a good position to compete. >>Now you mentioned that is the customer preference for good reason. Right? That gives them more flexibility but there's also Wall Street's preference, right? You see that, you know, huge valuations companies like snowflake data, dog elastic. It's that annual recurring revenue that is appealing. They want that they want growth. We saw Q3 hp that did a beaten raise I think 1100 customers for green lake, they announced the orders were up well over 40%. I think revenue was up 30 30 plus percent. So those are the kind of metrics that Wall Street wants to see interestingly though Daniel of course the shift to an A. R. R. Model hurts the income statement but it makes it more predictable and that's what investors today want, what your thoughts. >>Absolutely. I had a chance to speak multiple times over the past few years with the leadership at HP. And it was the exact thing. David that I that I raised, I said you realize that it might be a sidestep or even a half a step backwards before you start to gain momentum. And the real problem with Wall Street is there's no patients. So you mentioned a couple of names like data dog and snowflake. These companies have exponential valuations to earnings because they don't earn anything yet. But most of the market is forward looking and the market tries to anticipate where growth is going to come and saAS companies tend to drive fast growth and fast multiples. This is also left for somewhat slow growth evaluation for companies like HP. Despite the fact that it's doing a lot of the right things you mentioned of course mid double digit growth in green lake, large customer growth numbers. You know, I believe you're serving a billion dollars in revenue or in subscription dollars. Um, fact check that on their >>way to a billion on their way to be honest. I think >>it's booked maybe over >>700 million in revenue that way. >>And so as all those, the confluence of all those events, the market has to be able to basically cherry pick though a part of the business. And I think that's been a little bit of a problem. Not just for HP, but just for all these companies that are, that are struggling with smaller multiples of their P. E ratios. This is true for Cisco? This is true for IBM this is true for for HP and I'll kind of close my thought here. But as the company continues to talk about green Lake and it continues to lean into this, this is the part that has to rise to the front front of the Wall Street investor of the business media to say that existing part of the business is stable, It's solid. They have great customers. However, concurrently the part of the business that is the future, the subscription part that attaches to the public cloud that is enabling companies to grow. That is where they're at. And that is why we see more value. There's a lot of value to unlock and it's because, you know, these small multiples and the business is heading in what I believe is the right >>direction. And HPV last quarter cited, they hit almost 35% gross margin, which is, which is a high mark, high water mark for them if you extract VM ware out of Dell there in the mid twenties. So these are two different businesses and I think that's a big reason why Dell's moving into the space. I almost think like the board conversation at HP was, hey, let's, let's not keep thinking about building boxes. Let's build services and let's add value to those services that are software based and then we can kind of control our own destiny as opposed to kind of intel getting all the margins and or M. D. Or whatever it is. So so that so how do you see as a service driving value for H. P. E. It's customers and ultimately what do they have to do to convince Wall street >>recurring revenue companies drive higher multiples? It's not even a debate and companies that have a large percentage of their business as recurring tend to drive much higher evaluation and tend to also be more beloved by shareholders. The performance of HP has been good, it's been solid, it's been in the right place especially given the circumstances of the pandemic and the impact of on prem it we all saw the explosion of SAS the explosion of cloud, you know, SAS and chips are hot, they're always hot. But everything that was sort of sandwiched in the middle became a little bit more murky throughout the pandemic times. And the ability for HP. And these companies that are in this space are operating to be able to bridge this gap. The companies have 25 or so percent of workload during the public cloud. That means the rest need services from companies like HP. So the tam is growing because the overall size of the workload, the volumes of data are all growing exponentially and that's an opportunity but the market wants to see fast growth. Dave I mean they're not going to accept the single digit overall growth if you want to get the kind of multiples of a, you know, even a Microsoft at a 40 or a sales force at 100. But HPV with its software is starting to play in those spaces where investors in the market maybe can start to recognize that it is undervalued. >>So we live in a data centric world, Antonio talks about this all the time and we're seeing HP makes some moves in terms of data data management, you see what they're doing with his moral and that's a big part of the software place. So to the extent that you can lean into that wave have a higher contribution from software, higher margin business obviously and a more predictable revenue stream. That seems to be the right direction in my view. Um it's gonna take some time to play out. They're not gonna overnight, you know, they don't have a green sheet of paper, they clean sheet of paper, they have a business that they have to manage and they have to service their customers. But to the extent that the majority of their business over time can become as a service, shouldn't that confer higher margins and and greater value to investors? Yeah, it's sticky >>for enterprise users when you move to that subscription model, it's not as easy as just lifting and shifting you build your entire business process around these investments in these technologies. Software. It's sticky, it's organizationally complex because where HP sits in the stack, where their analytic solutions and software help you more successfully deploy S. A. P type workloads. The entire company runs on that. So the involvement and the importance of the role that HP is playing is huge. The challenge for customers isn't as big customers get this, the enterprise users, the C I O. S. They get the importance Wall Street though it's a little harder for them sometimes to digest. Whereas they might be looking at something like a snowflake that you mentioned. That's fairly straightforward. Almost all of its revenue is pure subscription and it's looked at as 20 years in a perpetuity where people are still trying to wonder is HP gonna be sticky? Are these customers not only going to keep with HP but are they going to increase? Right. Is that net revenue expansion going to take place across the portfolio? And HP rolls out more services right. Started with storage and then it moves to compute and then it adds edge layer services. Are people going to buy the whole stack? Because that of course, also as we've seen with some of the bigger players can be an extremely attractive value proposition. >>Well, I also think as they move into cloud, HP has always been about optionality. So I feel as though with their day to play, for example, they can get deeper into data management but they can also partner with others, you're leaning into open source so that means you can expand your portfolio that's kind of what the cloud game is is you know, here's the cloud, we got all these different options, choose what you want, we'll manage it for you, charge you for that but we'll take away that headache. That's a good business, >>choose your own cloud adventure last week oracle reported. Um and I'm only pointing this out because you know, you look at the company and everybody was what's with their i as number? Why is it not big or smaller? Why don't we know right. But over the last couple of years we've realized that it's no longer little seeing big see little C which I would call infrastructure as a service no longer exists. Cloud is one big number. So H P E being in the cloud through its hybrid services, its software, its platform support is just as much about being in the cloud is a company that offers I. S. Or company that offers SAs however convincing the market that this is the case is the trick. We're starting to see companies because you you hear when IBM reports how their numbers are, you know, they're they're tying in all kinds of global business services and they're tying in you know, red hat numbers and they're telling in their public cloud numbers but what I'm saying is up to this point, a lot of these hybrid services are kind of not necessarily being bucket ID like this big sea of cloud but it really is the entire stack of of infrastructure platform software and then of course all those attached services for companies to deploy this that equal a cloud number. And so the subscription number grows. Green Lakes customer account grows. And I think convincing the street and everybody in between that this is a cloud number and not a on prem or a attached to the cloud number is going to really help boomer boom, the overall value that people see and what HP is doing. >>And I think not only H P E but I think others are I think finally they're starting to realize that wow, you know, we all know everything is not going to public cloud. We understand it's a hybrid world Public cloud spend a company's the hyper scale is collectively spent $100 billion dollars last year on Capex. That's like a gift to a company like HP that can connect the dots and create that abstraction layer that hides the underlying complexity. We'll take care of that for you will make everything cloud native. We can bring cloud native on prem and go out to the edge, which is like the Wild West that is a that's a trillion dollar opportunity that there's no limit to market potential for companies out there and HP specifically. >>Well the edges a massive opportunity and that's what I said, you know, a lot of us are and we do this ourselves as both analysts and sometimes media personalities is we like to debate how big the opportunity of cloud is. And of course there are some firms that try to market size this, but I actually think it's extraordinarily difficult to market sizes, especially because of the edge. You talk about data and analytics. I recently attended the a event. It's a car event in Munich and you just look at the amount of data that vehicles are going to be creating in the in the coming years. They're basically massive rolling data centers full of chips, compute networking storage. This is all going to take significant infrastructure investments at scale and it's creating this humongous opportunity at the edge and you look at five Gs impact and as we roll out five G it's scale. Every one of these things brings more data connects, more devices and all that intelligence needs infrastructure, It needs software, it needs services. So the overall tam Dave is going to continue to grow and I think if anything it tends to be underestimated because it's really hard to define just how big the data equation is actually going to be in the market. >>Digital changes the equation. It's not, it's no longer servers, storage, networking database, its cloud services that are enabling digital transformations. I'll give you one more >>thing that just crossed my mind. But I think is important is if you even look at the the S. G. And sustainability efforts that most companies are going to be taking the amount of investment in trying to capture, comprehend manage just the data and analytics to understand your footprint and understand how you are going to achieve carbon neutrality and how you're going to do this up and down. And I mean that's just one thing and of course that's a, I wouldn't call it table stakes at this point, the market expects every company to be making this kind of investment well, when you run a multi national global enterprise that has edge, that has data centers that has manufacturing facilities, there is just unbelievable requirements on technology. And again, we've got to connect that public cloud somehow. So we can't ignore the fact that those public cloud players are all addressing this, they're all bringing solutions out. But companies like HP, this is where their sweet spot is, and this is where I believe they're going to have to compete very aggressively and efficiently to show we are a great partner to the public cloud, but our legacy and our capabilities mean we understand this part of the business, we believe we're the right fit and trust me, the Azure and AWS are, they're not going to make this easy, they're going to be competitive but they're also going to going to be very cooperative >>well, and they're coming into the home court of the on prem vendors. So that's gonna be interesting to see how that plays out as an observer, as an analyst, what do you want to see from HP, Green Lake cloud services? What are the, what are the areas that you're gonna be watching that could serve as indicators of success and momentum? >>Well, we didn't even talk because we did talk about some of that, but we didn't even talk about aI and amount for instance, all this data itself has to be managed and processed. So the fact that you're getting to that data management at scale, the fact that you're building out orchestration for containers. Well this is because of that data delusion conundrum, whatever word we want to use for it. But the best companies in the world are going to find a way to extract more value from that data and that's going to be through the application of aI of ml of neural networks, deep learning and other important capabilities. Having a foot into that Dave is something I want to see HP and it already does, but I want to see the participation there. This is an area that I think public cloud is doing really well there. They really made big investments both with homegrown chips with partnering with the likes of videos and intel to, to offer a lot of enhancement acceleration, um Ml and AI services. I think this is gonna be an area that on prem and through hybrid offerings. We're gonna want to see the company compete. Uh and then of course, I think back to the one thing Dave, I'll just kind of wrap on this, is that that customer growth, I mean you talked about how to get evaluation, how to get the street up, people get excited about overall growth. They need to get that narrative carved out about green, like about the subscription growth, the service growth point next and all that stuff, but all that has to start to equate to overall growth. Um you know, I think it needs to be made at least single high digits, single overall percentage growth, especially because the whole portfolio supposed to be there. You know, companies get those big multiples are growing >>fast growth on, on that large of a base would get people's attention. You mentioned custom chips, H P >>E, you >>know, H P S H P S heritage and HP. They have chops in custom silicon. So be interesting to see if, if you know the future, you talk about ai inference at the edge, huge disruptive potential opportunities and I'm really curious as to see how that plays out because that is another trillion dollar market opportunity. Daniel, thanks so much for coming to the cubes. Great to have you looking forward to working with you in the future. >>Yeah, it's great to be here. And sorry, we didn't get to those chips earlier. We could have gone down a whole, another whole, another >>half hour. Great, great to talk to you. All right, thank you for watching everybody. This is the cubes, continuous coverage of HBs, Big Green Lake announcement. Keep it right there for more, great content. Mhm.

>>AWS public sector summit here in person in Washington, D. C. For two days live. Finally a real event. I'm john for your host of the cube. Got a great guest Howard Levinson from data bricks, regional vice president and general manager of the federal team for data bricks. Uh Super unicorn. Is it a decade corn yet? It's uh, not yet public but welcome to the cube. >>I don't know what the next stage after unicorn is, but we're growing rapidly. >>Thank you. Our audience knows David bricks extremely well. Always been on the cube many times. Even back, we were covering them back when big data was big data. Now it's all data everything. So we watched your success. Congratulations. Thank you. Um, so there's no, you know, not a big bridge for us across to see you here at AWS public sector summit. Tell us what's going on inside the data bricks amazon relationship. >>Yeah. It's been a great relationship. You know, when the company got started some number of years ago we got a contract with the government to deliver the data brooks capability and they're classified cloud in amazon's classified cloud. So that was the start of a great federal relationship today. Virtually all of our businesses in AWS and we run in every single AWS environment from commercial cloud to Govcloud to secret top secret environments and we've got customers doing great things and experiencing great results from data bricks and amazon. >>The federal government's the classic, I call migration opportunity. Right? Because I mean, let's face it before the pandemic even five years ago, even 10 years ago. Glacier moving speed slow, slow and they had to get modernized with the pandemic forced really to do it. But you guys have already cleared the runway with your value problems. You've got lake house now you guys are really optimized for the cloud. >>Okay, hardcore. Yeah. We are, we only run in the cloud and we take advantage of every single go fast feature that amazon gives us. But you know john it's The Office of Management and Budget. Did a study a couple of years ago. I think there were 28,000 federal data centers, 28,000 federal data centers. Think about that for a minute and just think about like let's say in each one of those data centers you've got a handful of operational data stores of databases. The federal government is trying to take all of that data and make sense out of it. The first step to making sense out of it is bringing it all together, normalizing it. Fed aerating it and that's exactly what we do. And that's been a real win for our federal clients and it's been a real exciting opportunity to watch people succeed in that >>endeavour. We have another guest on. And she said those data center huggers tree huggers data center huggers, majority of term people won't let go. Yeah. So but they're slowly dying away and moving on to the cloud. So migrations huge. How are you guys migrating with your customers? Give us an example of how it's working. What are some of the use cases? >>So before I do that I want to tell you a quick story. I've I had the luxury of working with the Air Force Chief data officer Ailene vedrine and she is commonly quoted as saying just remember as as airmen it's not your data it's the Air Force's data. So people were data center huggers now their data huggers but all of that data belongs to the government at the end of the day. So how do we help in that? Well think about all this data sitting in all these operational data stores they're getting it's getting updated all the time. But you want to be able to Federated this data together and make some sense out of it. So for like an organization like uh us citizenship and immigration services they had I think 28 different data sources and they want to be able to pull that data basically in real time and bring it into a data lake. Well that means doing a change data capture off of those operational data stores transforming that data and normalizing it so that you can then enjoy it. And we've done that I think they're now up to 70 data sources that are continually ingested into their data lake. And from there they support thousands of users doing analysis and reports for the whole visa processing system for the United States, the whole naturalization environment And their efficiency has gone up I think by their metrics by 24 x. >>Yeah. I mean Sandy carter was just on the cube earlier. She's the Vice president partner ecosystem here at public sector. And I was coming to her that federal game has changed, it used to be hard to get into you know everybody and you navigate the trip wires and all the subtle hints and and the people who are friends and it was like cloak and dagger and so people were locked in on certain things databases and data because now has to be freely available. I know one of the things that you guys are passionate about and this is kind of hard core architectural thing is that you need horizontally scalable data to really make a I work right. Machine learning works when you have data. How far along are these guys in their thinking when you have a customer because we're seeing progress? How far along are we? >>Yeah, we still have a long way to go in the federal government. I mean, I tell everybody, I think the federal government's probably four or five years behind what data bricks top uh clients are doing. But there are clearly people in the federal government that have really ramped it up and are on a par were even exceeding some of the commercial clients, U. S. C. I. S CBP FBI or some of the clients that we work with that are pretty far ahead and I'll say I mentioned a lot about the operational data stores but there's all kinds of data that's coming in at U S. C. I. S. They do these naturalization interviews, those are captured in real text. So now you want to do natural language processing against them, make sure these interviews are of the highest quality control, We want to be able to predict which people are going to show up for interviews based on their geospatial location and the day of the week and other factors the weather perhaps. So they're using all of these data types uh imagery text and structure data all in the Lake House concept to make predictions about how they should run their >>business. So that's a really good point. I was talking with keith brooks earlier directive is development, go to market strategy for AWS public sector. He's been there from the beginning this the 10th year of Govcloud. Right, so we're kind of riffing but the jpl Nasa Jpl, they did production workloads out of the gate. Yeah. Full mission. So now fast forward today. Cloud Native really is available. So like how do you see the the agencies in the government handling Okay. Re platform and I get that but now to do the reef acting where you guys have the Lake House new things can happen with cloud Native technologies, what's the what's the what's the cross over point for that point. >>Yeah, I think our Lake House architecture is really a big breakthrough architecture. It used to be, people would take all of this data, they put it in a Hadoop data lake, they'd end up with a data swamp with really not good control or good data quality. And uh then they would take the data from the data swamp where the data lake and they curate it and go through an E. T. L. Process and put a second copy into their data warehouse. So now you have two copies of the data to governance models. Maybe two versions of the data. A lot to manage. A lot to control with our Lake House architecture. You can put all of that data in the data lake it with our delta format. It comes in a curated way. Uh there's a catalogue associated with the data. So you know what you've got. And now you can literally build an ephemeral data warehouse directly on top of that data and it exists only for the period of time that uh people need it. And so it's cloud Native. It's elastically scalable. It terminates when nobody's using it. We run the whole center for Medicaid Medicare services. The whole Medicaid repository for the United States runs in an ephemeral data warehouse built on Amazon S three. >>You know, that is a huge call out, I want to just unpack that for a second. What you just said to me puts the exclamation point on cloud value because it's not your grandfather's data warehouse, it's like okay we do data warehouse capability but we're using higher level cloud services, whether it's governance stuff for a I to actually make it work at scale for those environments. I mean that that to me is re factoring that's not re platform Ng. Just re platform that's re platform Ng in the cloud and then re factoring capability for on uh new >>advantages. It's really true. And now you know at CMS, they have one copy of the data so they do all of their reporting, they've got a lot of congressional reports that they need to do. But now they're leveraging that same data, not making a copy of it for uh the center for program integrity for fraud. And we know how many billions of dollars worth of fraud exist in the Medicaid system. And now we're applying artificial intelligence and machine learning on entity analytics to really get to the root of those problems. It's a game >>changer. And this is where the efficiency comes in at scale. Because you start to see, I mean we always talk on the cube about like how software is changed the old days you put on the shelf shelf where they called it. Uh that's our generation. And now you got the cloud, you didn't know if something is hot or not until the inventory is like we didn't sell through in the cloud. If you're not performing, you suck basically. So it's not working, >>it's an instant Mhm. >>Report card. So now when you go to the cloud, you think the data lake and uh the lake house what you guys do uh and others like snowflake and were optimized in the cloud, you can't deny it. And then when you compare it to like, okay, so I'm saving you millions and millions if you're just on one thing, never mind the top line opportunities. >>So so john you know, years ago people didn't believe the cloud was going to be what it is. Like pretty much today, the clouds inevitable. It's everywhere. I'm gonna make you another prediction. Um And you can say you heard it here first, the data warehouse is going away. The Lake house is clearly going to replace it. There's no need anymore for two separate copies, there's no need for a proprietary uh storage copy of your data and people want to be able to apply more than sequel to the data. Uh Data warehouses, just restrict. What about an ocean house? >>Yeah. Lake is kind of small. When you think about this lake, Michigan is pretty big now, I think it's I >>think it's going to go bigger than that. I think we're talking about Sky Computer, we've been a cloud computing, we're going to uh and we're going to do that because people aren't gonna put all of their data in one place, they're going to have, it spread across different amazon regions or or or amazon availability zones and you're going to want to share data and you know, we just introduced this delta sharing capability. I don't know if you're familiar with it but it allows you to share data without a sharing server directly from picking up basically the amazon, you RLS and sharing them with different organizations. So you're sharing in place. The data actually isn't moving. You've got great governance and great granularity of the data that you choose to share and data sharing is going to be the next uh >>next break. You know, I really loved the Lake House were fairly sing gateway. I totally see that. So I totally would align with that and say I bet with you on that one. The Sky net Skynet, the Sky computing. >>See you're taking it away man, >>I know Skynet got anything that was computing in the Sky is Skynet that's terminated So but that's real. I mean I think that's a concept where it's like, you know what services and functions does for servers, you don't have a data, >>you've got to be able to connect data, nobody lives in an island. You've got to be able to connect data and more data. We all know more data produces better results. So how do you get more data? You connect to more data sources, >>Howard great to have you on talk about the relationship real quick as we end up here with amazon, What are you guys doing together? How's the partnership? >>Yeah, I mean the partnership with amazon is amazing. We have, we work uh, I think probably 95% of our federal business is running in amazon's cloud today. As I mentioned, john we run across uh, AWS commercial AWS GovCloud secret environment. See to us and you know, we have better integration with amazon services than I'll say some of the amazon services if people want to integrate with glue or kinesis or Sagemaker, a red shift, we have complete integration with all of those and that's really, it's not just a partnership at the sales level. It's a partnership and integration at the engineering level. >>Well, I think I'm really impressed with you guys as a company. I think you're an example of the kind of business model that people might have been afraid of which is being in the cloud, you can have a moat, you have competitive advantage, you can build intellectual property >>and, and john don't forget, it's all based on open source, open data, like almost everything that we've done. We've made available to people, we get 30 million downloads of the data bricks technology just for people that want to use it for free. So no vendor lock in. I think that's really important to most of our federal clients into everybody. >>I've always said competitive advantage scale and choice. Right. That's a data bricks. Howard? Thanks for coming on the key, appreciate it. Thanks again. Alright. Cube coverage here in Washington from face to face physical event were on the ground. Of course, we're also streaming a digital for the hybrid event. This is the cubes coverage of a W. S. Public sector Summit will be right back after this short break.

