(bright music) >> Hello, everyone. Welcome to theCUBE special presentation of International Women's Day. I'm John Furrier, host of theCUBE. This is a global special open program we're doing every year. We're going to continue it every quarter. We're going to do more and more content, getting the voices out there and celebrating the diversity. And I'm excited to have an amazing guest here, LaDavia Drane, who's the head of Global Inclusion Diversity & Equity at AWS. LaDavia, we tried to get you in on AWS re:Invent, and you were super busy. So much going on. The industry has seen the light. They're seeing everything going on, and the numbers are up, but still not there, and getting better. This is your passion, our passion, a shared passion. Tell us about your situation, your career, how you got into it. What's your story? >> Yeah. Well, John, first of all, thank you so much for having me. I'm glad that we finally got this opportunity to speak. How did I get into this work? Wow, you know, I'm doing the work that I love to do, number one. It's always been my passion to be a voice for the voiceless, to create a seat at the table for folks that may not be welcome to certain tables. And so, it's been something that's been kind of the theme of my entire professional career. I started off as a lawyer, went to Capitol Hill, was able to do some work with members of Congress, both women members of Congress, but also, minority members of Congress in the US Congress. And then, that just morphed into what I think has become a career for me in inclusion, diversity, and equity. I decided to join Amazon because I could tell that it's a company that was ready to take it to the next level in this space. And sure enough, that's been my experience here. So now, I'm in it, I'm in it with two feet, doing great work. And yeah, yeah, it's almost a full circle moment for me. >> It's really an interesting background. You have a background in public policy. You mentioned Capitol Hill. That's awesome. DC kind of moves slow, but it's a complicated machinery there. Obviously, as you know, navigating that, Amazon grew significantly. We've been at every re:Invent with theCUBE since 2013, like just one year. I watched Amazon grow, and they've become very fast and also complicated, like, I won't say like Capitol, 'cause that's very slow, but Amazon's complicated. AWS is in the realm of powering a generation of public policy. We had the JEDI contract controversy, all kinds of new emerging challenges. This pivot to tech was great timing because one, (laughs) Amazon needed it because they were growing so fast in a male dominated world, but also, their business is having real impact on the public. >> That's right, that's right. And when you say the public, I'll just call it out. I think that there's a full spectrum of diversity and we work backwards from our customers, and our customers are diverse. And so, I really do believe, I agree that I came to the right place at the right time. And yeah, we move fast and we're also moving fast in this space of making sure that both internally and externally, we're doing the things that we need to do in order to reach a diverse population. >> You know, I've noticed how Amazon's changed from the culture, male dominated culture. Let's face it, it was. And now, I've seen over the past five years, specifically go back five, is kind of in my mental model, just the growth of female leaders, it's been impressive. And there was some controversy. They were criticized publicly for this. And we said a few things as well in those, like around 2014. How is Amazon ensuring and continuing to get the female employees feel represented and empowered? What's going on there? What programs do you have? Because it's not just doing it, it's continuing it, right? And 'cause there is a lot more to do. I mean, the half (laughs) the products are digital now for everybody. It's not just one population. (laughs) Everyone uses digital products. What is Amazon doing now to keep it going? >> Well, I'll tell you, John, it's important for me to note that while we've made great progress, there's still more that can be done. I am very happy to be able to report that we have big women leaders. We have leaders running huge parts of our business, which includes storage, customer experience, industries and business development. And yes, we have all types of programs. And I should say that, instead of calling it programs, I'm going to call it strategic initiatives, right? We are very thoughtful about how we engage our women. And not only how we hire, attract women, but how we retain our women. We do that through engagement, groups like our affinity groups. So Women at Amazon is an affinity group. Women in finance, women in engineering. Just recently, I helped our Black employee network women's group launch, BEN Women. And so you have these communities of women who come together, support and mentor one another. We have what we call Amazon Circles. And so these are safe spaces where women can come together and can have conversations, where we are able to connect mentors and sponsors. And we're seeing that it's making all the difference in the world for our women. And we see that through what we call Connections. We have an inclusion sentiment tracker. So we're able to ask questions every single day and we get a response from our employees and we can see how are our women feeling, how are they feeling included at work? Are they feeling as though they can be who they are authentically at Amazon? And so, again, there's more work that needs to be done. But I will say that as I look at the data, as I'm talking to engaging women, I really do believe that we're on the right path. >> LaDavia, talk about the urgent needs of the women that you're hearing from the Circles. That's a great program. The affinity circles, the groups are great. Now, you have the groups, what are you hearing? What are the needs of the women? >> So, John, I'll just go a little bit into what's becoming a conversation around equity. So, initially I think we talked a lot about equality, right? We wanted everyone to have fair access to the same things. But now, women are looking for equity. We're talking about not just leveling the playing field, which is equality, but don't give me the same as you give everyone else. Instead, recognize that I may have different circumstances, I may have different needs. And give me what I need, right? Give me what I need, not just the same as everyone else. And so, I love seeing women evolve in this way, and being very specific about what they need more than, or what's different than what a man may have in the same situation because their circumstances are not always the same and we should treat them as such. >> Yeah, I think that's a great equity point. I interviewed a woman here, ex-Amazonian, she's now a GSI, Global System Integrator. She's a single mom. And she said remote work brought her equity because people on her team realized that she was a single mom. And it wasn't the, how do you balance life, it was her reality. And what happened was, she had more empathy with the team because of the new work environment. So, I think this is an important point to call out, that equity, because that really makes things smoother in terms of the interactions, not the assumptions, you have to be, you know, always the same as a man. So, how does that go? What's the current... How would you characterize the progress in that area right now? >> I believe that employers are just getting better at this. It's just like you said, with the hybrid being the norm now, you have an employer who is looking at people differently based on what they need. And it's not a problem, it's not an issue that a single mother says, "Well, I need to be able to leave by 5:00 PM." I think that employers now, and Amazon is right there along with other employers, are starting just to evolve that muscle of meeting the needs. People don't have to feel different. You don't have to feel as though there's some kind of of special circumstance for me. Instead, it's something that we, as employers, we're asking for. And we want to meet those needs that are different in some situations. >> I know you guys do a lot of support of women outside of AWS, and I had a story I recorded for the program. This woman, she talked about how she was a nerd from day one. She's a tomboy. They called her a tomboy, but she always loved robotics. And she ended up getting dual engineering degrees. And she talked about how she didn't run away and there was many signals to her not to go. And she powered through, at that time, and during her generation, that was tough. And she was successful. How are you guys taking the education to STEM, to women, at young ages? Because we don't want to turn people away from tech if they have the natural affinity towards it. And not everyone is going to be, as, you know, (laughs) strong, if you will. And she was a bulldog, she was great. She's just like, "I'm going for it. I love it so much." But not everyone's like that. So, this is an educational thing. How do you expose technology, STEM for instance, and making it more accessible, no stigma, all that stuff? I mean, I think we've come a long way, but still. >> What I love about women is we don't just focus on ourselves. We do a very good job of thinking about the generation that's coming after us. And so, I think you will see that very clearly with our women Amazonians. I'll talk about three different examples of ways that Amazonian women in particular, and there are men that are helping out, but I'll talk about the women in particular that are leading in this area. On my team, in the Inclusion, Diversity & Equity team, we have a program that we run in Ghana where we meet basic STEM needs for a afterschool program. So we've taken this small program, and we've turned their summer camp into this immersion, where girls and boys, we do focus on the girls, can come and be completely immersed in STEM. And when we provide the technology that they need, so that they'll be able to have access to this whole new world of STEM. Another program which is run out of our AWS In Communities team, called AWS Girls' Tech Day. All across the world where we have data centers, we're running these Girls' Tech Day. They're basically designed to educate, empower and inspire girls to pursue a career in tech. Really, really exciting. I was at the Girls' Tech Day here recently in Columbus, Ohio, and I got to tell you, it was the highlight of my year. And then I'll talk a little bit about one more, it's called AWS GetIT, and it's been around for a while. So this is a program, again, it's a global program, it's actually across 13 countries. And it allows girls to explore cloud technology, in particular, and to use it to solve real world problems. Those are just three examples. There are many more. There are actually women Amazonians that create these opportunities off the side of their desk in they're local communities. We, in Inclusion, Diversity & Equity, we fund programs so that women can do this work, this STEM work in their own local communities. But those are just three examples of some of the things that our Amazonians are doing to bring girls along, to make sure that the next generation is set up and that the next generation knows that STEM is accessible for girls. >> I'm a huge believer. I think that's amazing. That's great inspiration. We need more of that. It's awesome. And why wouldn't we spread it around? I want to get to the equity piece, that's the theme for this year's IWD. But before that, getting that segment, I want to ask you about your title, and the choice of words and the sequence. Okay, Global Inclusion, Diversity, Equity. Not diversity only. Inclusion is first. We've had this debate on theCUBE many years now, a few years back, it started with, "Inclusion is before diversity," "No, diversity before inclusion, equity." And so there's always been a debate (laughs) around the choice of words and their order. What's your opinion? What's your reaction to that? Is it by design? And does inclusion come before diversity, or am I just reading it to it? >> Inclusion doesn't necessarily come before diversity. (John laughs) It doesn't necessarily come before equity. Equity isn't last, but we do lead with inclusion in AWS. And that is very important to us, right? And thank you for giving me the opportunity to talk a little bit about it. We lead with inclusion because we want to make sure that every single one of our builders know that they have a place in this work. And so it's important that we don't only focus on hiring, right? Diversity, even though there are many, many different levels and spectrums to diversity. Inclusion, if you start there, I believe that it's what it takes to make sure that you have a workplace where everyone knows you're included here, you belong here, we want you to stay here. And so, it helps as we go after diversity. And we want all types of people to be a part of our workforce, but we want you to stay. And inclusion is the thing. It's the thing that I believe makes sure that people stay because they feel included. So we lead with inclusion. Doesn't mean that we put diversity or equity second or third, but we are proud to lead with inclusion. >> Great description. That was fabulous. Totally agree. Double click, thumbs up. Now let's get into the theme. Embracing equity, 'cause this is a term, it's in quotes. What does that mean to you? You mentioned it earlier, I love it. What does embrace equity mean? >> Yeah. You know, I do believe that when people think about equity, especially non-women think about equity, it's kind of scary. It's, "Am I going to give away what I have right now to make space for someone else?" But that's not what equity means. And so I think that it's first important that we just educate ourselves about what equity really is. It doesn't mean that someone's going to take your spot, right? It doesn't mean that the pie, let's use that analogy, gets smaller. The pie gets bigger, right? >> John: Mm-hmm. >> And everyone is able to have their piece of the pie. And so, I do believe that I love that IWD, International Women's Day is leading with embracing equity because we're going to the heart of the matter when we go to equity, we're going to the place where most people feel most challenged, and challenging people to think about equity and what it means and how they can contribute to equity and thus, embrace equity. >> Yeah, I love it. And the advice that you have for tech professionals out there on this, how do you advise other groups? 'Cause you guys are doing a lot of great work. Other organizations are catching up. What would be your advice to folks who are working on this equity challenge to reach gender equity and other equitable strategic initiatives? And everyone's working on this. Sustainability and equity are two big projects we're seeing in every single company right now. >> Yeah, yeah. I will say that I believe that AWS has proven that equity and going after equity does work. Embracing equity does work. One example I would point to is our AWS Impact Accelerator program. I mean, we provide 30 million for early stage startups led by women, Black founders, Latino founders, LGBTQ+ founders, to help them scale their business. That's equity. That's giving them what they need. >> John: Yeah. >> What they need is they need access to capital. And so, what I'd say to companies who are looking at going into the space of equity, I would say embrace it. Embrace it. Look at examples of what companies like AWS is doing around it and embrace it because I do believe that the tech industry will be better when we're comfortable with embracing equity and creating strategic initiatives so that we could expand equity and make it something that's just, it's just normal. It's the normal course of business. It's what we do. It's what we expect of ourselves and our employees. >> LaDavia, you're amazing. Thank you for spending the time. My final couple questions really more around you. Capitol Hill, DC, Amazon Global Head of Inclusion, Diversity & Equity, as you look at making change, being a change agent, being a leader, is really kind of similar, right? You've got DC, it's hard to make change there, but if you do it, it works, right? (laughs) If you don't, you're on the side of the road. So, as you're in your job now, what are you most excited about? What's on your agenda? What's your focus? >> Yeah, so I'm most excited about the potential of what we can get done, not just for builders that are currently in our seats, but for builders in the future. I tend to focus on that little girl. I don't know her, I don't know where she lives. I don't know how old she is now, but she's somewhere in the world, and I want her to grow up and for there to be no question that she has access to AWS, that she can be an employee at AWS. And so, that's where I tend to center, I center on the future. I try to build now, for what's to come, to make sure that this place is accessible for that little girl. >> You know, I've always been saying for a long time, the software is eating the world, now you got digital transformation, business transformation. And that's not a male only, or certain category, it's everybody. And so, software that's being built, and the systems that are being built, have to have first principles. Andy Jassy is very strong on this. He's been publicly saying, when trying to get pinned down about certain books in the bookstore that might offend another group. And he's like, "Look, we have first principles. First principles is a big part of leading." What's your reaction to that? How would you talk to another professional and say, "Hey," you know this, "How do I make the right call? Am I doing the wrong thing here? And I might say the wrong thing here." And is it first principles based? What's the guardrails? How do you keep that in check? How would you advise someone as they go forward and lean in to drive some of the change that we're talking about today? >> Yeah, I think as leaders, we have to trust ourselves. And Andy actually, is a great example. When I came in as head of ID&E for AWS, he was our CEO here at AWS. And I saw how he authentically spoke from his heart about these issues. And it just aligned with who he is personally, his own personal principles. And I do believe that leaders should be free to do just that. Not to be scripted, but to lead with their principles. And so, I think Andy's actually a great example. I believe that I am the professional in this space at this company that I am today because of the example that Andy set. >> Yeah, you guys do a great job, LaDavia. What's next for you? >> What's next. >> World tour, you traveling around? What's on your plate these days? Share a little bit about what you're currently working on. >> Yeah, so you know, at Amazon, we're always diving deep. We're always diving deep, we're looking for root cause, working very hard to look around corners, and trying to build now for what's to come in the future. And so I'll continue to do that. Of course, we're always planning and working towards re:Invent, so hopefully, John, I'll see you at re:Invent this December. But we have some great things happening throughout the year, and we'll continue to... I think it's really important, as opposed to looking to do new things, to just continue to flex the same muscles and to show that we can be very, very focused and intentional about doing the same things over and over each year to just become better and better at this work in this space, and to show our employees that we're committed for the long haul. So of course, there'll be new things on the horizon, but what I can say, especially to Amazonians, is we're going to continue to stay focused, and continue to get at this issue, and doing this issue of inclusion, diversity and equity, and continue to do the things that work and make sure that our culture evolves at the same time. >> LaDavia, thank you so much. I'll give you the final word. Just share some of the big projects you guys are working on so people can know about them, your strategic initiatives. Take a minute to plug some of the major projects and things that are going on that people either know about or should know about, or need to know about. Take a minute to share some of the big things you guys got going on, or most of the things. >> So, one big thing that I would like to focus on, focus my time on, is what we call our Innovation Fund. This is actually how we scale our work and we meet the community's needs by providing micro grants to our employees so our employees can go out into the world and sponsor all types of different activities, create activities in their local communities, or throughout the regions. And so, that's probably one thing that I would like to focus on just because number one, it's our employees, it's how we scale this work, and it's how we meet our community's needs in a very global way. And so, thank you John, for the opportunity to talk a bit about what we're up to here at Amazon Web Services. But it's just important to me, that I end with our employees because for me, that's what's most important. And they're doing some awesome work through our Innovation Fund. >> Inclusion makes the workplace great. Empowerment, with that kind of program, is amazing. LaDavia Drane, thank you so much. Head of Global Inclusion and Diversity & Equity at AWS. This is International Women's Day. I'm John Furrier with theCUBE. Thanks for watching and stay with us for more great interviews and people and what they're working on. Thanks for watching. (bright music)

>> From the CUBE Studios in Palo Alto in Boston, bringing you data driven insights from the Cube and ETR. This is Breaking Analysis with Dave Vellante. >> A better than expected earnings report in late August got people excited about Snowflake again, but the negative sentiment in the market is weighed heavily on virtually all growth tech stocks and Snowflake is no exception. As we've stressed many times the company's management is on a long term mission to dramatically simplify the way organizations use data. Snowflake is tapping into a multi hundred billion dollar total available market and continues to grow at a rapid pace. In our view, Snowflake is embarking on its third major wave of innovation data apps, while its first and second waves are still bearing significant fruit. Now for short term traders focused on the next 90 or 180 days, that probably doesn't matter. But those taking a longer view are asking, "Should we still be optimistic about the future of this high flyer or is it just another over hyped tech play?" Hello and welcome to this week's Wiki Bond Cube Insights powered by ETR. Snowflake's Quarter just ended. And in this breaking analysis we take a look at the most recent survey data from ETR to see what clues and nuggets we can extract to predict the near term future in the long term outlook for Snowflake which is going to announce its earnings at the end of this month. Okay, so you know the story. If you've been investor in Snowflake this year, it's been painful. We said at IPO, "If you really want to own this stock on day one, just hold your nose and buy it." But like most IPOs we said there will be likely a better entry point in the future, and not surprisingly that's been the case. Snowflake IPOed a price of 120, which you couldn't touch on day one unless you got into a friends and family Delio. And if you did, you're still up 5% or so. So congratulations. But at one point last year you were up well over 200%. That's been the nature of this volatile stock, and I certainly can't help you with the timing of the market. But longer term Snowflake is targeting 10 billion in revenue for fiscal year 2028. A big number. Is it achievable? Is it big enough? Tell you what, let's come back to that. Now shorter term, our expert trader and breaking analysis contributor Chip Simonton said he got out of the stock a while ago after having taken a shot at what turned out to be a bear market rally. He pointed out that the stock had been bouncing around the 150 level for the last few months and broke that to the downside last Friday. So he'd expect 150 is where the stock is going to find resistance on the way back up, but there's no sign of support right now. He said maybe at 120, which was the July low and of course the IPO price that we just talked about. Now, perhaps earnings will be a catalyst, when Snowflake announces on November 30th, but until the mentality toward growth tech changes, nothing's likely to change dramatically according to Simonton. So now that we have that out of the way, let's take a look at the spending data for Snowflake in the ETR survey. Here's a chart that shows the time series breakdown of snowflake's net score going back to the October, 2021 survey. Now at that time, Snowflake's net score stood at a robust 77%. And remember, net score is a measure of spending velocity. It's a proprietary network, and ETR derives it from a quarterly survey of IT buyers and asks the respondents, "Are you adopting the platform new? Are you spending 6% or more? Is you're spending flat? Is you're spending down 6% or worse? Or are you leaving the platform decommissioning?" You subtract the percent of customers that are spending less or churning from those that are spending more and adopting or adopting and you get a net score. And that's expressed as a percentage of customers responding. In this chart we show Snowflake's in out of the total survey which ranges... The total survey ranges between 1,200 and 1,400 each quarter. And the very last column... Oh sorry, very last row, we show the number of Snowflake respondents that are coming in the survey from the Fortune 500 and the Global 2000. Those are two very important Snowflake constituencies. Now what this data tells us is that Snowflake exited 2021 with very strong momentum in a net score of 82%, which is off the charts and it was actually accelerating from the previous survey. Now by April that sentiment had flipped and Snowflake came down to earth with a 68% net score. Still highly elevated relative to its peers, but meaningfully down. Why was that? Because we saw a drop in new ads and an increase in flat spend. Then into the July and most recent October surveys, you saw a significant drop in the percentage of customers that were spending more. Now, notably, the percentage of customers who are contemplating adding the platform is actually staying pretty strong, but it is off a bit this past survey. And combined with a slight uptick in planned churn, net score is now down to 60%. That uptick from 0% and 1% and then 3%, it's still small, but that net score at 60% is still 20 percentage points higher than our highly elevated benchmark of 40% as you recall from listening to earlier breaking analysis. That 40% range is we consider a milestone. Anything above that is actually quite strong. But again, Snowflake is down and coming back to churn, while 3% churn is very low, in previous quarters we've seen Snowflake 0% or 1% decommissions. Now the last thing to note in this chart is the meaningful uptick in survey respondents that are citing, they're using the Snowflake platform. That's up to 212 in the survey. So look, it's hard to imagine that Snowflake doesn't feel the softening in the market like everyone else. Snowflake is guiding for around 60% growth in product revenue against the tough compare from a year ago with a 2% operating margin. So like every company, the reaction of the street is going to come down to how accurate or conservative the guide is from their CFO. Now, earlier this year, Snowflake acquired a company called Streamlit for around $800 million. Streamlit is an open source Python library and it makes it easier to build data apps with machine learning, obviously a huge trend. And like Snowflake, generally its focus is on simplifying the complex, in this case making data science easier to integrate into data apps that business people can use. So we were excited this summer in the July ETR survey to see that they added some nice data and pick on Streamlit, which we're showing here in comparison to Snowflake's core business on the left hand side. That's the data warehousing, the Streamlit pieces on the right hand side. And we show again net score over time from the previous survey for Snowflake's core database and data warehouse offering again on the left as compared to a Streamlit on the right. Snowflake's core product had 194 responses in the October, 22 survey, Streamlit had an end of 73, which is up from 52 in the July survey. So significant uptick of people responding that they're doing business in adopting Streamlit. That was pretty impressive to us. And it's hard to see, but the net scores stayed pretty constant for Streamlit at 51%. It was 52% I think in the previous quarter, well over that magic 40% mark. But when you blend it with Snowflake, it does sort of bring things down a little bit. Now there are two key points here. One is that the acquisition seems to have gained exposure right out of the gate as evidenced by the large number of responses. And two, the spending momentum. Again while it's lower than Snowflake overall, and when you blend it with Snowflake it does pull it down, it's very healthy and steady. Now let's do a little pure comparison with some of our favorite names in this space. This chart shows net score or spending velocity in the Y-axis, an overlap or presence, pervasiveness if you will, in the data set on the X-axis. That red dotted line again is that 40% highly elevated net score that we like to talk about. And that table inserted informs us as to how the companies are plotted, where the dots set up, the net score, the ins. And we're comparing a number of database players, although just a caution, Oracle includes all of Oracle including its apps. But we just put it in there for reference because it is the leader in database. Right off the bat, Snowflake jumps out with a net score of 64%. The 60% from the earlier chart, again included Streamlit. So you can see its core database, data warehouse business actually is higher than the total company average that we showed you before 'cause the Streamlit is blended in. So when you separate it out, Streamlit is right on top of data bricks. Isn't that ironic? Only Snowflake and Databricks in this selection of names are above the 40% level. You see Mongo and Couchbase, they know they're solid and Teradata cloud actually showing pretty well compared to some of the earlier survey results. Now let's isolate on the database data platform sector and see how that shapes up. And for this analysis, same XY dimensions, we've added the big giants, AWS and Microsoft and Google. And notice that those three plus Snowflake are just at or above the 40% line. Snowflake continues to lead by a significant margin in spending momentum and it keeps creeping to the right. That's that end that we talked about earlier. Now here's an interesting tidbit. Snowflake is often asked, and I've asked them myself many times, "How are you faring relative to AWS, Microsoft and Google, these big whales with Redshift and Synapse and Big Query?" And Snowflake has been telling folks that 80% of its business comes from AWS. And when Microsoft heard that, they said, "Whoa, wait a minute, Snowflake, let's partner up." 