>>Yeah. Hello and welcome back to the cubes coverage of AWS public sector summit here in Washington D. C. We're live on the ground for two days. Face to face conference and expo hall and everything here but keith brooks who is the director and head of technical business development for a dress government Govcloud selling brains 10th birthday. Congratulations. Welcome to the cube. Thank you john happy to be E. C. 2 15 S three is 9.5 or no, that maybe they're 10 because that's the same day as sqs So Govcloud. 10 years, 20 years. What time >>flies? 10 years? >>Big milestone. Congratulations. A lot of history involved in Govcloud. Yes. Take us through what's the current situation? >>Yeah. So um let's start with what it is just for the viewers that may not be familiar. So AWS Govcloud is isolated. AWS cloud infrastructure and services that were purposely built for our U. S. Government customers that had highly sensitive data or highly regulated data or applications and workloads that they wanted to move to the cloud. So we gave customers the ability to do that with AWS Govcloud. It is subject to the fed ramp I and D O D S R G I L four L five baselines. It gives customers the ability to address ITAR requirements as well as Seaga's N'est ce MMC and Phipps requirements and gives customers a multi region architecture that allows them to also designed for disaster recovery and high availability in terms of why we built it. It starts with our customers. It was pretty clear from the government that they needed a highly secure and highly compliant cloud infrastructure to innovate ahead of demand and that's what we delivered. So back in august of 2011 we launched AWS GovCloud which gave customers the best of breed in terms of high technology, high security, high compliance in the cloud to allow them to innovate for their mission critical workloads. Who >>was some of the early customers when you guys launched after the C. I. A deal intelligence community is a big one but some of the early customers. >>So the Department of Health and Human Services, the Department of Veterans Affairs, the Department of Justice and the Department of Defense were all early users of AWS GovCloud. But one of our earliest lighthouse customers was the Nasa jet propulsion laboratory and Nasa Jpl used AWS GovCloud to procure Procure resources ahead of demand which allowed them to save money and also take advantage of being efficient and only paying for what they needed. But they went beyond just I. T. Operations. They also looked at how do they use the cloud and specifically GovCloud for their mission programs. So if you think back to all the way to 2012 with the mars curiosity rover, Nasa Jpl actually streamed and processed and stored that data from the curiosity rover on AWS Govcloud They actually streamed over 150 terabytes of data responded to over 80,000 requests per second and took it beyond just imagery. They actually did high performance compute and data analytics on the data as well. That led to additional efficiencies for future. Over there >>were entire kicking they were actually >>hard core missing into it. Mission critical workloads that also adhere to itar compliance which is why they used AWS GovCloud. >>All these compliance. So there's also these levels. I remember when I was working on the jetty uh stories that were out there was always like level for those different classifications. What does all that mean like? And then this highly available data and highly high availability all these words mean something in these top secret clouds. Can you take us through kind of meetings >>of those? Yeah absolutely. So it starts with the federal compliance program and the two most popular programs are Fed ramp and Dodi srg fed ramp is more general for federal government agencies. There are three levels low moderate and high in the short and skinny of those levels is how they align to the fisma requirements of the government. So there's fisma low fisma moderate fisma high depending on the sensitivity of the government data you will have to align to those levels of Fed ramp to use workloads and store data in the cloud. Similar story for D. O. D. With srg impact levels to 45 and six uh impacts levels to four and five are all for unclassified data. Level two is for less sensitive public defense data levels. Four and five cover more sensitive defense data to include mission critical national security systems and impact level six is for classified information. So those form the basis of security and compliance, luckily with AWS GovCloud celebrating our 10th anniversary, we address Fed ramp high for our customers that require that and D. O. D impact levels to four and five for a sensitive defense guy. >>And that was a real nuanced point and a lot of the competition can't do that. That's real people don't understand, you know, this company, which is that company and all the lobbying and all the mudslinging that goes on. We've seen that in the industry. It's unfortunate, but it happens. Um, I do want to ask you about the Fed ramp because what I'm seeing on the commercial side in the cloud ecosystem, a lot of companies that aren't quote targeting public sector are coming in on the Fed ramp. So there's some good traction there. You guys have done a lot of work to accelerate that. Any new, any new information to share their. >>Yes. So we've been committed to supporting the federal government compliance requirements effectively since the launch of GovCloud. And we've demonstrated our commitment to Fed ramp over the last number of years and GovCloud specifically, we've taken dozens of services through Fed ramp high and we're 100% committed to it because we have great relationships with the Fed ramp, Jabor the joint authorization board. We work with individual government agencies to secure agency A. T. O. S. And in fact we actually have more agency A. T. O. S. With AWS GovCloud than any other cloud provider. And the short and skinny is that represents the baseline for cloud security to address sensitive government workloads and sensitive government data. And what we're seeing from industry and specifically highly regulated industries is the standard that the U. S. Government set means that they have the assurance to run control and classified information or other levels of highly sensitive data on the cloud as well. So Fed ramp set that standard. It's interesting >>that the cloud, this is the ecosystem within an ecosystem again within crossover section. So for instance um the impact of not getting Fed ramp certified is basically money. Right. If you're a supplier vendor uh software developer or whatever used to being a miracle, no one no one would know right bed ramp. I'm gonna have to hire a whole department right now. You guys have a really easy, this is a key value proposition, isn't it? >>Correct. And you see it with a number of I. S. V. S. And software as the service providers. If you visit the federal marketplace website, you'll see dozens of providers that have Fed ramp authorized third party SAAS products running on GovCloud industry leading SAAS companies like Salesforce dot com driven technology Splunk essay PNS to effectively they're bringing their best of breed capabilities, building on top of AWS GovCloud and offering those highly compliant fed ramp, moderate fed ramp high capabilities to customers both in government and private industry that need that level of compliance. >>Just as an aside, I saw they've got a nice tweet from Teresa Carlson now it's plunk Govcloud yesterday. That was a nice little positive gesture uh, for you guys at GovCloud, what other areas are you guys moving the needle on because architecturally this is a big deal. What are some areas that you're moving the needle on for the GovCloud? >>Well, when I look back across the last 10 years, there were some pretty important developments that stand out. The first is us launching the second Govcloud infrastructure region in 2018 And that gave customers that use GovCloud specifically customers that have highly sensitive data and high levels of compliance. The ability to build fault tolerant, highly available and mission critical workloads in the cloud in a region that also gives them an additional three availability zones. So the launch of GovCloud East, which is named AWS GovCloud Us East gave customers to regions a total of six availability zones that allowed them accelerate and build more scalable solutions in the cloud. More recently, there is an emergence of another D O D program called the cybersecurity maturity model, C M M C and C M M C is something where we looked around the corner and said we need to Innovate to help our customers, particularly defense customers and the defense industrial based customers address see MMC requirements in the cloud. So with Govcloud back in December of 2020, we actually launched the AWS compliant framework for federal defense workloads, which gives customers a turnkey capability and tooling and resources to spin up environments that are configured to meet see MMC controls and D. O. D. Srg control. So those things represent some of the >>evolution keith. I'm interested also in your thoughts on how you see the progression of Govcloud outside the United States. Tactical Edge get wavelength coming on board. How does how do you guys look at that? Obviously us is global, it's not just the jet, I think it's more of in general. Edge deployments, sovereignty is also going to be world's flat, Right? I mean, so how does that >>work? So it starts back with customer requirements and I tie it back to the first question effectively we built Govcloud to respond to our U. S. Government customers and are highly regulated industry customers that had highly sensitive data and a high bar to meet in terms of regulatory compliance and that's the foundation of it. So as we look to other customers to include those outside of the US. It starts with those requirements. You mentioned things like edge and hybrid and a good example of how we marry the two is when we launched a W. S. Outpost in Govcloud last year. So outpost brings the power of the AWS cloud to on premises environments of our customers, whether it's their data centers or Coehlo environments by bringing AWS services, a. P. I. S and service and points to the customer's on premises facilities >>even outside the United States. >>Well, for Govcloud is focused on us right now. Outside of the U. S. Customers also have availability to use outpost. It's just for us customers, it's focused on outpost availability, geography >>right now us. Right. But other governments gonna want their Govcloud too. Right, Right, that's what you're getting at, >>Right? And it starts with the data. Right? So we we we spent a lot of time working with government agencies across the globe to understand their regulations and their requirements and we use that to drive our decisions. And again, just like we started with govcloud 10 years ago, it starts with our customer requirements and we innovate from there. Well, >>I've been, I love the D. O. D. S vision on this. I know jet I didn't come through and kind of went scuttled, got thrown under the bus or whatever however you want to call it. But that whole idea of a tactical edge, it was pretty brilliant idea. Um so I'm looking forward to seeing more of that. That's where I was supposed to come in, get snowball, snowmobile, little snow snow products as well, how are they doing? And because they're all part of the family to, >>they are and they're available in Govcloud and they're also authorized that fed ramp and Gov srg levels and it's really, it's really fascinating to see D. O. D innovate with the cloud. Right. So you mentioned tactical edge. So whether it's snowball devices or using outposts in the future, I think the D. O. D. And our defense customers are going to continue to innovate. And quite frankly for us, it represents our commitment to the space we want to make sure our defense customers and the defense industrial base defense contractors have access to the best debris capabilities like those edge devices and edge capable. I >>think about the impact of certification, which is good because I just thought of a clean crows. We've got aerospace coming in now you've got D O. D, a little bit of a cross colonization if you will. So nice to have that flexibility. I got to ask you about just how you view just in general, the intelligence community a lot of uptake since the CIA deal with amazon Just overall good health for eight of his gum cloud. >>Absolutely. And again, it starts with our commitment to our customers. We want to make sure that our national security customers are defense customers and all of the customers and the federal government that have a responsibility for securing the country have access to the best of breed capability. So whether it's the intelligence community, the Department of Defense are the federal agencies and quite frankly we see them innovating and driving things forward to include with their sensitive workloads that run in Govcloud, >>what's your strategy for partnerships as you work on the ecosystem? You do a lot with strategy. Go to market partnerships. Um, it's got its public sector pretty much people all know each other. Our new firms popping up new brands. What's the, what's the ecosystem looks like? >>Yeah, it's pretty diverse. So for Govcloud specifically, if you look at partners in the defense community, we work with aerospace companies like Lockheed martin and Raytheon Technologies to help them build I tar compliant E. R. P. Application, software development environments etcetera. We work with software companies I mentioned salesforce dot com. Splunk and S. A. P. And S. To uh and then even at the state and local government level, there's a company called Pay It that actually worked with the state of Kansas to develop the Icann app, which is pretty fascinating. It's a app that is the official app of the state of Kansas that allow citizens to interact with citizens services. That's all through a partner. So we continue to work with our partner uh broad the AWS partner network to bring those type of people >>You got a lot of MST is that are doing good work here. I saw someone out here uh 10 years. Congratulations. What's the coolest thing uh you've done or seen. >>Oh wow, it's hard to name anything in particular. I just think for us it's just seeing the customers and the federal government innovate right? And, and tie that innovation to mission critical workloads that are highly important. Again, it reflects our commitment to give these government customers and the government contractors the best of breed capabilities and some of the innovation we just see coming from the federal government leveraging the count now. It's just super cool. So hard to pinpoint one specific thing. But I love the innovation and it's hard to pick a favorite >>Child that we always say. It's kind of a trick question I do have to ask you about just in general, the just in 10 years. Just look at the agility. Yeah, I mean if you told me 10 years ago the government would be moving at any, any agile anything. They were a glacier in terms of change, right? Procure Man, you name it. It's just like, it's a racket. It's a racket. So, so, but they weren't, they were slow and money now. Pandemic hits this year. Last year, everything's up for grabs. The script has been flipped >>exactly. And you know what, what's interesting is there were actually a few federal government agencies that really paved the way for what you're seeing today. I'll give you some examples. So the Department of Veterans Affairs, they were an early Govcloud user and way back in 2015 they launched vets dot gov on gov cloud, which is an online platform that gave veterans the ability to apply for manage and track their benefits. Those type of initiatives paved the way for what you're seeing today, even as soon as last year with the U. S. Census, right? They brought the decennial count online for the first time in history last year, during 2020 during the pandemic and the Census Bureau was able to use Govcloud to launch and run 2020 census dot gov in the cloud at scale to secure that data. So those are examples of federal agencies that really kind of paved the way and leading to what you're saying is it's kind >>of an awakening. It is and I think one of the things that no one's reporting is kind of a cultural revolution is the talent underneath that way, the younger people like finally like and so it's cooler. It is when you go fast and you can make things change, skeptics turned into naysayers turned into like out of a job or they don't transform so like that whole blocker mentality gets exposed just like shelf where software you don't know what it does until the cloud is not performing, its not good. Right, right. >>Right. Into that point. That's why we spend a lot of time focused on education programs and up skilling the workforce to, because we want to ensure that as our customers mature and as they innovate, we're providing the right training and resources to help them along their journey, >>keith brooks great conversation, great insight and historian to taking us to the early days of Govcloud. Thanks for coming on the cube. Thanks thanks for having me cubes coverage here and address public sector summit. We'll be back with more coverage after this short break. Mhm. Mhm mm.

>>Mhm >>Welcome to this preview of couch based connect online 2021. My name is Dave Volonte with the cube and we're here with couch based ceo matt cain matt. Good to see you again. Welcome >>Thanks Dave. Great to be here. >>We are super excited at the Cube to partner with Couch Base this year to share the news, the analysis from connect online 21. What can attendees expect from the event this year? What's the theme? What can people really take away? >>They were fired up, you know, there is no different. Our theme this year is modernized now and it's something that we're hearing from our customers across the world is they think about leveraging technology to get closer to their customers and at the top of every one of their strategic agendas is figuring out how to build the best applications to service our needs as our personal lives and in our business lives and we're really focused on talking about the technology that we uniquely architected to enable this that stands aspects of relational database technology and new capabilities, leveraging those people technology, putting that into an integrated platform and really supporting customers. And we love talking about what we built Dave but we love even more when our customers share what they've been doing with our platform, customers like Pepsi and Amadeus and American greetings, you're going to hear them and their development meant teams talk about how they have leverage couch base to solve some of the most fundamental application challenges and how that's really opening up new businesses for them in their end markets. >>Let's talk a little bit more mad about that, the modernized now. I mean the trends that we're seeing in in the market place, they were in motion before the pandemic. But digital digitization and modernization has really become a high priority. Talk about why in your view now is the time to modernize and what's the mandate for enterprises? >>Well look, I think digital transformation has been a focus point for some time and I think that's going to continue as we go forward. But I think as enterprise think about the challenges they have in front of them to successfully transform digitally, they may be thinking about the problem a little bit differently in light of current circumstances. Uh and what we're seeing is enterprises have the desire to innovate, but they may not always have the resources or the capabilities to do it at the place they want to. And so how do they approach this challenge first and foremost, they need a platform that can help bridge the legacy world and the new one that they can safely evolve applications and modernize, you know, workloads that were dependent on relational databases while putting them into new platforms. At the same time, they need people to do this work. So if I'm an democrats, almost an insatiable demand to build new applications, but I don't necessarily have all the people and teams and capability and skill sets needed to support that. So as a technology company, we've got to think through how do we help provide the tools that will open up more people's ability to contribute to that digital transformation leveraging things like sequel is the fact of language in the database technology allowing enterprises to repurpose workforces free up investment dollars, free up people to really focus on the next generation of properties that are going to change their businesses. And so I think the current economic conditions haven't changed the fact that digital transformation is the top of the priority list. If anything, that reinforced the urge with which enterprises need to go after this, but also the way that they need to do it. But I can't just continue to throw niche technologies of problems. I've really got to think about what kind of platforms tonight and then in the future and a couch base as the modern database for enterprise applications. This is what we're going to spend time talking about and helping customers understand the value that we can unlock for them as they invest in the couch based platform. >>Super relevant now since we last talked matt, he made some big moves, not the least of which is you're now a public company. We've been following that. But what's changed what's new product wise and maybe one of the fundamentals of the market that that your your customers and your culture or driving. >>Yeah, well let's talk about first, what's not changed? We continue to be long term oriented couch basically believe we're in truly what we call a generational market transition and the challenges in front of enterprises unparalleled. So too are the opportunities for enterprises that get this right? They will innovate and thriving in their respective markets. And so as a company, we pride ourselves in being maniacally focused at solving unmet, underserved needs in the world of databases. And really thinking through what technological challenges do we need to innovate on store, customers can take that technology and successful. That's not, that hasn't changed that, that won't change. We continue to be insanely customer focused and really studying those problems and making sure that we're adding value in everything we do from a product perspective services, how we show up to help our customers and that's really important. Um certainly as you said, it's a big milestone for the company step in the public market. We're very proud of what we've accomplished over our first decade or so of existence. But we truly believe that we've been built for this moment and that market transition that ever have referred to um that that movement into the public markets allows us to talk more broadly about all that we've built and how customers are taking advantage of our technology case in point is probably the biggest release in company history couch based server seven oh, so while we were busy taking a step into the public market, we also continue to innovate as I said and are very pleased to be a market with couch base 70 which fundamentally bridges for enterprise customers to move from relational to modern databases and do that in a single integrated platform. And we're going to talk about that connect in more detail and how application developers can re platform applications in a much more seamless way and then start to innovate in a way, you know, that they never have. So a ton of work underway. We've got some really exciting announcements which I think we'll talk about here in the second at least plant the seeds on those. But we're going to be really focused on the innovation that we've delivered up to this point because it's so fundamentally valuable to the enterprise customers we serve and couldn't be more excited to share the benefits of that. That's actually what we're going to help customers do as we go forward. >>Well, we see a lot of companies and as as we evaluated, you've hit critical mass in terms of how we think about it successful I. P. O. Your surpassed $100 million in revenue 500 plus customers talk about the opportunity for couch based to continue to grow. What's in store. What's the focus? >>Well, as I mentioned, we're going to we're going to continue to innovate and so you know, ahead of the conference. We're going to talk about some really important upcoming innovations and I'm not gonna steal too much of the thunder from the show, people are really pumped and putting that material together? We we focus a lot on ensuring that we have the best database in the market, particularly for enterprise applications. Uh and really thinking through the architecture that will support applications today and going forward and we've been really successful with that date. As you mentioned, we have not only a lot of enterprise customers and we're really proud of those customers would support what were even more proud of though. Dave is the mission critical nature the enterprise nature of those applications. These companies are truly running their businesses on applications powered by pouches as we go forward. We have almost unlimited potential for new opportunity in acquiring new customers. Um and we're really focused on that and evangelizing what we've done successfully with our existing base to new customers and their respective markets and we continue to acquire those and you know will successfully expand because of the power of our platform. We've done a lot to invest in our partner ecosystem. So you know we have many I. S. V. S. That are taking our solutions to market. We have G. S. I. S. That are building practices around couch base because our database provides capabilities that others don't and they can run their businesses and help their end customers transform with the power of couch face. But Dave what we like to talk about a couch bases, we have opportunities to really help customers once we get in. We think about many factors of growth. So when we support a customer with an application, what often happens is that application growth because the enterprises successful and they put more users in or they deployed a new new geography at the same time, they realize, wow, if I can support highly interactive, highly scalable distributed applications in this particular area, I have hundreds, if not thousands of those in my enterprise, so I can use the platform for that. Then one of the things that we focus on is giving more and more capabilities to developers to enhance the performance and the personalization of their applications I mentioned, we support the sequel query language, we've got operational analytics, we've embedded full text search, we have things like eventing all of these are elegantly architected features that allow developers to build great applications and the more that were successful in helping developers do that, you know, the more, the more the company is going to grow. Um and then on top of all that we couldn't be more excited about about cloud and couch based cloud from the very outset has been a cloud, native platform, are enterprises are running this and multi and hybrid cloud deployments, but what we really have an opportunity to do is help them and run more of the service of, of that cloud solution and we're gonna be talking a lot more uh you know, come come the show about some specifics around that offering and could be more excited about augmenting or portfolio with some new capabilities there >>lot to learn at this event. Tons of meat on the bone. Okay. Matt, we're gonna leave it right there. Couch based, connect online. It's a two day event, october 20th to the 21st. More than 80 sessions geared for architects, developers, business users, open source advocates. Now the easiest way to register, all you gotta do is go to couch base dot com. You'll see the link there. There's a hackathon with prizes. So start developing and win. And while you're there, check out the free downloads with a number of different deployment options. Couch based, connect 2021 modernized. Now we'll see you there. >>Mhm mm.

>>from the cube studios in Palo alto in boston connecting with thought leaders all around the world. This is a cute conversation. >>Welcome to the cubes coverage of HP discoverer 2021. I'm lisa martin Janice Zenga's joins me next. The vice president of innovation for social impact in H. P. S. Office of the C T. O Janice. Welcome to the cube. Hi lisa. Great to be here. So let's talk about this. You lead H. P. S. Tech for good program. I always love talking about programs like this. Talk to me about that industry tech academia government partnering to solve key challenges that society is facing and crack that for us. Yeah. So so >>we we um are really proud to be able to look at big challenges in the world and look where our strengths, where our innovations are emerging technologies and our employee expertise could actually contribute to a problem. And so >>we began >>a program uh to actually pick some projects particularly in food systems, world hunger and Health Systems, where we thought some of our technologies could really be impactful. And so >>we have been working with a number of >>clients and partners to actually uh work on ai contributions, high performance compute contributions um and uh and a contribution around this notion of data spaces that we're talking about all of these emerged through um complex interactions around social, good engagement. >>So the concept you mentioned, data space is the concept of data spaces isn't new but do explain that. Give us an overview Janice for those folks that might not be familiar with what it is. >>So so the notion of data spaces is to connect data producers to data consumers. And so um in the past um you know connecting producers and consumers has really been limited about, you know, where is your data located? Um Do you have access to the right data? Um Is the data a good quality set of data? What's the providence of that data? What's the quality of it? And is it trustworthy? And so um >>our >>concept of data spaces is actually trying to address all of those um notions with with a new approach >>so collecting ensuring data isn't anything new. But of course what we talk about every day on this program is the volume of data in that context. What are some of the challenges that you're seeing with clients and how can you help them eliminate those challenges and be able to make data driven decisions? >>So um the first challenge is finding the data. And uh there is a big challenge. I mean there's new roles emerging called data hunters and a great amount of time being spent by data scientists just trying to find sources of data. And that's a big challenge. And then when you find this data, is it in the right format and how expensive is it to move the data so that you could have it in a place where it can actually be analyzed. So, um, so what we're working on recognizing that there is a vast amount of data at the edge, a vast amount of data that's probably never going to move from the edge and from those locations. Um but what we're trying to do is recognize that and actually work to bring the algorithms and the analytics to the data and to work with making sure that data is accessible >>and can be >>understood and >>and processed uh in a consistent way. And >>today there is um a lot >>of silos in in place around uh where data >>exists. And uh and so our approach here is to kind of address is from an open source community perspective to build uh and and provide >>a metadata layer, >>standard of all standards. Kind of a super metadata layer for a non technical way to represent that. And and then to use that to help um connect to uh analytics platforms, both citizen users. Um, you know, subject matter experts who may not be data scientists as well as the data scientists. So actually being able to connect a broader set of users into data analytics that are currently available and have the knowledge to be able to get information and insights out of that data. >>So democratizing that access to data. One of the things I'm curious about what you've seen is that's a cultural shift. You talked about some of the new rules. Data hunters and people get very sort of territorial about that. How I'm just curious what are some of the things that you've seen that where HP and data spaces have been able to help companies to be able to democratize that access and also kind of transform their culture >>Well. So um a few >>things. First of all, there has >>to be a strong motivation >>for someone to share data and in order for them to feel safe and sharing that data. Um you know there has to be security and trust established and most data producers want to control who gets to see their data and under what conditions there needs to be governance of data as well. So those are important aspects that have to be in place. Our approach is to kind of build in exchange for that so that um data consumers understand the conditions in which they can access and use the data um And and also potentially contribute back the new datasets that they're creating through their analytics back into a catalogue being a provisioning of data. This improving kind of the standardization and the simplicity Of how data gets exchanged today. In effect allows a greater democratization of access of data so so that you don't have to be a data scientist. I mean data scientist today can spend 7-8 months actually getting their data that they're going to use um into a format that they can they can actually process. And we think that that's inefficient. We think there's a lot that can be done. Um The other challenge around this is that oftentimes data is multi entity. Even inside of a company, you can find data, you >>know, in different departments and different >>businesses. Um >>But even when you think beyond a >>company, if you think about entities that are that are, you know globally >>distributed um >>and maybe multi, you know, multi entity, there are new challenges about how data can come together from those sources and still be of the right providence and be understood to be trustworthy. >>Well, one of the things that I think one of the many things I think we've learned during the last year is that the, the need and access for real time data has been a critical factor in helping businesses pivot and survive versus those that that might not. So what are you seeing in terms of like you said, data scientist spending so much time getting access to clean data, the opportunities to miss, you know, opportunities for new products and services and to and to meet customer demand in new ways to talk to me about how data spaces can facilitate that faster real time access. >>Right? So, so by having an exchange that can be implemented inside of an enterprise or across enterprises, we actually think it allows some of that kind of pre work to be done, allows that cataloging and provisions. So you can come to uh come to a place, it's a place where an exchange can occur and actually be able to, you know, um get more ready >>access to the data. You don't have to >>necessarily go through a cleansing process and through a deep investigation on providence and then, you know, oftentimes uh you learn as you process data about new data or the data sets change. Right? So, so can there be improvements around keeping those ml algorithms current and helping you that in a very efficient way without having to rerun and rewrite code and rerun your algorithms um every single time. So we think there's a lot of improvement that can be done there as well. >>So let's look at, did a great job of explaining data space is the opportunity, the challenges that we've seen the opportunities. But let us help the audience understand what makes what HPV is doing with data spaces different, unique. What are some of the differentiators? There? >>A few things. One is we're approaching this from an open source approach, so we expect to be able to contribute back to the open source communities and allow for a greater ecosystem to develop around these solutions and that will enable greater sharing and trustworthy sharing. The second thing is security, we intend to apply a great security layer into this that allows data to be trusted um and then the governance capabilities, so being able to use things like our data fabric to actually help support um the governance that producers and consumers want to have uh is also important. And then finally being able to work multi cloud across um, on prem and in the cloud >>is a great >>advantage. So you don't get vendor lock in, you'll be able to be able to kind of minimize your data egress because >>maybe you're not gonna be doing data egress out of the cloud >>and instead you'll be you'll be able to process your data right where it's at without having to pay for that movement. >>And I imagine that would facilitate that speed of real time that I mentioned a minute ago. >>That's right, That's right. >>So let's now look at HP data spaces compared to data marketplace. Give me the compare and contrast with respect to those two. So, data >>marketplaces are typically very siloed and very specific to a sector or an industry today, um, and they're they're typically built on their own platforms and to end, they're not always open by design. Um so uh we expect to be able to support multiple data data marketplaces through a plug in into the data spaces um platform that that we build and that will allow greater connectivity and greater access to many different marketplaces. Um and so the data spaces is not intended to be siloed by industry or narrowly kind of focused, >>so helping to remove those silos, which we also, another thing that we talk about, what are some, I'm just curious some of the feedback from the open source community about what you're doing here building on this open foundation. >>So it's um it's actually been very positive. So the very first thing we did was because of our work as I start at the top of the conversation in agriculture, which is a great, a great example of where there's immense amounts of data that is not well standardized, are structured in a way that can be used towards addressing things like world hunger and some of the food supply and food system challenges. We have we uh in working through this >>kind of distilled some >>of the problems that to being this lack of access to data. And so one of the reasons we explored was like why is there this lack of use of data and lack of access to data? And it came down to not being able to access the data where it's generated and not being able to actually share it broadly across entities. And so, um so what we did is we joined the Linux Foundation has a new open source community called Ag stack and we are a founding company uh as part of that new community and we have shared the concepts around data spaces and the metadata layer standardisation that we've envisioned uh into the community and that's just getting kicked off. But it's also a great first step for us um to kind of build an open source community around it. >>Excellent. Sounds like you said positive feedback. If we crack open the hood of data spaces, what are some of the technologies that we see underneath that are making it and its evolution possible? >>Right? So um multi cloud uh across uh data, you know, support um edge processing um data fabric um Israel's solution as well, so being able to kind of move data and then of course, kind of a key layer. This is this notion of a metadata layer, standard on top >>of metadata layer standards. >>And what is that going to allow in terms of connecting the data consumers with the data producers? >>It's going to make it easier, it's going to make it faster, it's going to minimize costs. Uh it's gonna allow for a quality exchange with more information for consumers to have that trust and most importantly the security. Um and it will also create kind of motivation, kind of give and take because exchange has to be equitable for producers and consumers to both be at the >>table. That's a great point about about the being equitable. So this whole initiative that we've been talking about is coming out of the Office of the CTO at HP where we talked about. So the focus is on Uh projects that are emerging not yet on the road map. So what can we expect, what can your audience expect in the next 12-18 months? >>So our approach in the Office of the CTO is to take emerging technologies and ideas and actually bring them into kind of what we would call advanced development stages. So we do proof of concepts, we do a lot of piloting, we worked with customers and clients directly to kind of tune and test commercialization possibilities uh and value of a solution that we're evolving and to kind of get it ready for market if it makes sense to do that. And so We have proof of concepts with the dozens of customers right now in this topic area and more that want to join in and get involved in having access to it as well. Um so I would say most of the work we do in the coming 12 months will be driven by what these proof of concepts with these clients actually uncovered for us. Um and so we know first and foremost we're working with, you know, a large financial services company, we're looking we're working on the agricultural front with a number of important customers that are testing kind of a multi entity data sharing aspects. Were working also with the health care industry client, which is looking at extreme sets of large data that are kind of unanticipated datasets, you would normally think that would be important for disease prediction. And so all of those different kind of use cases are helping us kind of think about um, you know, which features are most important and by when I can tell you the security, the trustworthiness, the data provenance, the data governance are essential elements that are going to have to be there. >>I think those are essential elements that in any industry, especially that security front. >>Yes, very much so. >>So. In terms of the event at hp, what are some of the things that the audience is going to be able to to learn and glean about? Data sources, data spaces? >>So we've had a kind of a great three days um first starting out with Antonio neary and and and F. I. S to talk about kind of the the insight, the age of insights and and how data is actually becoming the currency of the future if you will. And so that we started that way. And then on day two we had a panel of some of our clients talking about in their particular industry, what's happening with data. So you start to see the kind of um sharing out of uh requirements and how urgent these requirements are growing. Uh And then on day three we actually go into more technology. So you'll see there. We have a number of demos and sessions Uh one specifically around agriculture use case, another around health care use case as well. And then we go into a little bit more detail around the data spaces concept in the keynote for day three. >>So action packed three days Janice. Thank you so much for joining me. Talking to us about data space is what you guys are doing for social impact out of h p. S. Office of the C t. O. We appreciate your time. >>Thank you lisa >>for Janice. Thank yous. I'm lisa martin. You're watching the cubes coverage of HP discover 2021 mm.

>>mhm Yes, Welcome back to the cubes coverage of red hat summit 2021 virtual, which we were in person this year but we're still remote. We still got the Covid coming around the corner. Soon to be in post. Covid got a great guest here, Clayton Coleman architect that red hat cuba love and I've been on many times expanded role again this year. More cloud, more cloud action. Great, great to see you. Thanks for coming on. >>It's a pleasure >>to be here. So great to see you were just riffing before we came on camera about distributed computing uh and the future of the internet, how it's all evolving, how much fun it is, how it's all changing still. The game is still the same, all that good stuff. But here at Red had some and we're gonna get into that, but I want to just get into the hard news and the real big, big opportunities here you're announcing with red hat new managed cloud services portfolio, take us through that. >>Sure. We're continuing to evolve our open shift managed offerings which has grown now to include um the redhead open shift service on amazon to complement our as your redhead open shift service. Um that means that we have um along with our partnership on IBM cloud and open ship dedicated on both a W S and G C P. We now have um managed open shift on all of the major clouds. And along with that we are bringing in and introducing the first, I think really the first step what we see as uh huh growing and involving the hybrid cloud ecosystem on top of open shift and there's many different ways to slice that, but it's about bringing capabilities on top of open shift in multiple environments and multiple clouds in ways that make developers and operation teams more productive because at the heart of it, that's our goal for open shift. And the broader, open source ecosystem is do what makes all of us safer, more, uh, more productive and able to deliver business value? >>Yeah. And that's a great steak you guys put in the ground. Um, and that's great messaging, great marketing, great value proposition. I want to dig into a little bit with you. I mean, you guys have, I think the only native offering on all the clouds out there that I know of, is that true? I mean, you guys have, it's not just, you know, you support AWS as your and I B M and G C P, but native offerings. >>We do not have a native offering on GCPD offered the same service. And this is actually interesting as we've evolved our approach. You know, everyone, when we talk about hybrid, Hybrid is, um, you know, dealing with the realities of the computing world, We live in, um, working with each of the major clouds, trying to deliver the best immigration possible in a way that drives that consistency across those environments. And so actually are open shift dedicated on AWS service gave us the inspiration a lot of the basic foundations for what became the integrated Native service. And we've worked with amazon very closely to make sure that that does the right thing for customers who have chosen amazon. And likewise, we're trying to continue to deliver the best experience, the best operational reliability that we can so that the choice of where you run your cloud, um, where you run your applications, um, matches the decisions you've already made and where your future investments are gonna be. So we want to be where customers are, but we also want to give you that consistency. That has been a hallmark of um of open shift since the beginning. >>Yeah. And thanks for clarifying, I appreciate that because the manage serves on GCB rest or native. Um let me ask about the application services because Jeff Barr from AWS posted a few weeks ago amazon celebrated their 15th birthday. They're still teenagers uh relatively speaking. But one comment he made that he that was interesting to me. And this applies kind of this cloud native megatrend happening is he says the A. P. I. S are basically the same and this brings up the hybrid environment. You guys are always been into the api side of the management with the cloud services and supporting all that. As you guys look at this ecosystem in open source. How is the role of A PS and these integrations? Because without solid integration all these services could break down and certainly the open source, more and more people are coding. So take me through how you guys look at these applications services because many people are predicting more service is going to be on boarding faster than ever before. >>It's interesting. So um for us working across multiple cloud environments, there are many similarities in those mps, but for every similarity there is a difference and those differences are actually what dr costs and drive complexity when you're integrating. Um and I think a lot of the role of this is, you know, the irresponsible to talk about the role of an individual company in the computing ecosystem moving to cloud native because as many of these capabilities are unlocked by large cloud providers and transformations in the kinds of software that we run at scale. You know, everybody is a participant in that. But then you look at the broad swath of developer and operator ecosystem and it's the communities of people who paper over those differences, who write run books and build um you know, the policies and who build the experience and the automation. Um not just in individual products or an individual clouds, but across the open source ecosystem. Whether it's technologies like answerable or Terror form, whether it's best practices websites around running kubernetes, um every every part of the community is really involved in driving up uh driving consistency, um driving predictability and driving reliability and what we try to do is actually work within those constraints um to take the ecosystem and to push it a little bit further. So the A. P. I. S. May be similar, but over time those differences can trip you up. And a lot of what I think we talked about where the industry is going, where where we want to be is everyone ultimately is going to own some responsibility for keeping their services running and making sure that their applications and their businesses are successful. The best outcome would be that the A. P. R. S are the same and they're open and that both the cloud providers and the open source ecosystem and vendors and partners who drive many of these open source communities are actually all working together to have the most consistent environment to make portability a true strength. But when someone does differentiate and has a true best to bring service, we don't want to build artificial walls between those. I mean, I mean, that's hybrid cloud is you're going to make choices that make sense for you if we tell people that their choices don't work or they can't integrate or, you know, an open source project doesn't support this vendor, that vendor, we're actually leaving a lot of the complexity buried in those organizations. So I think this is a great time to, as we turn over for cloud. Native looking at how we, as much as possible try to drive those ap is closer together and the consistency underneath them is both a community and a vendor. And uh for red hat, it's part of what we do is a core mission is trying to make sure that that consistency is actually real. You don't have to worry about those details when you're ignoring them. >>That's a great point. Before I get into some architectural impact, I want to get your thoughts on um, the, this trends going on, Everyone jumps on the bandwagon. You know, you say, oh yeah, I gotta, I want a data cloud, you know, everything is like the new, you know, they saw Snowflake Apollo, I gotta have some, I got some of that data, You've got streaming data services, you've got data services and native into the, these platforms. But a lot of these companies think it's just, you're just gonna get a data cloud, just, it's so easy. Um, they might try something and then they get stuck with it or they have to re factor, >>how do you look >>at that as an architect when you have these new hot trends like say a data cloud, how should customers be thinking about kicking the tires on services like that And how should they think holistically around architect in that? >>There's a really interesting mindset is, uh, you know, we deal with this a lot. Everyone I talked to, you know, I've been with red hat for 10 years now in an open shift. All 10 years of that. We've gone through a bunch of transformations. Um, and every time I talked to, you know, I've talked to the same companies and organizations over the last 10 years, each point in their evolution, they're making decisions that are the right decision at the time. Um, they're choosing a new capability. So platform as a service is a great example of a capability that allowed a lot of really large organizations to standardize. Um, that ties into digital transformation. Ci CD is another big trend where it's an obvious wind. But depending on where you jumped on the bandwagon, depending on when you adopted, you're going to make a bunch of different trade offs. And that, that process is how do we improve the ability to keep all of the old stuff moving forward as well? And so open api is open standards are a big part of that, but equally it's understanding the trade offs that you're going to make and clearly communicating those so with data lakes. Um, there was kind of the 1st and 2nd iterations of data lakes, there was the uh, in the early days these capabilities were knew they were based around open source software. Um, a lot of the Hadoop and big data ecosystem, you know, started based on some of these key papers from amazon and google and others taking infrastructure ideas bringing them to scale. We went through a whole evolution of that and the input and the output of that basically let us into the next phase, which I think is the second phase of data leak, which is we have this data are tools are so much better because of that first phase that the investments we made the first time around, we're going to have to pay another investment to make that transformation. And so I've actually, I never want to caution someone not to jump early, but it has to be the right jump and it has to be something that really gives you a competitive advantage. A lot of infrastructure technology is you should make the choices that you make one or two big bets and sometimes people say this, you call it using their innovation tokens. You need to make the bets on big technologies that you operate more effectively at scale. It is somewhat hard to predict that. I certainly say that I've missed quite a few of the exciting transformations in the field just because, um, it wasn't always obvious that it was going to pay off to the degree that um, customers would need. >>So I gotta ask you on the real time applications side of it, that's been a big trend, certainly in cloud. But as you look at hybrid hybrid cloud environments, for instance, streaming data has been a big issue. Uh any updates there from you on your managed service? >>That's right. So one of we have to manage services um that are both closely aligned three managed services that are closely aligned with data in three different ways. And so um one of them is redhead open shift streams for Apache Kafka, which is managed cloud service that focuses on bringing that streaming data and letting you run it across multiple environments. And I think that, you know, we get to the heart of what's the purpose of uh managed services is to reduce operational overhead and to take responsibilities that allow users to focus on the things that actually matter for them. So for us, um managed open shift streams is really about the flow of data between applications in different environments, whether that's from the edge to an on premise data center, whether it's an on premise data center to the cloud. And increasingly these services which were running in the public cloud, increasingly these services have elements that run in the public cloud, but also key elements that run close to where your applications are. And I think that bridge is actually really important for us. That's a key component of hybrid is connecting the different locations and different footprints. So for us the focus is really how do we get data moving to the right place that complements our API management service, which is an add on for open ship dedicated, which means once you've brought the data and you need to expose it back out to other applications in the environment, you can build those applications on open shift, you can leverage the capabilities of open shift api management to expose them more easily, both to end customers or to other applications. And then our third services redhead open shift data science. Um and that is a, an integration that makes it easy for data scientists in a kubernetes environment. On open shift, they easily bring together the data to make, to analyze it and to help route it is appropriate. So those three facets for us are pretty important. They can be used in many different ways, but that focus on the flow of data across these different environments is really a key part of our longer term strategy. >>You know, all the customer checkboxes there you mentioned earlier. I mean I'll just summarize that that you said, you know, obviously value faster application velocity time to value. Those are like the checkboxes, Gardner told analysts check those lower complexity. Oh, we do the heavy lifting, all cloud benefits, so that's all cool. Everyone kind of gets that, everyone's been around cloud knows devops all those things come into play right now. The innovation focuses on operations and day to operations, becoming much more specific. When people say, hey, I've done some lift and shift, I've done some Greenfield born in the cloud now, it's like, whoa, this stuff, I haven't seen this before. As you start scaling. So this brings up that concept and then you add in multi cloud and hybrid cloud, you gotta have a unified experience. So these are the hot areas right this year, I would say, you know, that day to operate has been around for a while, but this idea of unification around environments to be fully distributed for developers is huge. >>How do you >>architect for that? This is the number one question I get. And I tease out when people are kind of talking about their environments that challenges their opportunities, they're really trying to architect, you know, the foundation that building to be um future proof, they don't want to get screwed over when they have, they realize they made a decision, they weren't thinking about day to operation or they didn't think about the unified experience across clouds across environments and services. This is huge. What's your take on this? >>So this is um, this is probably one of the hardest questions I think I could get asked, which is uh looking into the crystal ball, what are the aspects of today's environments that are accidental complexity? That's really just a result of the slow accretion of technologies and we all need to make bets when, when the time is right within the business, um and which parts of it are essential. What are the fundamental hard problems and so on. The accidental complexity side for red hat, it's really about um that consistent environment through open shift bringing capabilities, our connection to open source and making sure that there's an open ecosystem where um community members, users vendors can all work together to um find solutions that work for them because there's not, there's no way to solve for all of computing. It's just impossible. I think that is kind of our that's our development process and that's what helps make that accidental complexity of all that self away over time. But in the essential complexity data is tied the location, data has gravity data. Lakes are a great example of because data has gravity. The more data that you bring together, the bigger the scale the tools you can bring, you can invest in more specialized tools. I've almost do that as a specialization centralization. There's a ton of centralization going on right now at the same time that these new technologies are available to make it easier and easier. Whether that's large scale automation um with conflict management technologies, whether that's kubernetes and deploying it in multiple sites in multiple locations and open shift, bringing consistency so that you can run the apps the same way. But even further than that is concentrating, mhm. More of what would have typically been a specialist problem, something that you build a one off around in your organization to work through the problem. We're really getting to a point where pretty soon now there is a technology or a service for everyone. How do you get the data into that service out? How do you secure it? How do you glue it together? Um I think of, you know, some people might call this um you know, the ultimate integration problem, which is we're going to have all of this stuff and all of these places, what are the core concepts, location, security, placement, topology, latency, where data resides, who's accessing that data, We think of these as kind of the building blocks of where we're going next. So for us trying to make investments in, how do we make kubernetes work better across lots of environments. I have a coupon talk coming up this coupon, it's really exciting for me to talk about where we're going with, you know, the evolution of kubernetes, bringing the different pieces more closely together across multiple environments. But likewise, when we talk about our managed services, we've approached the strategy for managed services as it's not just the service in isolation, it's how it connects to the other pieces. What can we learn in the community, in our services, working with users that benefits that connectivity. So I mentioned the open shift streams connecting up environments, we'd really like to improve how applications connect across disparate environments. That's a fundamental property of if you're going to have data uh in one geographic region and you didn't move services closer to that well, those services I need to know and encode and have that behavior to get closer to where the data is, whether it's one data lake or 10. We gotta have that flexibility in place. And so those obstructions are really, and to >>your point about the building blocks where you've got to factor in those building blocks, because you're gonna need to understand the latency impact, that's going to impact how you're gonna handle the compute piece, that's gonna handle all these things are coming into play. So, again, if you're mindful of the building blocks, just as a cloud concept, um, then you're okay. >>We hear this a lot. Actually, there's real challenges in the, the ecosystem of uh, we see a lot of the problems of I want to help someone automate and improved, but the more balkanize, the more spread out, the more individual solutions are in play, it's harder for someone to bring their technology to bear to help solve the problem. So looking for ways that we can um, you know, grease the skids to build the glue. I think open source works best when it's defining de facto solutions that everybody agrees on that openness and the easy access is a key property that makes de facto standards emerged from open source. What can we do to grow defacto standards around multi cloud and application movement and application interconnect I think is a very, it's already happening and what can we do to accelerate it? That's it. >>Well, I think you bring up a really good point. This is probably a follow up, maybe a clubhouse talk or you guys will do a separate session on this. But I've been riffing on this idea of uh, today's silos, tomorrow's component, right, or module. If most people don't realize that these silos can be problematic if not thought through. So you have to kill the silos to bring in kind of an open police. So if you're open, not closed, you can leverage a monolith. Today's monolithic app or full stack could be tomorrow's building block unless you don't open up. So this is where interesting design question comes in, which is, it's okay to have pre existing stuff if you're open about it. But if you stay siloed, you're gonna get really stuck >>and there's going to be more and more pre existing stuff I think, you know, uh even the data lake for every day to lake, there is a huge problem of how to get data into the data lake or taking existing applications that came from the previous data link. And so there's a, there's a natural evolutionary process where let's focus on the mechanisms that actually move that day to get that data flowing. Um, I think we're still in the early phases of thinking about huge amounts of applications. Microservices or you know, 10 years old in the sense of it being a fairly common industry talking point before that we have service oriented architecture. But the difference now is that we're encouraging and building one developer, one team might run several services. They might use three or four different sas vendors. They might depend on five or 10 or 15 cloud services. Those integration points make them easier. But it's a new opportunity for us to say, well, what are the differences to go back to? The point is you can keep your silos, we just want to have great integration in and out of >>those. Exactly, they don't have to you have to break down the silos. So again, it's a tried and true formula integration, interoperability and abstracting away the complexity with some sort of new software abstraction layer. You bring that to play as long as you can paddle with that, you apply the new building blocks, you're classified. >>It sounds so that's so simple, doesn't it? It does. And you know, of course it'll take us 10 years to get there. And uh, you know, after cloud native will be will be galactic native or something like that. You know, there's always going to be a new uh concept that we need to work in. I think the key concepts we're really going after our everyone is trying to run resilient and reliable services and the clouds give us in the clouds take it away. They give us those opportunities to have some of those building blocks like location of geographic hardware resources, but they will always be data that spread. And again, you still have to apply those principles to the cloud to get the service guarantees that you need. I think there's a completely untapped area for helping software developers and software teams understand the actual availability and guarantees of the underlying environment. It's a property of the services you run with. If you're using a disk in a particular availability zone, that's a property of your application. I think there's a rich area that hasn't been mined yet. Of helping you understand what your effective service level goals which of those can be met. Which cannot, it doesn't make a lot of sense in a single cluster or single machine or a single location world the moment you start to talk about, Well I have my data lake. Well what are the ways my data leg can fail? How do we look at your complex web of interdependencies and say, well clearly if you lose this cloud provider, you're going to lose not just the things that you have running there, but these other dependencies, there's a lot of, there's a lot of next steps that we're just learning what happens when a major cloud goes down for a day or a region of a cloud goes down for a day. You still have to design and work around those >>cases. It's distributed computing. And again, I love the space where galactic cloud, you got SpaceX? Where's Cloud X? I mean, you know, space is the next frontier. You know, you've got all kinds of action happening in space. Great space reference there. Clayton, Great insight. Thanks for coming on. Uh, Clayton Coleman architect at red Hat. Clayton, Thanks for coming on. >>Pretty pleasure. >>Always. Great chat. I'm talking under the hood. What's going on in red hats? New managed cloud service portfolio? Again, the world's getting complex, abstract away. The complexities with software Inter operate integrate. That's the key formula with the cloud building blocks. I'm john ferry with the cube. Thanks for watching. Yeah.