'Cause Microsoft is smart, and they understand that the market is enormous. And if they could do better with Snowflake, one, they may steal some business from AWS. And two, even if Snowflake is winning against some of the Microsoft database products, if it wins on Azure, Microsoft is going to sell more compute and more storage, more AI tools, more other stuff to these customers. Now AWS is really aggressive from a partnering standpoint with Snowflake. They're openly negotiating, not openly, but they're negotiating better prices. They're realizing that when it comes to data, the cheaper that you make the offering, the more people are going to consume. At scale economies and operating leverage are really powerful things at volume that kick in. Now Microsoft, they're coming along, they obviously get it, but Google is seemingly resistant to that type of go to market partnership. Rather than lean into Snowflake as a great partner Google's field force is kind of fighting fashion. Google itself at Cloud next heavily messaged what they call the open data cloud, which is a direct rip off of Snowflake. So what can we say about Google? They continue to be kind of behind the curve when it comes to go to market. Now just a brief aside on the competitive posture. I've seen Slootman, Frank Slootman, CEO of Snowflake in action with his prior companies and how he depositioned the competition. At Data Domain, he eviscerated a company called Avamar with their, what he called their expensive and slow post process architecture. I think he actually called it garbage, if I recall at one conference I heard him speak at. And that sort of destroyed BMC when he was at ServiceNow, kind of positioning them as the equivalent of the department of motor vehicles. And so it's interesting to hear how Snowflake openly talks about the data platforms of AWS, Microsoft, Google, and data bricks. I'll give you this sort of short bumper sticker. Redshift is just an on-prem database that AWS morphed to the cloud, which by the way is kind of true. They actually did a brilliant job of it, but it's basically a fact. Microsoft Excel, a collection of legacy databases, which also kind of morphed to run in the cloud. And even Big Query, which is considered cloud native by many if not most, is being positioned by Snowflake as originally an on-prem database to support Google's ad business, maybe. And data bricks is for those people smart enough to get it to Berkeley that love complexity. And now Snowflake doesn't, they don't mention Berkeley as far as I know. That's my addition. But you get the point. And the interesting thing about Databricks and Snowflake is a while ago in the cube I said that there was a new workload type emerging around data where you have AWS cloud, Snowflake obviously for the cloud database and Databricks data for the data science and EML, you bring those things together and there's this new workload emerging that's going to be very powerful in the future. And it's interesting to see now the aspirations of all three of these platforms are colliding. That's quite a dynamic, especially when you see both Snowflake and Databricks putting venture money and getting their hooks into the loyalties of the same companies like DBT labs and Calibra. Anyway, Snowflake's posture is that we are the pioneer in cloud native data warehouse, data sharing and now data apps. And our platform is designed for business people that want simplicity. The other guys, yes, they're formidable, but we Snowflake have an architectural lead and of course we run in multiple clouds. So it's pretty strong positioning or depositioning, you have to admit. Now I'm not sure I agree with the big query knockoffs completely. I think that's a bit of a stretch, but snowflake, as we see in the ETR survey data is winning. So in thinking about the longer term future, let's talk about what's different with Snowflake, where it's headed and what the opportunities are for the company. Snowflake put itself on the map by focusing on simplifying data analytics. What's interesting about that is the company's founders are as you probably know from Oracle. And rather than focusing on transactional data, which is Oracle's sweet spot, the stuff they worked on when they were at Oracle, the founder said, "We're going to go somewhere else. We're going to attack the data warehousing problem and the data analytics problem." And they completely re-imagined the database and how it could be applied to solve those challenges and reimagine what was possible if you had virtually unlimited compute and storage capacity. And of course Snowflake became famous for separating the compute from storage and being able to completely shut down compute so you didn't have to pay for it when you're not using it. And the ability to have multiple clusters hit the same data without making endless copies and a consumption/cloud pricing model. And then of course everyone on the planet realized, "Wow, that's a pretty good idea." Every venture capitalist in Silicon Valley has been funding companies to copy that move. And that today has pretty much become mainstream in table stakes. But I would argue that Snowflake not only had the lead, but when you look at how others are approaching this problem, it's not necessarily as clean and as elegant. Some of the startups, the early startups I think get it and maybe had an advantage of starting later, which can be a disadvantage too. But AWS is a good example of what I'm saying here. Is its version of separating compute from storage was an afterthought and it's good, it's... Given what they had it was actually quite clever and customers like it, but it's more of a, "Okay, we're going to tier to storage to lower cost, we're going to sort of dial down the compute not completely, we're not going to shut it off, we're going to minimize the compute required." It's really not true as separation is like for instance Snowflake has. But having said that, we're talking about competitors with lots of resources and cohort offerings. And so I don't want to make this necessarily all about the product, but all things being equal architecture matters, okay? So that's the cloud S-curve, the first one we're showing. Snowflake's still on that S-curve, and in and of itself it's got legs, but it's not what's going to power the company to 10 billion. The next S-curve we denote is the multi-cloud in the middle. And now while 80% of Snowflake's revenue is AWS, Microsoft is ramping up and Google, well, we'll see. But the interesting part of that curve is data sharing, and this idea of data clean rooms. I mean it really should be called the data sharing curve, but I have my reasons for calling it multi-cloud. And this is all about network effects and data gravity, and you're seeing this play out today, especially in industries like financial services and healthcare and government that are highly regulated verticals where folks are super paranoid about compliance. There not going to share data if they're going to get sued for it, if they're going to be in the front page of the Wall Street Journal for some kind of privacy breach. And what Snowflake has done is said, "Put all the data in our cloud." Now, of course now that triggers a lot of people because it's a walled garden, okay? It is. That's the trade off. It's not the Wild West, it's not Windows, it's Mac, it's more controlled. But the idea is that as different parts of the organization or even partners begin to share data that they need, it's got to be governed, it's got to be secure, it's got to be compliant, it's got to be trusted. So Snowflake introduced the idea of, they call these things stable edges. I think that's the term that they use. And they track a metric around stable edges. And so a stable edge, or think of it as a persistent edge is an ongoing relationship between two parties that last for some period of time, more than a month. It's not just a one shot deal, one a done type of, "Oh guys shared it for a day, done." It sent you an FTP, it's done. No, it's got to have trajectory over time. Four weeks or six weeks or some period of time that's meaningful. And that metric is growing. Now I think sort of a different metric that they track. I think around 20% of Snowflake customers are actively sharing data today and then they track the number of those edge relationships that exist. So that's something that's unique. Because again, most data sharing is all about making copies of data. That's great for storage companies, it's bad for auditors, and it's bad for compliance officers. And that trend is just starting out, that middle S-curve, it's going to kind of hit the base of that steep part of the S-curve and it's going to have legs through this decade we think. And then finally the third wave that we show here is what we call super cloud. That's why I called it multi-cloud before, so it could invoke super cloud. The idea that you've built a PAS layer that is purpose built for a specific objective, and in this case it's building data apps that are cloud native, shareable and governed. And is a long-term trend that's going to take some time to develop. I mean, application development platforms can take five to 10 years to mature and gain significant adoption, but this one's unique. This is a critical play for Snowflake. If it's going to compete with the big cloud players, it has to have an app development framework like Snowpark. It has to accommodate new data types like transactional data. That's why it announced this thing called UniStore last June, Snowflake a summit. And the pattern that's forming here is Snowflake is building layer upon layer with its architecture at the core. It's not currently anyway, it's not going out and saying, "All right, we're going to buy a company that's got to another billion dollars in revenue and that's how we're going to get to 10 billion." So it's not buying its way into new markets through revenue. It's actually buying smaller companies that can complement Snowflake and that it can turn into revenue for growth that fit in to the data cloud. Now as to the 10 billion by fiscal year 28, is that achievable? That's the question. Yeah, I think so. Would the momentum resources go to market product and management prowess that Snowflake has? Yes, it's definitely achievable. And one could argue to $10 billion is too conservative. Indeed, Snowflake CFO, Mike Scarpelli will fully admit his forecaster built on existing offerings. He's not including revenue as I understand it from all the new stuff that's in the pipeline because he doesn't know what it's going to look like. He doesn't know what the adoption is going to look like. He doesn't have data on that adoption, not just yet anyway. And now of course things can change quite dramatically. It's possible that is forecast for existing businesses don't materialize or competition picks them off or a company like Databricks actually is able in the longer term replicate the functionality of Snowflake with open source technologies, which would be a very competitive source of innovation. But in our view, there's plenty of room for growth, the market is enormous and the real key is, can and will Snowflake deliver on the promises of simplifying data? Of course we've heard this before from data warehouse, the data mars and data legs and master data management and ETLs and data movers and data copiers and Hadoop and a raft of technologies that have not lived up to expectations. And we've also, by the way, seen some tremendous successes in the software business with the likes of ServiceNow and Salesforce. So will Snowflake be the next great software name and hit that 10 billion magic mark? I think so. Let's reconnect in 2028 and see. Okay, we'll leave it there today. I want to thank Chip Simonton for his input to today's episode. Thanks to Alex Myerson who's on production and manages the podcast. Ken Schiffman as well. Kristin Martin and Cheryl Knight help get the word out on social media and in our newsletters. And Rob Hove is our Editor in Chief over at Silicon Angle. He does some great editing for us. Check it out for all the news. Remember all these episodes are available as podcasts. Wherever you listen, just search Breaking Analysis podcast. I publish each week on wikibon.com and siliconangle.com. Or you can email me to get in touch David.vallante@siliconangle.com. DM me @dvellante or comment on our LinkedIn post. And please do check out etr.ai, they've got the best survey data in the enterprise tech business. This is Dave Vellante for the CUBE Insights, powered by ETR. Thanks for watching, thanks for listening and we'll see you next time on breaking analysis. (upbeat music)

(bright music) >> "Supermetafragilisticexpialadotious." What's in a name? In an homage to the inimitable Charles Fitzgerald, we've chosen this title for today's session because of all the buzz surrounding "supercloud," a term that we introduced last year to signify a major architectural trend and shift that's occurring in the technology industry. Since that time, we've published numerous videos and articles on the topic, and on August 9th, kicked off "Supercloud22," an open industry event designed to advance the supercloud conversation, gathering input from more than 30 experienced technologists and business leaders in "The Cube" and broader technology community. We're talking about individuals like Benoit Dageville, Kit Colbert, Ali Ghodsi, Mohit Aron, David McJannet, and dozens of other experts. And today, we're pleased to welcome David Linthicum, who's a Chief Strategy Officer of Cloud Services at Deloitte Consulting. David is a technology visionary, a technical CTO. He's an author and a frequently sought after keynote speaker at high profile conferences like "VMware Explore" next week. David Linthicum, welcome back to "The Cube." Good to see you again. >> Oh, it's great to be here. Thanks for the invitation. Thanks for having me. >> Yeah, you're very welcome. Okay, so this topic of supercloud, what you call metacloud, has created a lot of interest. VMware calls it cross-cloud services, Snowflake calls it their data cloud, there's a lot of different names, but recently, you published a piece in "InfoWorld" where you said the following. "I really don't care what we call it, "and I really don't care if I put "my own buzzword into the mix. "However, this does not change the fact "that metacloud is perhaps the most important "architectural evolution occurring right now, "and we need to get this right out of the gate. "If we do that, who cares what it's named?" So very cool. And you also mentioned in a recent article that you don't like to put out new terms out in the wild without defining them. So what is a metacloud, or what we call supercloud? What's your definition? >> Yeah, and again, I don't care what people call it. The reality is it's the ability to have a layer of cross-cloud services. It sits above existing public cloud providers. So the idea here is that instead of building different security systems, different governance systems, different operational systems in each specific cloud provider, using whatever native features they provide, we're trying to do that in a cross-cloud way. So in other words, we're pushing out data integration, security, all these other things that we have to take care of as part of deploying a particular cloud provider. And in a multicloud scenario, we're building those in and between the clouds. And so we've been tracking this for about five years. We understood that multicloud is not necessarily about the particular public cloud providers, it's about things that you build in and between the clouds. >> Got it, okay. So I want to come back to that, to the definition, but I want to tie us to the so-called multicloud. You guys did a survey recently. We've said that multicloud was mostly a symptom of multi-vendor, Shadow Cloud, M&A, and only recently has become a strategic imperative. Now, Deloitte published a survey recently entitled "Closing the Cloud Strategy, Technology, Innovation Gap," and I'd like to explore that a little bit. And so in that survey, you showed data. What I liked about it is you went beyond what we all know, right? The old, "Our research shows that on average, "X number of clouds are used at an individual company." I mean, you had that too, but you really went deeper. You identified why companies are using multiple clouds, and you developed different categories of practitioners across 500 survey respondents. But the reasons were very clear for "why multicloud," as this becomes more strategic. Service choice scale, negotiating leverage, improved business resiliency, minimizing lock-in, interoperability of data, et cetera. So my question to you, David, is what's the problem supercloud or metacloud solves, and what's different from multicloud? >> That's a great question. The reality is that if we're... Well, supercloud or metacloud, whatever, is really something that exists above a multicloud, but I kind of view them as the same thing. It's an architectural pattern. We can name it anything. But the reality is that if we're moving to these multicloud environments, we're doing so to leverage best of breed things. In other words, best of breed technology to provide the innovators within the company to take the business to the next level, and we determine that in the survey. And so if we're looking at what a multicloud provides, it's the ability to provide different choices of different services or piece parts that allows us to build anything that we need to do. And so what we found in the survey and what we found in just practice in dealing with our clients is that ultimately, the value of cloud computing is going to be the innovation aspects. In other words, the ability to take the company to the next level from being more innovative and more disruptive in the marketplace that they're in. And the only way to do that, instead of basically leveraging the services of a particular walled garden of a single public cloud provider, is to cast a wider net and get out and leverage all kinds of services to make these happen. So if you think about that, that's basically how multicloud has evolved. In other words, it wasn't planned. They didn't say, "We're going to go do a multicloud." It was different developers and innovators in the company that went off and leveraged these cloud services, sometimes with the consent of IT leadership, sometimes not. And now we have these multitudes of different services that we're leveraging. And so many of these enterprises are going from 1000 to, say, 3000 services under management. That creates a complexity problem. We have a problem of heterogeneity, different platforms, different tools, different services, different AI technology, database technology, things like that. So the metacloud, or the supercloud, or whatever you want to call it, is the ability to deal with that complexity on the complexity's terms. And so instead of building all these various things that we have to do individually in each of the cloud providers, we're trying to do so within a cross-cloud service layer. We're trying to create this layer of technology, which removes us from dealing with the complexity of the underlying multicloud services and makes it manageable. Because right now, I think we're getting to a point of complexity we just can't operate it at the budgetary limits that we are right now. We can't keep the number of skills around, the number of operators around, to keep these things going. We're going to have to get creative in terms of how we manage these things, how we manage a multicloud. And that's where the supercloud, metacloud, whatever they want to call it, comes that. >> Yeah, and as John Furrier likes to say, in IT, we tend to solve complexity with more complexity, and that's not what we're talking about here. We're talking about simplifying, and you talked about the abstraction layer, and then it sounds like I'm inferring more. There's value that's added on top of that. And then you also said the hyperscalers are in a walled garden. So I've been asked, why aren't the hyperscalers superclouds? And I've said, essentially, they want to put your data into their cloud and keep it there. Now, that doesn't mean they won't eventually get into that. We've seen examples a little bit, Outposts, Anthos, Azure Arc, but the hyperscalers really aren't building superclouds or metaclouds, at least today, are they? >> No, they're not. And I always have the predictions for every major cloud conference that this is the conference that the hyperscaler is going to figure out some sort of a multicloud across-cloud strategy. In other words, building services that are able to operate across clouds. That really has never happened. It has happened in dribs and drabs, and you just mentioned a few examples of that, but the ability to own the space, to understand that we're not going to be the center of the universe in how people are going to leverage it, is going to be multiple things, including legacy systems and other cloud providers, and even industry clouds that are emerging these days, and SaaS providers, and all these things. So we're going to assist you in dealing with complexity, and we're going to provide the core services of being there. That hasn't happened yet. And they may be worried about conflicting their market, and the messaging is a bit different, even actively pushing back on the concept of multicloud, but the reality is the market's going to take them there. So in other words, if enough of their customers are asking for this and asking that they take the lead in building these cross-cloud technologies, even if they're participating in the stack and not being the stack, it's too compelling of a market that it's not going to drag a lot of the existing public cloud providers there. >> Well, it's going to be interesting to see how that plays out, David, because I never say never when it comes to a company like AWS, and we've seen how fast they move. And at the same time, they don't want to be commoditized. There's the layer underneath all this infrastructure, and they got this ecosystem that's adding all this tremendous value. But I want to ask you, what are the essential elements of supercloud, coming back to the definition, if you will, and what's different about metacloud, as you call it, from plain old SaaS or PaaS? What are the key elements there? >> Well, the key elements would be holistic management of all of the IT infrastructure. So even though it's sitting above a multicloud, I view metacloud, supercloud as the ability to also manage your existing legacy systems, your existing security stack, your existing network operations, basically everything that exists under the purview of IT. If you think about it, we're moving our infrastructure into the clouds, and we're probably going to hit a saturation point of about 70%. And really, if the supercloud, metacloud, which is going to be expensive to build for most of the enterprises, it needs to support these things holistically. So it needs to have all the services, that is going to be shareable across the different providers, and also existing legacy systems, and also edge computing, and IoT, and all these very diverse systems that we're building there right now. So if complexity is a core challenge to operate these things at scale and the ability to secure these things at scale, we have to have commonality in terms of security architecture and technology, commonality in terms of our directory services, commonality in terms of network operations, commonality in term of cloud operations, commonality in terms of FinOps. All these things should exist in some holistic cross-cloud layer that sits above all this complexity. And you pointed out something very profound. In other words, that is going to mean that we're hiding a lot of the existing cloud providers in terms of their interfaces and dashboards and things like that that we're dealing with today, their APIs. But the reality is that if we're able to manage these things at scale, the public cloud providers are going to benefit greatly from that. They're going to sell more services because people are going to find they're able to leverage them easier. And so in other words, if we're removing the complexity wall, which many in the industry are calling it right now, then suddenly we're moving from, say, the 25 to 30% migrated in the cloud, which most enterprises are today, to 50, 60, 70%. And we're able to do this at scale, and we're doing it at scale because we're providing some architectural optimization through the supercloud, metacloud layer. >> Okay, thanks for that. David, I just want to tap your CTO brain for a minute. At "Supercloud22," we came up with these three deployment models. Kit Colbert put forth the idea that one model would be your control planes running in one cloud, let's say AWS, but it interacts with and can manage and deploy on other clouds, the Kubernetes Cluster Management System. The second one, Mohit Aron from Cohesity laid out, where you instantiate the stack on different clouds and different cloud regions, and then you create a layer, a common interface across those. And then Snowflake was the third deployment model where it's a single global instance, it's one instantiation, and basically building out their own cloud across these regions. Help us parse through that. Do those seem like reasonable deployment models to you? Do you have any thoughts on that? >> Yeah, I mean, that's a distributed computing trick we've been doing, which is, in essence, an agent of the supercloud that's carrying out some of the cloud native functions on that particular cloud, but is, in essence, a slave to the metacloud, or the supercloud, whatever, that's able to run across the various cloud providers. In other words, when it wants to access a service, it may not go directly to that service. It goes directly to the control plane, and that control plane is responsible... Very much like Kubernetes and Docker works, that control plane is responsible for reaching out and leveraging those native services. I think that that's thinking that's a step in the right direction. I think these things unto themselves, at least initially, are going to be a very complex array of technology. Even though we're trying to remove complexity, the supercloud unto itself, in terms of the ability to build this thing that's able to operate at scale across-cloud, is going to be a collection of many different technologies that are interfacing with the public cloud providers in different ways. And so we can start putting these meta architectures together, and I certainly have written and spoke about this for years, but initially, this is going to be something that may escape the detail or the holistic nature of these meta architectures that people are floating around right now. >> Yeah, so I want to stay on this, because anytime I get a CTO brain, I like to... I'm not an engineer, but I've been around a long time, so I know a lot of buzzwords and have absorbed a lot over the years, but so you take those, the second two models, the Mohit instantiate on each cloud and each cloud region versus the Snowflake approach. I asked Benoit Dageville, "Does that mean if I'm in "an AWS east region and I want to do a query on Azure West, "I can do that without moving data?" And he said, "Yes and no." And the answer was really, "No, we actually take a subset of that data," so there's the latency problem. From those deployment model standpoints, what are the trade-offs that you see in terms of instantiating the stack on each individual cloud versus that single instance? Is there a benefit of the single instance for governance and security and simplicity, but a trade-off on latency, or am I overthinking this? >> Yeah, you hit it on the nose. The reality is that the trade-off is going to be latency and performance. If we get wiggy with the distributed nature, like the distributed data example you just provided, we have to basically separate the queries and communicate with the databases on each instance, and then reassemble the result set that goes back to the people who are recording it. And so we can do caching systems and things like that. But the reality is, if it's distributed system, we're going to have latency and bandwidth issues that are going to be limiting us. And also security issues, because if we're removing lots of information over the open internet, or even private circuits, that those are going to be attack vectors that hackers can leverage. You have to keep that in mind. We're trying to reduce those attack vectors. So it would be, in many instances, and I think we have to think about this, that we're going to keep the data in the same physical region for just that. So in other words, it's going to provide the best performance and also the most simplistic access to dealing with security. And so we're not, in essence, thinking about where the data's going, how it's moving across things, things like that. So the challenge is going to be is when you're dealing with a supercloud or metacloud is, when do you make those decisions? And I think, in many instances, even though we're leveraging multiple databases across multiple regions and multiple public cloud providers, and that's the idea of it, we're still going to localize the data for performance reasons. I mean, I just wrote a blog in "InfoWorld" a couple of months ago and talked about, people who are trying to distribute data across different public cloud providers for different reasons, distribute an application development