>>Thank you for joining us for accelerate next event. I hope you're enjoying it so far. I know you've heard about the industry challenges the I. T. Trends HP strategy from leaders in the industry and so today what we wanna do is focus on going deep on workload solutions. So in the most important workload solutions, the ones we always get asked about and so today we want to share with you some best practices, some examples of how we've helped other customers and how we can help you. All right with that. I'd like to start our panel now and introduce chris idler, who's the vice president and general manager of the element. Chris has extensive solution expertise, he's led HP solution engineering programs in the past. Welcome chris and Mark Nickerson, who is the Director of product management and his team is responsible for solution offerings, making sure we have the right solutions for our customers. Welcome guys, thanks for joining me. >>Thanks for having us christa. >>Yeah, so I'd like to start off with one of the big ones, the ones that we get asked about all the time, what we've been all been experienced in the last year, remote work, remote education and all the challenges that go along with that. So let's talk a little bit about the challenges that customers have had in transitioning to this remote work and remote education environments. >>Uh So I I really think that there's a couple of things that have stood out for me when we're talking with customers about V. D. I. Um first obviously there was a an unexpected and unprecedented level of interest in that area about a year ago and we all know the reasons why, but what it really uncovered was how little planning had gone into this space around a couple of key dynamics. One is scale. Um it's one thing to say, I'm going to enable V. D. I. For a part of my work force in a pre pandemic environment where the office was still the central hub of activity for work. It's a completely different scale. When you think about okay I'm going to have 50, 60, 80, maybe 100 of my workforce now distributed around the globe. Um Whether that's in an educational environment where now you're trying to accommodate staff and students in virtual learning, Whether that's in the area of things like Formula one racing, where we had the desire to still have events going on. But the need for a lot more social distancing. Not as many people able to be trackside but still needing to have that real time experience. This really manifested in a lot of ways and scale was something that I think a lot of customers hadn't put as much thought into. Initially the other area is around planning for experience a lot of times the V. D. I. Experience was planned out with very specific workloads are very specific applications in mind. And when you take it to a more broad based environment, if we're going to support multiple functions, multiple lines of business, there hasn't been as much planning or investigation that's gone into the application side. And so thinking about how graphically intense some applications are. Uh one customer that comes to mind would be Tyler I. S. D. Who did a fairly large rollout pre pandemic and as part of their big modernization effort, what they uncovered was even just changes in standard Windows applications Had become so much more graphically intense with Windows 10 with the latest updates with programs like Adobe that they were really needing to have an accelerated experience for a much larger percentage of their install base than they had counted on. So, um, in addition to planning for scale, you also need to have that visibility into what are the actual applications that are going to be used by these remote users? How graphically intense those might be. What's the logging experience going to be as well as the operating experience. And so really planning through that experience side as well as the scale and the number of users is kind of really two of the biggest, most important things that I've seen. >>You know, Mark, I'll just jump in real quick. I think you covered that pretty comprehensively there and it was well done. The a couple of observations I've made, one is just that um, V. D. I suddenly become like mission critical for sales. It's the front line, you know, for schools, it's the classroom, you know, that this isn't Uh cost cutting measure or uh optimization in IT. measure anymore. This is about running the business in a way it's a digital transformation. One aspect of about 1000 aspects of what does it mean to completely change how your business does. And I think what that translates to is that there's no margin for error, right? You know, you really need to to deploy this in a way that that performs, that understands what you're trying to use it for. That gives that end user the experience that they expect on their screen or on their handheld device or wherever they might be, whether it's a racetrack classroom or on the other end of a conference call or a boardroom. Right? So what we do in the engineering side of things when it comes to V. D. I. R. Really understand what's a tech worker, What's a knowledge worker? What's the power worker? What's a gP really going to look like? What time of day look like, You know, who's using it in the morning, Who is using it in the evening? When do you power up? When do you power down? Does the system behave? Does it just have the, it works function and what our clients can can get from H. P. E. Is um you know, a worldwide set of experiences that we can apply to, making sure that the solution delivers on its promises. So we're seeing the same thing you are christa, We see it all the time on beady eye and on the way businesses are changing the way they do business. >>Yeah. It's funny because when I talked to customers, you know, one of the things I heard that was a good tip is to roll it out to small groups first so you can really get a good sense of what the experiences before you roll it out to a lot of other people and then the expertise. Um It's not like every other workload that people have done before. So if you're new at it make sure you're getting the right advice expertise so that you're doing it the right way. Okay. One of the other things we've been talking a lot about today is digital transformation and moving to the edge. So now I'd like to shift gears and talk a little bit about how we've helped customers make that shift and this time I'll start with chris. >>All right Hey thanks. Okay so you know it's funny when it comes to edge because um the edge is different for every customer and every client and every single client that I've ever spoken to of. H. P. S. Has an edge somewhere. You know whether just like we were talking about the classroom might be the edge. But I think the industry when we're talking about edges talking about you know the internet of things if you remember that term from not too not too long ago you know and and the fact that everything is getting connected and how do we turn that into um into telemetry? And I think Mark is going to be able to talk through a a couple of examples of clients that we have in things like racing and automotive. But what we're learning about Edge is it's not just how do you make the Edge work? It's how do you integrate the edge into what you're already doing? And nobody's just the edge. Right. And so if it's if it's um ai ml dl there that's one way you want to use the edge. If it's a customer experience point of service, it's another, you know, there's yet another way to use the edge. So, it turns out that having a broad set of expertise like HP does, um, to be able to understand the different workloads that you're trying to tie together, including the ones that are running at the, at the edge. Often it involves really making sure you understand the data pipeline. What information is at the edge? How does it flow to the data center? How does it flow? And then which data center, which private cloud? Which public cloud are you using? Um, I think those are the areas where we, we really sort of shine is that we we understand the interconnectedness of these things. And so, for example, Red Bull, and I know you're going to talk about that in a minute mark, um the racing company, you know, for them the edges, the racetrack and, and you know, milliseconds or partial seconds winning and losing races, but then there's also an edge of um workers that are doing the design for the cars and how do they get quick access? So, um, we have a broad variety of infrastructure form factors and compute form factors to help with the edge. And this is another real advantage we have is that we we know how to put the right piece of equipment with the right software. And we also have great containerized software with our admiral container platform. So we're really becoming um, a perfect platform for hosting edge centric workloads and applications and data processing. Uh, it's uh um all the way down to things like a Superdome flex in the background. If you have some really, really, really big data that needs to be processed and of course our workhorse reliance that can be configured to support almost every combination of workload you have. So I know you started with edge christa but and and we're and we nail the edge with those different form factors, but let's make sure, you know, if you're listening to this, this show right now, um make sure you you don't isolate the edge and make sure they integrated with um with the rest of your operation, Mark, you know, what did I miss? >>Yeah, to that point chris I mean and this kind of actually ties the two things together that we've been talking about here at the Edge has become more critical as we have seen more work moving to the edge as where we do work, changes and evolves. And the edge has also become that much more closer because it has to be that much more connected. Um, to your point talking about where that edge exists, that edge can be a lot of different places. Um, but the one commonality really is that the edge is an area where work still needs to get accomplished. It can't just be a collection point and then everything gets shipped back to a data center back to some other area for the work. It's where the work actually needs to get done. Whether that's edge work in a used case like V. D. I. Or whether that's edge work. In the case of doing real time analytics, you mentioned red bull racing, I'll bring that up. I mean, you talk about uh, an area where time is of the essence, everything about that sport comes down to time. You're talking about wins and losses that are measured as you said in milliseconds. And that applies not just to how performance is happening on the track, but how you're able to adapt and modify the needs of the car, adapt to the evolving conditions on the track itself. And so when you talk about putting together a solution for an edge like that, you're right. It can't just be, here's a product that's going to allow us to collect data, ship it back someplace else and and wait for it to be processed in a couple of days, you have to have the ability to analyze that in real time. When we pull together a solution involving our compute products are storage products or networking products. When we're able to deliver that full package solution at the edge, what you see results like a 50 decrease in processing time to make real time analytic decisions about configurations for the car and adapting to real time test and track conditions. >>Yeah, really great point there. Um, and I really love the example of edge and racing because I mean that is where it all every millisecond counts. Um, and so important to process that at the edge. Now, switching gears just a little bit. Let's talk a little bit about um some examples of how we've helped customers when it comes to business agility and optimizing the workload for maximum outcome for business agility. Let's talk about some things that we've done to help customers with that >>mark, give it a >>shot. >>Uh, So when we, when we think about business agility, what you're really talking about is the ability to implement on the fly to be able to scale up and scale down the ability to adapt to real time changing situations. And I think the last year has been, has been an excellent example of exactly how so many businesses have been forced to do that. Um I think one of the areas that I think we've probably seen the most ability to help with customers in that agility area is around the space of private and hybrid clouds. Um if you take a look at the need that customers have to be able to migrate workloads and migrate data between public cloud environments, app development environments that may be hosted on site or maybe in the cloud, the ability to move out of development and into production and having the agility to then scale those application rollouts up, having the ability to have some of that. Um some of that private cloud flexibility in addition to a public cloud environment is something that is becoming increasingly crucial for a lot of our customers. >>All right, well, we could keep going on and on, but I'll stop it there. Uh, thank you so much Chris and Mark. This has been a great discussion. Thanks for sharing how we help other customers and some tips and advice for approaching these workloads. I thank you all for joining us and remind you to look at the on demand sessions. If you want to double click a little bit more into what we've been covering all day today, you can learn a lot more in those sessions. And I thank you for your time. Thanks for tuning in today.

>>from >>around the globe. It's the cube with digital >>Coverage of IBM think 2021 brought to you by IBM. >>Welcome back to IBM Think 2021 The virtual edition. My name is Dave Volonte and you're watching the cubes continuous coverage of think 21. And right now we're gonna talk about banking in the post isolation economy. I'm very pleased to welcome our next guest. Look at wag lee is the general manager, Global banking financial markets at IBM and john Degnan is the global ceo and vice president and distinguished engineer for banking and financial services. Gentlemen, welcome to the cube. >>Thank you. Yeah >>that's my pleasure. Look at this current economic upheaval. It's quite a bit different from the last one, isn't it? I mean liquidity doesn't seem to be a problem for most pecs these days. I mean if anything they're releasing loan loss reserves that they didn't need. What's from your perspective, what's the state of banking today and hopefully as we exit this pandemic soon. >>So so dave, I think, like you say, it's, you know, it's a it's a state and a picture that in a significantly different from what people were expecting. And I think some way, in some ways you're seeing the benefits of a number of the regulations that were put into into place after the, you know, the financial crisis last time around, right? And therefore this time, you know, a health crisis did not become a financial crisis, because I think the banks were in better shape. And also, you know, governments clearly have put worldwide a lot of liquidity into the, into the system. I think if you look at it though, maybe two or three things ready to call out firstly, there's a there's a massive regional variation. So if you look at the U. S. Banking industry, it's extremely buoyant and I'll come back to that in a minute in the way in which is performing, you know, the banks that are starting to report their first quarter results are going to show profitability. That's you know significantly ahead of where they were last year and probably some of the some of their best performance for quite a long time. If you go into europe, it's a completely different picture. I think the banks are extremely challenged out there and I think you're going to see a much bleaker outlook in terms of what those banks report and as far as Asia pacific is concerned again, you know because they they have come out of the pandemic much faster than consumer businesses back into growth. Again, I think they're showing some pretty buoyant performance as far as as far as banking performance is concerned. I think the piece that's particularly interesting and I think him as a bit of a surprise to most is what we've seen in the U. S. Right. And in the US what's actually happened is uh the investment banking side of banking businesses has been doing better than they've ever done before. There's been the most unbelievable amount of acquisition activity. You've seen a lot of what's going on with this facts that's driving deal raised, you know, deal based fee income for the banks. The volatility in the marketplace is meaning that trading income is much much higher than it's ever been. And therefore the banks are very much seeing a profitability on that investment banking side. That was way ahead of what I think they were. They were expecting consumer businesses definitely down. If you look at the credit card business, it's down. If you look at, you know, lending activity that's going down going out is substantially less than where it was before. There's hardly any lending growth because the economy clearly is flat at this moment in time. But again, the good news that, and I think this is a worldwide which are not just in us, the good news here is that because of the liquidity and and some of the special measures the government put out there, there has not been the level of bankruptcies that people were expecting, right. And therefore most of the provisioning that the banks did um in expectation of non performing loans has been, I think, a much more, much greater than what they're going to need, which is why you're starting to see provisions being released as well, which are kind of flattering, flattering the income, flattering the engine. I think going forward that you're going to see a different picture >>is the re thank you for the clarification on the regional divergence, is that and you're right on, I mean, european central banks are not the same, the same position uh to to affect liquidity. But is that nuances that variation across the globe? Is that a is that a blind spot? Is that a is that a concern or the other other greater concerns? You know, inflation and and and the the pace of the return to the economy? What are your thoughts on that? >>So, I think, I think the concern, um, you know, as far as the european marketplace is concerned is um you know, whether whether the performance that and particularly, I don't think the level of provisions in there was quite a generous, as we saw in other parts of the world, and therefore, you know, is the issue around non performing loans in in europe, going to hold the european uh european banks back? And are they going to, you know, therefore, constrain the amount of lending that they put into the economy and that then, um, you know, reduces the level of economic growth that we see in europe. Right? I think, I think that is certainly that is certainly a concern. Um I would be surprised and I've been looking at, you know, forecasts that have been put forward by various people around the world around inflation. I would be surprised if inflation starts to become a genuine problem in the, in the kind of short to medium term, I think in the industry that are going to be two or three other things that are probably going to be more, you know, going to be more issues. Right. I think the first one which is becoming top of mind for chief executives, is this whole area around operational resiliency. So, you know, regulators universally are making very very sure that banks do not have a technical debt or a complexity of legacy systems issue. They are and you know, the U. K. Has taken the lead on this and they are going so far as even requiring non executive directors to be liable if banks are found to not have the right policies in place. This is now being followed by other regulators around the world. Right. So so that is very much drop in mind at this moment in time. So I think discretionary investment is going to be put you know, towards solving that particular problem. I think that's that's one issue. I think the other issue is what the pandemic has shown is that and and and this was very evident to me and I mean I spent the last three years out in Singapore where you know, banks have become very digital businesses. Right? When I came into the U. S. In my current role, it was somewhat surprising to me as to where the U. S. Market place was in terms of digitization of banking. But if you look in the last 12 months, you know, I think more has been achieved in terms of banks becoming digital businesses and they've probably done in the last two or three years. Right. And that the real acceleration of that digitization which is going to continue to happen. But the downside of that has been that the threat to the banking industry from essentially fintech and big tex has exactly, it's really accelerated. Right, Right. Just to give you an example, Babel is the second largest financial services institutions in the US. Right. So that's become a real problem I think with the banking industry is going to have to deal with >>and I want to come back to that. But now let's bring john into the conversation. Let's talk about the tech stack. Look, it was talking about whether it was resiliency going digital, We certainly saw over the pandemic, remote work, huge, huge volumes of things like TPP and and and and and mortgages and with dropping rates, etcetera. So john, how is the tech stack Been altered in the past 14 months? >>Great question. Dave. And it's top of mind for almost every single financial services firm, regardless of the sector within the overall industry, every single business has been taking stock of how they handled the pandemic and the economic conditions thereafter and all of the business needs that were driven by the pandemic. In so many situations, firms were unable to service their clients or we're not competitive in serving their clients. And as a result they've had to do very deep uh architectural transformation and digital transformation around their core platforms. Their systems of analytics and their systems different end systems of engagement In terms of the core processing systems that many of these institutions, some in many cases there are 50 years old And with any 50 year old application platform there are inherent limitations. There's an in flex itty inflexibility. There's an inability to innovate for the future. There's a speed of delivery issue. In other words, it can be very hard to accelerate the delivery of new capabilities onto an aging platform. And so in every single case um institutions are looking to hybrid cloud and public cloud technology and pre packaged a ai and prepackaged solutions from an I. S. V. Ecosystem of software vendor ecosystem to say. As long as we can crack open many of these old monolithic cause and surround them with new digitalization, new user experience that spans every channel and automation from the front to back of every interaction. That's where most institutions are prioritizing. >>Banks aren't going to migrate, they're gonna they're gonna build an abstraction layer. I want to come back to the disruption is so interesting. The coin base I. P. O. Last month see Tesla and microstrategy. They're putting Bitcoin on their balance sheets. Jamie diamonds. Traditional banks are playing a smaller role in the financial system because of the new fin text. Look at, you mentioned Paypal, the striped as Robin Hood, you get the Silicon Valley giants have this dual disrupt disruption agenda. Apple amazon even walmart facebook. The question is, are traditional banks going to lose control of the payment systems? >>Yeah. I mean I think to a large extent that is that has already happened, right? Because I think if you look at, you know, if you look at the experience in ASia, right? And you look at particularly organizations like and financial, you know, in India, you look at organizations like A T. M. You know, very substantial chance, particularly on the consumer payments side has actually moved away from the banks. And I think you're starting to see that in the west as well, right? With organizations like, you know, cloud, No, that's coming out with this, you know, you know, buying out a later type of schemes. You've got great. Um, and then so you've got paper and as you said, strike, uh and and others as well, but it's not just, you know, in the payment side. Right. I think, I think what's starting to happen is that there are very core part of the banking business. You know, especially things like lending for instance, where again, you are getting a number of these Frontex and big, big tech companies entering the marketplace. And and I think the threat for the banks is this is not going to be small chunks of market share that you're going to actually lose. Right? It's it's actually, it could actually be a Kodak moment. Let me give you an example. Uh, you know, you will have just seen that grab is going to be acquired by one of these facts for about $40 billion. I mean, this organization started like the Uber in Singapore. It very rapidly got into both the payment site. Right? So it actually went to all of these moment pop shops and then offered q are based um, 12 code based payment capabilities to these very small retailers, they were charging about half or a third or world Mastercard or Visa were charging to run those payment rails. They took market share overnight. You look at the Remittance business, right? They went into the Remittance business. They set up these wallets in 28 countries around the Asean region. They took huge chunks of business completely away from DBS, which is the local bank out there from Western Union and all of these, all of these others. So, so I think it's a real threat. I think Jamie Dimon is saying what the banking industry has said always right, which is the reason we're losing is because the playing field is not even, this is not about playing fields. Been even write, all of these businesses have been subject to exactly the same regulation that the banks are subject to. Regulations in Singapore and India are more onerous than maybe in other parts of the world. This is about the banking business, recognizing that this is a threat and exactly as john was saying, you've got to get to delivering the customer experience that consumers are wanting at the level of cost that they're prepared to pay. And you're not going to do that by purely sorting out the channels and having a cool app on somebody's smartphone, Right? If that's not funny reported by arcade processes and legacy systems when I, you know, like, like today, you know, you make a payment, your payment does not clear for five days, right? Whereas in Singapore, I make a payment. The payment is instantaneously clear, right? That's where the banking system is going to have to get to. In order to get to that. You need to water the whole stack. And the really good news is that many examples where this has been done very successfully by incumbent banks. You don't have to set up a digital bank on the site to do it. And incumbent bank can do it and it can do it in a sensible period of time at a sensible level of investment. A lot of IBM s business across our consulting as well as our technology stack is very much trying to do that with our clients. So I am personally very bullish about what the industry >>yeah, taking friction out of the system, sometimes with a case of crypto taking the middle person out of the system. But I think you guys are savvy, you understand that, you know, you yeah, Jamie Diamond a couple years ago said he'd fire anybody doing crypto Janet Yellen and says, I don't really get a Warren Buffett, but I think it's technology people we look at and say, okay, wait a minute. This is an interesting Petri dish. There's, there's a fundamental technology here that has massive funding that is going to inform, you know, the future. And I think, you know, big bags are gonna lean in some of them and others, others won't john give you the last word here >>for sure, they're leaning in. Uh so to just to to think about uh something that lick it said a moment ago, the reason these startups were able to innovate fast was because they didn't have the legacy, They didn't have the spaghetti lying around. They were able to be relentlessly laser focused on building new, using the app ecosystem going straight to public and hybrid cloud and not worrying about everything that had been built for the last 50 years or so. The benefit for existing institutions, the incumbents is that they can use all of the same techniques and tools and hybrid cloud accelerators in terms And we're not just thinking about uh retail banking here. Your question around the industry that disruption from Bitcoin Blockchain technologies, new ways of processing securities. It is playing out in every single securities processing and capital markets organization right now. I'm working with several organizations right now exactly on how to build custody systems to take advantage of these non fungible digital assets. It's a hard, hard topic around which there's an incredible appetite to invest. An incredible appetite to innovate. And we know that the center of all these technologies are going to be cloud forward cloud ready. Ai infused data infused technologies >>Guys, I want to have you back. I wish I had more time. I want to talk about SPAC. So I want to talk about N. F. T. S. I want to talk about technology behind all this. You really great conversation. I really appreciate your time. I'm sorry. We got to go. >>Thank you. Thanks very much indeed for having us. It was a real pleasure. >>Really. Pleasure was mine. Thank you for watching everybody's day. Volonte for IBM think 2021. You're watching the Cube. Mhm.

>>Sony. Betty is here with me. He's the CEO and chief data officer for Snowflake. Sunny. Thanks for making the time today. Good to see >>you. Same here, Dave. Thanks for having me or >>yeah, so you're welcome. So before we get into it, I gotta ask you I mean, you recently left in video to join Snowflake. I mean, one of the few cos they're almost is hot. A snowflake. How come? Well, you know, >>Dave, I joined and video 12 years ago. I was there for 12 years when the video was less than 2000 people company and in video, you know, have an unbelievable growth trajectory. We went from 2000 employees to 16,000 when I left in, uh, December of 2019 and slowly kind of provided the same opportunity to come in Onda help scale the company. I thrive in an environment where I can be creative. I thrive in an environment where I can build things I can scale things. I could grow things, and it's been just a perfect opportunity to come and repeat that success over here. >>Awesome. Well, we wish you the best talking about your role. A little bit. I mean, it's not totally unique. I mean, especially in certain smaller organizations that have the same person in the role of chief information officer and chief data officer. But oh, which are you? Are you more CEO CEO? How do you balance that >>out? I would say that I'm both to be an effective CEO. You need immersion with automation. You need immersion with data. You need a motion with security. And you also need emotion with compliance. So if all these things are together, things that integrated, you have a cohesive way of handling all the pieces that come together. We believe if you keep them separated, you create silos and we definitely don't want silos. We want integration. We want seamless integration to drive and scale the company for future. I always felt nighttime is balanced between both areas. I >>mean, I always felt like a lot of the CEO, so I talked to They'd love to get more involved in the data, but they're just too busy trying to keep the lights on, you know, kind of. So maybe what are your thoughts on the priorities of each Hat CEO and CTO? >>Yeah. So look I mean, I think because we're full cloud company, we don't have anything on Prem. I don't have any work clothes in the on Prem. I don't We don't have a data center. I really don't have to worry about all the operational challenges that you have to deal with being a non prime company. So the cycles that I can be involved from a transformational perspective, trans driving transformation for the company, both on the data side as well as on the i d I t side I have I have that cycles to be to invest that time and energy into both areas. Uh, typically in a traditional company which is not yet migrated towards the cloud. A major portion of the abandoned gets wasted CEOs, bandwidth and I t professionals. Bandwidth gets wasted in dealing with the operational challenges that you have in an on prem environment. So having not to worry about that over here gives me all the cycles to be investing my time in both areas. >>Yeah, a lot of wasted I t labor over the decades. Let me ask you, how is running a data company? You know you're inside of a fast moving Silicon Valley Tech company. One of the similarities and the differences from some of the customers. I mean, on the one hand, you're moving faster than your customers, at least most of them. And you don't have the technical day. You just describe See XO Nirvana. On the other hand, you're an example of what's possible. You could sort of set the best practice. Mark, How do you see that dynamic >>eso? You know, for a world class I T organization, it needs to be data driven. It needs to be highly automated. It needs to enable world class user experience on then to secure and make the environment compliant, resilient. The cloud platform that we have inside snowflake allows us to achieve all of that. Now, that is, um, you know, an ideal situation to be in, but you don't have to deal with, you know, all the on time type of work clothes. Um, so finding that balance is what we're going after. And however this is a This is a journey right for other companies who are not on the cloud. It's a journey. They have to prioritize that they have to start moving things to the cloud and that's where we are Different and similar, right? Were different that we don't have to worry about that. Everything is in the cloud for us on then. Uh, that's kind of where we are, How we see it. >>So, you know, used to call the dog Fuding segment. But Oliver Bushman was the sea was the CEO of s a piece. I don't know, Dave. We call it drinking your own champagne, which is how you guys refer to it. But, you know, sometimes still in such situations, you're inside the sausage factory, which is, you know, good in a way, because you see it before it goes into production. But so what's your journey with with snowflake been like, Yeah, >>so that's a really good question. That's a major portion of what I do at work and the let's start with the first principles. We believe that we want to measure everything in the company that's important for companies performance. If we measure the right things, we believe we can drive. The best outcomes were driven through those first principles, and we leverage our business applications, our data, our security, our automation and our compliance to integrate our with our product to power. All these use cases and workloads, uh, in our own environment, we call that Snow house, which is nothing but a snowflake Instance. So, um, for all the new products that we are coming into market with, we work very closely with the engineering team with the product management team to make sure that we actually become customer zero and try Thio. Use as much functionality of that inside the our own enterprise and give as much feedback to our engineering and product management team so that they can make the customer one experience to be world class. Eso. That's kind of in a nutshell. What we how we go to market with all those products. So >>your customer zero So all the products that they suck up to you Are they afraid of you? >>I think I think it's I think it's a very mutual beneficial relationship. So, you know, they know that they that my feed, my team's feedback is important to how they're kind of shaping up the product. And it's just not necessarily I t right. We have folks in finance, folks and, um, sales, marketing. Everybody is you know, drinking the champagne. Right. And icty and the data team actually enable that deployment. But the use cases are pretty much in the entire enterprise off the company in every in every aspect of it. >>Well, you know, including security. Well, you know, there's I was saying we always talk about alignment, but its's almost alignment by design as opposed to being this force thing. I'm interested in this, you know, sort of snowflake on on snowflake, You know, concept that that you guys talk about. You know what? We're objectives you're going in and maybe thinking about the outcomes, you know? What did you expect? Did you work backwards from that? You know, what were you trying >>to achieve? Yeah. I mean, look the again, back to the first principles. We believe we want to measure everything that's important to our business. That would drive the outright outcomes. We then later the application layer. We then overlay the business process layer. We then overlay the, um, compliance and security layer and and the end result really is operational izing snowflake internally to drive a business making the right choices, right? Decisions for the company. Yeah. So we have a ton of use cases that are just ideal. Um, using snowflake on Snowflake. Um, you know, I can give you some examples of that if you like, But Security being one of the biggest use cases way use the the entire monitoring and remediation work that goes in the security compliance world all through snowflake. And we're finding real time events through data sharing with our key suppliers. And we're ensuring that we're protecting our environment as much as possible with that whole infrastructure. >>If you talk about layering, you know, governance, security, it's etcetera. Yeah, I'm imagining a you know, a coat of primer paint, you know, nice and smooth over. It's not a bolt on. I want you. I wanna press you on that because because it can't be an afterthought. And what you're describing is much more of a modern approach. And I want you to sort of differentiate between the layers that you talked about and what you surely seen in your experience over the years is a bolt on. What's the difference? >>Well, I mean, you know, security. Well, there's a lot of data and a lot of the data that is critical to your environment. Um, you wanna make sure it's fully complete? You're getting it in the right hands in the right platform to understand that and doing the correlation work that needs to happen. Really time. Our platform allows all that data to be ingested and, you know, real time and anything that is suspicious. That's being out there. We're finding that stuff in real time. The monitoring has to be real time. And if there is an event, somebody needs to take an action. Real time. Eso the platform allows it to integrate all together. And basically, um, the suppliers that we're using are also doing data sharing with us on this platform. So it makes the whole security remediation to be really, really fantastic experience. >>Well, I think two I share often with my audiences. When I talked to practitioners, they're using stuff like they surprising to me. When I first heard this, they said, Well, what you chose snowflake is the security. I went What? But the simplicity and the workflow is simpler, and it just means, you know, less human labor involved in setting, setting these things up. So I wonder if you could talk about the team that you put together the culture that you're you're building And you know what? What's the makeup look like? >>Sure s o e specifically asking about the characteristics off how we're building up the culture. Yeah, absolutely. Okay, So I think they're looking for, you know, obviously very much high energy folks. People who have hi accountability, their data driven. We want to measure everything that's important to us. We're looking for folks who have situational awareness on then finally, high sense of urgency. I think all of these elements, uh, allows I t organization to be integrated with the business in law of the traditional companies. I T organizations kind of disintegrate with the business. We wanna integrate with the business to drive the best outcomes that are needed for the company. >>I want to ask you about some of your favorite use cases, but you mentioned measurement. How do you measure? What do you What do you measuring? >>Uh, sure. So I would say that Let's let's just take security because we talked about security. Let's just use security as a use case. Eso insecurity. There are many different frameworks. As you may know, right, there is the nest framework. There is a C s framework. Um, there's a I S O framework we have adopted towards a CS framework inside Snowflake. Ah, that framework has 20 controls. And that 20 controls has, you know, another 20 sub controls. So we're talking about 400 controls? Potentially. Um, not every control is applicable to us, but majority of them are. And so, for every control, that is a source of data that's being ingested in snowflake or give you an example of that is asset management. So asset management for endpoints asset management for our servers or asset management for our network gear, all of that data gets ingested inside. Snowflake. We measure that we can tell you exactly how many endpoints I have. I can tell you exactly when an employee gets on boarded. What the what laptop we have given them. What is Ah, um you know, when the employee leaves the company are recollecting that laptop back on time. Are we revoking all that access? That's part of CS Control. One as an example. And we're measuring all of that and I can tell you exactly at my real time, inside Snowflake, How effective I am for that specific control. That's just an example of that day. Now imagine 400 of these items that make up the whole security CS framework that you know, you want to measure everything on that 400 controls or 400 sub controls. And you want to make sure that if any of that control is not being managed properly, you're alerted about it and you're remediating it to prevent a security issue that might that may pop up >>awesome visibility and the automation component are you Are you the sea? So to sunny? I >>don't really have that title. We don't really have a CSO title, but I do better security. Hadas. Well, it's actually a joint responsibility between I managed the corporate security. The product security is inside the product team, but we use the same common framework. We use the same common telemetry. We use the same common, um um methodology. Uh, incident management response teams are very similar. Andi, it's all power to snowflake. >>Okay? And thank you for watching. Keep it right there. We've got mortgage rate content coming your way

>>from around the globe. It's the Cube with digital coverage of Dell Technologies. World Digital Experience Brought to You by Dell Technologies. Welcome to the Cubes Coverage of Dell Technologies. World 2020. The Digital Experience. I'm Lisa Martin, and I'm pleased to welcome back one of our Cube alumni. John Shirley is with us. The vice president of unstructured storage product management. John. Welcome back to the Cube. >>Thank you for having me. It's great to be back. >>So so much has changed since we last saw you were very socially distant. But talk to me from from a storage and unstructured of data perspective, lot of changes in the year of 2020. >>Yeah, a lot of changes everywhere, but especially in our spaces. While we're seeing just a phenomenal amount of growth with storage. Still, that's continuing. But what we've really seen is things changing pretty pretty rapidly, actually, two new cloud based applications and it almost seems like everything that's happened during the pandemic has kind of been an accelerant to getting to that next level of technology. And so we're really excited to be working with our customers, really guide them in the journey to get into, you know, new cloud based applications, cloud native applications and really just helping them take advantage of all of this on structure data that's being generated. >>Yeah, we've heard about acceleration in so many facets this year and that it's, you know, we're accelerated by, you know, 24 to 36 months. Talk to me about, For example. I was talking Thio, Adele Technologies customer Earth down the other day. And, of course, the massive amount of video that they're generating 24 by seven by 3. 65 from all over the world. The edge, cloud core, So much growth there. How are you seeing customers be able to pivot quickly and adapt to how different things are? >>Yeah, you know, the interesting part two isn't just a collection of data anymore. It's how customers want to treat that data. And what we're seeing over and over again is that we get the video streams coming in. But there's also all of these sensors in the world and so marrying up the video streams with sensor information and keeping that in a repository so that you can do things like, uh, real Time analytics, but also be able to take that same data set and also get the historical view is becoming critically important. And that's the thing that's really changed, is how the data is being used yesterday that keeps coming in. But customers are really, really taking a different view in terms of how they want to go use that data. So we have a lot of tools that we've created over the last year or two that are helping our customers harness and really use that data, something that they just weren't able to do a couple years ago. >>Now we always talk about data as currency or data as gold or data equals trust and the most important factor for any businesses extracting value from that data. I think now, really time is even more important if you think of contact tracing, for example, or the accelerated work going on to develop a vaccine, so much access has to be now because data from yesterday isn't good enough. It's not gonna help solve some of these big use cases. What is she gonna key use cases that you're seeing accelerate in the last few months? >>You just hit it right on the head. So the way we look at it, it kind of two points within the timeline of data. That's the most valuable. And, of course, what you just said. Get the right away in the here. Now that's that's one of the times that is the most valuable toe have that data. But then if we kind of take a look at that data as it ages because it get less important, well, some of it might. But actually the data has a big scale data like data repository and be able to extract value out of that kind of holistically as a big set of data is extremely important as well. And so we we have tools, everything from our streaming data platform that talks about how we can extract value from that data, right as it's coming off the sensor of the videos video streams, we've got our power scale product, which provides very, very high performance storage so that customers 10 stream a bunch of data and get some of that AI and ml off of that data. And then we've got our PCs object storage based product what customers want exabytes of data, and they just want a really long term, robust storage repositories. So we've kind of got all the tools together that really helping our customers extract that value. >>Talk to me about doing a migration. That's always a big challenge, especially as many businesses live in a hybrid or multi cloud world where they've got or using public cloud services on from edge maybe, for example, but in terms of being able to get to the data and run algorithms on it to do a I. How can a customer give me, like a snapshot of a of an example infrastructure that, you see is common with customers that allows them to harness data wherever it is and be able to run a I on wherever it is without having to move it around and pale those charges and, of course, lose precious time? >>Yeah, that's a great question. What we're seeing a lot, too, is customers wanting to take advantage of things like the cloud, the power that compete in the cloud, and, uh, they don't necessarily want to move the data in and out of the cloud. But at the same time, you know, we want to make sure that the customers have the flexibility to choose which cloud that they want to go to. So we have multiple cloud offerings that were given to our customers, specifically the ability to take the data. We host the service for the customer so that it's all in all operated within the Dell EMC, uh, infrastructure team. And then we can map that data data up to the clouds. Whether they want to go to any of the Big three cloud providers, we could map that out. There's no egress fees, and they could go ahead and take advantage of the data very quickly, easily. >>So really, from a flexibility perspective, being able to meet them where they are, >>that's absolutely right. So whether the customers are in the edge or in their in their core or in the cloud will be there to help their needs. >>So this is the first Dell Technologies world that is digital, a lot of opportunity for folks. Thio learn and still be able to have as much engagement as possible. Talk to us about some of the things that you're excited about. The customers are gonna learn in terms of how you're helping them get more value out of the data faster in a time of such massive change. >>Yeah, so we're doing so much within the within the team. So earlier this year we introduced a new product called Power Scale which is taking our industry leading one FS software for scale out file. And we have put that in and really taken advantage of what we have within the Dell family and taking the best server hard work power edge. We've taken on one of one FS software married and together we're really extracting the best value of the data with those platforms. So again, the industry leading scale of file solution marrying that up with the industry leading server solution. And now we've got even though even more robust solution. On top of that, we have, uh, announced our objects scale solution. And so objects Scale is a knob decked store solution that's specifically targeted for customers running kubernetes. We've partnered up with our friends over at VM Ware and we've developed an object store specifically for developers on top of kubernetes environment, so that when customers want to go and start generating new applications with object store on new cloud native app they can really quickly spin up new object, store new buckets and start writing data. It's very simple and easy to use, and then when they want to grow at scale, we've got our PCs object store, too, into that petabytes scale. So it's it's very exciting. >>Can you give us an example of a customer that's that's already doing that That, you see, is really achieving some significant benefits? >>Yeah, yeah, So, uh, probably the one that's the most fun toe watches were working with a company that's doing amusement park rides and really taking a look at all the sensor information so that they can get predictive analytics in terms of the maintenance of the rides, making sure that if there is maintenance that needs to get done, they could get that fixed as quickly as possible so that customers going through those rights a. If, of course, they're going to be safety. Safety is always number one. But being able to make shape, make sure those rides are maintained so that the lines move quickly and they can keep customers going through. And you get us many people enjoying those rises. You can, and that's all coming from our streaming data platform, which is again taking that information. All of that sensors feet, and they need that that real time value that we talked about before to get that real time value. But they also get the historical view so they could see how the maintenance is kind of evolved over time. So that's that's one that's been, ah, lot of fun to work with here over the last couple. >>And hopefully we get to go back to amusement parks and calendar year 2021. Wouldn't that be nice? You mentioned safety and and that Yeah, that kind of makes me think about security. We've seen so much about increases like companies like Zoom, for example, with increased scrutiny on their data security, a more compliance requirements, Um, data protection being even mawr. Important as there was this massive pivot toe work from home seven months ago, and a lot of folks are still there are not going to be there. Tell me a little bit about some of the things that you're doing it to facilitate that this data, this massive increase in unstructured data, is managed securely so that if there's any sort of breach or incident, your customers air in good shape. >>We We have a lot of focus on security within the organization, and that's really across the board. That's really across all of Dell Technologies products. Eso We do a lot of things around encrypted drives to make sure that if the driver ever pulled out of the system, there's no way to go access that data. There's just no way to go do that without the original keys. You can't get those original kids when they're not in the system, so we make sure that we do a lot of hard enough the system at that level. We work very closely with the broader partner and ecosystem community to make sure that we provide things like ransom or protection, uh, isolated. So in case if something does happen a you identified as quickly as you can but be you make sure that you have a good data set, like a good golden copy of that data that you can always go back. Thio, >>you mentioned ransom where it's it's really been on the rise in 2020. I read a stat a couple days ago that every 11 seconds are Ransomware attack occurs when we think about how many new industries are exposed. I saw I read recently that the the New Zealand Stock Exchange was hit a couple of times. Carnival Cruise Line, the Department of veterans of There's a social media with Facebook Tick Toke Instagram on 235 million user profile straight from a unsecured cloud database. So not only is that threat landscape expanding, but we've got more people accessing. Um, you know, corporate networks with maybe personal devices for those phishing emails are probably even getting more sophisticated. >>Yeah, we spend. Like I said, we spend a lot of time. We have a whole security team within the storage group that does nothing but thanks about security and how we can harden the products to make sure they stay secure and robust. And we keep the bad, the bad people away. >>Now that's excellent. Alright, So any predictions what we might see in the next 6 to 9 months, who from Dell Technologies with respect to helping customers who are hopefully have pivoted from this survival mode to now being able to thrive, leverage data extract values from it to identify new revenue streams renew products are new innovation. What do you see on the horizon? >>Yeah, I see just the continued acceleration of the technology. I see Dell Technologies spending a lot of our time focused on solutions so that when we can go into a customer environment, we talk about solutions. We talk about how we can get time to value. So how quickly can we get up the customer up and running with a known good configuration? You know, supportable. It's enterprise grade on. We can have our customers spend time writing code and developing new applications and not worrying about how to go build that infrastructure. So you're gonna see a lot of things. A lot of partnerships across our entire infrastructure team, which internally we call I S G. And we're really working together is one SG team to make sure all of our networking, our storage and our compute and all of the software that goes around that we act as 111 overall family for our customers provide that solution. And we also partner very close with VM ware to provide that software layer. So that again when we go to our customers, uh, and they want to start a new project. We have all of the tools within our portfolio. Uh, we've been around for a very long time. We have very strong focus on both the horizontal, the various workloads that customers were running and also very specific vertical through the industry and teams that just are dedicated on that. So But I think you're going to see a lot more. Is the solution based approaches where we could go into customers? We can provide that solution, and it's up and running in the very, very short amount. All right, >>last question. You said you mentioned you guys have been doing this a long time. I know you've been with Dell for 10 years. What are the three things that you would say if you're in a customer situation and they're looking at Dell and maybe they're looking at HP, for example, or some other competitors? One of the three things that you think really differentiate what Dell Technologies can deliver with respect to extracting value from massive amounts of unstructured data. >>Absolutely. I mean, this is where I get really excited when I'm so proud to be at del, uh, because if I look at all of the advantages that we have that we could bring to our customers. We have just the knowledge. So I think first and foremost when it comes to on structure data, we have been the most prevalent player in the market. And again, if you take a look at different verticals, think about like media and entertainment. We've won an Emmy just because we've been around and we have the technology that's really met the needs. We, um but that's one. We have all of the deep knowledge, and that's really going to give a lot of benefit to our customers to we've got the breath of the portfolio. So not only do we have very specific knowledge in one area where actually cover all of the unstructured portfolio for our customers needs, whether that's file or object or streaming data might even be the data management data management. When we have data I Q. To help our customers understand that data. Our portfolio is really broad, so deep knowledge we have a broad portfolio and then we have the overall Dell Technologies family that that we go forward with. So again, it's not just about the unstructured data. It's everything that goes around that it's the servers. It's that computes all the infrastructure. But it's the software that's also our partners and that whole ecosystem that we built up across the technologies. That's what really makes us strong and really the best person to partner with >>excellent knowledge, bread and a large ecosystem. John, thank you so much for joining us on the Cube today, talking to us about all the exciting things that you're working on. What's to come? We appreciate your time. >>Thank you very much >>for John Shirley. I'm Lisa Martin. You're watching the Cubes Coverage of Dell Technologies World 2020.