system, things like that, you can do it. With enough time and money, you can do anything. I think the challenge is going to be operating that thing, and also providing a viable business return based on the application. And so why it may look like a good science experiment, and it's cool unto itself as an architect, the reality is the more pragmatic approach is going to be a leavitt in a single region on a single cloud. >> Very interesting. The other reason I like to talk to companies like Deloitte and experienced people like you is 'cause I can get... You're agnostic, right? I mean, you're technology agnostic, vendor agnostic. So I want to come back with another question, which is, how do you deal with what I call the lowest common denominator problem? What I mean by that is if one cloud has, let's say, a superior service... Let's take an example of Nitro and Graviton. AWS seems to be ahead on that, but let's say some other cloud isn't quite quite there yet, and you're building a supercloud or a metacloud. How do you rationalize that? Does it have to be like a caravan in the army where you slow down so all the slowest trucks can keep up, or are the ways to adjudicate that that are advantageous to hide that deficiency? >> Yeah, and that's a great thing about leveraging a supercloud or a metacloud is we're putting that management in a single layer. So as far as a user or even a developer on those systems, they shouldn't worry about the performance that may come back, because we're dealing with the... You hit the nail on the head with that one. The slowest component is the one that dictates performance. And so we have to have some sort of a performance management layer. We're also making dynamic decisions to move data, to move processing, from one server to the other to try to minimize the amount of latency that's coming from a single component. So the great thing about that is we're putting that volatility into a single domain, and it's making architectural decisions in terms of where something will run and where it's getting its data from, things are stored, things like that, based on the performance feedback that's coming back from the various cloud services that are under management. And so if you're running across clouds, it becomes even more interesting, because ultimately, you're going to make some architectural choices on the fly in terms of where that stuff runs based on the active dynamic performance that that public cloud provider is providing. So in other words, we may find that it automatically shut down a database service, say MySQL, on one cloud instance, and moved it to a MySQL instance on another public cloud provider because there was some sort of a performance issue that it couldn't work around. And by the way, it does so dynamically. Away from you making that decision, it's making that decision on your behalf. Again, this is a matter of abstraction, removing complexity, and dealing with complexity through abstraction and automation, and this is... That would be an example of fixing something with automation, self-healing. >> When you meet with some of the public cloud providers and they talk about on-prem private cloud, the general narrative from the hyperscalers is, "Well, that's not a cloud." Should on-prem be inclusive of supercloud, metacloud? >> Absolutely, I mean, and they're selling private cloud instances with the edge cloud that they're selling. The reality is that we're going to have to keep a certain amount of our infrastructure, including private clouds, on premise. It's something that's shrinking as a market share, and it's going to be tougher and tougher to justify as the public cloud providers become better and better at what they do, but we certainly have edge clouds now, and hyperscalers have examples of that where they run a instance of their public cloud infrastructure on premise on physical hardware and software. And the reality is, too, we have data centers and we have systems that just won't go away for another 20 or 30 years. They're just too sticky. They're uneconomically viable to move into the cloud. That's the core thing. It's not that we can't do it. The fact of the matter is we shouldn't do it, because there's not going to be an economic... There's not going to be an economic incentive of making that happen. So if we're going to create this meta layer or this infrastructure which is going to run across clouds, and everybody agrees on, that's what the supercloud is, we have to include the on-premise systems, including private clouds, including legacy systems. And by the way, include the rising number of IoT systems that are out there, and edge-based systems out there. So we're managing it using the same infrastructure into cloud services. So they have metadata systems and they have specialized services, and service finance and retail and things like doing risk analytics. So it gets them further down that path, but not necessarily giving them a SaaS application where they're forced into all of the business processes. We're giving you piece parts. So we'll give you 1000 different parts that are related to the finance industry. You can assemble anything you need, but the thing is, it's not going to be like building it from scratch. We're going to give you risk analytics, we're giving you the financial analytics, all these things that you can leverage within your applications how you want to leverage them. We'll maintain them. So in other words, you don't have to maintain 'em just like a cloud service. And suddenly, we can build applications in a couple of weeks that used to take a couple of months, in some cases, a couple of years. So that seems to be a large take of it moving forward. So get it up in the supercloud. Those become just other services that are under managed... That are under management on the supercloud, the metacloud. So we're able to take those services, abstract them, assemble them, use them in different applications. And the ability to manage where those services are originated versus where they're consumed is going to be managed by the supercloud layer, which, you're dealing with the governance, the service governance, the security systems, the directory systems, identity access management, things like that. They're going to get you further along down the pike, and that comes back as real value. If I'm able to build something in two weeks that used to take me two months, and I'm able to give my creators in the organization the ability to move faster, that's a real advantage. And suddenly, we are going to be valued by our digital footprint, our ability to do things in a creative and innovative way. And so organizations are able to move that fast, leveraging cloud computing for what it should be leveraged, as a true force multiplier for the business. They're going to win the game. They're going to get the most value. They're going to be around in 20 years, the others won't. >> David Linthicum, always love talking. You have a dangerous combination of business and technology expertise. Let's tease. "VMware Explore" next week, you're giving a keynote, if they're going to be there. Which day are you? >> Tuesday. Tuesday, 11 o'clock. >> All right, that's a big day. Tuesday, 11 o'clock. And David, please do stop by "The Cube." We're in Moscone West. Love to get you on and continue this conversation. I got 100 more questions for you. Really appreciate your time. >> I always love talking to people at "The Cube." Thank you very much. >> All right, and thanks for watching our ongoing coverage of "Supercloud22" on "The Cube," your leader in enterprise tech and emerging tech coverage. (bright music)

(upbeat music) >> (Narrator) From around the globe, it's theCUBE. With digital coverage of IBM Think 2021. Brought to you by IBM. >> Hello, welcome back to theCUBE's coverage of IBM Think 2021 virtual. Soon we'll be back in person in real life, but this year again it's a virtual conference. I'm John Furrier, your host of the cube for more cube coverage. We've got a great guest here, Debbie Vavangas, Global Garage Lead for IBM Services. Global Garage, great program. Debbie, great to see you. Thanks for coming on theCUBE. >> Thanks for having me. >> So, we've covered the Garage a lot on theCUBE in the past, and a success, everyone loves the Garage. Things are born in the Garage, entrepreneurship, innovation, has been kind of categorically known for, kind of, the Garage startup. >> Absolutely. >> But also, it's become known for, really, agility, which has been a cloud phenomenon, DevOps. Now we're seeing dev SecOps as a big trend this year with hybrid cloud. So, I've got to ask you, how is Garage doing with the pandemic? Obviously, I can almost imagine people at home kind of disrupted from the office, but maybe more creativity, maybe more energy online? What's going on with the Garage? How has your transformation journey been with COVID? >> Well, John, COVID has been the leveler for us all, right? There isn't a person who hasn't had some challenge or some complexity to And that includes our clients. And I'm incredibly proud to be able to say that IBM Garage, because it is so digitally native, when the COVID pandemic has struck around the world every single one of our Garages was able to switch to being virtual without fail, without a single days lost productivity. And that's hugely beneficial to clients who are on an incredibly time-sensitive journey. And so, we've seen as a result of COVID actually there are a huge acceleration in Garages, for two reasons. So, number one, from a virtualization perspective, actually it's much easier when everybodies together in the same space. So everybody's together virtually in the same space, and we've seen, you know, acceleration in our velocity, in our collaboration, because everybody is really learning how to work in that same space. But two, because of the pandemic, because of the pressure on our client's needs to make decisions fast, know not guess, really be focused on their outcomes, not just doing stuff, the Garage really plays to that objective for them. And so we've seen a huge rise, you know, we've gone from in 2019 to just a few hundred garages, to finishing 2020 with over two and a half thousand garages. And it being embedded across services and with the goal of being the primary way our clients experience it. So COVID has been a big accelerator. >> Sorry, Debbie, can you repeat the numbers again? I just want to capture that, I missed that. >> Sure, sure. >> I did a double take on the numbers. (Debbie laughs) >> So then, we finished 2019 with just under 300 garages, and we finished 2020 with just over two and a half thousand. So, we've had a huge growth, and it isn't just the number of garages, it's the range of garages and what we're serving with our clients, and how we're collaborating with our clients, and the topics we're unpacking that has really broadened. >> Yeah, I mean I covered, and we've reported on the Garage on theCUBE and also on www.siliconangle.com in the past things and through your news coverage, but that's amazing growth. I got to believe the tailwind from COVID and just the energy around it has energized you. I want to get your thoughts on that because, you know, what we've reported on in the past has been about design thinking, human-centered design, all of those beautiful things that come with cloud-scale, right? You know, you're moving faster, you're innovating, and so that's been kind of there. But what you're getting at with this growth is, and with COVID has proven, and again, we've been pointing this out, you're seeing the pattern, it's clear. Companies are either retrenching, okay, which is refactoring, redesigning, doing those things to kind of get ready to come out of COVID with a growth strategy, and you're seeing other companies build net new innovations. So, they're building new capabilities, because COVID's shown them, kind of pulled back the curtain if you will on where the action is. So, this means there's two threads going on. You've got, "Okay, I've got to transform my business, and I got to refactor', or 'Hey, we got net new business models'. These are kind of two different things and not mutually exclusive. What's your comment on that? >> And I think that my comment on it is that is the sweet spot that Garage comes into its own, right? You mentioned lots of things in there. You talked about design thinking, and agility, and, you know, these other buzzwords that are used all the time, and Garage of course is synonymous with those. Of course, Garage uses the best design thinking, and AGILE practices, and all of those things that absolutely call to what we do. DevOps, even through down to DesignOps. You know, we have the whole range depending on what the client objective is. But, I think what is really happening now is that innovation being something separate is no longer how to accelerate your outcomes, and your business outcomes. Regardless of whether that is in refactoring and modernizing your existing estate, or diversifying, creating new ecosystems, new platforms, new offerings. Regardless of what that is, you can't do it separate to your core business. I mean, it's a well known fact, John, right? Like 75% of transformation programs fail to deliver an impact to the business performance, right? And in the same period of time there's been huge cuts in innovation funding, and that's because for the same reason, because they don't deliver the impact to the business performance. And that's why Garage is unique, because it is entirely focused on the outcome, right? We're using user research, through design thinking of course, using agile to deliver it at speed, and all of those other things. But, it's focused on value, on benefits realization and driving to your outcome. And we do that by putting that innovation at the heart of your enterprise in order to drive that transformation, rather than it being something separate. >> Debbie, I saw you gave a talk called 'Innovation is Dead'. Obviously, that's a provocative title, that's an attention-getter. Tell me what you mean by that. Because it seems to be a setup. >> I mean, if the innovation is dead, >> Of course. was it with a question mark? Were you, kind of, trying to highlight that innovation is transformation? >> So, the full title was 'Innovation is dead and transformation is pointless'. And, of course, it's meant to be an eye-catching title so people show up and listen to my pitch rather than somebody else's. But, the reality is I mean it most sincerely, it's back to that stat. 75% of these transformation programs fail to deliver the impact, and I speculate that that is for a few reasons. Because, the idea itself wasn't a good one, or wasn't at the right time. Because, you were unable to understand what the measure of good looked like, and therefore just being able to create that path. And, in order to transform a company, you must transform the individuals within a company. And so that way of working becomes incredibly holistic. And it's those three things, that I think amongst the whole myriad of others, that are the primary reasons why those programs fail. And what Garage does, is it breaks that. By putting innovation at the heart of your enterprise, and by using data-driven value orchestration, that means that we don't guess where the value to be gained is, we know. It's no longer chucking ideas at the wall to see what sticks, it's meaningful research. This is my favorite quote from my dear friend, Courtney Noll, who says, "It's not about searching for the innovation needle in the proverbial haystack, it's using your research in order to de-risk your investment, and drive your innovation to enable your outcomes." And so, if you do innovation without a view to how it's going to yield your business outcomes, I agree, I fundamentally agree that it's pointless. >> Yeah, exactly. And, you know, of course we're on the writing side, we love titles like, 'Innovation is dead, long live innovation'. So, it's classic, you know, to get your attention. >> Exactly, exactly. And of course, what I really mean is that innovation is a separate entity. >> Totally. >> There's no longer relevance for a company to make sure they achieve their business outcomes. >> Well, this is what I wanted to just double-click on that with you on is that you look at transformation. You guys are essentially saying transformation meets innovation with the Garage philosophy, if I get that right. >> Yep >> And it's interesting, and we've experienced this here with theCUBE, we're theCUBE virtual, we're not at IBM Think, there is no physical game day like some of us normally do. >> Well, as you can see, I'm at my house. (Debbie laughs) And so, I was talking to a CEO and I said, "Hey, you guys are doing really, really good. We had to pivot with the cube", and he goes, "You guys did a good pivot yourself". He goes, "No, John, we did not pivot. We actually put our business on hold because of the pandemic. We actually created a line extension, so, technically, we're going to bring that business back when COVID has gone and come back to real life, so it's technically not a pivot, we're not pivoting our business, we've created new functionality." Through the innovations that they were doing. So, this is kind of like, this is the real deal here. Share your thoughts on that. >> To me, it's about people get so focused on the output that they lose track of the outcome, right? And so, be really clear on what you're doing, and why. And the outcomes can be really broad, so instead of saying, "We're all going to implement a new ERP, or build a new mobile app". That's not an outcome, right? What we should be saying is, "What we're trying to achieve is a 10 percent growth in net promoter score in China, right? In this group." Or whatever it is we were trying to achieve, right? Or, "We want to make a 25% reduction in our operating cost base by simplifying our estate". Whatever those outcomes are, that's the starting point, and then driving that to use as the vehicle for what is the right innovation, what is going to deliver that value, and fast, right? Garage delivers three to five times faster than other models and at a reduced delivery cost, and so it's all about that speed. Speed of decision, speed of insight, speed of culture and training, speed of new skills, and speed to outcomes. >> Well, Debbie, you did a great job, love what you're doing, and Garage has got a great model. Congratulations on the growth, love this intersection, or transformation meets innovation because innovation is transformation, and vice versa, this interplay going on there. >> Exactly. >> I think COVID has proven that. Let me dig into a little bit more about the garage, what's going on. How many practitioners do you guys have there now at IBM? You've got growth, are you adding more people in? Obviously, Virtual First, COVID, is there still centers of design? Take us through what's going on at Garage. >> Certainly, so like, I think I mentioned it right up front. Our goal is to make IBM Garage the primary way our clients experience us. We've proven in that it delivers higher value to our clients and they get a really rich and broad set of outcomes. And so, in order for us to deliver on that promise we have to be enabled across IBM to deliver to it, right? So, over the last 18 months or so we've had a whole range of training programs in Enable, we've had a whole badging and certification program, we have all the skills, and the pathways, and the career pathways to find. But Garage is for everybody, right? And so, it isn't about creating a select group that can do this across IBM. This is about making all of services capable. So, in 2020 we trained over 28,000 people, in all the different skills that are needed, from selling, to execution, to QA, to user research, whatever it is. And this year we're launching our Garage Skills Academy, which will take that across all of services and make it easily available. So, you know, we've got hundreds of thousands. >> And talk about the footprint on the global side, because, again, not to bring up global, but global is what is in your title. >> Yep. >> Companies need to be global, because now with virtual workforces you're seeing much more tapped creativity and ability to execute from global teams. How does that impact you? >> Well, so it's global in two perspectives, right? So, number one, we have Garages all around the world, right? It isn't just the market of, you know, our most developed nations in Americas and Europe, it is everywhere, we see it in all emerging markets. From Latin America, through to all parts of eastern Europe, which are really beginning to come into their own. So, we see all these different Garages at different scales and opportunities. So, definitely global from that image. But, what virtualization has also enabled is truly global teams. Because, it's really easy to go, "Oh, I need one of those. Okay, I need a supply chain expert, and I need an AI expert, and I need somebody who's got industry experience in whatever it is." And you can quickly gather them around the virtual table, you know, faster than you can in a physical table. But, we still leverage the global communities with those physical. >> It's an expert network. You have an expert network there at IBM. >> We have a huge network, yeah. And both within IBM, and of course a growing network of ecosystem partners that we continue to work with. >> Well, Debbie, I'm really excited. Congratulations on the growth. I'm looking forward to partnering with you on your ecosystem as that develops. I can almost imagine you must be getting a lot of outside IBM practitioners and experts coming in to collaborate in a social construct. >> Absolutely. >> It's a great program, thanks for sharing. >> My pleasure, it's been great to be here, thank you. >> Okay, IBM's Global Garage Lead, Debbie Vavangas, who's here on theCUBE with IBM Services. A phenomenon, it's a social construct that's helping companies with digital transformation. Intersecting, with innovation. I'm John Furrier, your host. Thanks for watching. (upbeat music)

>>from around the globe, it's the >>Cube with digital coverage of IBM think 2020 >>one brought to you >>by IBM. Hello, welcome back to the cubes coverage of IBM Think 2021 virtual soon we'll be back in person in real life. But this year again it's a virtual conference. I'm john for your host of the cube for more cube coverage. You got a great guest here Debbie Viviendas Global garage lead for IBM Services Global garage great program. Ah Debbie, great to see you. Thanks for coming on the cube. >>Thanks for having me. >>So we've covered the garage a lot on the cube in the past and the success, Everyone loves the garage things are born in the garage, entrepreneurship innovation has been kind of categorically known for kind of the garage start up um but also it's become um known for really agile agility and which has been a cloud phenomenon, devops and now we're seeing Deb sec apps as a big trend this year with hybrid cloud. So I gotta ask you, how is garage doing with the pandemic? I was I can almost imagine people at home kind of disrupted from the office, but maybe more creativity, maybe more energy online. What's going on with the garage? How has your transformation journey been with Covid? >>Well, don't I mean it's Covid has been the level of for us. All right, there isn't a person who hasn't had some challenge or some complexity to Yeah, and that includes our clients and I'm incredibly proud to be able to say that IBM garage because it is so digitally native. When the covid pandemic has struck around the world, every single one of our garages was able to switch to being virtual without fail without a single days lost productivity. And that I mean that's hugely beneficial to clients who are on an incredible time sensitive journey. And so we've seen as a result of Covid actually there are a huge acceleration in garages from two reasons. The number one from a virtualization perspective. Actually it's much easier when everybody's together in the same space, everybody's together virtually in the same space. And we've seen acceleration in our velocity and our collaboration because everybody is really learning how to work in that century. But to because of the pandemic, because of the pressure on our client's needs to make decisions fast. No, not guess really, be focused on their outcomes, not just doing stuff, the garage really plays to that objective for them. And so we've seen a huge rise. We've gone from 2019 to just a few 100 garages to finishing 2020 with over 2.5 1000 garages and being embedded across services and the goal of being the primary way our clients experiencing COVID has been a big accelerator. >>Sorry Debbie, can you repeat the numbers again? I just want to capture that. I missed that. >>Sure. Sure. So we finished >>training on the numbers. >>Yeah. So that we finished 2019 with just under 300 garages and we finished 2020 with just over 2.5 1000. So we've had a huge growth in the in the rain and it isn't just the number of garages, it's the range of garages and what we're what we're serving with our clients and how we're collaborating with our clients and the topics were unpacking. That is is really broadened. >>Yeah. I mean I I covered and we've reported on the garage on the Cuban also in silicon angle dot com. And the past thinks and through your your news coverage. That's amazing growth. Um I gotta believe the tailwind from Covid and just the energy around it has energized. You wanna get your thoughts on that because you know what we've reported the past, it's been about design, thinking human centered design, all those beautiful things that come with cloud, cloud scale, right? You know, you're moving faster, you're innovating. Um and so that's been kind of there, but what you're getting at with this growth is with and what Covid has proven. And again, we've been pointing this out, you're seeing the pattern, It's clear companies are either retrenching okay. Which is re factoring, redesigning, doing those things to kind of get ready to come out to cope with a growth strategy and you're seeing other companies um build net new innovations so they're building new capabilities because Covid shown them kind of pulled back the curtain if you will on where the action is. So this means there's two threads going on. You got okay, I got to transform my business and I gotta re factor and then, or hey, we got net new business models, these are kind of two different things and not mutually exclusive. What's your comment on that? >>Uh, and I think that my comment on is that is the sweet spot that garage comes into its own right. You mentioned lots of things in that, you talked about design thinking and agility and you know, these other buzzwords that are used all the time and garage of course is synonymous with those of course, you know, it's Gap uses the best design thinking and agile practices and all of those things that absolutely core to what we do, devops, even through down to design up, we have the whole range depending on what the client objective is, but I think what is really happening now is the innovation, you know, being something separate. It is no longer how to accelerate your outcomes and your business outcomes regardless of whether that is in re factoring and modernizing your existing estate or diversifying creating new ecosystems and new platforms and new offerings. Regardless of what that is, you can't do it separate to your, To your core business. I mean it's a well known fact John right, like 75 of transformation programmes failed to deliver an impact on the business performance. Right? And in the same period of time there's been huge cuts in innovation funding and that's because for the same reason because they don't deliver the impact of the business performance and that's why garage is unique because it is entirely focused on the outcome, right? But using user research through design thinking of course using agile to deliver it at speed and all of those other things, but it's focused on value, on benefits, realization and driving to your outcome. And we do that by putting that innovation at the heart of your enterprise in order to drive that transformation rather than it being something separate. >>Debbie, I saw you gave a talk uh called Innovation Is Dead. Um obviously that's a provocative title. That's an attention getter. Um tell me what you mean by that because it seems to be a setup. I mean many mentions dead. Was it with a question mark? What you're kind of trying to highlight that innovation is transformation? Or were you trying >>to do the full title? The full title was Innovation is Dead and transformation is pointless. And of course, it's meant to be an eye catching title. So people show up and listen to my pitch rather than somebody else's. But But the reality is I mean that most sincerely it's back to that step, 75 of these transformation programmes failed to deliver the impact. And I and I speculate that that is for a few reasons because the idea itself wasn't a good one or wasn't at the right time because you were unable to understand what the measure of good looked like and therefore him just be able to create that path. And in order to transform a company, you must transform the individuals within a company. And so that way of working becomes incredibly holistic and it's those three things, I think amongst the whole myriad of others are the primary reasons why those programs fail. And what garage does is it breaks this by putting innovation at the heart of your enterprise and by using data driven value orchestration. That means that we don't no, we don't guess where the value to be gained is. We know it's no longer checking ideas at the wall to see what sticks it's meaningful research. It's not searching. This is my favorite quote from my dear friend Courtney, know, who says it's not about searching for the innovation needle in the proverbial haystack. It's using your research in order to de risk your investment and drive your innovation to enable your outcomes. So if you do innovation without a view to how it's going to yield your business outcomes, I agree. I fundamentally agree that it's pointless. >>Exactly. Of course, we're on the writing side. We love titles like innovation is dead long live innovation, so that's classic. Get your attention. But I think >>Exactly, and of course what I really mean is that innovation is a separate entity, >>totally. >>There