>>We're here at the Data cloud Summer 2020. Tracking the rise of the data cloud. We're talking about the ecosystem powering the next generation of innovation in cloud. You know, for decades, the technology industry has been powered by great products. Well, the cloud introduced a new type of platform that transcended point products. And the next generation of cloud platforms is unlocking data centric ecosystems where access to data is that the core of innovation tapping the resource is of many versus the capabilities of one. Casey McGee is here. He's the vice president of Global I S V. Sales at Microsoft in He's joined by Colleen Capsule, who is the VP of partnerships and global alliances that snowflake folks, welcome to the Cube. It's great to see you. Thanks. >>Very good to see you. Thank you. >>You're >>very welcome. So, Casey, let me start with you, please. Microsoft's get a long heritage. Of course, working with partners renowned in that regard built a unbelievable ecosystem, the envy of many in the industry. So if you think about as enterprises, they're speeding up their cloud adoption. What are you seeing is the role and the importance of ecosystem the i s v ecosystem specifically in helping make customers outcomes successful. >>Yeah, let me start by saying, we have, ah, 45 year history of partnerships. So from our very beginning as a company, we invested to build these partnerships. And so let me start by saying from day one we looked at a diverse ecosystem as one of the most important strategies for us, uh, both to bring innovation to customers and also to drive growth. And so we're looking to build that environment even today. So 45 years later, focused on how do we zero in on the business outcomes that matter most to >>customers usually >>identified by the industry that they're serving and so really building an ecosystem that helps us serve >>both the >>customers and the business outcomes They're looking to drive. And so we're building that ecosystem of SVs on the Microsoft cloud and focused on bringing that innovation as a platform provider through those companies. >>Okay, so let's let's stay on that for a moment if we can. I mean, you work with a lot of I s V s and you got a big portfolio of your own solutions. Now, sometimes they overlap with the I S V offerings of your partners. How do you balance the focus on, you know, First Party Solutions and third party I E S p Partner Solutions? >>Yeah, First and foremost, we're a platform company. So our whole intent is to bring value to that partner ecosystem. While sometimes that means we may have offers in market day that may complement one another. Our focus is really on serving the customer. So anytime we see that we're looking at what is the most desired outcome for a customer driving innovation into that into that specific business requirements? So for us, it's always focusing on the customer and really zeroing in on making sure that we're solving their business problems. Sometimes we do that together with partners like snowflakes. Sometimes that means we do that on our own. But the key for us is really deeply understanding what's important customer and then bringing the best of the Microsoft and Snowflakes scenarios to bear. >>You know, Casey, I appreciate that a lot of times people say Dave, don't Don't ask me that question. It's kind of uncomfortable. So, Colleen, I wanna bring you into the discussion. How does snowflake view this dynamic? Where you simultaneously partnering and competing sometimes with some of the big cloud companies on the planet? >>Yeah, Dave, I think it's a great question. And really, in this era of innovation, so many large companies, like Microsoft are so diverse in their products, said it's almost impossible for them to not have some overlap with most of their ecosystem. But I think Casey said it really well to long as we stay laser focused on the customer. Um, and there are a lot of very happy snowflake customers and happy as your customers, we really win together. And I think we're finding ways in which we're working better and better together, uh, from a technology standpoint and from a field standpoint. And customers want to see us come together and bring best of breed solution. So, um, I think we're doing a lot better, and I'm looking forward to our future to >>So Casey Snowflake, you know, they're really growing. They got a pretty large footprint on on Azure because they're gonna hundreds of customers here, you know, that are active on that platform. I >>wonder if you >>could talk about the product integration points that you kind of completed initially on then kind of what's on the horizon that you see is particularly important for your joint customers. >>You have to say so. One of the things that I love about this partnership is that while we start with what the customer wants, we bring that back into the engineering level relationship that we have between the two companies. And so that's produced some pretty, incredibly rich functionality together. So let me start by saying, You know, we've got eight azure regions today, with nine coming on soon on. So we have a geographic diversity that is important for many of our customers. We've also got a Siris of engineering level integrations that we've already built. So that's functionality for Azure privately because well, as integration between power bi I, Azure data factory and Azure data, like all of this back again to serve the business outcomes that are required for our customers. So it's this level of integration that I think really speaks to the power of the partnership, so were intently focused on the democratization of data. So we know that snowflake is the premier partner to help us do that so getting that right >>is >>key to enabling high concurrency use cases with large numbers of businesses, users coming together and getting the performance they expect. >>I appreciate that case because a lot of times, you know, look at the press release. Sometimes we laugh. We call them Barney deals. You know I love you, You love me. But I listened for, you know, the word engineering and integration. Those air sort of important triggers Colleen or Casey, too. But I want to start with Colleen. Anything you would add to that. Are there things that you guys have worked on together that you're particularly proud of, or maybe that have push the envelope and enabled new capabilities for customers Would have given you great feedback Any any examples you can share >>Great question on beer, definitely focusing on making sure stability is a core value for both of us, and so that what we offer that our customers can trust eyes going to work well and be dependable. So that's a key focus for us. Um, we're also looking at How can we advance into the future? What can we do around machine learning? It's a an area that's really exciting for a lot of the sea XO level leadership at our customers. So we're certainly focused on that. Um, and also looking at power bi I and the visualization of how do we bring these solutions together as well? I'd also say, at the same time, we're trying to make the buying experience frictionless for our customers. So we're also leveraging and innovating with azure is market place so that our customers can easily acquire Snowflake together with azure. And even that is being helpful for our customers. Casey, what are your thoughts too? Let me add to >>that. I think the work that we've done with power bi I is >>pretty >>pretty powerful. I mean, ultimately, we've got customers out there that are looking to better visualize the data better informed decisions that they're making so as much as a i n m l. And the inherent power of the data that's being stored within snowflake, um is important in and of itself. How r b I really unlocks that and helps drive better decisions, better visualization. Onda helped drive to decision outcomes that are important to the customer. So I love the work that we're doing on power by on stuff >>like, Yeah, >>you guys both mentioned, you know, machine learning. I mean, there really are an ecosystem of tools. And the thing to me about azure, it's It's all about Optionality you mentioned earlier case. You guys are a platform. So, you know, customer A may want to use power. Bi I. Another custom might want to use another visualization tool. Find from a platform perspective. You really don't care, do you? So I wonder, Colleen, if we could and again maybe case you can chime in afterwards. You guys, obviously everybody these days, but you particularly focused on customer outcomes. That's the sort of starting point and snowflake for sure, is built pretty significant experience Working with large enterprises and working along the side alongside of Microsoft. You get other partners in your experience what a customer is really looking for out of the two joint companies when they engage with Snowflake and Microsoft, so that one plus one is, you know, much bigger than 2 may be calling. You could start. >>Yeah, I definitely think that what our customers are looking for is both trust and seamlessness. They just want the technology to work. The beauty of snowflake is our ease of use. Um, so many customers have questions about their business. More so now in this guy, um, you know, pandemic world than ever before. So the seamlessness, the ease of use, um, the frictionless. All of these things really matter to our joint customers and seeing our teams come together to in the field to show. Here's how Snowflake and Azure are better together, um, in your local area and having examples of customers where we've had wind winds, which I'd say, Casey, we're getting more and more of those every day, frankly, so pretty exciting times Onda having our sales teams work as a partnership. Even though we compete, we know where we play well together on guy. See us doing that over and over again, more and more around the world to which is really important as snowflake pushes forward, you know, beyond the North America, geography ease into stronger and stronger in the global, um, regions where frankly, Microsoft had a long, storied history at, so that's very exciting, especially in Europe and Asia. >>Okay, so anything you would add to that >>Yeah, >>calling it's well said, I think it ultimately, what customers are looking for is that when our two companies come together, we bring new innovation, new ideas, new ways to solve old problems. And so I think what I love about this partnership is ultimately when we come together, whether it's engineering teams coming together to build new product, whether it's our sales and marketing teams out in front of the customers across that spectrum, I think customers looking for US toe help bring new ideas. And I love the fact that we've engineered this partnership to do to do just that. But ultimately we're focused on how do we come together and build something new and different? And I think we can solve some of the most challenging problems with the power of the data on the innovation that we're bringing to the table. >>I mean, you know, Casey, I mean, everybody is really quite an odd and amazed that Microsoft's transformation, um and really openness and willingness to really, really change and lean into some of the big waves. I >>wonder if you >>could talk about your multi platform strategy and what problems that you're solving in conjunction with snowflake. >>Yeah, let me start by saying, You know, I think as much as we appreciate that that feedback on on the progress that we've been striving for. I mean, we're still learning every day, looking for new opportunities to learn from customers from partners. And so, ah, lot of what you see on the outside is the result of a really focused culture really focusing on what's important to our customers focusing on how do we build diversity and inclusion to everything we do, whether that's within Microsoft with our partners or customers on. Ultimately, how do we show up? Aziz? One Microsoft. I call one Microsoft kind of the partners gift. It's ultimately how do our companies show up together? So I think if you look multi platform, we have the same concept, right? We have the Microsoft cloud that we're offering out in the marketplace. The Microsoft Cloud consists of what we're serving up. A Sfar is the platform consists what we're serving up for data and AI modern workplace on business applications. And so this multi cloud strategy for us is really focused on how do we bring innovation across each of the solution areas that matter most to customers And so I see, Really, the power of the snowflake partnership playing in there. >>Awesome calling. Are there any examples you can share Where, you know, maybe this partnership is unlocked. The customer opportunity or unique value? >>Yeah. I can't speak about the customer specific, but what I can do and say is, um you know, Casey and I play very corporate roles in terms of we're thinking about the long term partnership. We're driving the strategy. Um, hey, look, we'll get called in. We're working a deal right now. It's almost close of, uh, of the quarter for us who are literally working on an opportunity right now. How can we win together? How can we be competitive? The customers? The CEO has asked us to come together to work out that solution. Um, very large, well known brand and were able to get up to the very senior levels of our customer era companies very quickly to make decisions on what do we need to do to be better and stronger together? And, uh um, that's really what a partnership is about. You could do the long term plans in the strategic, and you can have great products But when you're executives, come pick up the phone and call each other toe work on a particular deal for particular customers need, uh, I think that's where the power of the partnership really comes together. And that's where we're at. And that's been a growth opportunity for us. This year's wasn't necessarily where we were at. And I really have to thank Casey for that. He's done a ton, Um, you know, getting us the right glue between our executives, making sure the relationships air there and making sure the trust is there. So when our customers needs to come together, that dialogue and the that shared addiction of putting customers first is there between both companies. So thank you, Casey. >>No, thanks. Coming. Feeling's mutual. >>Well, I think this is key because as a cent upfront, we've gone from sort of very product focused the platform focus. And now we're tapping the power of the ecosystem. That's not always easy to get all the parts moving together. But we live in this. A P I economy you could say is, Hey, I'm I'm a company. Everything is gonna be homogeneous. Everything is gonna be my stack and maybe That's one way to solve the problem. But really, that's not how customers want to solve the problem. Okay, so I'll give you last word. >>Yeah, let me just end by saying, You know, first off, the cultures between our two companies couldn't be more well aligned. So I think ultimately, when you ask yourself the question, what do we do? The best show up in front of our customers. It is focused on there. This is outcomes focused on the things that matter most to them. And this partnership will show up well, I think ultimately our greatest opportunity eyes to tap into that need that interest on. I couldn't be happier about the partnership on the fact that we are so well aligned. So thank you for that. >>Well, guys, thanks very much for coming in the Cube and unpacking some of the really critical aspects of the ecosystem was really a pleasure having you. >>Thank you so much for having us. Alright, >>Keep it right there. Everybody, this is Dave Volonte for the Cube were powering on with data Cloud Summit 2020. Keep it right there.

>>from around the globe. It's the Q. With digital coverage >>of exa scale day made possible by Hewlett Packard Enterprise. We're back at the celebration of Exa Scale Day. This is Dave Volant, and I'm pleased to welcome to great guests Brian Dance Berries Here. Here's what The ISS Program Science office at the Johnson Space Center. And Dr Mark Fernandez is back. He's the Americas HPC technology officer at Hewlett Packard Enterprise. Gentlemen, welcome. >>Thank you. Yeah, >>well, thanks for coming on. And, Mark, Good to see you again. And, Brian, I wonder if we could start with you and talk a little bit about your role. A T. I s s program Science office as a scientist. What's happening these days? What are you working on? >>Well, it's been my privilege the last few years to be working in the, uh, research integration area of of the space station office. And that's where we're looking at all of the different sponsors NASA, the other international partners, all the sponsors within NASA, and, uh, prioritizing what research gets to go up to station. What research gets conducted in that regard. And to give you a feel for the magnitude of the task, but we're coming up now on November 2nd for the 20th anniversary of continuous human presence on station. So we've been a space faring society now for coming up on 20 years, and I would like to point out because, you know, as an old guy myself, it impresses me. That's, you know, that's 25% of the US population. Everybody under the age of 20 has never had a moment when they were alive and we didn't have people living and working in space. So Okay, I got off on a tangent there. We'll move on in that 20 years we've done 3000 experiments on station and the station has really made ah, miraculously sort of evolution from, ah, basic platform, what is now really fully functioning national lab up there with, um, commercially run research facilities all the time. I think you can think of it as the world's largest satellite bus. We have, you know, four or five instruments looking down, measuring all kinds of things in the atmosphere during Earth observation data, looking out, doing astrophysics, research, measuring cosmic rays, X ray observatory, all kinds of things, plus inside the station you've got racks and racks of experiments going on typically scores, you know, if not more than 50 experiments going on at any one time. So, you know, the topic of this event is really important. Doesn't NASA, you know, data transmission Up and down, all of the cameras going on on on station the experiments. Um, you know, one of one of those astrophysics observatory's you know, it has collected over 15 billion um uh, impact data of cosmic rays. And so the massive amounts of data that that needs to be collected and transferred for all of these experiments to go on really hits to the core. And I'm glad I'm able toe be here and and speak with you today on this. This topic. >>Well, thank you for that, Bryan. A baby boomer, right? Grew up with the national pride of the moon landing. And of course, we've we've seen we saw the space shuttle. We've seen international collaboration, and it's just always been something, you know, part of our lives. So thank you for the great work that you guys were doing their mark. You and I had a great discussion about exa scale and kind of what it means for society and some of the innovations that we could maybe expect over the coming years. Now I wonder if you could talk about some of the collaboration between what you guys were doing and Brian's team. >>Uh, yeah, so yes, indeed. Thank you for having me early. Appreciate it. That was a great introduction. Brian, Uh, I'm the principal investigator on Space Born computer, too. And as the two implies, where there was one before it. And so we worked with Bryant and his team extensively over the past few years again high performance computing on board the International Space Station. Brian mentioned the thousands of experiments that have been done to date and that there are currently 50 orm or going on at any one time. And those experiments collect data. And up until recently, you've had to transmit that data down to Earth for processing. And that's a significant amount of bandwidth. Yeah, so with baseball and computer to we're inviting hello developers and others to take advantage of that onboard computational capability you mentioned exa scale. We plan to get the extra scale next year. We're currently in the era that's called PETA scale on. We've been in the past scale era since 2000 and seven, so it's taken us a while to make it that next lead. Well, 10 years after Earth had a PETA scale system in 2017 were able to put ah teraflop system on the International space station to prove that we could do a trillion calculations a second in space. That's where the data is originating. That's where it might be best to process it. So we want to be able to take those capabilities with us. And with H. P. E. Acting as a wonderful partner with Brian and NASA and the space station, we think we're able to do that for many of these experiments. >>It's mind boggling you were talking about. I was talking about the moon landing earlier and the limited power of computing power. Now we've got, you know, water, cool supercomputers in space. I'm interested. I'd love to explore this notion of private industry developing space capable computers. I think it's an interesting model where you have computer companies can repurpose technology that they're selling obviously greater scale for space exploration and apply that supercomputing technology instead of having government fund, proprietary purpose built systems that air. Essentially, you use case, if you will. So, Brian, what are the benefits of that model? The perhaps you wouldn't achieve with governments or maybe contractors, you know, kind of building these proprietary systems. >>Well, first of all, you know, any any tool, your using any, any new technology that has, you know, multiple users is going to mature quicker. You're gonna have, you know, greater features, greater capabilities, you know, not even talking about computers. Anything you're doing. So moving from, you know, governor government is a single, um, you know, user to off the shelf type products gives you that opportunity to have things that have been proven, have the technology is fully matured. Now, what had to happen is we had to mature the space station so that we had a platform where we could test these things and make sure they're gonna work in the high radiation environments, you know, And they're gonna be reliable, because first, you've got to make sure that that safety and reliability or taken care of so that that's that's why in the space program you're gonna you're gonna be behind the times in terms of the computing power of the equipment up there because, first of all and foremost, you needed to make sure that it was reliable and say, Now, my undergraduate degree was in aerospace engineering and what we care about is aerospace engineers is how heavy is it, how big and bulky is it because you know it z expensive? You know, every pound I once visited Gulfstream Aerospace, and they would pay their employees $1000 that they could come up with a way saving £1 in building that aircraft. That means you have more capacity for flying. It's on the orders of magnitude. More important to do that when you're taking payloads to space. So you know, particularly with space born computer, the opportunity there to use software and and check the reliability that way, Uh, without having to make the computer, you know, radiation resistance, if you will, with heavy, you know, bulky, um, packaging to protect it from that radiation is a really important thing, and it's gonna be a huge advantage moving forward as we go to the moon and on to Mars. >>Yeah, that's interesting. I mean, your point about cots commercial off the shelf technology. I mean, that's something that obviously governments have wanted to leverage for a long, long time for many, many decades. But but But Mark the issue was always the is. Brian was just saying the very stringent and difficult requirements of space. Well, you're obviously with space Born one. You got to the point where you had visibility of the economics made sense. It made commercial sense for companies like Hewlett Packard Enterprise. And now we've sort of closed that gap to the point where you're sort of now on that innovation curve. What if you could talk about that a little bit? >>Yeah, absolutely. Brian has some excellent points, you know, he said, anything we do today and requires computers, and that's absolutely correct. So I tell people that when you go to the moon and when you go to the Mars, you probably want to go with the iPhone 10 or 11 and not a flip phone. So before space born was sent up, you went with 2000 early two thousands computing technology there which, like you said many of the people born today weren't even around when the space station began and has been occupied so they don't even know how to program or use that type of computing. Power was based on one. We sent the exact same products that we were shipping to customers today, so they are current state of the art, and we had a mandate. Don't touch the hardware, have all the protection that you can via software. So that's what we've done. We've got several philosophical ways to do that. We've implemented those in software. They've been successful improving in the space for one, and now it's space born to. We're going to begin the experiments so that the rest of the community so that the rest of the community can figure out that it is economically viable, and it will accelerate their research and progress in space. I'm most excited about that. Every venture into space as Brian mentioned will require some computational capability, and HP has figured out that the economics air there we need to bring the customers through space ball into in order for them to learn that we are reliable but current state of the art, and that we could benefit them and all of humanity. >>Guys, I wanna ask you kind of a two part question. And, Brian, I'll start with you and it z somewhat philosophical. Uh, I mean, my understanding was and I want to say this was probably around the time of the Bush administration w two on and maybe certainly before that, but as technology progress, there was a debate about all right, Should we put our resource is on moon because of the proximity to Earth? Or should we, you know, go where no man has gone before and or woman and get to Mars? Where What's the thinking today, Brian? On that? That balance between Moon and Mars? >>Well, you know, our plans today are are to get back to the moon by 2024. That's the Artemus program. Uh, it's exciting. It makes sense from, you know, an engineering standpoint. You take, you know, you take baby steps as you continue to move forward. And so you have that opportunity, um, to to learn while you're still, you know, relatively close to home. You can get there in days, not months. If you're going to Mars, for example, toe have everything line up properly. You're looking at a multi year mission you know, it may take you nine months to get there. Then you have to wait for the Earth and Mars to get back in the right position to come back on that same kind of trajectory. So you have toe be there for more than a year before you can turn around and come back. So, you know, he was talking about the computing power. You know, right now that the beautiful thing about the space station is, it's right there. It's it's orbiting above us. It's only 250 miles away. Uh, so you can test out all of these technologies. You can rely on the ground to keep track of systems. There's not that much of a delay in terms of telemetry coming back. But as you get to the moon and then definitely is, you get get out to Mars. You know, there are enough minutes delay out there that you've got to take the computing power with you. You've got to take everything you need to be able to make those decisions you need to make because there's not time to, um, you know, get that information back on the ground, get back get it back to Earth, have people analyze the situation and then tell you what the next step is to do. That may be too late. So you've got to think the computing power with you. >>So extra scale bring some new possibilities. Both both for, you know, the moon and Mars. I know Space Born one did some simulations relative. Tomorrow we'll talk about that. But But, Brian, what are the things that you hope to get out of excess scale computing that maybe you couldn't do with previous generations? >>Well, you know, you know, market on a key point. You know, bandwidth up and down is, of course, always a limitation. In the more computing data analysis you can do on site, the more efficient you could be with parsing out that that bandwidth and to give you ah, feel for just that kind of think about those those observatory's earth observing and an astronomical I was talking about collecting data. Think about the hours of video that are being recorded daily as the astronauts work on various things to document what they're doing. They many of the biological experiments, one of the key key pieces of data that's coming back. Is that video of the the microbes growing or the plants growing or whatever fluid physics experiments going on? We do a lot of colloids research, which is suspended particles inside ah liquid. And that, of course, high speed video. Is he Thio doing that kind of research? Right now? We've got something called the I s s experience going on in there, which is basically recording and will eventually put out a syriza of basically a movie on virtual reality recording. That kind of data is so huge when you have a 360 degree camera up there recording all of that data, great virtual reality, they There's still a lot of times bringing that back on higher hard drives when the space six vehicles come back to the Earth. That's a lot of data going on. We recorded videos all the time, tremendous amount of bandwidth going on. And as you get to the moon and as you get further out, you can a man imagine how much more limiting that bandwidth it. >>Yeah, We used to joke in the old mainframe days that the fastest way to get data from point a to Point B was called C Tam, the Chevy truck access method. Just load >>up a >>truck, whatever it was, tapes or hard drive. So eso and mark, of course space born to was coming on. Spaceport one really was a pilot, but it proved that the commercial computers could actually work for long durations in space, and the economics were feasible. Thinking about, you know, future missions and space born to What are you hoping to accomplish? >>I'm hoping to bring. I'm hoping to bring that success from space born one to the rest of the community with space born to so that they can realize they can do. They're processing at the edge. The purpose of exploration is insight, not data collection. So all of these experiments begin with data collection. Whether that's videos or samples are mold growing, etcetera, collecting that data, we must process it to turn it into information and insight. And the faster we can do that, the faster we get. Our results and the better things are. I often talk Thio College in high school and sometimes grammar school students about this need to process at the edge and how the communication issues can prevent you from doing that. For example, many of us remember the communications with the moon. The moon is about 250,000 miles away, if I remember correctly, and the speed of light is 186,000 miles a second. So even if the speed of light it takes more than a second for the communications to get to the moon and back. So I can remember being stressed out when Houston will to make a statement. And we were wondering if the astronauts could answer Well, they answered as soon as possible. But that 1 to 2 second delay that was natural was what drove us crazy, which made us nervous. We were worried about them in the success of the mission. So Mars is millions of miles away. So flip it around. If you're a Mars explorer and you look out the window and there's a big red cloud coming at you that looks like a tornado and you might want to do some Mars dust storm modeling right then and there to figure out what's the safest thing to do. You don't have the time literally get that back to earth have been processing and get you the answer back. You've got to take those computational capabilities with you. And we're hoping that of these 52 thousands of experiments that are on board, the SS can show that in order to better accomplish their missions on the moon. And Omar, >>I'm so glad you brought that up because I was gonna ask you guys in the commercial world everybody talks about real time. Of course, we talk about the real time edge and AI influencing and and the time value of data I was gonna ask, you know, the real time, Nous, How do you handle that? I think Mark, you just answered that. But at the same time, people will say, you know, the commercial would like, for instance, in advertising. You know, the joke the best. It's not kind of a joke, but the best minds of our generation tryingto get people to click on ads. And it's somewhat true, unfortunately, but at any rate, the value of data diminishes over time. I would imagine in space exploration where where you're dealing and things like light years, that actually there's quite a bit of value in the historical data. But, Mark, you just You just gave a great example of where you need real time, compute capabilities on the ground. But but But, Brian, I wonder if I could ask you the value of this historic historical data, as you just described collecting so much data. Are you? Do you see that the value of that data actually persists over time, you could go back with better modeling and better a i and computing and actually learn from all that data. What are your thoughts on that, Brian? >>Definitely. I think the answer is yes to that. And, you know, as part of the evolution from from basically a platform to a station, we're also learning to make use of the experiments in the data that we have there. NASA has set up. Um, you know, unopened data access sites for some of our physical science experiments that taking place there and and gene lab for looking at some of the biological genomic experiments that have gone on. And I've seen papers already beginning to be generated not from the original experimenters and principal investigators, but from that data set that has been collected. And, you know, when you're sending something up to space and it to the space station and volume for cargo is so limited, you want to get the most you can out of that. So you you want to be is efficient as possible. And one of the ways you do that is you collect. You take these earth observing, uh, instruments. Then you take that data. And, sure, the principal investigators air using it for the key thing that they designed it for. But if that data is available, others will come along and make use of it in different ways. >>Yeah, So I wanna remind the audience and these these these air supercomputers, the space born computers, they're they're solar powered, obviously, and and they're mounted overhead, right? Is that is that correct? >>Yeah. Yes. Space borne computer was mounted in the overhead. I jokingly say that as soon as someone could figure out how to get a data center in orbit, they will have a 50 per cent denser data station that we could have down here instead of two robes side by side. You can also have one overhead on. The power is free. If you can drive it off a solar, and the cooling is free because it's pretty cold out there in space, so it's gonna be very efficient. Uh, space borne computer is the most energy efficient computer in existence. Uh, free electricity and free cooling. And now we're offering free cycles through all the experimenters on goal >>Eso Space born one exceeded its mission timeframe. You were able to run as it was mentioned before some simulations for future Mars missions. And, um and you talked a little bit about what you want to get out of, uh, space born to. I mean, are there other, like, wish list items, bucket bucket list items that people are talking about? >>Yeah, two of them. And these air kind of hypothetical. And Brian kind of alluded to them. Uh, one is having the data on board. So an example that halo developers talk to us about is Hey, I'm on Mars and I see this mold growing on my potatoes. That's not good. So let me let me sample that mold, do a gene sequencing, and then I've got stored all the historical data on space borne computer of all the bad molds out there and let me do a comparison right then and there before I have dinner with my fried potato. So that's that's one. That's very interesting. A second one closely related to it is we have offered up the storage on space borne computer to for all of your raw data that we process. So, Mr Scientist, if if you need the raw data and you need it now, of course, you can have it sent down. But if you don't let us just hold it there as long as they have space. And when we returned to Earth like you mentioned, Patrick will ship that solid state disk back to them so they could have a new person, but again, reserving that network bandwidth, uh, keeping all that raw data available for the entire duration of the mission so that it may have value later on. >>Great. Thank you for that. I want to end on just sort of talking about come back to the collaboration between I S s National Labs and Hewlett Packard Enterprise, and you've got your inviting project ideas using space Bourne to during the upcoming mission. Maybe you could talk about what that's about, and we have A We have a graphic we're gonna put up on DSM information that you can you can access. But please, mark share with us what you're planning there. >>So again, the collaboration has been outstanding. There. There's been a mention off How much savings is, uh, if you can reduce the weight by a pound. Well, our partners ice s national lab and NASA have taken on that cost of delivering baseball in computer to the international space station as part of their collaboration and powering and cooling us and giving us the technical support in return on our side, we're offering up space borne computer to for all the onboard experiments and all those that think they might be wanting doing experiments on space born on the S s in the future to take advantage of that. So we're very, very excited about that. >>Yeah, and you could go toe just email space born at hp dot com on just float some ideas. I'm sure at some point there'll be a website so you can email them or you can email me david dot volonte at at silicon angle dot com and I'll shoot you that that email one or that website once we get it. But, Brian, I wanna end with you. You've been so gracious with your time. Uh, yeah. Give us your final thoughts on on exa scale. Maybe how you're celebrating exa scale day? I was joking with Mark. Maybe we got a special exa scale drink for 10. 18 but, uh, what's your final thoughts, Brian? >>Uh, I'm going to digress just a little bit. I think I think I have a unique perspective to celebrate eggs a scale day because as an undergraduate student, I was interning at Langley Research Center in the wind tunnels and the wind tunnel. I was then, um, they they were very excited that they had a new state of the art giant room size computer to take that data we way worked on unsteady, um, aerodynamic forces. So you need a lot of computation, and you need to be ableto take data at a high bandwidth. To be able to do that, they'd always, you know, run their their wind tunnel for four or five hours. Almost the whole shift. Like that data and maybe a week later, been ableto look at the data to decide if they got what they were looking for? Well, at the time in the in the early eighties, this is definitely the before times that I got there. They had they had that computer in place. Yes, it was a punchcard computer. It was the one time in my life I got to put my hands on the punch cards and was told not to drop them there. Any trouble if I did that. But I was able thio immediately after, uh, actually, during their run, take that data, reduce it down, grabbed my colored pencils and graph paper and graph out coefficient lift coefficient of drag. Other things that they were measuring. Take it back to them. And they were so excited to have data two hours after they had taken it analyzed and looked at it just pickled them. Think that they could make decisions now on what they wanted to do for their next run. Well, we've come a long way since then. You know, extra scale day really, really emphasizes that point, you know? So it really brings it home to me. Yeah. >>Please, no, please carry on. >>Well, I was just gonna say, you know, you talked about the opportunities that that space borne computer provides and and Mark mentioned our colleagues at the I S s national lab. You know, um, the space station has been declared a national laboratory, and so about half of the, uh, capabilities we have for doing research is a portion to the national lab so that commercial entities so that HP can can do these sorts of projects and universities can access station and and other government agencies. And then NASA can focus in on those things we want to do purely to push our exploration programs. So the opportunities to take advantage of that are there marks opening up the door for a lot of opportunities. But others can just Google S s national laboratory and find some information on how to get in the way. Mark did originally using s national lab to maybe get a good experiment up there. >>Well, it's just astounding to see the progress that this industry is made when you go back and look, you know, the early days of supercomputing to imagine that they actually can be space born is just tremendous. Not only the impacts that it can have on Space six exploration, but also society in general. Mark Wayne talked about that. Guys, thanks so much for coming on the Cube and celebrating Exa scale day and helping expand the community. Great work. And, uh, thank you very much for all that you guys dio >>Thank you very much for having me on and everybody out there. Let's get the XO scale as quick as we can. Appreciate everything you all are >>doing. Let's do it. >>I've got a I've got a similar story. Humanity saw the first trillion calculations per second. Like I said in 1997. And it was over 100 racks of computer equipment. Well, space borne one is less than fourth of Iraq in only 20 years. So I'm gonna be celebrating exa scale day in anticipation off exa scale computers on earth and soon following within the national lab that exists in 20 plus years And being on Mars. >>That's awesome. That mark. Thank you for that. And and thank you for watching everybody. We're celebrating Exa scale day with the community. The supercomputing community on the Cube Right back

>>from Boston, Massachusetts. It's the Q covering I. F s World Conference 2019. Brought to you by I F s. Hi, buddy. Welcome to Boston. You're watching the cubes coverage of I s s World in the Heinz Auditorium in Boston. I'm Day Volonte with my co host, Paul Gill and Paul. This is the the largest enterprise resource planning software company that our audience probably has never heard of. This is our second year covering I f s World. Last year was in Atlanta. They moved to Boston. I f s is a Swedish based company. They do about $600 million in annual revenue, about 3700 employees. And interestingly, they have a development center in Sri Lanka, of all places. Which is kind of was war torn for the last 15 years or so, but nonetheless, evidently, a lot of talent and beautiful views, but so welcome. >>Thank you, Dave. I have to admit, before our coverage last year, I had never even heard of this company been around this industry for more than 30 years. Never heard of this company. They've got 10,000 customers. They've got a full house next door in the keynote and very enthusiastic group. This is a focus company. It's a company that has a lot of ah ah, vision about where wants to go some impressive vision documents and really a company that I think it's coming out of the shadows in the U. S. And it will be a force to be reckoned with. >>So I should say they were founded in the in the mid 19 eighties, and then it kind of re architected their whole platform around Client server. You remember the component move? It was a sort of big trends in the in the nineties. In the mid nineties opened up offices in the United States. We're gonna talk to the head of North America later, and that's one of the big growth areas that growing at about three. They claim to be growing at three x the overall market rate, which is a good benchmark. They're really their focus is really three areas e r. P asset management software and field service management, and they talk about deep functionality. So, for instance, they compete with Oracle ASAP. Certainly Microsoft and in four company we've covered in four talks a lot about the last mile functionality. That's not terminology that I f s uses, but they do similar types of things. I'll give you some examples because, okay, what's last mile? Functionality? Things like, um, detailed invoicing integration, contract management. Very narrow search results on things like I just want to search for a refurbished parts so they have functionality to allow you to do that. Chain. A custom e custody chain of custody for handling dangerous toxic chemicals. Certain modules to handle FDA compliance. A real kind of nitty gritty stuff to help companies avoid custom modifications in certain industries. Energy, construction, aerospace and defense is a big area for that. For them, a CZ well as manufacturing, >>there's a segment of the e r P market that often is under uh is under seeing. There's a lot of these companies that started out in niches Peoples off being a famous example, starting out on a niche of the market and then growing into other areas. And this company continues to be very focused even after 35 years, as you mentioned, just energy aerospace, a few construction, a few basic industries that they serve serve them at a very deep level focused on the mid market primarily, but they have a new positioning this year. They're calling the challengers for the challengers, which I like. It's a it's a message that I think resonates. It's easy to understand there position their customers is being the companies that are going to challenge the big guys in their industries and this time of digital transformation and disruption. You know, that's what it's all about. I think it's a great message of bringing out this year. >>Of course I like it because the Cube is a challenger, right? Okay, even though we're number one of the segments that we cover, we started out as a sort of a challenger. Interestingly, I f s and the gardener Magic Corners actually, leader and Field Service Management. They made an acquisition that they announced today of a company called Asked. He asked, U S he is a pink sheet OTC company. I mean, they're very small is a tuck in acquisition that maybe they had a They had a sub $20 million market cap. They probably do 25 $30 million in revenue. Um, Darren rules. The CEO said that this place is them is the leader in field service management, which is interesting. We're gonna ask him about that to your other point. You look around the ecosystem here that they have 400 partners. I was surprised last night. I came early to sort of walk around the hall floor. You see large companies here like Accenture. Um and I'm surprised. I mean, I remember the early days when we did the service. Now conferences 2013 or so you didn't see accent. You're Delloye E Y p W c. Now you see them at the service now event here that you see them? I mean, and I talked to essential last night. They said, Yeah, well, we actually do a lot of business in Europe, particularly in the Scandinavian region, and we want to grow the business in the U. S. >>Europe tends to be kind of a blind spot for us cos they don't see the size of the European market, all the activities where some of the great e. R. P. Innovation has come out of Europe. This company, as you mentioned growing three times the rate of the market, they have a ah focus on your very tight with those customers that they serve and they understand them very well. And this is a you can see why it's centuries is is serving this market because, you know they're simply following the money. There's only so much growth left in the S a P market in the Oracle market. But as the CEO Darren said this morning, Ah, half of their revenues last year were from net new customers. So that's that's a great metric. That indicates that there's a lot of new business for these partners to pursue. >>Well, I think there's there's some fatigue, obviously, for big, long multi year s AP integrations, you're also seeing, you know, at the macro we work with Enterprise Technology Research and we have access to their data set. One of the things that we're seeing is a slowdown in the macro. Clearly, buyers are planning to spend less on I T in the second half of 2019 than they did in the first half of 2019 and they expect to spend less in Q four than they expected to in July. So things are clearly softening at the macro level. They're reverting back to pre 2018 levels but it's not falling off a cliff. One of the things that I've talked to e t. R about the premise we put forth love to get your thoughts is essentially we started digital transformation projects, Let's say in earnest in 2016 2017 doing a lot of pilots started kind of pre production in 2018. And during that time, what people were doing is they were had a lot of redundancy. They would maintain the legacy systems and they were experimenting with disruptive technologies. You saw, obviously a lot of you. I path a lot of snowflake and other sort of disruptive technology. Certainly an infrastructure. Pure storage was the beneficiary of that. So you had this sort of dual strategy. We had redundancy of legacy systems, and then the new stuff. What's happening now is, is the theory is that we're going into production. Would digital transformation projects and where were killing the legacy stuff? Okay, we're ready to cut over >>to a new land on that anymore, >>right? We're not going to spend them anymore. Dial that down. Number one. Number two is we're not just gonna spray and pray on all new tech Blockchain a i rp et cetera. We're gonna now focus on those areas that we think are going to drive business value. So both the incumbents and the disruptors are getting somewhat affected by that. That slowdown in that narrowing of the focused. And so I think that's really what's happening. And we're gonna, I think, have to absorb that for a year or so before we start to see new wave of spending. >>There's been a lot of spending on I t over the last three years. As you say, driven by this need, this transition that's going on now we're being going to see some of those legacy systems turned off. The more important thing I have to look at, I think the overall spending is where is that money being spent is being spent on on servers or is it being spent on cloud service is, and I think you would see a fairly dramatic shift going on. They're so the overall, the macro. I think it's still healthy for I t. There's still a lot of spending going on, but it's shifting to a new area there. They're killing off some of that redundancy. >>Well, the TR data shows couple things. There's no question that server and storage spending is has been declining and attenuating for a number of quarters now. And there's been a shift going on from that. Core infrastructure, obviously, into Cloud Cloud continues its steady march in terms of taking over market share. Other areas of bright spots security is clearly one. You're seeing a lot of spending in an analytics, especially new analytics. I mentioned Snowflake before we're disrupting kind of terror Data's traditional legacy enterprise data warehouse market. The R P. A market is also very hot. You AI path is a company that continues to extend beyond its its peers, although I have to say automation anywhere looks very strong. Blue Prison looks very strong. Cloudera interestingly used to be the darling is hitting sort of all time lows in the E. T R database, which is, by the way, that one of the best data sets I've ever seen on on spending enterprise software is actually still pretty strong. Particularly, uh, you know, workday look strong. Sales force still looks pretty strong. Splunk Because of the security uplift, it still looks pretty strong. I have a lot of data on I f s Like you said, they don't really show up in the e t R survey base. Um, but I would expect, with kind of growth, we're seeing $600 million. Company hopes to be a $1,000,000,000 by 2022 2021. I would think they're going to start showing up in the spending >>service well again in Europe. They may be They may be more dominant player than we see in the US. As I said, I really had not even heard of the company before last year, which was surprising for a company with 10,000 customers. Again, they're focused on the mid market in the mid market tends to fly a bit under the radar. Everyone thinks about what's happening in the enterprise is a huge opportunity out there. Many more mid market companies and there are enterprises. And that's a that's been historically a fertile ground for e. R. P. Companies to launch. You know J. D. Edwards came out of the mid market thes are companies that may end up being acquired by the Giants, but they build up a very healthy base of customers, sort of under the radar. >>Well, the other point I wanted to make I kind of started to about the digital transformation is, as they say, people are getting sort of sick of the big, long, ASAP complicated implementations. As small companies become midsize companies and larger midsize companies, they they look toward an enterprise resource planning, type of, of platform. And they're probably saying, All right, wait. I've got some choices here. I could go with an an I F. S, you know, or maybe another alternative. T s a p. You know, A S A P is maybe maybe the safe bet. Although, you know, it looks like i f s is got when you look around at the customers, they have has some real traction, obviously a lot of references, no question about it. One of things they've been digging for saw this gardener doing them for a P I integrations. Well, they've announced some major AP I integrations. We're gonna talk to them about that and poke it that a little bit and see if that will So to solve that criticism, that what Gardner calls caution, you know, let's see how real that is in talking to some of the customers will be talkinto the executives on members of the ecosystem. And obviously Paul and I will be giving our analysis as well. Final thoughts >>here. Just the challenge, I think, is you note for these midmarket focus Cos. Has been growing with their customers. And that's why you see of Lawson's in the JD Edwards of the World. Many of these these mid market companies eventually are acquired by the big E R P vendors. The customers eventually, if they grow, have to go through this transition. If they're going to go to Enterprise. The R P you know, they're forced into a couple of big choices. The opportunity and the challenge for F s is, can they grow those customers as they move into enterprise grade size? Can they grow them with with E. I. F s product line without having them forcing them to transition to something bigger? >>So a lot of here a lot of action here in Boston, we heard from several outside speakers. There was Linda Hill from Harvard. They had a digital transformation CEO panel, the CEO of soo say who will be on later uh PTC, a Conway, former PeopleSoft CEO was on there. And then, of course, Tony Hawk, which was a lot of fun, obviously a challenger. All right, so keep it right there, buddy. You're watching the Cube live from I F s World Conference at the Heinz in Boston right back, right after this short break.