is no longer relevant for company to make sure they achieve their business >>outcome. Well, this is what I wanted to just double click on that with you on is that you look at transformation, you guys essentially saying transformation meets innovation with the garage philosophy if I get that right. Um, and, and, and it's interesting I had, and we've experienced here with the cube where the cube virtual, we're not at IBM think there is no physical game day, like >>my house. >>And, and so I was talking to a Ceo and he said, I said, hey you guys are doing really, really good. You know, we had to pivot with the cube and he goes, you guys did a good pivot yourself because no, john we did not pivot, we actually put our business on hold because of the pandemic. We actually created a line extension. So technically we're going to bring that business back when Covid is gone and we come back to real life. So it's technically not a pivot. We're not pivoting our business. We've created new functionality through the innovations that they were doing. So this is kind of like, this is the real deal here. This is like depends proven what's your share your thoughts on that? >>Well, it's just to me it's about people get so focused on the output that they lose track of the outcome, right? And so being really clear on what you're doing and why and the outcomes can be really broad that, you know, so instead of saying, you know, we're all going to implement the new E. R. P. Or build a new mobile app. That's that's that's not an outcome, right? What we should be saying is what we're trying to achieve is a 10% growth in net promoter score in china, Right in this group or whatever it is we were trying to achieve right, we want to make a 25 reduction in our operating cost base by simplifying our estate whatever those outcomes are. I mean that's the starting point and then driving that use to use as the vehicle for what is the right innovation, what is going to deliver that value and fast right garage delivers 3-5 times faster than other models and reduced delivery costs. And so it's all about that speed, speed of decision, speed of insight, speed of culture and training, speed of new skills and speed to outcomes. >>You got a great job, love what you're doing in Karaj got a great model, congratulations on the growth. Love this intersection or transformation meets innovation because innovation is transformation advice versus interplay going on there I think has proven that. Let me dig into a little bit more about the garage. What's going on? How many practitioners you guys have there now at IBM? Um, you've got growth. Are you adding more people in? I'll see virtual first. Covid. Is there still centers of design take us through what's going on at garage? >>Certainly. So I think I mentioned it right up front. Right. So our goal is to make IBM guards the primary way our clients experiences. We've proven that it delivers higher value to our clients and they get really rich and broad set of outcomes. And so in order for us to deliver on that promise, we have to be unable to cross IBM to deliver to it. Right? So over the last 18 months or so we've had a whole range of training programs and enable we have a whole badging and certification program. We have all the skills and the pathways and the career pathways to find. But garages for everybody. Right? And so it isn't about creating a selected group that can do this across IBM, this is about making all of services capable. So in 2020 we we trained over 28,000 people right? In in all the different skills that are needed from selling to execution to QA to use a research, whatever it is. And this year we're launching our garage skills academy which will take that across all of services and make it easily available. So we will, you've got to >>talk about the footprint of the global side because again, not to bring up global, but global is what yours in your title companies need to be global because now with virtual workforce is you're seeing much more tapped creativity and execution ability to execute from global teams. How does that impact you? >>Well, so garages as in its global in two perspectives. Right, So number one, we have garages all around the world. Right? It isn't it isn't just the market of you are most developed nations in the Americas and europe. It is everywhere. We see it in all emerging markets, from latin America through to you all parts of eastern europe which are really beginning to come into their own. So we see all these different garages of different different scales and opportunity. So definitely global from that image. But what what what virtualization has also enabled these truly global teams because it's really easy to go, I need one of those. Okay, I need a supply chain expert and I need an Ai expert and I need somebody who's got industry experience in whatever it is and you can quickly gather them around the virtual table faster than you can in a physical table. But we still leverage the global community >>for the network. You have an expert network there at IBM. >>You have a huge network. Yeah. And both both within IBM and of course a growing network of ecosystem partners that we continue to work >>with. Debbie. I'm really excited. Congratulations. Growth. I'm looking forward to partnering with you on your ecosystem as that develops. I can almost imagine you must be getting a lot of outside IBM practitioners and experts coming in to collaborate. It is a social construct. It's a great program. Thanks for sharing >>my pleasure. It's been great to be here. Thank >>you. Okay, IBM's global garage. Lee Debbie Vegas who's here on the queue with IBM services, a phenomenon. This is social construct is helping companies with digital transformation intersecting with innovation. I'm john for your host. Thanks for watching

(upbeat music) >> Welcome to this special cloud virtual event, theCUBE on cloud. This is our continuing editorial series of the most important stories in cloud. We're going to explore the cutting edge most relevant technologies and companies that will impact business and society. We have special guests from Jeff Barr, Michael Liebow, Jerry Chen, Ben Haynes, Michael skulk, Mike Feinstein from AWS all today are presenting the top startups in the AWS ecosystem. This is the AWS showcase of startups. I'm showing with Dave Vellante. Dave great to see you. >> Hey John. Great to be here. Thanks for having me. >> So awesome day today. We're going to feature a 10 grade companies amplitude, auto grid, big ID, cordial Dremio Kong, multicloud, Reltio stardog wire wheel, companies that we've talked to. We've researched. And they're going to present today from 10 for the rest of the day. What's your thoughts? >> Well, John, a lot of these companies were just sort of last decade, they really, were keyer kicker mode, experimentation mode. Now they're well on their way to hitting escape velocity which is very exciting. And they're hitting tens of millions dollars of ARR, many are planning IPO's and it's just it's really great to see what the cloud has enabled and we're going to dig into that very deeply today. So I'm super excited. >> Before we jump into the keynote (mumbles) our non Huff from AWS up on stage Jeremy is the brains behind this program that we're doing. We're going to do this quarterly. Jeremy great to see you, you're in the global startups program at AWS. Your job is to keep the crops growing, keep the startups going and keep the flow of innovation. Thanks for joining us. >> Yeah. Made it to startup showcase day. I'm super excited. And as you mentioned my team the global startup program team, we kind of provide white glove service for VC backed startups and help them with go to market activities. Co-selling with AWS and we've been looking for ways to highlight all the great work they're doing and partnering with you guys has been tremendous. You guys really know how to bring their stories to life. So super excited about all the partner sessions today. >> Well, I really appreciate the vision and working with Amazon this is like truly a bar raiser from theCUBE virtual perspective, using the virtual we can get more content, more flow and great to have you on and bring that the top hot startups around data, data ops. Certainly the most important story in tech is cloud scale with data. You you can't look around and seeing more innovation happening. So I really appreciate the work. Thanks for coming on. >> Yeah, and don't forget, we're making this a quarterly series. So the next one we've already been working on it. The next one is Wednesday, June 16th. So mark your calendars, but super excited to continue doing these showcases with you guys in the future. >> Thanks for coming on Jeremy. I really appreciate it,. Dave so I want to just quick quickly before we get Jeff up here, Jeff Barr who's a luminary guests for us this week who has been in the industry has been there from the beginning of AWS the role of data, and what's happened in cloud. And we've been watching the evolution of Amazon web services from the beginning, from the startup market to dominate in the enterprise. If you look at the top 10 enterprise companies Amazon wasn't on that list in 2010 they weren't even bringing the top 10 Andy Jassy's keynote at reinvent this past year. Highlighted that fact, I think they were number five or four as vendor in just AWS. So interesting to see that you've been reporting and doing a lot of analysis on the role of data. What's your analysis for these startups and as businesses need to embrace the new technologies and be on the right side of history not part of that old guard, incumbent failed model. >> Well, I think again, if you look back on the early days of cloud, it was really about storage and networking and compute infrastructure. And then we collected all this data and now you're seeing the next generation of innovation and value. We're going to talk to Michael Liebow about this is really if you look at all the value points in the leavers, it's all around data and data is going through a massive change in the way that we think about it, that we talk about it. And you hear that a lot. Obviously you talk about the volumes, the giant volumes but there's something else going on as AWS brings the cloud to the edge. And of course it looks at the data centers, just another edge device, data is getting highly decentralized. And what we're seeing is data getting into the hands of business owners and data product builders. I think we're going to see a new parlance emerge and that's where you're seeing the competitive advantage. And if you look at all the real winners these days in the marketplace especially in the digital with COVID, it all comes back to the data. And we're going to talk about that a lot today. >> One of the things that's coming up in all of our cube interviews, certainly we've seen, I mean we've had a great observation space across all the ecosystems, but the clear thing that's coming out of COVID is speed, agility, scale, and data. If you don't have that data you are going to be a non-player. And I think I heard some industry people talking about the future of how the stock market's going to work and that if you're not truly in market with an AI or machine learning data value play you probably will be shorted on the stock market or delisted. I think people are looking at that as a table stakes competitive advantage item, where if you don't have some sort of data competitive strategy you're going to be either delisted or sold short. And that's, I don't think delisted but the point is this table-stakes Dave. >> Well, I think too, I think the whole language the lingua franca of data is changing. We talk about data as an asset all the time, but you think about it now, what do we do with assets? We protect it, we hide it. And we kind of we don't share it. But then on the other hand, everybody talks about sharing the data and that is a huge trend in the marketplace. And so I think that everybody is really starting to rethink the whole concept of data, what it is, its value and how we think about it, talk about it, share it make it accessible, and at the same time, protect it and make it governed. And I think you're seeing, computational governance and automation really hidden. Couldn't do this without the cloud. I mean, that's the bottom line. >> Well, I'm super excited to have Jeff Barr here from AWS as our special keynote guests. I've been following Jeff's career for a long, long time. He's a luminaries, he's a technical, he's in the industry. He's part of the community, he's been there from the beginning AWS just celebrate its 15th birthday as he was blogging hard. He's been a hardcore blogger. I think Jeff, you had one of the original ping service. If I remember correctly, you were part of the web services foundational kind of present at creation. No better guests to have you Jeff thanks for coming up on our stage. >> John and Dave really happy to be here. >> So I got to ask you, you've been blogging hard for the past decade or so, going hard and your job has evolved from blogging about what's new with Amazon. A couple of building blocks a few services to last reinvent them. You must have put out I don't know how many blog posts did you put out last year at every event? I mean, it must have been a zillion. >> Not quite a zillion. I think I personally wrote somewhere between 20 and 25 including quite a few that I did in the month or so run up to reinvent and it's always intense, but it's always really, really fun. >> So I've got to ask you in the past couple of years, I mean I quoted Andy Jassy's keynote where we highlight in 2010 Amazon wasn't even on the top 10 enterprise players. Now in the top five, you've seen the evolution. What is the big takeaway from your standpoint as you look at the enterprise going from Amazon really dominating the start of a year startups today, you're in the cloud, you're born in the cloud. There's advantage to that. Now enterprises are kind of being reborn in the cloud at the same time, they're building these new use cases rejuvenating themselves and having innovation strategy. What's your takeaway? >> So I love to work with our customers and one of the things that I hear over and over again and especially the last year or two is really the value that they're placing on building a workforce that has really strong cloud skills. They're investing in education. They're focusing on this neat phrase that I learned in Australia called upskilling and saying let's take our set of employees and improve their skill base. I hear companies really saying we're going to go cloud first. We're going to be cloud native. We're going to really embrace it, adopt the full set of cloud services and APIs. And I also see that they're really looking at cloud as part of often a bigger picture. They often use the phrase digital transformation, in Amazon terms we'd say they're thinking big. They're really looking beyond where they are and who they are to what they could be and what they could grow into. Really putting a lot of energy and creativity into thinking forward in that way. >> I wonder Jeff, if you could talk about sort of how people are thinking about the future of cloud if you look at where the spending action is obviously you see it in cloud computing. We've seen that as the move to digital, serverless Lambda is huge. If you look at the data it's off the charts, machine learning and AI also up there containers and of course, automation, AWS leads in all of those. And they portend a different sort of programming model a different way of thinking about how to deploy workloads and applications maybe different than the early days of cloud. What's driving that generally and I'm interested in serverless specifically. And how do you see the next several years folding out? >> Well, they always say that the future is the hardest thing to predict but when I talked to our enterprise customers the two really big things that I see is there's this focus that says we need to really, we're not simply like hosting the website or running the MRP. I'm working with one customer in particular where they say, well, we're going to start on the factory floor all the way up to the boardroom effectively from IOT and sensors on the factory floor to feed all the data into machine learning. So they understand that the factory is running really well to actually doing planning and inventory maintenance to putting it on the website to drive the analytics, to then saying, okay, well how do we know that we're building the right product mix? How do we know that we're getting it out through the right channels? How are our customers doing? So they're really saying there's so many different services available to us in the cloud and they're relatively easy and straightforward to deploy. They really don't think in the old days as we talked about earlier that the old days where these multi-year planning and deployment cycles, now it's much more straightforward. It's like let's see what we can do today. And this week and this month, and from idea to some initial results is a much, much shorter turnaround. So they can iterate a lot more quickly which is just always known to produce better results. >> Well, Jeff and the spirit of the 15th birthday of AWS a lot of services have been built from the original three. I believe it was the core building blocks and there's been a lot of history and it's kind of like there was a key decoupling of compute from storage, those innovations what's the most important architectural change if any has happened or built upon those building blocks with AWS that you could share with companies out there as many people are coming into the cloud not just lifting and shifting and having that innovation but really building cloud native and now hybrid full cloud operations, day two operations. However you want to look at it. That's a big thing. What architecturally has changed that's been innovative from those original building blocks? >> Well, I think that the basic architecture has proven to be very, very resilient. When I wrote about the 15 year birthday of Amazon S3 a couple of weeks ago one thing that I thought was really incredible was the fact that the same APIs that you could have used 15 years ago they all still work. The put, the get, the list, the delete, the permissions management, every last one of those were chosen with extreme care. And so they all still work. So one of the things you think about when you put APIs out there is in Amazon terms we always talk about going through a one-way door and a one way door says, once you do it you're committed for the indefinite future. And so you we're very happy to do that but we take those steps with extreme care. And so those basic building blocks so the original S3 APIs, the original EC2 APIs and the model, all those things really worked. But now they're running at this just insane scale. One thing that blows me away I routinely hear my colleagues talking about petabytes and exabytes, and we throw around trillions and quadrillions like they're pennies. It's kind of amazing. Sometimes when you hear the scale of requests per day or request per month, and the orders of magnitude are you can't map them back to reality anymore. They're simply like literally astronomical. >> If I can just jump in real quick Dave before you ask Jeff, I was watching the Jeff Bezos interview in 1999 that's been going around on LinkedIn in a 60 minutes interview. The interviewer says you are reporting that you can store a gigabyte of customer data from all their purchases. What are you going to do with that? He basically nailed the answer. This is in 99. We're going to use that data to create, that was only a gig. >> Well one of the things that is interesting to me guys, is if you look at again, the early days of cloud, of course I always talked about that in small companies like ours John could have now access to information technology that only big companies could get access to. And now you've seen we just going to talk about it today. All these startups rise up and reach viability. But at the same time, Jeff you've seen big companies get the aha moment on cloud and competition drives urgency and that drives innovation. And so now you see everybody is doing cloud, it's a mandate. And so the expectation is a lot more innovation, experimentation and speed from all ends. It's really exciting to see. >> I know this sounds hackneyed and overused but it really, really still feels just like day one. We're 15 plus years into this. I still wake up every morning, like, wow what is the coolest thing that I'm going to get to learn about and write about today? We have the most amazing customers, one of the things that is great when you're so well connected to your customers, they keep telling you about their dreams, their aspirations, their use cases. And we can just take that and say we can actually build awesome things to help you address those use cases from the ground on up, from building custom hardware things like the nitro system, the graviton to the machine learning inferencing and training chips where we have such insight into customer use cases because we have these awesome customers that we can make these incredible pieces of hardware and software to really address those use cases. >> I'm glad you brought that up. This is another big change, right? You're getting the early days of cloud like, oh, Amazon they're just using off the shelf components. They're not buying these big refrigerator sized disc drives. And now you're developing all this custom Silicon and vertical integration in certain aspects of your business. And that's because workload is demanding. You've got to get more specialized in a lot of cases. >> Indeed they do. And if you watch Peter DeSantis' keynote at re-invent he talked about the fact that we're researching ways to make better cement that actually produces less carbon dioxide. So we're now literally at the from the ground on up level of construction. >> Jeff, I want to get a question from the crowd here. We got, (mumbles) who's a good friend of theCUBE cloud Arate from the beginning. He asked you, he wants to know if you'd like to share Amazon's edge aspirations. He says, he goes, I mean, roadmaps. I go, first of all, he's not going to talk about the roadmaps, but what can you share? I mean, obviously the edge is key. Outpost has been all in the news. You obviously at CloudOps is not a boundary. It's a distributed network. What's your response to-- >> Well, the funny thing is we don't generally have technology roadmaps inside the company. The roadmap is always listen really well to customers not just where they are, but the customers are just so great at saying, this is where we'd like to go. And when we hear edge, the customers don't generally come to us and say edge, they say we need as low latency as possible between where the action happens within our factory floors and our own offices and where we might be able to compute, analyze, store make decisions. And so that's resulted in things like outposts where we can put outposts in their own data center or their own field office, wavelength, where we're working with 5G telecom providers to put computing storage in the carrier hubs of the various 5G providers. Again, with reducing latency, we've been doing things like local zones, where we put zones in an increasing number of cities across the country with the goal of just reducing the average latency between the vast majority of customers and AWS resources. So instead of thinking edge, we really think in terms of how do we make sure that our customers can realize their dreams. >> Staying on the flywheel that AWS has built on ship stuff faster, make things faster, smaller, cheaper, great mission. I want to ask you about the working backwards document. I know it's been getting a lot of public awareness. I've been, that's all I've learned in interviewing Amazon folks. They always work backwards. I always mentioned the customer and all the interviews. So you've got a couple of customer references in there check the box there for you. But working backwards has become kind of a guiding principles, almost like a Harvard Business School case study approach to management. As you guys look at this working backwards and ex Amazonians have written books about it now so people can go look at, it's a really good methodology. Take us back to how you guys work back from the customers because here we're featuring 10 startups. So companies that are out there and Andy has been preaching this to customers. You should think about working backwards because it's so fast. These companies are going into this enterprise market your ecosystem of startups to provide value. What things are you seeing that customers need to think about to work backwards from their customer? How do you see that? 'Cause you've been on the community side, you see the tech side customers have to move fast and work backwards. What are the things that they need to focus on? What's your observation? >> So there's actually a brand new book called "Working Backwards," which I actually learned a lot about our own company from simply reading the book. And I think to me, a principal part of learning backward it's really about humility and being able to be a great listener. So you don't walk into a customer meeting ready to just broadcast the latest and greatest that we've been working on. You walk in and say, I'm here from AWS and I simply want to learn more about who you are, what you're doing. And most importantly, what do you want to do that we're not able to help you with right now? And then once we hear those kinds of things we don't simply write down kind of a bullet item of AWS needs to improve. It's this very active listening process. Tell me a little bit more about this challenge and if we solve it in this way or this way which one's a better fit for your needs. And then a typical AWS launch, we might talk to between 50 and 100 customers in depth to make sure that we have that detailed understanding of what they would like to do. We can't always meet all the needs of these customers but the idea is let's see what is the common base that we can address first. And then once we get that first iteration out there, let's keep listening, let's keep making it better and better and better as quickly. >> A lot of people might poopoo that John but I got to tell you, John, you will remember this the first time we ever met Andy Jassy face-to-face. I was in the room, you were on the speaker phone. We were building an app on AWS at the time. And he was asking you John, for feedback. And he was probing and he pulled out his notebook. He was writing down and he wasn't just superficial questions. He was like, well, why'd you do it that way? And he really wanted to dig. So this is cultural. >> Yeah. I mean, that's the classic Amazon. And that's the best thing about it is that you can go from zero startups zero stage startup to traction. And that was the premise of the cloud. Jeff, I want to get your thoughts and commentary on this love to get your opinion. You've seen this grow from the beginning. And I remember 'cause I've been playing with AWS since the beginning as well. And it says as an entrepreneur I remember my first EC2 instance that didn't even have custom domain support. It was the long URL. You seen the startups and now that we've been 15 years in, you see Dropbox was it just a startup back in the day. I remember these startups that when they were coming they were all born on Amazon, right? These big now unicorns, you were there when these guys were just developers and these gals. So what's it like, I mean, you see just the growth like here's a couple of people with them ideas rubbing nickels together, making magic happen who knows what's going to turn into, you've been there. What's it been like? >> It's been a really unique journey. And to me like the privilege of a lifetime, honestly I've like, you always want to be part of something amazing and you aspire to it and you study hard and you work hard and you always think, okay, somewhere in this universe something really cool is about to happen. And if you're really, really lucky and just a million great pieces of luck like lineup in series, sometimes it actually all works out and you get to be part of something like this when it does you don't always fully appreciate just how awesome it is from the inside, because you're just there just like feeding the machine and you are just doing your job just as fast as you possibly can. And in my case, it was listening to teams and writing blog posts about their launches and sharing them on social media, going out and speaking, you do it, you do it as quickly as possible. You're kind of running your whole life as you're doing that as well. And suddenly you just take a little step back and say, wow we did this kind of amazing thing, but we don't tend to like relax and say, okay, we've done it at Amazon. We get to a certain point. We recognize it. And five minutes later, we're like, okay, let's do the next amazingly good thing. But it's been this just unique privilege and something that I never thought I'd be fortunate enough to be a part of. >> Well, then the last few minutes we have Jeff I really appreciate you taking the time to spend with us for this inaugural launch of theCUBE on cloud startup showcase. We are showcasing 10 startups here from your ecosystem. And a lot of people who know AWS for the folks that don't you guys pride yourself on community and ecosystem the global startups program that Jeremy and his team are running. You guys nurture these startups. You want them to be successful. They're vectoring out into the marketplace with growth strategy, helping customers. What's your take on this ecosystem? As customers are out there listening to this what's your advice to them? How should they engage? Why is these sets of start-ups so important? >> Well, I totally love startups and I've spent time in several startups. I've spent other time consulting with them. And I think we're in this incredible time now wheres, it's so easy and straightforward to get those basic resources, to get your compute, to get your storage, to get your databases, to get your machine learning and to take that and to really focus on your customers and to build what you want. And we see this actual exponential growth. And we see these startups that find something to do. They listen to