>> from our studios in the heart of Silicon Valley, Palo Alto, California It is >> a cute conversation. Hey, welcome back. Get ready. Geoffrey here with the Cube. We're gonna rip out the studios for acute conversation. It's the middle of the summer, the conference season to slow down a little bit. So we get a chance to do more cute conversation, which is always great. Excited of our next guest. He's Ridge, IP, Ops Statik. He's a VP and GM from key. Cite, Reject. Great to see you. >> Thank you for hosting us. >> Yeah. So we've had Marie on a couple of times. We had Bethany on a long time ago before the for the acquisition. But for people that aren't familiar with key site, give us kind of a quick overview. >> Sure, sure. So I'm within the excess solutions group Exhale really started was founded back in 97. It I peered around 2000 really started as a test and measurement company quickly after the I poet became the number one vendor in the space, quickly grew around 2012 and 2013 and acquired two companies Net optics and an ooey and net optics and I knew we were in the visibility or monitoring space selling taps, bypass witches and network packet brokers. So that formed the Visibility Group with a nice Xia. And then around 2017 key cite acquired Xia and we became I S G or extra Solutions group. Now, key site is also a very large test and measurement company. It is the actual original HB startup that started in Palo Alto many years ago. An HB, of course, grew, um it also started as a test and measurement company. Then later on it, it became a get a gun to printers and servers. HB spun off as agile in't, agile in't became the test and measurement. And then around 2014 I would say, or 15 agile in't spun off the test and measurement portion that became key site agile in't continued as a life and life sciences organization. And so key sites really got the name around 2014 after spinning off and they acquired Xia in 2017. So more joy of the business is testing measurement. But we do have that visibility and monitoring organization to >> Okay, so you do the test of measurement really on devices and kind of pre production and master these things up to speed. And then you're actually did in doing the monitoring in life production? Yes, systems. >> Mostly. The only thing that I would add is that now we are getting into live network testing to we see that mostly in the service provider space. Before you turn on the service, you need to make sure that all the devices and all the service has come up correctly. But also we're seeing it in enterprises to, particularly with security assessments. So reach assessment attacks. Security is your eye to organization really protecting the network? So we're seeing that become more and more important than they're pulling in test, particularly for security in that area to so as you. As you say, it's mostly device testing. But then that's going to network infrastructure and security networks, >> Right? So you've been in the industry for a while, you're it. Until you've been through a couple acquisitions, you've seen a lot of trends, so there's a lot of big macro things happening right now in the industry. It's exciting times and one of the ones. Actually, you just talked about it at Cisco alive a couple weeks ago is EJ Computer. There's a lot of talk about edges. Ej the new cloud. You know how much compute can move to the edge? What do you do in a crazy oilfield? With hot temperatures and no powers? I wonder if you can share some of the observations about EJ. You're kind of point of view as to where we're heading. And what should people be thinking about when they're considering? Yeah, what does EJ mean to my business? >> Absolutely, absolutely. So when I say it's computing, I typically include Io TI agent. It works is along with remote and branch offices, and obviously we can see the impact of Io TI security cameras, thermal starts, smart homes, automation, factory automation, hospital animation. Even planes have sensors on their engines right now for monitoring purposes and diagnostics. So that's one group. But then we know in our everyday lives, enterprises are growing very quickly, and they have remote and branch offices. More people are working from remotely. More people were working from home, so that means that more data is being generated at the edge. What it's with coyote sensors, each computing we see with oil and gas companies, and so it doesn't really make sense to generate all that data. Then you know, just imagine a self driving car. You need to capture a lot of data and you need to process. It just got really just send it to the cloud. Expect a decision to mate and then come back and so that you turn left or right, you need to actually process all that data, right? We're at the edge where the source of the data is, and that means pushing more of that computer infrastructure closer to the source. That also means running business critical applications closer to the source. And that means, you know, um, it's it's more of, ah, madness, massively distributed computer architecture. Um, what happens is that you have to then reliably connect all these devices so connectivity becomes important. But as you distribute, compute as well as applications, your attack surface increases right. Because all of these devices are very vulnerable. We're probably adding about 5,000,000 I ot devices every day to our network, So that's a lot of I O T. Devices or age devices that we connect many of these devices. You know, we don't really properly test. You probably know from your own home when you can just buy something and could easily connect it to your wife. I Similarly, people buy something, go to their work and connect to their WiFi. Not that device is connected to your entire network. So vulnerabilities in any of these devices exposes the entire network to that same vulnerability. So our attack surfaces increasing, so connection reliability as well as security for all these devices is a challenge. So we enjoy each computing coyote branch on road officers. But it does pose those challenges. And that's what we're here to do with our tech partners. Toe sold these issues >> right? It's just instinct to me on the edge because you still have kind of the three big um, the three big, you know, computer things. You got the networking right, which is just gonna be addressed by five g and a lot better band with and connectivity. But you still have store and you still have compute. You got to get those things Power s o a cz. You're thinking about the distribution of that computer and store at the edge versus in the cloud and you've got the Leighton see issue. It seems like a pretty delicate balancing act that people are gonna have to tune these systems to figure out how much to allocate where, and you will have physical limitations at this. You know the G power plant with the sure by now the middle of nowhere. >> It's It's a great point, and you typically get agility at the edge. Obviously, don't have power because these devices are small. Even if you take a room order branch office with 52 2 100 employees, there's only so much compute that you have. But you mean you need to be able to make decisions quickly. They're so agility is there. But obviously the vast amounts of computer and storage is more in your centralized data center, whether it's in your private cloud or your public cloud. So how do you do the compromise? When do you run applications at the edge when you were in applications in the cloud or private or public? Is that in fact, a compromise and year You might have to balance it, and it might change all the time, just as you know, if you look at our traditional history off compute. He had the mainframes which were centralized, and then it became distributed, centralized, distributed. So this changes all the time and you have toe make decisions, which which brings up the issue off. I would say hybrid, I t. You know, they have the same issue. A lot of enterprises have more of a, um, hybrid I t strategy or multi cloud. Where do you run the applications? Even if you forget about the age even on, do you run an on Prem? Do you run in the public cloud? Do you move it between class service providers? Even that is a small optimization problem. It's now even Matt bigger with H computer. >> Right? So the other thing that we've seen time and time again a huge trend, right? It's software to find, um, we've seen it in the networking space to compete based. It's offered to find us such a big write such a big deal now and you've seen that. So when you look at it from a test a measurement and when people are building out these devices, you know, obviously aton of great functional capability is suddenly available to people, but in terms of challenges and in terms of what you're thinking about in software defined from from you guys, because you're testing and measuring all this stuff, what's the goodness with the badness house for people, you really think about the challenges of software defined to take advantage of the tremendous opportunity. >> That's a really good point. I would say that with so far defined it working What we're really seeing is this aggregation typically had these monolithic devices that you would purchase from one vendor. That wonder vendor would guarantee that everything just works perfectly. What software defined it working, allows or has created is this desegregated model. Now you have. You can take that monolithic application and whether it's a server or a hardware infrastructure, then maybe you have a hyper visor or so software layer hardware, abstraction, layers and many, many layers. Well, if you're trying to get that toe work reliably, this means that now, in a way, the responsibility is on you to make sure that you test every all of these. Make sure that everything just works together because now we have choice. Which software packages should I install from which Bender This is always a slight differences. Which net Nick Bender should I use? If PJ smart Nick Regular Nick, you go up to the layer of what kind of ax elation should I use? D. P. D K. There's so many options you are responsible so that with S T N, you do get the advantage of opportunity off choice, just like on our servers and our PCs. But this means that you do have to test everything, make sure that everything works. So this means more testing at the device level, more testing at the service being up. So that's the predeployment stage and wants to deploy the service. Now you have to continually monitor it to make sure that it's working as you expected. So you get more choice, more diversity. And, of course, with segregation, you can take advantage of improvements on the hardware layer of the software layer. So there's that the segregation advantage. But it means more work on test as well as monitoring. So you know there's there's always a compromise >> trade off. Yeah, so different topic is security. Um, weird Arcee. This year we're in the four scout booth at a great chat with Michael the Caesars Yo there. And he talked about, you know, you talk a little bit about increasing surface area for attack, and then, you know, we all know the statistics of how long it takes people to know that they've been reach its center center. But Mike is funny. He you know, they have very simple sales pitch. They basically put their sniffer on your network and tell you that you got eight times more devices on the network than you thought. Because people are connecting all right, all types of things. So when you look at, you know, kind of monitoring test, especially with these increased surface area of all these, Iet devices, especially with bring your own devices. And it's funny, the H v A c seemed to be a really great place for bad guys to get in. And I heard the other day a casino at a casino, uh, connected thermometer in a fish tank in the lobby was the access point. How is just kind of changing your guys world, you know, how do you think about security? Because it seems like in the end, everyone seems to be getting he breached at some point in time. So it's almost Maur. How fast can you catch it? How do you minimize the damage? How do you take care of it versus this assumption that you can stop the reaches? You >> know, that was a really good point that you mentioned at the end, which is it's just better to assume that you will be breached at some point. And how quickly can you detect that? Because, on average, I think, according to research, it takes enterprise about six months. Of course, they're enterprise that are takes about a couple of years before they realize. And, you know, we hear this on the news about millions of records exposed billions of dollars of market cap loss. Four. Scout. It's a very close take partner, and we typically use deploy solutions together with these technology partners, whether it's a PM in P. M. But very importantly, security, and if you think about it, there's terabytes of data in the network. Typically, many of these tools look at the packet data, but you can't really just take those terabytes of data and just through it at all the tools, it just becomes a financially impossible toe provide security and deploy such tools in a very large network. So where this is where we come in and we were the taps, we access the data where the package workers was essentially groom it, filtering down to maybe tens or hundreds of gigs that that's really, really important. And then we feed it, feed it to our take partners such as Four Scout and many of the others. That way they can. They can focus on providing security by looking at the packets that really matter. For example, you know some some solutions only. Look, I need to look at the package header. You don't really need to see the send the payload. So if somebody is streaming Netflix or YouTube, maybe you just need to send the first mega byte of data not the whole hundreds of gigs over that to our video, so that allows them to. It allows us or helps us increase the efficiency of that tool. So the end customer can actually get a good R Y on that on that investment, and it allows for Scott to really look at or any of the tech partners to look at what's really important let me do a better job of investigating. Hey, have I been hacked? And of course, it has to be state full, meaning that it's not just looking at flow on one data flow on one side, looking at the whole communication. So you can understand What is this? A malicious application that is now done downloading other malicious applications and infiltrating my system? Is that a DDOS attack? Is it a hack? It's, Ah, there's a hole, equal system off attacks. And that's where we have so many companies in this in this space, many startups. >> It's interesting We had Tom Siebel on a little while ago actually had a W s event and his his explanation of what big data means is that there's no sampling air. And we often hear that, you know, we used to kind of prior to big day, two days we would take a sample of data after the fact and then tried to to do someone understanding where now the more popular is now we have a real time streaming engines. So now we're getting all the data basically instantaneously in making decisions. But what you just bring out is you don't necessarily want all the data all the time because it could. It can overwhelm its stress to Syria. That needs to be a much better management approach to that. And as I look at some of the notes, you know, you guys were now deploying 400 gigabit. That's right, which is bananas, because it seems like only yesterday that 100 gigabyte Ethan, that was a big deal a little bit about, you know, kind of the just hard core technology changes that are impacting data centers and deployments. And as this band with goes through the ceiling, what people are physically having to do, do it. >> Sure, sure, it's amazing how it took some time to go from 1 to 10 gig and then turning into 40 gig, but that that time frame is getting shorter and shorter from 48 2 108 100 to 400. I don't even know how we're going to get to the next phase because the demand is there and the demand is coming from a number of Trans really wants five G or the preparation for five G. A lot of service providers are started to do trials and they're up to upgrading that infrastructure because five G is gonna make it easier to access state of age quickly invest amounts of data. Whenever you make something easy for the consumer, they will consume it more. So that's one aspect of it. The preparation for five GS increasing the need for band with an infrastructure overhaul. The other piece is that we're with the neutralization. We're generating more Eastern West traffic, but because we're distributed with its computing, that East West traffic can still traverse data centers and geography. So this means that it's not just contained within a server or within Iraq. It actually just go to different locations. That also means your data center into interconnect has to support 400 gig. So a lot of network of hitmen manufacturers were typically call them. Names are are releasing are about to release 400 devices. So on the test side, they use our solutions to test these devices, obviously, because they want to release it based the standards to make sure that it works on. So that's the pre deployment phase. But once these foreign jiggy devices are deployed and typically service providers, but we're start slowly starting to see large enterprises deploy it as a mention because because of visualization and computing, then the question is, how do you make sure that your 400 gig infrastructure is operating at the capacity that you want in P. M. A. P M. As well as you're providing security? So there's a pre deployment phase that we help on the test side and then post deployment monitoring face. But five G is a big one, even though we're not. Actually we haven't turned on five year service is there's tremendous investment going on. In fact, key site. The larger organization is helping with a lot of these device testing, too. So it's not just Xia but key site. It's consume a lot of all of our time just because we're having a lot of engagements on the cellphone side. Uh, you know, decide endpoint side. It's a very interesting time that we're living in because the changes are becoming more and more frequent and it's very hot, so adapt and make sure that you're leading that leading that wave. >> In preparing for this, I saw you in another video camera. Which one it was, but your quote was you know, they didn't create electricity by improving candles. Every line I'm gonna steal it. I'll give you credit. But as you look back, I mean, I don't think most people really grown to the step function. Five g, you know, and they talk about five senior fun. It's not about your phone. It says this is the first kind of network built four machines. That's right. Machine data, the speed machine data and the quantity of Mr Sheen data. As you sit back, What kind of reflectively Again? You've been in this business for a while and you look at five G. You're sitting around talking to your to your friends at a party. So maybe some family members aren't in the business. How do you How do you tell them what this means? I mean, what are people not really seeing when they're just thinking it's just gonna be a handset upgrade there, completely missing the boat? >> Yeah, I think for the for the regular consumer, they just think it's another handset. You know, I went from three G's to 40 year. I got I saw bump in speed, and, you know, uh, some handset manufacturers are actually advertising five G capable handsets. So I'm just going to be out by another cell phone behind the curtain under the hurt. There's this massive infrastructure overhaul that a lot of service providers are going through. And it's scary because I would say that a lot of them are not necessarily prepared. The investment that's pouring in is staggering. The help that they need is one area that we're trying to accommodate because the end cell towers are being replaced. The end devices are being replaced. The data centers are being upgraded. Small South sites, you know, Um, there's there's, uh how do you provide coverage? What is the killer use case? Most likely is probably gonna be manufacturing just because it's, as you said mission to make mission machine learning Well, that's your machine to mission communication. That's where the connected hospitals connected. Manufacturing will come into play, and it's just all this machine machine communication, um, generating vast amounts of data and that goes ties back to that each computing where the edge is generating the data. But you then send some of that data not all of it, but some of that data to a centralized cloud and you develop essentially machine learning algorithms, which you then push back to the edge. The edge becomes a more intelligent and we get better productivity. But it's all machine to machine communication that, you know, I would say that more of the most of the five communication is gonna be much information communication. Some small portion will be the consumers just face timing or messaging and streaming. But that's gonna be there exactly. Exactly. That's going to change. I'm of course, we'll see other changes in our day to day lives. You know, a couple of companies attempted live gaming on the cloud in the >> past. It didn't really work out just because the network latency was not there. But we'll see that, too, and was seeing some of the products coming out from the lecture of Google into the company's where they're trying to push gaming to be in the cloud. It's something that we were not really successful in the past, so those are things that I think consumers will see Maur in their day to day lives. But the bigger impact is gonna be for the for the enterprise >> or jet. Thanks for ah, for taking some time and sharing your insight. You know, you guys get to see a lot of stuff. You've been in the industry for a while. You get to test all the new equipment that they're building. So you guys have a really interesting captaincy toe watches developments. Really exciting times. >> Thank you for inviting us. Great to be here. >> All right, Easier. Jeff. Jeff, you're watching the Cube. Where? Cube studios and fellow out there. Thanks for watching. We'll see you next time.