one of their customers, they build that solution. And they're just that feedback cycle gets started. It's really incredible. And I love to see the energy of these startups. I love to hear from them. And at any point if we've got an AWS powered startup and they build something awesome and want to share it with me, I'm all ears. I love to hear about them. Emails, Twitter mentions, whatever I'll just love to hear about all this energy all those great success with our startups. >> Jeff Barr, thank you for coming on. And congratulations, please pass on to Andy Jassy who's going to take over for Jeff Bezos and I saw the big news that he's picking a successor an Amazonian coming back into the fold, Adam. So congratulations on that. >> I will definitely pass on your congratulations to Andy and I worked with Adam in the past when AWS was just getting started and really looking forward to seeing him again, welcoming back and working with him. >> All right, Jeff Barr with AWS guys check out his Twitter and all the social coordinates. He is pumping out all the resources you need to know about if you're a developer or you're an enterprise looking to go to the next level, next generation, modern infrastructure. Thanks Jeff for coming on. Really appreciate it. Our next guests want to bring up stage Michael Liebow from McKinsey cube alumni, who is a great guest who is very timely in his McKinsey role with a paper he and his colleagues put out called cloud's trillion dollar prize up for grabs. Michael, thank you for coming up on stage with Dave and I. >> Hey, great to be here, John. Thank you. >> One of the things I loved about this and why I wanted you to come on was not only is the report awesome. And Dave has got a zillion questions, he want us to drill into. But in 2015, we wrote a story called Andy Jassy trillion dollar baby on Forbes, and then on medium and silken angle where we were the first ones to profile Andy Jassy and talk about this trillion dollar term. And Dave came up with the calculation and people thought we were crazy. What are you talking about trillion dollar opportunity. That was in 2015. You guys have put this together with a serious research report with methodology and you left a lot on the table. I noticed in the report you didn't even have a whole section quantified. So I think just scratching the surface trillion. I'd be a little light, Dave, so let's dig into it, Michael thanks for coming on. >> Well, and I got to say, Michael that John's a trillion dollar baby was revenue. Yours is EBITDA. So we're talking about seven to X, seven to eight X. What we were talking back then, but great job on the report. Fantastic work. >> Thank you. >> So tell us about the report gives a quick lowdown. I got some questions. You guys are unlocking the value drivers but give us a quick overview of this report that people can get for free. So everyone who's registered will get a copy but give us a quick rundown. >> Great. Well the question I think that has bothered all of us for a long time is what's the business value of cloud and how do you quantify it? How do you specify it? Because a lot of people talk around the infrastructure or technical value of cloud but that actually is a big problem because it just scratches the surface of the potential of what cloud can mean. And we focus around the fortune 500. So we had to box us in somewhat. And so focusing on the fortune 500 and fast forwarding to 2030, we put out this number that there's over a trillion dollars worth of value. And we did a lot of analysis using research from a variety of partners, using third-party research, primary research in order to come up with this view. So the business value is two X the technical value of cloud. And as you just pointed out, there is a whole unlock of additional value where organizations can pioneer on some of the newest technologies. And so AWS and others are creating platforms in order to do not just machine learning and analytics and IOT, but also for quantum or mixed reality for blockchain. And so organizations specific around the fortune 500 that aren't leveraging these capabilities today are going to get left behind. And that's the message we were trying to deliver that if you're not doing this and doing this with purpose and with great execution, that others, whether it's others in your industry or upstarts who were motioning into your industry, because as you say cloud democratizes compute, it provides these capabilities and small companies with talent. And that's what the skills can leverage these capabilities ahead of slow moving incumbents. And I think that was the critical component. So that gives you the framework. We can deep dive based on your questions. >> Well before we get into the deep dive, I want to ask you we have startups being showcased here as part of the, it will showcase, they're coming out of the ecosystem. They have a lot of certification from Amazon and they're secure, which is a big issue. Enterprises that you guys talk to McKinsey speaks directly to I call the boardroom CXOs, the top executives. Are they realizing that the scale and timing of this agility window? I mean, you want to go through these key areas that you would break out but as startups become more relevant the boardrooms that are making these big decisions realize that their businesses are up for grabs. Do they realize that all this wealth is shifting? And do they see the role of startups helping them? How did you guys come out of them and report on that piece? >> Well in terms of the whole notion, we came up with this framework which looked at the opportunity. We talked about it in terms of three dimensions, rejuvenate, innovate and pioneer. And so from the standpoint of a board they're more than focused on not just efficiency and cost reduction basically tied to nation, but innovation tied to analytics tied to machine learning, tied to IOT, tied to two key attributes of cloud speed and scale. And one of the things that we did in the paper was leverage case examples from across industry, across-region there's 17 different case examples. My three favorite is one is Moderna. So software for life couldn't have delivered the vaccine as fast as they did without cloud. My second example was Goldman Sachs got into consumer banking is the platform behind the Apple card couldn't have done it without leveraging cloud. And the third example, particularly in early days of the pandemic was Zoom that added five to 6,000 servers a night in order to scale to meet the demand. And so all three of those examples, plus the other 14 just indicate in business terms what the potential is and to convince boards and the C-suite that if you're not doing this, and we have some recommendations in terms of what CEOs should do in order to leverage this but to really take advantage of those capabilities. >> Michael, I think it's important to point out the approach at sometimes it gets a little wonky on the methodology but having done a lot of these types of studies and observed there's a lot of superficial studies out there, a lot of times people will do, they'll go I'll talk to a customer. What kind of ROI did you get? And boom, that's the value study. You took a different approach. You have benchmark data, you talked to a lot of companies. You obviously have a lot of financial data. You use some third-party data, you built models, you bounded it. And ultimately when you do these things you have to ascribe a value contribution to the cloud component because fortunate 500 companies are going to grow even if there were no cloud. And the way you did that is again, you talk to people you model things, and it's a very detailed study. And I think it's worth pointing out that this was not just hey what'd you get from going to cloud before and after. This was a very detailed deep dive with really a lot of good background work going into it. >> Yeah, we're very fortunate to have the McKinsey Global Institute which has done extensive studies in these areas. So there was a base of knowledge that we could leverage. In fact, we looked at over 700 use cases across 19 industries in order to unpack the value that cloud contributed to those use cases. And so getting down to that level of specificity really, I think helps build it from the bottom up and then using cloud measures or KPIs that indicate the value like how much faster you can deploy, how much faster you can develop. So these are things that help to kind of inform the overall model. >> Yeah. Again, having done hundreds, if not thousands of these types of things, when you start talking to people the patterns emerge, I want to ask you there's an exhibit tool in here, which is right on those use cases, retail, healthcare, high-tech oil and gas banking, and a lot of examples. And I went through them all and virtually every single one of them from a value contribution standpoint the unlocking value came down to data large data sets, document analysis, converting sentiment analysis, analytics. I mean, it really does come down to the data. And I wonder if you could comment on that and why is it that cloud is enabled that? >> Well, it goes back to scale. And I think the word that I would use would be data gravity because we're talking about massive amounts of data. So as you go through those kind of three dimensions in terms of rejuvenation one of the things you can do as you optimize and clarify and build better resiliency the thing that comes into play I think is to have clean data and data that's available in multiple places that you can create an underlying platform in order to leverage the services, the capabilities around, building out that structure. >> And then if I may, so you had this again I want to stress as EBITDA. It's not a revenue and it's the EBITDA potential as a result of leveraging cloud. And you listed a number of industries. And I wonder if you could comment on the patterns that you saw. I mean, it doesn't seem to be as simple as Negroponte bits versus Adam's in terms of your ability to unlock value. What are the patterns that you saw there and why are the ones that have so much potential why are they at the top of the list? >> Well, I mean, they're ranked based on impact. So the five greatest industries and again, aligned by the fortune 500. So it's interesting when you start to unpack it that way high-tech oil, gas, retail, healthcare, insurance and banking, right? Top. And so we did look at the different solutions that were in that, tried to decipher what was fully unlocked by cloud, what was accelerated by cloud and what was perhaps in this timeframe remaining on premise. And so we kind of step by step, expert by expert, use case by use case deciphered of the 700, how that applied. >> So how should practitioners within organizations business but how should they use this data? What would you recommend, in terms of how they think about it, how they apply it to their business, how they communicate? >> Well, I think clearly what came out was a set of best practices for what organizations that were leveraging cloud and getting the kind of business return, three things stood out, execution, experience and excellence. And so for under execution it's not just the transaction, you're not just buying cloud you're changing their operating model. And so if the organization isn't kind of retooling the model, the processes, the workflows in order to support creating the roles then they aren't going to be able, they aren't going to be successful. In terms of experience, that's all about hands-on. And so you have to dive in, you have to start you have to apply yourself, you have to gain that applied knowledge. And so if you're not gaining that experience, you're not going to move forward. And then in terms of excellence, and it was mentioned earlier by Jeff re-skilling, up-skilling, if you're not committed to your workforce and pushing certification, pushing training in order to really evolve your workforce or your ways of working you're not going to leverage cloud. So those three best practices really came up on top in terms of what a mature cloud adopter looks like. >> That's awesome. Michael, thank you for coming on. Really appreciate it. Last question I have for you as we wrap up this trillion dollar segment upon intended is the cloud mindset. You mentioned partnering and scaling up. The role of the enterprise and business is to partner with the technologists, not just the technologies but the companies talk about this cloud native mindset because it's not just lift and shift and run apps. And I have an IT optimization issue. It's about innovating next gen solutions and you're seeing it in public sector. You're seeing it in the commercial sector, all areas where the relationship with partners and companies and startups in particular, this is the startup showcase. These are startups are more relevant than ever as the tide is shifting to a new generation of companies. >> Yeah, so a lot of think about an engine. A lot of things have to work in order to produce the kind of results that we're talking about. Brad, you're more than fair share or unfair share of trillion dollars. And so CEOs need to lead this in bold fashion. Number one, they need to craft the moonshot or the Marshot. They have to set that goal, that aspiration. And it has to be a stretch goal for the organization because cloud is the only way to enable that achievement of that aspiration that's number one, number two, they really need a hardheaded economic case. It has to be defined in terms of what the expectation is going to be. So it's not loose. It's very, very well and defined. And in some respects time box what can we do here? I would say the cloud data, your organization has to move in an agile fashion training DevOps, and the fourth thing, and this is where the startups come in is the cloud platform. There has to be an underlying platform that supports those aspirations. It's an art, it's not just an architecture. It's a living, breathing live service with integrations, with standardization, with self service that enables this whole program. >> Awesome, Michael, thank you for coming on and sharing the McKinsey perspective. The report, the clouds trillion dollar prize is up for grabs. Everyone who's registered for this event will get a copy. We will appreciate it's also on the website. We'll make sure everyone gets a copy. Thanks for coming, I appreciate it. Thank you. >> Thanks, Michael. >> Okay, Dave, big discussion there. Trillion dollar baby. That's the cloud. That's Jassy. Now he's going to be the CEO of AWS. They have a new CEO they announced. So that's going to be good for Amazon's kind of got clarity on the succession to Jassy, trusted soldier. The ecosystem is big for Amazon. Unlike Microsoft, they have the different view, right? They have some apps, but they're cultivating as many startups and enterprises as possible in the cloud. And no better reason to change gears here and get a venture capitalist in here. And a friend of theCUBE, Jerry Chen let's bring them up on stage. Jerry Chen, great to see you partner at Greylock making all the big investments. Good to see you >> John hey, Dave it's great to be here with you guys. Happy marks.Can you see that? >> Hey Jerry, good to see you man >> So Jerry, our first inaugural AWS startup showcase we'll be doing these quarterly and we're going to be featuring the best of the best, you're investing in all the hot startups. We've been tracking your careers from the beginning. You're a good friend of theCUBE. Always got great commentary. Why are startups more important than ever before? Because in the old days we've talked about theCUBE before startups had to go through certain certifications and you've got tire kicking, you got to go through IT. It's like going through security at the airport, take your shoes off, put your belt on thing. I mean, all kinds of things now different. The world has changed. What's your take? >> I think startups have always been a great way for experimentation, right? It's either new technologies, new business models, new markets they can move faster, the experiment, and a lot of startups don't work, unfortunately, but a lot of them turned to be multi-billion dollar companies. I thing startup is more important because as we come out COVID and economy is recovery is a great way for individuals, engineers, for companies for different markets to try different things out. And I think startups are running multiple experiments at the same time across the globe trying to figure how to do things better, faster, cheaper. >> And McKinsey points out this use case of rejuvenate, which is essentially retool pivot essentially get your costs down or and the next innovation here where there's Tam there's trillion dollars on unlock value and where the bulk of it is is the innovation, the new use cases and existing new use cases. This is where the enterprises really have an opportunity. Could you share your thoughts as you invest in the startups to attack these new waves these new areas where it may not look the same as before, what's your assessment of this kind of innovation, these new use cases? >> I think we talked last time about kind of changing the COVID the past year and there's been acceleration of things like how we work, education, medicine all these things are going online. So I think that's very clear. The first wave of innovation is like, hey things we didn't think we could be possible, like working remotely, e-commerce everywhere, telemedicine, tele-education, that's happening. I think the second order of fact now is okay as enterprises realize that this is the new reality everything is digital, everything is in the cloud and everything's going to be more kind of electronic relation with the customers. I think that we're rethinking what does it mean to be a business? What does it mean to be a bank? What does it mean to be a car company or an energy company? What does it mean to be a retailer? Right? So I think the rethinking that brands are now global, brands are all online. And they now have relationships with the customers directly. So I think if you are a business now, you have to re experiment or rethink about your business model. If you thought you were a Nike selling shoes to the retailers, like half of Nike's revenue is now digital right all online. So instead of selling sneakers through stores they're now a direct to consumer brand. And so I think every business is going to rethink about what the AR. Airbnb is like are they in the travel business or the experience business, right? Airlines, what business are they in? >> Yeah, theCUBE we're direct to consumer virtual totally opened up our business model. Dave, the cloud premise is interesting now. I mean, let's reset this where we are, right? Andy Jassy always talks about the old guard, new guard. Okay we've been there done that, even though they still have a lot of Oracle inside AWS which we were joking the other day, but this new modern era coming out of COVID Jerry brings this up. These startups are going to be relevant take territory down in the enterprises as new things develop. What's your premise of the cloud and AWS prospect? >> Well, so Jerry, I want to to ask you. >> Jerry: Yeah. >> The other night, last Thursday, I think we were in Clubhouse. Ben Horowitz was on and Martine Casado was laying out this sort of premise about cloud startups saying basically at some point they're going to have to repatriate because of the Amazon VIG. I mean, I'm paraphrasing and I guess the premise was that there's this variable cost that grows as you scale but I kind of shook my head and I went back. You saw, I put it out on Twitter a clip that we had the a couple of years ago and I don't think, I certainly didn't see it that way. Maybe I'm getting it wrong but what's your take on that? I just don't see a snowflake ever saying, okay we're going to go build our own data center or we're going to repatriate 'cause they're going to end up like service now and have this high cost infrastructure. What do you think? >> Yeah, look, I think Martin is an old friend from VMware and he's brilliant. He has placed a lot of insights. There is some insights around, at some point a scale, use of startup can probably run things more cost-effectively in your own data center, right? But I think that's fewer companies more the vast majority, right? At some point, but number two, to your point, Dave going on premise versus your own data center are two different things. So on premise in a customer's environment versus your own data center are two different worlds. So at some point some scale, a lot of the large SaaS companies run their own data centers that makes sense, Facebook and Google they're at scale, they run their own data centers, going on premise or customer's environment like a fortune 100 bank or something like that. That's a different story. There are reasons to do that around compliance or data gravity, Dave, but Amazon's costs, I don't think is a legitimate reason. Like if price is an issue that could be solved much faster than architectural decisions or tech stacks, right? Once you're on the cloud I think the thesis, the conversation we had like a year ago was the way you build apps are very different in the cloud and the way built apps on premise, right? You have assume storage, networking and compute elasticity that's independent each other. You don't really get that in a customer's data center or their own environment even with all the new technologies. So you can't really go from cloud back to on-premise because the way you build your apps look very, very different. So I would say for sure at some scale run your own data center that's why the hyperscale guys do that. On-premise for customers, data gravity, compliance governance, great reasons to go on premise but for vast majority of startups and vast majority of customers, the network effects you get for being in the cloud, the network effects you get from having everything in this alas cloud service I think outweighs any of the costs. >> I couldn't agree more and that's where the data is, at the way I look at it is your technology spend is going to be some percentage of revenue and it's going to be generally flat over time and you're going to have to manage it whether it's in the cloud or it's on prem John. >> Yeah, we had a quote on theCUBE on the conscious that had Jerry I want to get your reaction to this. The executive said, if you don't have an AI strategy built into your value proposition you will be shorted as a stock on wall street. And I even went further. So you'll probably be delisted cause you won't be performing with a tongue in cheek comment. But the reality is that that's indicating that everyone has to have AI in their thing. Mainly as a reality, what's your take on that? I know you've got a lot of investments in this area as AI becomes beyond fashion and becomes table stakes. Where are we on that spectrum? And how does that impact business and society as that becomes a key part of the stack and application stack? >> Yeah, I think John you've seen AI machine learning turn out to be some kind of novelty thing that a bunch of CS professors working on years ago to a funnel piece of every application. So I would say the statement of the sentiment's directionally correct that 20 years ago if you didn't have a web strategy or a website as a company, your company be sure it, right? If you didn't have kind of a internet website, you weren't real company. Likewise, if you don't use AI now to power your applications or machine learning in some form or fashion for sure you'd be at a competitive disadvantage to everyone else. And just like if you're not using software intelligently or the cloud intelligently your stock as a company is going to underperform the rest of the market. And the cloud guys on the startups that we're backing are making AI so accessible and so easy for developers today that it's really easy to use some level of machine learning, any applications, if you're not doing that it's like not having a website in 1999. >> Yeah. So let's get into that whole operation side. So what would you be your advice to the enterprises that are watching and people who are making decisions on architecture and how they roll out their business model or value proposition? How should they look at AI and operations? I mean big theme is day two operations. You've got IT service management, all these things are being disrupted. What's the operational impact to this? What's your view on that? >> So I think two things, one thing that you and Dave both talked about operation is the key, I mean, operations is not just the guts of the business but the actual people running the business, right? And so we forget that one of the values are going to cloud, one of the values of giving these services is you not only have a different technology stack, all the bits, you have a different human stack meaning the people running your cloud, running your data center are now effectively outsource to Amazon, Google or Azure, right? Which I think a big part of the Amazon VIG as Dave said, is so eloquently on Twitter per se, right? You're really paying for those folks like carry pagers. Now take that to the next level. Operations is human beings, people intelligently trying to figure out how my business can run better, right? And that's either accelerate revenue or decrease costs, improve my margin. So if you want to use machine learning, I would say there's two areas to think about. One is how I think about customers, right? So we both talked about the amount of data being generated around enterprise individuals. So intelligently use machine learning how to serve my customers better, then number two AI and machine learning internally how to run my business better, right? Can I take cost out? Can I optimize supply chain? Can I use my warehouses more efficiently my logistics more efficiently? So one is how do I use AI learning to be a more familiar more customer oriented and number two, how can I take cost out be more efficient as a company, by writing AI internally from finance ops, et cetera. >> So, Jerry, I wonder if I could ask you a little different subject but a question on tactical valuations how coupled or decoupled are private company valuations from the public markets. You're seeing the public markets everybody's freaking out 'cause interest rates are going to go up. So the future value of cash flows are lower. Does that trickle in quickly into the private markets? Or is it a whole different dynamic? >> If I could weigh in poly for some private markets Dave I would have a different job than I do today. I think the reality is in the long run it doesn't matter as much as long as you're investing early. Now that's an easy answer say, boats have to fall away. Yes, interest rates will probably go up because they're hard to go lower, right? They're effectively almost zero to negative right now in most of the developed world, but at the end of the day, I'm not going to trade my Twilio shares or Salesforce shares for like a 1% yield bond, right? I'm going to hold the high growth tech stocks because regardless of what interest rates you're giving me 1%, 2%, 3%, I'm still going to beat that with a top tech performers, Snowflake, Twilio Hashi Corp, bunch of the private companies out there I think are elastic. They're going to have a great 10, 15 year run. And in the Greylock portfolio like the things we're investing in, I'm super bullish on from Roxanne to Kronos fear, to true era in the AI space. I think in the long run, next 10 years these things will outperform the market that said, right valuation prices have gone up and down and they will in our careers, they have. In the careers we've been covering tech. So I do believe that they're high now they'll come down for sure. Will they go back up again? Definitely, right? But as long as you're betting these macro waves I think we're all be good. >> Great answer as usual. Would you trade them for NFTs Jerry? >> That $69 million people piece of artwork look, I mean, I'm a longterm believer in kind of IP and property rights in the blockchain, right? And I'm waiting for theCUBE to mint this video as the NFT, when we do this guys, we'll mint this video's NFT and see how much people pay for the original Dave, John, Jerry (mumbles). >> Hey, you know what? We can probably get some good bang for that. Hey it's all about this next Jerry. Jerry, great to have you on, final question as we got this one minute left what's your advice to the people out there that either engaging with these innovative startups, we're going to feature startups every quarter from the in the Amazon ecosystem, they are going to be adding value. What's the advice to the enterprises that are engaging startups, the approach, posture, what's your advice. >> Yeah, when I talk to CIOs and large enterprises, they often are wary like, hey, when do I engage a startup? How, what businesses, and is it risky or low risk? Now I say, just like any career managing, just like any investment you're making in a big, small company you should have a budget or set of projects. And then I want to say to a CIO, Hey, every priority on your wish list, go use the startup, right? I mean, that would be 10 for 10 projects, 10 startups. Probably too much risk for a lot of tech companies. But we would say to most CIOs and executives, look, there are strategic initiatives in your business that you want to accelerate. And I would take the time to invest in one or two startups each quarter selectively, right? Use the time, focus on fewer startups, go deep with them because we can actually be game changers in terms of inflecting your business. And what I mean by that is don't pick too many startups because you can't devote the time, but don't pick zero startups because you're going to be left behind, right? It'd be shorted as a stock by the John, Dave and Jerry hedge fund apparently but pick a handful of startups in your strategic areas, in your top tier three things. These really, these could be accelerators for your career. >> I have to ask you real quick while you're here. We've got a couple minutes left on startups that are building apps. I've seen DevOps and the infrastructure as code movement has gone full mainstream. That's really what we're living right now. That kind of first-generation commercialization of DevOps. Now DevSecOps, what are the trends that you've seen that's different from say a couple of years ago now that we're in COVID around how apps are being built? Is it security? Is it the data integration? What can you share as a key app stack impact (mumbles)? >> Yeah, I think there're two things one is security is always been a top priority. I think that was the only going forward period, right? Security for sure. That's why you said that DevOps, DevSecOps like security is often overlooked but I think increasingly could be more important. The second thing is I think we talked about Dave mentioned earlier just the data around customers, the data on premise or the cloud, and there's a ton of data out there. We keep saying this over and over again like data's new oil, et cetera. It's evolving and not changing because the way we're using data finding data is changing in terms of sources of data we're using and discovering and also speed of data, right? In terms of going from Basser real-time is changing. The speed of business has changed to go faster. So I think these are all things that we're thinking about. So both security and how you use your data faster and better. >> Yeah you were in theCUBE a number of years ago and I remember either John or I asked you about you think Amazon is going to go up the stack and start developing applications and your answer was you know what I think no, I think they're going to enable a new set of disruptors to come in and disrupt the SaaS world. And I think that's largely playing out. And one of the interesting things about Adam Selipsky appointment to the CEO, he comes from Tableau. He really helped Tableau go from that sort of old guard model to an ARR model obviously executed a great exit to Salesforce. And now I see companies like Salesforce and service now and Workday is potential for your scenario to really play out. They've got in my view anyway, outdated pricing models. You look at what's how Snowflake's pricing and the consumption basis, same with Datadog same with Stripe and new startups seem to really be a leading into the consumption-based pricing model. So how do you, what are your thoughts on that? And maybe thoughts on Adam and thoughts on SaaS disruption? >> I think my thesis still holds that. I don't think Selipsky Adam is going to go into the app space aggressively. I think Amazon wants to enable next generation apps and seeing some of the new service that they're doing is they're kind of deconstructing apps, right? They're deconstructing the parts of CRM or e-commerce and they're offering them as services. So I think you're going to see Amazon continue to say, hey we're the core parts of an app like payments or custom prediction or some machine learning things around applications you want to buy bacon, they're going to turn those things to the API and sell those services, right? So you look at things like Stripe, Twilio which are two of the biggest companies out there. They're not apps themselves, they're the components of the app, right? Either e-commerce or messaging communications. So I can see Amazon going down that path. I think Adam is a great choice, right? He was a longterm early AWS exact from the early days latent to your point Dave really helped take Tableau into kind of a cloud business acquired by Salesforce work there for a few years under Benioff the guy who created quote unquote cloud and now him coming home again and back to Amazon. So I think it'll be exciting to see how Adam runs the business. >> And John I think he's the perfect choice because he's got operations chops and he knows how to... He can help the startups disrupt. >> Yeah, and he's been a trusted soldier of Jassy from the beginning, he knows the DNA. He's got some CEO outside experience. I think that was the key he knows. And he's not going to give up Amazon speed, but this is baby, right? So he's got him in charge and he's a trusted lieutenant. >> You think. Yeah, you think he's going to hold the mic? >> Yeah. We got to go. Jerry Chen thank you very much for coming on. Really appreciate it. Great to see you. Thanks for coming on our inaugural cube on cloud AWS startup event. Now for the 10 startups, enjoy the sessions at 12:30 Pacific, we're going to have the closing keynote. I'm John Ferry for Dave Vellante and our special guests, thanks for watching and enjoy the rest of the day and the 10 startups. (upbeat music)

>> Announcer: Live from Las Vegas, it's theCUBE! Covering Splunk .conf19. Brought to you by Splunk. Okay, welcome back, everyone. This is day three live CUBE coverage here in Las Vegas for Splunk's .conf. Its 10 years anniversary of their big customer event. I'm John Furrier, theCUBE. This is our seventh year covering, riding the wave with Splunk. From scrappy startup, to going public company, massive growth, now a market leader continuing to innovate. We're here with the CEO, Doug Merritt of Splunk. Thanks for joining me, good to see you. >> Thank you for being here, thanks for having me. >> John: How ya feelin'? (laughs) >> Exhausted and energized simultaneously. (laughs) it was a fun week. >> You know, every year when we have the event we discuss Splunk's success and the loyalty of the customer base, the innovation, you guys are providing the value, you got a lot of happy customers, and you got a great ecosystem and partner network growing. You're now growing even further, every year it just gets better. This year has been a lot of big highlights, new branding, so you got that next level thing goin' on, new platform, tweaks, bringing this cohesive thing. What's your highlights this year? I mean, what's the big, there's so much goin' on, what's your highlights? >> So where you started is always my highlight of the show, is being able to spend time with customers. I have never been at a company where I feel so fortunate to have the passion and the dedication and the enthusiasm and the gratitude of customers as we have here. And so that, I tell everyone at Splunk this is similar to a holiday function for a kid for me where the energy keeps me going all year long, so that always is number one, and then around the customers, what we've been doing with the technology architecture, the platform, and the depth and breadth of what we've been working on honestly for four plus years. It really, I think, has come together in a unique way at this show. >> Last year you had a lot of announcements that were intentional announcements, it's coming. They're coming now, they're here, they're shipping. >> They're here, they're here. >> What is some of the feedback you're hearing because a lot of it has a theme where, you know, we kind of pointed this out a couple of years ago, it's like a security show now, but it's not a security show, but there's a lot of security in there. What are some of the key things that have come out of the oven that people should know about that are being delivered here? >> So the core of what we're trying to communicate with Data-to-Everything is that you need a very multifaceted data platform to be able to handle the huge variety of data that we're all dealing with, and Splunk has been known and been very successful at being able to index data, messy, non-structured data, and make sense of it even though it's not structured in the index, and that's been, still is incredibly valuable. But we started almost four years ago on a journey of adding in stream processing before the data gets anywhere, to our index or anywhere else, it's moving all around the world, how do you actually find that data and then begin to take advantage of it in-flight? And we announced that the beta of Data Stream Processor last year, but it went production this year, four years of development, a ton of patents, a 40 plus person, 50 plus person, development team behind that, a lot of hard engineering, and really elegant interface to get that there. And then on the other end, to complement the index, data is landing all over the place, not just in our index, and we're very aware that different structures exist for different needs. A data warehouse has different properties than a relational database which has different properties than a NoSQL column store in-memory database, and data is going to only continue to be more dispersed. So again, four plus years ago we started on what now is Data Fabric Search which we pre-announced in beta format last year. That went production at this show, but the ability to address a distributed Splunk landscape, but more importantly we demoed the integration with HTFS and S3 landscapes as the proof point of we've built a connector framework, so that this really cannot just be a incredibly high-speed, high-cardinality search processing engine, but it really is a federated search engine as well. So now we can operate on data in the stream when it's in motion. We obviously still have all the great properties of the Splunk index, and I was really excited about Splunk 8.0 and all the features in that, and we can go get data wherever it lives across a distributed Splunk environment, but increasingly across the more and more distributed data environment. >> So this is a data platform. This is absolutely a data platform, so that's very clear. So the success of platforms, in the enterprise at least, not just small and medium-sized businesses, you can have a tool and kind of look like a platform, there's some apps out there that I would point to and say, "Hey, that looks like a tool, it's really not a platform." You guys are a platform. But the success of a platform are two things, ecosystem and apps, because if you're in a platform that's enabling value, you got to have those. Talk about how you see the ecosystem success and the app success. Is that happening in your view? >> It is happening. We have over 2,000 apps on our Splunkbase framework which is where any of our customers can go and download the application to help draw value of a Palo Alto firewall, or ensure integration with a ServiceNow trouble ticketing system, and thousands of other examples that exist. And that has grown from less than 300 apps, when I first got here six years ago, to over 2,000 today. But that is still the earliest inning, for earliest pitch and your earliest inning journey. Why are there 20,000, 200,000, two million apps out there? A piece of it is we have had to up the game on how you interface with the platform, and for us that means through a stable set of services, well-mannered, well-articulated, consistently maintained services, and that's been a huge push with the core Splunk index, but it's also a big amount of work that we've been doing on everything from the separation between Phantom runbooks and playbooks with the underlying orchestration automation, it's a key component of our Stream Processor, you know, what transformations are you doing, what enrichments are you doing? That has to live separate than the underlying technology, the Kafka transport mechanism, or Kinesis, or whatever happens in the future. So that investment to make sure we got a effective and stable set of services has been key, but then you complement that with the amazing set of partners that are out here, and making sure they're educated and enabled on how to take advantage of the platform, and then feather in things like the Splunk Ventures announcement, the Innovation Fund and Social Impact Fund, to further double down on, hey, we are here to help in every way. We're going to help with enablement, we're going to help with sell-through and marketing, and we'll help with investment. >> Yeah, I think this is smart, and I think one of the things I'll point out is that feedback we heard from customers in conversations we had here on theCUBE and the hallway is, there's a lot of great feedback on the automation, the machine learning toolkit, which is a good tell sign of the engagement level of how they're dealing with data, and this kind of speaks to data as a value... The value creation from data seems to be the theme. It's not just data for data's sake, I mean, managing data is all hard stuff, but value from the data. You mentioned the Ventures, you got a lot of tech for good stuff goin' on. You're investing in companies where they're standing up data-driven companies to solve world problems, you got other things, so you guys are adjusting. In the middle innings of the data game, platform update, business model changes. Talk about some of the consumption changes, now you got Splunk Cloud, what's goin' on on (laughs) how you charge, how are customers consuming, what moves did you guys make there and what's the result? >> Yeah, it's a great intro on data is awesome, but we all have data to get to decisions first and actions second. Without an action there is no point in gathering data, and so many companies have been working their tails off to digitize their landscapes. Why, well you want a more flexible landscape, but why the flexibility? Because there's so much data being generated that if you can get effective decisions and then actions, that landscape can adapt very, very rapidly, which goes back to machine learning and eventual AI-type opportunities. So that is absolutely, squarely where we've been focused, is translating that data into value and into actual outcomes, which is why our orchestration automation piece was so important. One of the gating factors that we felt has existed is for the Splunk index, and it's only for the Splunk index, the pricing mechanism has been data volume, and that's a little bit contrary to the promise, which is you don't know where the value is going to be within data, and whether it's a gigabyte or whether it's a petabyte, why shouldn't you be able to put whatever data you want in to experiment? And so we came out with some updates in pricing a month and change ago that we were reiterating at the show and will continue to drive on a, hopefully, very aggressive and clear marketing and communications framework, that for people that have adjusted to the data volume metric, we're trying to make that much simpler. There's now a limited set of bands, or tiers, from 100 gigs to unlimited, so that you really get visibility on, all right, I think that I want to play with five terabytes, I know what that band looks like and it's very liberal. So that if you wind up with six and a half terabytes you won't be penalized, and then there's a complimentary metric which I think is ultimately going to be the more long-lived metric for our infrastructurally-bound products, which is virtual CPU or virtual core. And when I think about our index, stream processing, federated search, the execution of automation, all those are basically a factor of how much infrastructure you're going to throw at the problem, whether it's CPU or whether it's storage or network. So I can see a day when Splunk Enterprise and the index, and everything else at that lower level, or at that infrastructure layer, are all just a series of virtual CPUs or virtual cores. But I think both, we're offering choice, we really are customer-centric, and whether you want a more liberal data volume or whether you want to switch to an infrastructure, we're there and our job is to help you understand the value translation on both of those because all that matters is turning it into action and into doing. >> It's interesting, in the news yesterday quantum supremacy was announced. Google claims it, IBM's debating it, but quantum computing just points to the trend that more compute's coming. So this is going to be a good thing for data. You mentioned the pricing thing, this brings up a topic we've been hearing all week on theCUBE is, diverse data's actually great for machine learning, great for AI. So bringing in diverse data gives you more aperture into data, and that actually helps. With the diversity comes confusion and this is where the pricing seems to hit. You're trying to create, if I get this right, pricing that matches the needs of the diverse use of data. Is that kind of how you guys are thinkin' about it? >> Meets the needs of diverse data, and also provides a lot of clarity for people on when you get to a certain threshold that we stop charging you altogether, right? Once you get above 10s of terabytes to 100 terabytes, just put as much data in as you want. The foundation of Splunk, going back to the first data, is we're the only technology that still exists on the index side that takes raw, non-formatted data, doesn't force you to cleanse or scrub it in any way, and then takes all that raw data and actually provides value through the way that we interact with the data with our query language. And that design architecture, I've said it for five, six years now, is completely unique in the industry. Everybody else thinks that you've got to get to the data you want to operate on, and then put it somewhere, and the way that life works is much more organic and emergent. You've got chaos happening, and then how do you find patterns and value out of that chaos? Well, that chaos winds up being pretty voluminous. So how do we help more organizations? Some of the leading organizations are at five to 10 petabytes of data per day going through the index. How do we help everybody get there? 'Cause you don't know the nugget across that petabyte or 10 petabyte set is going to be the key to solving a critical issue, so let's make it easy for you to put that data in to find those nuggets, but then once you know what the pattern is, now you're in a different world, now you're in the structured data world of metrics, or KPIs, or events, or multidimensional data that is much more curated, and by nature that's going to be more fine-grained. There's not as much volume there as there is in the raw data. >> Doug, I notice also at the event here there's a focus on verticals. Can you comment on the strategy there, is that by design? Is there a vertical focus? >> It's definitely by design. >> Share some insight into that. >> So we launched with an IT operations focus, we wound up progressing over the years to a security operations focus, and then our doubling down with Omnition, SignalFx, VictorOps, and now Streamlio is a new acquisition on the DevOps and next gen app dev buying centers. As a company and how we go to market and what we are doing with our own solutions, we stay incredibly focused on those three very technical buying centers, but we've also seen that data is data. So the data you're bringing in to solve a security problem can be used to solve a manufacturing problem, or a logistics and supply chain problem, or a customer sentiment analysis problem, and so how do you make use of that data across those different buying centers? We've set up a verticals group to seed, continue to seed, the opportunity within those different verticals. >> And that's compatible with the horizontally scalable Splunk platform. That's kind of why that exists, right? >> That the overall platform that was in every keynote, starting with mine, is completely agnostic and horizontal. The solutions on top, the security operations, ITOps, and DevOps, are very specific to those users but they're using the horizontal platform, and then you wind up walking into the Accenture booth and seeing how they've taken similar data that the SecOps teams gathered to actually provide insight on effective rail transport for DB cargo, or effective cell tower triangulation and capacity for a major Australian cell company, or effective manufacturing and logistics supply chain optimization for a manufacturer and all their different retail distribution centers. >> Awesome, you know, I know you've talked with Jeff Frick in the past, and Stu Miniman and Dave Vellante about user experience, I know that's something that's near and dear to your heart. You guys, it has been rumored, there's going to be some user experience work done on the onboarding for your Splunk Cloud and making it easier to get in to this new Splunk platform. What can we expect on the user experience side? (laughs) >> So, for any of you out there that want to try, we've got Splunk Investigate, that's one of the first applications on top of the fully decomposed, services layered, stateless Splunk Cloud. Mission Control actually is a complementary other, those are the first two apps on top of that new framework. And the UI and experience that is in Splunk Investigate I think is a good example of both the ease of coming to and using the product. There's a very liberal amount of data you get for free just to experiment with Splunk Investigate, but then the onboarding experience of data is I think very elegant. The UI is, I love the UI, it's a Jupyter-style workbook-type interface, but if you think about what do investigators need, investigators need both some bread crumbs on where to start and how to end, but then they also need the ability to bring in anybody that's necessary so that you can actually swarm and attack a problem very efficiently. And so when you go back and look at, why did we buy VictorOps? Well, it wasn't because we think that the IT alerting space is a massive space we're going to own, it's because collaboration is incredibly important to swarm incidents of any type, whether they're security incidents or manufacturing incidents. So the facilities at VictorOps gave, on allowing distributed teams and virtual teams to very quickly get to resolution. You're going to find those baked into all products like Mission Control 'cause it's one of the key facilities of, that Tim talked about in his keynote, of indulgent design, mobility, high collaboration, 'cause luckily people still matter, and while ML is helping all of us be more productive it isn't taking away the need for us, but how do you get us to cooperate effectively? And so our cloud-based apps, I encourage any of you out there, go try Splunk Investigate, it's a beautiful product and I think you'll be blown away by it. >> Great success on the product side, and then great success on the customer side, you got great, loyal customers. But I got to ask you about the next level Splunk. As you look at this event, what jumps out at me is the cohesiveness of the story around the platform and the apps, ecosystem's great, but the new branding, Data-to-Everything. It's not product-specific 'cause you have product leadership. This is a whole next level Splunk. What is the next level Splunk vision? >> And I love the pink and orange, in bold colors. So when I've thought about what are the issues that are some of the blockers to Splunk eventually fulfilling the destiny that we could have, the number one is awareness. Who the heck is Splunk? People have very high variance of their understanding of Splunk. Log aggregation, security tool, IT tool, and what we've seen over and over is it is much more this data platform, and certainly with the announcements, it's becoming more of this data fabric or platform that can be used for anything. So how do we bring awareness to Splunk? Well, let's help create a category, and it's not up to us to create the category, it's up to all of you to create the category, but Data-to-Everything in our minds represents the power of data, and while we will continue internally to focus on those technical buying centers, everything is solvable with data. So we're trying to really reinforce the importance of data and the capabilities that something like Splunk brings. Cloud becomes a really important message to that because that makes it, execution to that, 'cause it makes it so much easier for people to immediately try something and get value, but on-prem will always be important as well 'cause data has gravity, data has risk, data has cost to move. And there are so many use cases where you would just never push data to the cloud, and it's not because we don't love cloud. If you have a factory that's producing 100 terabytes an hour in a area where you've got poor bandwidth, there's no option for a cloud connect there of high scale, so you better be able to process, make sense of, and act on that data locally. >> And you guys are great in the cloud too, on-premise, but final word, I want to get your thoughts to end this segment, I know you got to run, thanks for your time, and congratulations on all your success. Data for good. There's a lot of tech for bad kind of narratives goin' on, but there's a real resurgence of tech for good. A lot of people, entrepreneurs, for-profit, for-nonprofit, are doing ventures for good. Data is a real theme. Data for good is something that you have, that's part of the Data-to-Everything. Talk about the data for good real quick. >> Yeah, we were really excited about what we've done with Splunk4Good as our nonprofit focused entity. The Splunk Pledge which is a classic 1-1-1 approach to make sure that we're able to help organizations that need the help do something meaningful within their world, and then the Splunk Social Impact Fund which is trying to put our money where our mouth is to ensure that if funding and scarcity of funds is an issue of getting to effective outcomes, that we can be there to support. At this show we've featured three awesome charities, Conservation International, NetHope, and the Global Emancipation Network, that are all trying to tackle really thorny problems with different, in different ways, different problems in different ways, but data winds up being at the heart of one of the ways to unlock what they're trying to get done. We're really excited and proud that we're able to actually make meaningful donations to all three of those, but it is a constant theme within Splunk, and I think something that all of us, from the tech community and non-tech community are going to have to help evangelize, is with every invention and with every thing that occurs in the world there is the power to take it and make a less noble execution of it, you know, there's always potential harmful activities, and then there's the power to actually drive good, and data is one of those. >> Awesome. >> Data can be used as a weapon, it can be used negatively, but it also needs to be liberated so that it can be used positively. While we're all kind of concerned about our own privacy and really, really personal data, we're not going to get to the type of healthcare and genetic, massive shifts in changes and benefits without having a way to begin to share some of this data. So putting controls around data is going to be important, putting people in the middle of the process to decide what happens to their data, and some consequences around misuse of data is going to be important. But continuing to keep a mindset of all good happens as we become more liberal, globalization is good, free flow of good-- >> The value is in the data. >> Free flow of people, free flow of data ultimately is very good. >> Doug, thank you so much for spending the time to come on theCUBE, and again congratulations on great culture. Also is worth noting, just to give you a plug here, because it's, I think, very valuable, one of the best places to work for women in tech. You guys recently got some recognition on that. That is a huge accomplishment, congratulations. >> Thank you, thank you, we had a great diversity track here which is really important as well. But we love partnering with you guys, thank you for spending an entire week with us and for helping to continue to evangelize and help people understand what the power of technology and data can do for them. >> Hey, video is data, and we're bringin' that data to you here on theCUBE, and of course, CUBE cloud coming soon. I'm John Furrier here live at Splunk .conf with Doug Merritt the CEO. We'll be back with more coverage after this short break. (futuristic music)

>>live from Las Vegas. It's the Cube covering Splunk dot com. 19. Brought to You by spunk. >>Hey, welcome back. Everyone's live Cube coverage in Las Vegas. That's plunks dot com. 2019 thistles their annual customer conference, where they unleash all the new technologies, announce all the new things. Everyone's here. It's the 10th anniversary of Splunk dot com cubes. Seventh year we've been covering slung been quite the journey from scrappy, startup going public growth phase. Now market leader on Outside has to come to success from the products and the engineering. And, of course, the people in the field that that served customers. And we're here with Susan St Leger, who's the president of worldwide field operations. Thanks for coming back to see you. >>Thank you, John. It's exciting to be here. >>So in the keynote, bringing data to every outcome is really the theme. Um, you seem to got a spring to your step here. You excited this year? What an amazing successful show because you got a platform. But the proof is out there. You got that ecosystem. You got people building APS on top of it. It's kind of all coming together this year, >>It sure is experience. It's it's it's just it's a huge leap forward, and I think so. Much of it is a vision of data to everything. And if you think about it, we talk about. We want to bring data to every question, every problem in every action. And the biggest thing you're going to see that you did see in the show is it's no longer just about the Splunk index. We're going to help you get you get value out of data wherever it lives. >>You had some big news on acquisition front Signal FX. Big chunk of change for that company. Private hot category. Observe ability, which really taste is out. That next 20 mile stare in the marketplace, which is cloud native. >>That's a >>cloud Service is, which comes together in the platform with logging coming together. >>Yeah, so exciting Way looked hard at that entire market, and signal FX was definitely the right answer. They operated a scale similar to us. They know how to how to operate it that scale, and so they're gonna be able to serve our customers well. And our view of the world is it's going to be hybrid for a very long time. But they serve that new cloud native world better than anybody else. It's It's when you do monitoring the cloud native world. It's really interesting to think about it. It's all made up of Micro service is right. So thousands of Micro Service's hundreds, thousands of Micro Service's and so in traditional monitoring, it's always you're tryingto monitor things you know could go wrong. In a microt service landscape, you don't know everything that could possibly go wrong. And so it's a level of complexity that's just very different. And so it's all about instrument ing, so that when something does go wrong, you can solve it. >>You guys have a very loyal based customer base, and that's again testament success. But the product has changed, and the value problems is emerging even further with data. That's a big theme. Data to everywhere, everything and security has come up on the radar a few years ago, here, the show. But this almost is a full blown security show at this point, because security center of everything you can't ignore it's become a centerpiece of everything data, the access to the diversity, How is that impacting the field because you're not. I mean, I guess you're a security company enabler and solve security problems. Date is a big part of it. Sure, I was at shaping your operations, >>So I think the thing to understand is correct. We're not just a security company, but we are number one in the security Magic quadrant. We're number one in both I. D. C and Gardner, and so that's important. But what happens is all the data the equal act for security can also be used for all these other use cases. So, generally speaking, whatever you're collecting for security is also valuable for I t operations, and it's also valuable for many other use cases. So I'll give you an example. Dominoes, which is a great customer of ours. They're gone 65% of their orders now come in digitally, okay? And so they monitor the entire intend customer experience. But they monitor it not only from a nightie operations perspective. That same data that they used righty operations also tells them you know what's being ordered, what special orders are being made and they use that data for promotions based upon volume and traffic and timing. they actually create promotion. So now you're talking about the same data that he collected for security night operations you can actually use for promotions, which is marketing is >>not a lot of operating leverage in data. You're getting out this. The old model was is a database. Make a queer. You get a report. Little time problem there. But now you have. Well, that other date is over there in another database. Who runs that data? So the world has certainly changes now, data needs to be addressable. This seems to be a big theme here on undercurrent. I know data to everywhere is kind of global theme, but don't diverse data feeds a I cracked and address ability allows for application access. >>Correct. So we look at the entire data landscape and say, we want to help you get data value out of your data wherever it lives. And it's right now, we've changed to the point where we are operating on data in motion, which is with data stream processor, which is hugely beneficial. You mentioned you know, a I m l way actually do something so unique from an ML perspective because we're actually doing the ml on the live streaming so, so much more valuable than doing it in batch mode. And so the ability to create those ML models by working on live data is super powerful. >>Good announcement. So you guys had the data processor. You have the search fabric, >>data fabric search, >>real time and acceleration our themes there. I want to get your thoughts on your new pricing options. Yes. Why now? What's that mean for customers? >>So if we want to bring data to everything, we have to allow them to actually get all the data right? So we needed to give them more flexible models and more alternative models. So for some people and just motto is very comfortable. But what they want it was more flexibility. So if you look at our new traunch pricing are predictable pricing, there's a couple of things that we've done with it. Number one is from 125 gig all the way up to unlimited. We'll show your predictable pricing so you don't have to guess. Well, if I move from 20 terabytes 2 50 what's that gonna cost me? We're gonna tell you, and you're gonna know and so That's one. The second thing is you don't have to land on the exact ingest. So before, if you bought a terabyte, you got a terabyte. Right now there's a traunch from 1 to 2 terabytes. There's a trunk from 2 to 5 terabytes. And so it gives the customers flexibility so that they don't have to worry about it coming back to buy more right away. >>So that's kind of cloud by as you go variable pricing. Exactly. I want your thoughts on some of the sales motions and position and you guys have out in the field. Visa VI. The industry has seen a lot of success and say Observe ability. For instance, Southern to Rick and Kartik About this. Yes, you guys are an enterprise software cloud and on premises provider you Enterprise sales motion. >>Yes, >>there's a lot of other competition up there that sells for the SNB. They're like tools. What's the difference between an offering that might look like Splunk but may be targeting the SNB? Small means business and one that needs to be full blown enterprise. >>Yeah, so I think the first and foremost most of the offerings that we see land in S and B. They have scale issues over time, I and so what we look at it and say is and they're mostly point products, right? So you can you can clutter up your environment with a bunch of point products, doing all these different things and try and stitch them together. Or you can go with this fun clock for him. So which allows you thio perform all of the same operations, whether B I t Security or Data Analytics in general. But it really isn't. It's about having the platform. >>You guys, what reduced the steps it takes to implement our What's the value? I guess. Here's Here's the thing. What's the pitch? So I'm on Enterprise. I'm like, Okay, I kept Dad. I got a lot of potential things going on platform. I need to make my data work for me any day to be everywhere. I au g Enterprise Cloud. What's the Splunk pitch? >>So our pitches were bringing dated everything, and first and foremost it's important. Understand why? Because we believe at the heart of every problem is a data problem. And we're not just talking t and security. As you know, you saw so many examples. I think you talk to his own haven earlier this week. Right? Wildfires is a data problem New York Presbyterian is using using us for opioid crisis. Right? That's a data problem. So everything's a data problem. What you want is a platform that can operate against that data and remove the barriers between data and action. And that's really what we're focused on. >>He mentions own haven that was part of Splunk Ventures Fund. You have a social impact fund? Yes, what's the motivation line that is just for social good? Is there a business reason behind it or both? >>What's this? So we actually have to social focuses. One is long for good, and that is non profit. What we announced this, what we announced a couple weeks ago that we reiterated yesterday was the spunk, social impact funds, a splint venture social impact fund, and this is to invest in for profit companies using data for social good. And the whole reason is that we look at it and so we say we're a platform. If you're a platform, you want to build out the ecosystem, right? And so the Splunk Innovation Fund splint Ventures Innovation Fund is to invest in new technology focused on that that brings value out of data. And on the other side, it's the spunk. Social impact. Thio get data companies that are taking data and creating such a >>Splunk for good as Splunk employees or a separate nonprofit. And >>it's not a separate nonprofit entity, but it is what we what we invest in. Okay. >>Oh, investing in >>investing in non for profit. Exactly like when we talked about the Global Emancipation Network right, which uses Splunk to fight human trafficking. That's on the nonprofit side. >>So take me through. This is a really hot area we've been covering for good because all roads I want now is for bad. Mark Zuckerberg's testifying from the Congress this morning kind of weird to watch that, actually, but there's a lot of good use cases. Tech tech can be shaped for good. A lot of companies are starting and getting off the ground for good things, but they're kind of like SMB, but they want the Splunk benefit. How do they engage with spunk if I'm gonna do ah social impact thing say cube for good? I got all this Tech. How do I engage punk? I wanted, but I don't know what to do. Have access to tools? How do I buy or engage with Splunk? >>Yes, start parties. Fund managers is making sure it's not just money, right? It's money, its access to talent. It's access to our product. And it's, you know, help with actually thinking through what they're trying to achieve, so it really is the entire focus. It's not just about the tech, Thea. Other thing I would say is you saw that we put out a Splunk investigate, and you also saw us talking about spunk, business slow and mission control. Those air now all built on a native SAS platform. And so the ability for our ecosystem now to go build on a native son platform is going to be incredibly powerful. >>So you expect more accelerated opportunities that all right, what's your favorite customer success stories? I know it's hard to pick your favorites, like picking a favorite child may be filled with the categories. Most ambitious class clown class favorite me. What's the ones you would call a really strong, >>so hit on a couple of my lover Domino story and the other one that I love, that I touched on. But I want to expand on because I think it's an amazing story. Is New York Presbyterian on using the Yes See you sprung for traditional security for private patient privacy. They also use it for medical devices. But here's the thing they use it for to help the opioid crisis. And you're like, How is opioid crisis a data problem? What they do is they actually correlate all the data that so doctors are prescribing the opioids who they're prescribing them to a number of prescriptions being building their pharmacy and then the inventory of opioids. Because they actually have sensors on all the cabinets where they get the opioids, they correlate all the data, and they make sure that if they understand if opioids being stolen from the hospital, because what people don't understand is that the opioid a lot of big part of the opioid crisis starts with hospitals to say of such a big volume of opioids. And so that, to me, is just I guess I love it because it's a great customer success story. But it's also again, it's so much fun doing good problem. >>A lot of deaths. I gotta ask you around your favorite moments here dot com, and you're a lot of conversations in your customer conversations this year. Let's do a little Splunk of the Cube right now can take the patterns, all the data, your meetings. What's the top patterns that are emerging? What are some of the top conversation themes that just keep popping up with customer? Specifically, >>I think the biggest thing is that they have seen more innovation unleash this year than they have ever seen in one year from Splunk. The other thing is that we've gone far outside of our traditional spunk index right and that the portfolio has grown so much and that we're allowing them to operate and get value out of the data wherever it lives. So data in motion and then you saw in data fabric search. We'll let you query not only the Splunk indices, but also H D. F s and s three buckets and more buckets to come. So more sinks if you will. So, really, what we're trying to do is say, we're just going to be your date a platform to help you get value >>Susan, you're a great leader and slung. Congratulations on your success again. They continue to grow every year. Splunk defies the critics. Now you're a market leader. Culture is a big part of this. What is your plans this year To take it to the next level? You're president of field worldwide, field operations, global business landscape. What are some of your goals and objectives on culture >>and the culture? So thank you, Jon. First of all, for your comments and were so committed to our culture, I think you know, as you grow so quickly, it takes a real effort to stay focused on culture way, have an incredible diversity and inclusion program. Onda We do way. It's a business imperative for us. Every single leader has diversity, diversity, inclusion, focuses and targets. And so I think that's a huge part of our culture. And the reason I say that, John, I don't know if you've ever heard about a 1,000,000 data points. Did anybody ever way Always talk about, you know in different different settings will share a couple of our 1,000,000 data points. What we want to make sure is a culture is that way. >>We >>have our employees showing up with their authentic self and because you do your best work when you can show up is your authentic self. And so we have people share a handful of their 1,000,000 data points at all different times throughout the year to get to know each other as individuals, as human beings and really understand what matters to each other. And I love that 1,000,000 data points culture, and I got that. We truly live it. And again it's It's about authenticity. And so I think that's what makes us incredibly special. >>And inclusion helps that trust >>fund elaboration, yes, and also just add to that. We're very proud of the fact that we made the fortune list this year for best places to work for women. So it shows that our focus, you know, we started. We started revealing our metrics just about two years ago, and we've had significant improvement way. Believe that what you focus on what you measure is what you improve. So we started measuring and improving it, and this year we made the list for a fortune that's called walking. It is Congratulations. Thank you. We're very excited about >>awesome on global expansion. I'm assuming is on the radar. Well, >>always, especially at this point. We're ready to double down and some of the tier one mark. It's a lovely for sure >>wasn't saying. Legend. President of worldwide field operations here inside the Cube. Where day to slung dot com 10th anniversary of their customer conference Our seventh year covering Splunk Amazing Ride They continue to ride the big wave. Thats a Q bring you all the data on insights here. I'm John Ferrier. Thanks for watching.

>> from Bahrain. It's the Q covering AWS Public sector Bahrain brought to you by Amazon Web service is >> Okay Welcome back, everyone to the cube coverage We are hearing by rain for a W s summit where cloud computing is changing the games. The Fintech panel discussion Yasmine el Sharif, head of Fintech Innovation Unit, Central Bank of Rain Thank you for joining >> us. Thank you for having me >> Elmo Yacht. Whose founder and CEO of Ammonia Technologies Thank you for coming on. Thank you for having so We're very robust Conversation before they turn on the cameras Fit in tech is hot. I'll see in global fintech Everyone knows what that is, but it's interesting because entrepreneurship and innovation is not just for start ups. It's for countries and hearing by rain, this ecosystem and the mandate to go cloud first has had a ripple effect. We were talking about open banking, mandate, open banking versus regulation, chasing innovation, holding it back. You guys here taking a different approach. Take a minute to explain the philosophy. >> Yeah, I think there's there's benefits to being late adopters to the game. I think in the case of behind it's been a very interesting journey. I think the we started with the whole AWS. But if you look at the prerequisites of technical adoption and creating Data Pool's for analytics to run on, I think the what's interesting about Bahrain is it's really led by regulation. If you look at the prerequisites of creating a digital economy, what's happening in financial service is, or the digitization or openness of financial service. Is it really one context off the bigger picture of Bahrain's digitization plan or the economic strategy? And really, what happens here is if you look at first built the data fools and or the data centers bring a W. A s in and create the data centers. Number two is creator data or cloud First policy. Move the entire government onto the cloud and then give the ownership of the data to the people by implementing the Bahrain personal data protection laws. Once you've done that, then you've given the ownership to the people and you've created what we have is we started with a unique identifies. So the citizens of the country or the residents of the country have a unique identify our number where they're known by once you've done that and then you start mandating certain sectors to open up with a P I integrations. You're creating a very, very interesting value proposition. It creates a much faster you leap frog, a generation of technology. You're going from the classic screen scraping technologies or whatever to a very a completely open infrastructure and open a P I. Where things air cryptographic Lee signed. People are in control of their data, people can control the mobility of their date, and you're really creating a very robust data pool for a lot of algorithms to sit on. >> You know what I love about this has me were talking before he came on cameras that you guys are thinking holistically as a knocking operating system is being in a geek that I am. I love that. But it's not just one thing you're doing, it's a it's a system and it's it's a modernization view. Now we all know that financial systems, power economies and fin tech innovation unit, but you're in. This is important. You gotta have that. That leg of the stool, that pillar that's working absolutely sandbox. You have technology mechanisms to roll in tech, move things quickly moving fast. What's the strategy? What if some of the key things What's the sandbox? >> Let me start by saying The Kingdom of Bahrain has always been considered as a centre of excellence as a financial centre of excellence. And we do realize at the Central Bank in order for us to maintain that position, we have to innovate. We have to remain dynamic and agile enough to make the necessary reforms within our regulations to meet the dynamics off the digital economy. Technology is changing the paradigm off the financial system on the changes happening extremely fast. Regulators have had to come up with a mechanism whereby they can harness and test the feasibility of these innovations whilst putting the risks in a controlled environments as regulators were not typically assigned to host incubators to host startups. However, because of all this change in technology, it has become extremely essential that we come up with a regulatory approach to enable startups as well as existing financial institutions to test out their innovative financial solutions in a controlled environment. So a sandbox is really a controlled live bounds time bounds environment, enabling startups as well as existing financial institutions to test out their innovative solutions under the strict supervision off the regulator, without being required to abide by full regulatory requirements directly with volunteer customers. >> You have to put this trick standards now but means sandboxes. What developers? No, it's a collaborative approach, absolutely not being an incubator. But you're setting up a rules of engagement, Senator startups to take what they know how to do >> exactly >> end up sandboxes in the cloud. That's what everyone does >> absolutely, and our journey with the sandbox has been very successful. We've launched our sandbox back in 2000 and 17. Up to date, we have 35 companies that have been admitted into the sun box. We have been able to graduate to companies successfully. One of them has been licensed as a crypto acid provider, the other as an open biking service provider. We have four other companies in the pipeline ready to graduates. I think all in all, our experience with Sun Box has enabled us to grow and develop his regulators. It has enabled us to maintain open communication with animators, to come tea, to learn the needs of innovators and to enable innovators to live, get familiar realized. With the regulatory environment of the Kingdom of Bahrain, >> you know, you guys are doing some really pioneering work. I wouldn't want to say it's really commendable. I know it's fast and new, but if you look at the United States with Facebook there now asking to be regulated regulation if it comes too late is bad because you know things got out of control and if you're too early, you can put a clamp down and stifle innovation. So the balance between regulation and innovation has always been an art, if you will. >> Exactly. >> What do you guys, How do you view that? What's the philosophy? >> So from a regular perspective, we think that regulation and innovation goes hand in hand, and we have to embrace innovation open heartedly. However, having said that, regulators have to run all common sense checks, meaning that we don't accept an innovation that will potentially pulls more harm to the financial stability of the economy as opposed to the advantages that puzzles. We've passed the number of different regulations to support innovation in the financial services sector dating back to 2014 when we first issued our payment service provider licenses allowing more competition and innovation within the payments sector. We've issued CROWDFUNDING regulations. We've issued robo advisory regulations. We've issued insurance aggregator regulations, crypto asset service provider regulations, open banking regulations, Justin in a few. And I think that each of the regulations that we have issued solves a specific pain point, whether it's to enhance financial inclusion, whether it's to empower customers by retaining ownership back, uh, of their financial information and data, Whether it's too also empower startups and to enable them to get it gain access to funding through digital platforms. >> Have dual. I want to get you in here because as an entrepreneur, like I love all that great, I just wanna get funded. I want my product to market. I need a capital market that's going to be robust. And I need to have that's capital providers state venture capital for private equity supporting their limited partners. So I want to see that I don't wanna be standing there when I need gas for my car. I need fuel. I got to get to the next level. This is what I want And he bought >> on. I think, the one thing John that is very important that people look at in the context of fintech today. Raising money investing into fintech Regulatory uncertainty is one that defines scalability today. Once your technology is proven, where you go next really is dependent on the regulator that you'll be dealing with in the context of that specific activity that you'll be performing. In the case of Bahrain, I must say we were blown away by the receptiveness. We in what way? Yes, yes, mean mentioned open banking, for example. We got into the regulatory sandbox, which you hear a lot about sandboxes all around the world. We got into the sandbox. We got into the sandbox with contact with with with an idea of building and accounts aggregator direct FBI integration to these banks. And we got into the sandbox. We There were no regulations at the time. They like the idea. We started bouncing ideas back and forth on how to develop it. We developed the technology. We started piloting the technology. We integrated to 15 banks in the country on a sandbox environment. The consul, the white paper on open banking, was listed. They sent it out for consultation. We integrated on a production environment to more than 70% of the banks in it in the country. The central Bank of Bahrain mandated open banking across the entire nation. With every retail bank all in a period of less than 18 months. That's insane. That's the kind of context. So as a no Vester exactly so as an investor or as an entrepreneur that looks at the sector. The question is here. If anything, I think the regulator in Bahrain is the one that's leading the innovation and these air the benefits of being late adopters. We get to test out and see what's going on in the rest of the world and really develop great regulations that will embrace and and foster innovation. >> You know, I love the liquidity conversation because this neck goes to the next level. Liquidity is a wonderful thing started. Wanna go public? If that's what happens in the U. S. Mergers and acquisitions, we have an incubator that we're gonna interview here flat Six labs just had to come. One of their companies got sold to match dot com. So you're seeing a lot of cross border liquidity. Yeah, this is a new dynamic. It's only gonna get stronger, more come. He's gonna come out of my reign in the region. Liquid is important. Absent. So how do you guys want to foster that? What's the strategy? Continue to do the same. >> So from a regular perspective again, we don't really holds. Thank you. Beaters are actually two accelerators, but what we do as we refined our regulations to support startups to gain access to liquidity, for example, are crowdfunding regulations that have been passed in 2017 and they support both. Equity is one of financing crowdfunding, including conventional as well as Sharia compliant. Crowdfunding transactions were also currently working on refining our regulations for enabling venture capitalists to take roots and marine and to support these startups. >> Yeah, I think John, you mentioned two things you mentioned regulation leading. When you mandate something like open banking, you are ultimately pushing the entire sector forward, saying you better innovators fastest possible. And there's a gap that you need to you need to basically bridge, and that really loosens up a lot of liquidity when it comes to partnerships. When it comes to acquisitions, when it comes to these banks ultimately looking for better solutions, so they that's the role of the regulator. Here we are seeing a lot of VC activity come to the region right now, the region is only starting to open up. AWS just went live a few months ago. We're seeing the cloud adoption start to really take effect, and this is where you'll start seeing real scalability. But I think the most compelling thing here is Previously people would look at the Middle East with a boot with a bit of skepticism. How much innovation can really take place and the reality is here. There are a few prerequisites that have been put in place. Foreign ownership is at 100% cloud. First policy. There's a lot of things that can really foster innovation. And we're, I mean, where as an entrepreneur, where living proof off this whole Team Bahrain initiative of the fact that you can get in you can build in accounts aggregator in a country that never even had the regulations to adopted to mandate it and to be Ultimately, I think Bahrain will become the global reference point for open banking very soon because it has mandated a regulation of open AP eyes with cryptographic signatures ultimate security frameworks with a robust infrastructure across an entire nation. And don't forget, we still have a population of below the age of 30 70% of our population below. So it gives a very compelling story t test your technology. And then what we end up saying is, once you're on AWS or any cloud for that matter than the scalability of the technology just depends on where you want to go in there. >> No doubt the demographics are solid here, and I love the announcement here. The bachelor's degree. Yeah, cloud computing. We've seen some data science degrees, so new skills are coming on. My vision is interesting. I think that would interest me about the region of Amazon. Being here is these regions create revitalisation? >> Yeah, you >> guys are in perfect position with this Modernization trend is beautiful, not only to be a template for the world but a center for global banking. So I think to me, is that, you know is I'm trying to put together and connect the dots of where this goes in the next two decades. I mean, if crypto currency market continues to get matured and stabilized, that's still flowing with a lot of money. A lot of money in the relay >> absolutely >> was not just the region business to do here for couples to come here. It's you guys playing a role in global financial system. That's of interest to me. What's your vision? >> Absolutely. I think that regulators around the world are starting to realize the importance of collaborating together, to try and work on policy challenges in line with innovation within the financial service of sector and to share experiences to share lessons learned at the Central Bank of Bahrain were a member of the Global Financial Innovation Network, which is an initiative that has Bean passed by the F C A in the UK Again, we're also a member of the authentic working group of the GCC and through these two different initiatives, we work alongside other regulators to collaborate on solving policy issues, to solve, to share experiences and knowledge and to try and harmonize our regulations. Because of the end of the day, startups and innovators ultimately will want to scale up and want to serve customers across the friend jurisdictions. So it's important to have that kind of harmonization in terms of regulations to foster innovation as well as to safeguard the overall security of the international financial. Um, >> keep partnerships. Do you guys need to do to kind of go global on this 20 year vision? Is there other things they have to fall into place? That needs to happen? >> I think >> 20 years is a long time, I say in the next. Let's take five years, for example. If you say in the next five years and where I see this going, the question is, what do entrepreneurs and startups need to look at a jurisdiction and say That's where I want to test my technology. You need a robust infrastructure. You need a regulator than embraces you. You need technical subsidies and financial subsidies that are available, and then you need an independent arm that can really hand hold you and take you to that >> thrust. Its critical trust, money making absolutely ability. >> Just add to that and Byron, we take great pride in our human capital, which we believe is one of our biggest assets. And today, with having your Amazon web service is in Bahrain, this has enabled training of young Bahrainis for the data and knowledge economies which is expected Thio greet around 5000 jobs within becoming five years through different schemes such as Amazon education. For example. >> This is super exciting, which we had more time. Congratulations. Love the vision again. Occupiers like to make money. They wanted environments could be trustworthy and some scalability on behind it. So good luck. We're behind you. We'll keep following up. Thanks for having a cube coverage here and by rain for AWS. I'm John Ferrier. Stay tuned for more after this short break.

>> from atop the Salesforce Tower in downtown San Francisco. It's the Q covering Accenture Innovation Date brought to you by ex center >> Hey, welcome back Your body jefe Rick here from the Cube were high atop San Francisco in the essential innovation hub. It's in the middle of the Salesforce Tower. It's a beautiful facility. They think you had it. The grand opening about six months ago. We're here for the grand opening. Very cool space. I got maker studios. They've got all kinds of crazy stuff going on. But we're here today to talk about Cloud in this continuing evolution about cloud in the enterprise and hybrid cloud and multi cloud in Public Cloud and Private Cloud. And we're really excited to have a couple of guys who really helping customers make this journey, cause it's really tough to do by yourself. CEOs are super busy. They worry about security and all kinds of other things. So centers, often a trusted partner. We got two of the leaders from center joining us today's Prasad Sankaran. He's the senior managing director of Intelligent Cloud infrastructure for Center Welcome and Larry Soccer, the global managing director. Intelligent cloud infrastructure offering from central gentlemen. Welcome. I love it. It intelligent cloud. What is an intelligent cloud all about? Got it in your title. It must mean something pretty significant. >> Yeah, I think First of all, thank you for having us, but you're absolutely Everything's around becoming more intelligent around using more automation. And the work that, you know we delivered to our clients and cloud, as you know, is the platform to which all of our clients are moving. So it's all about bringing the intelligence not only into infrastructure, but also into cloud generally. And it's all driven by software, >> right? It's just funny to think where we are in this journey. We talked a little bit before we turn the cameras on and there you made an interesting comment when I said, You know, when did this cloud for the Enterprise start? And you took it back to sass based applications, which, >> you know, you were sitting in the sales force builder. >> That's true. It isn't just the tallest building in here, and everyone all right, everyone's >> had a lot of focus on AWS is rise, etcetera. But the real start was really getting into sass. I mean, I remember We used to do a lot of Siebel deployments for CR M, and we started to pivot to sales, for some were moving from remedy into service. Now I mean, we went through on premise collaboration, email todo 360 5 So So we've actually been at it for quite a while in the particularly the SAS world. And it's only more recently that we started to see that kind of push to the, you know, the public pass, and it's starting to cloud native development. But But this journey started, you know, it was that 78 years ago that we really start to see some scale around it >> and tell me if you agree. I think really, what? The sales forces of the world and the service now is of the world off. 3 65 kind of broke down some of those initial barriers which were all really about security and security. Security secure. It's always too here where now security is actually probably an attribute >> and loud can brink Absolutely. In fact, I'm in those barriers took years to bring down. I still saw clients where they were forcing salesforce tor service. Now to put you know instances on Prime, and I think I think they finally woke up toe. You know, these guys invested ton in their security organizations. You know, there's a little of that needle in the haystack. You know, if you breach a data set, you know what you're getting after. But when you happen to sail sports, it's a lot harder. And so you know. So I think that security problems, I've certainly got away. We still have some compliance, regulatory things, data sovereignty. But I think security and not not that it's all by any means that you know, it's always giving an ongoing problem. But I think they're getting more comfortable with their data being up in the public domain, right? Not public. >> I think it also help them with their progress towards getting cloud native. So, you know, you pick certain applications which were obviously hosted by sales force and other companies, and you did some level of custom development around it. And now I think that's paved the way for more complex applications and different workloads now going into, you know, the public cloud and the private cloud. But that's the next part of the journey, >> right? So Let's back up 1/2 a step cause then, as you said, a bunch of stuff then went into Public Cloud, right? Everyone's putting in AWS and Google. Um, IBM has got a public how there was a lot more. They're not quite so many as there used to be. Um, but then we ran into a whole new home, Those of issues, right, Which is kind of opened up this hybrid cloud. This multi cloud world, which is you just can't put everything into a public clouds there certain attributes that you need to think about and yet from the application point of view, before you decide where you deploy that. So I'm just curious. If you can share now, would you guys do with clients? How should they think about applications? How, after they think about what to deploy where I >> think I'll start in the, You know, Larry has a lot of expertise in this area. I think you know, we have to obviously start from an application centric perspectives. You got to take a look at you know where your applications have to live water. What are some of the data implications on the applications or do you have by way of regulatory and compliance issues? Or do you have to do as faras performance because certain applications have to be in a high performance environment? Certain other applications don't think a lot of these factors will then drive where these applications need to recite. And then what we're seeing in today's world is really accomplish. Complex, um, situation where you have a lot of legacy, but you also have private as well as public cloud. So you approach it from an application perspective. >> Yeah. I mean, if you really take a look at Army, you look at it centers clients, and we were totally focused on up into the market Global 2000 savory. You know, clients typically have application portfolios ranging from 520,000 applications. And really, I mean, if you think about the purpose of cloud or even infrastructure for that, they're there to serve the applications. No one cares if your cloud infrastructure is not performing the absolute. So we start off with an application monetization approach and ultimately looking, you know, you know, with our tech advisory guys coming in, there are intelligent engineering service is to do the cloud native and at mod work our platforms. Guys, who do you know everything from sales forward through ASAP. They should drive a strategy on how those applications going to evolve with its 520,000 and determined hey, and usually using some like the six orders methodology. And I'm I am I going to retire this Am I going to retain it? And I'm gonna replace it with sass. Am I gonna re factor in format? And it's ultimately that strategy that's really gonna dictate a multi in and, you know, hybrid cloud story. So it's based on the applications data, gravity issues where they gonna reside on their requirements around regulatory, the requirements for performance, et cetera. That will then dictate the cloud strategies. I'm you know, not a big fan of going in there and just doing a multi hybrid cloud strategy without a really good up front application portfolio approach, right? How we're gonna modernize that >> it hadn't had a you segment. That's a lot of applications. And you know, how do you know the old thing? How do you know that one by that time, how do you help them pray or size? Where they should be focusing on. Yes, >> it. Typically, what we do is work with our clients to do a full application portfolio analysis, and then we're able to then segment the applications based on, you know, important to the business and some of the factors that both of us mentioned. And once we have that, then we come up with an approach where certain sets of applications have moved to sass certain other applications you moved past. So you know, you're basically doing the re factoring and the modernization, and then certain others, you know, you can just, you know, lift and shift. So it's really a combination off both modernization as well as migration. It's a combination off that, but to do that, you have initially look at the entire set of applications and come up with that approach. >> I'm just curious where within that application assessment, where is cost savings? Where is, uh, this is just old and where is opportunities to innovate faster? Because we know a lot of lot of talk really. Days has cost savings, but what the real advantages is execution speed if you can get it. >> If >> you could go back three or four years and we had there was a lot of CEO discussions around cost savings. I'm not really have seen our clients shift. It costs never goes away, obviously right. But there's a lot greater emphasis now on business agility. You know, howto innovate faster, get, get new capabilities, market faster to change my customer experience. So it's really I t is really trying to step up and, you know, enabled the business toe to compete in the marketplace. So we're seeing a huge shift in emphasis or focus at least starting with, you know, how do I get better business agility outta leverage to cloud and cloud native development to get there upper service levels? Actually, we started seeing increase on Hey, you know, these applications need to work. It's actress, So obviously cost still remains a factor, but we seem much more, you know, much more emphasis on agility, you know, enabling the business on giving the right service levels of right experience to the user. Little customers. Big pivot there, >> Okay. And let's get the definitions out because you know a lot of lot of conversation about public clouds. Easy private clouds, easy but hybrid cloud and multi cloud and confusion about what those are. How do you guys define them? How do you help your customers think about the definition? Yes, >> I think it's a really good point. So what we're starting to see is there were a lot of different definitions out there. But I think as I talk to my clients and our partners, I think we're all starting to come toe. You know, the same kind of definition on multi cloud. It's really about using more than one cloud. But hybrid, I think, is a very important concept because hybrid is really all about the placement off the workload or where your application is going to run on. And then again, it goes to all of these points that we talked about data, gravity and performance and other things. Other factors. But it's really all about where do you place the specific workload >> if you look at that, so if you think about public, I mean obviously gives us the innovation of the public providers. You look at how fast Amazon comes out with new versions of Lambda etcetera, so that's the innovations. There obviously agility. You could spend up environments very quickly which is, you know, one of the big benefits of it. The consumption economic models. So that is the number of drivers that are pushing in the direction of public. You know, on the private side, they're still it's quite a few benefits that don't get talked about as much. Um, so you know, if you look at it performance, you know, if you think the public world, you know, although they're scaling up larger T shirts, et cetera, they're still trying to do that for a large array of applications on the private side, you can really Taylor somethingto very high performance characteristics. Whether it's you know, 30 to 64 terabyte Hana, you can get a much more focused precision environment for business critical workloads like that article, article rack. You know, the Duke clusters everything about fraud analysis. So that's a big part of it. Related to that is the data gravity that Prasad just mentioned. You know, if I've got a 64 terrified Hana database, you know, sitting in my private cloud, it may not be that convenient to go and put get that data shared up in red shift or in Google's tensorflow. So So there's some data gravity out. Networks just aren't there. The Laden sea of moving that stuff around is a big issue. And then a lot of people of investments in their data centers. I mean, the other piece, that's interesting. His legacy, you know, You know, as we start to look at the world a lot, there's a ton of Could still living in, You know, whether it's you, Nick system, that IBM mainframes. There's a lot of business value there, and sometimes the business cases aren't aren't necessarily there toe to replace them. Right. And in world of digital, the decoupling where I can start to use micro service is we're seeing a lot of trends. We worked with one hotel to take the reservation system. You know, Rapid and Micro Service is, um, we then didn't you know, open shift couch base, front end. And now when you go against, you know, when you go and browsing properties, you're looking at rates you actually going into distributed database cash on, you know, in using the latest cloud native technologies that could be dropped every two weeks or every three or four days for my mobile application and It's only when it goes, you know, when the transaction goes back, to reserve the room that it goes back there. So we're seeing a lot of power with digital decoupling, but we still need to take advantage of, you know, we've got these legacy applications. So So the data centers air really were trying to evolve them. And really, just, you know, how do we learn everything from the world of public and struck to bring those saints similar type efficiencies to the to the world of private? And really, what we're saying is this emerging approach where I can start to take advantage of the innovation cycles that land is that you know, the red shifts the azure functions of the public world. But then maybe keep some of my more business critical regulated workloads. You know, that's the other side of the private side, right? I've got G X p compliance. If I've got hip data that I need to worry about GDP are you know, the whole set of regular two requirements Over time, we do anticipate the public guys will get much better and more compliant. In fact, they made great headway already, but they're Still not a number of clients are still, you know, not 100% comfortable from rail client's perspective. >> Gotta meet Teresa Carlson. She'll change him. Who runs that AWS Public Sector is doing amazing things, obviously with big government contracts. But but you raise real inching point later. You almost described what I would say is really a hybrid application in this thing. This hotel example that you use because it's is, you know, kind of break in the application and leveraging micro service is to do things around the core that allowed to take advantage of some this agility and hyper fast development, yet still maintain that core stuff that either doesn't need to move Works fine. Be too expensive. Drea Factor. It's a real different weight. Even think about workloads and applications into breaking those things into bits. >> And we see that pattern all over the place. I'm gonna give you the hotel Example Where but finance, you know, look at financial service. Is retail banking so open banking a lot. All those rito applications are on the mainframe. I'm insurance claims and and you look at it, the business value, replicating a lot of like the regulatory stuff, the locality stuff. It doesn't make sense to write it. There's no rule inherent business values of I can wrap it, expose it and you know the micro service's architecture now. D'oh cloud native front end. That's gonna give me a 360 view a customer, Change the customer experience. You know, I've got a much you know, I can still get that agility. The the innovation cycles by public. Bye bye. Wrapping my legacy environment >> in person, you rated jump in and I'll give you something to react to, Which is which is the single glass right now? How do I How did I manage all this stuff now? Not only do I have distributed infrastructure now, I've got distributed applications and the thing that you just described and everyone wants to be that single pane of glass Everybody wants to be the app that's upon everybody. Screen. How are you seeing people deal with the management complexity of these kind of distributed infrastructures? If you will Yeah, >> I think that that's that's an area that's, ah, actually very topical these days because, you know, you're starting to see more and more workers. Goto private cloud and so you've got a hybrid infrastructure you're starting to see move movement from just using the EMS to, you know, the cantinas and Cuban Edie's. And, you know, we talked about Serval s and so on. So all of our clients are looking for a way, and you have different types of users as well. Yeah, developers. You have data scientists. You have, you know, operators and so on. So they're all looking for that control plane that allows them access and a view toe everything that is out there that is being used in the enterprise. And that's where I think you know, a company like Accenture were able to use the best of breed toe provide that visibility to our clients. >> Yeah. I mean, you hit the nail on the head. It's becoming, you know, with all the promise of cloud and all the power. And these new architectures is becoming much more dynamic, ephemeral, with containers and kubernetes with service computing that that one application for the hotel, they're actually started, and they've got some actually, now running a native us of their containers and looking at serverless. So you gonna even a single application can span that and one of things we've seen is is first. You know, a lot of our clients used to look at, you know, application management, you know, different from their their infrastructure. And the lines are now getting very blurry. You need to have very tight alignment. You take that single application. You know, if any my public side goes down or my mid tier with my you know, you know, open shipped on VM where it goes down on my back and mainframe goes down. Or the networks that connected to go down the devices that talked it. It's a very well, despite the power, very complex environment. So what we've been doing is first we've been looking at, you know, how do we get better synergy across what we you know, application service is teams that do the application manager an optimization cloud infrastructure, you know, how do we get better alignment that are embedded security, You know, how do you know what are managed to Security Service's and bringing those together? And then what we did was we looked at, you know, we got very aggressive of cloud for a strategy and, you know, how do we manage the world of public. But when looking at the public providers of hyper scale er's and how they hit incredible degrees of automation, we really looked at, said and said, Hey, look, you gotta operate differently in this new world. What can we learn from how the public guys they're doing that? We came up with this concept We call it running different. You know, how do you operate differently in this new multi speed? You know, you know, hot, very hybrid world across public, private demon, legacy environment and started looking say OK, what is it that they do? You know, first they standardize, and that's one of the big challenges you know, going to almost all of our clients in this a sprawl. And you know, whether it's application sprawl, its infrastructure, sprawl and >> my business is so unique. The Larry no business out there has the same process that we have. So we started make you know how to be >> standardized like center hybrid cloud solution apart with HP. Envy em where we, you know, how do we that was an example. So we can get thio because you can't automate unless you standardise. So that was the first thing you know, standardizing service catalog. Standardizing that, um, you know, the next thing is the operating model. They obviously operate differently. So we've been putting a lot of time and energy and what I call a cloud and agile operating model. And also a big part of that is truly you hear a lot about Dev ops right now, but truly putting the security and and operations into Deb set cops of bringing, you know, the development in the operations much tied together. So spending a lot of time looking at that and transforming operations re skilling the people you know, the operators of the future aren't eyes on glass there. Developers, they're writing the data ingestion, the analytic algorithms, you know, to do predictive operations. They're writing the automation script to take work, you know, test work out. Right. And over time, they'll be tuned in the air. Aye, aye. Engines to really optimize the environment and then finally has presided. Looted thio. Is that the platforms that control planes? That doing that? So, you know, we What we've been doing is we've had a significant investments in the eccentric cloud platform, our infrastructure automation platforms and then the application teams with it with our my wizard framework, and we've been starting to bring that together. You know, it's an integrated control plane that can plug into our clients environments to really manage seamlessly, you know, and provide, you know, automation Analytics. Aye, aye. Across APS, cloud infrastructure and even security. Right. And that, you know, that really is a iob is right. I mean, that's delivering on, you know, as the industry starts toe define and really coalesce around, eh? I ops, that's what we use. >> So just so I'm clear that so it's really your layer your software layer kind of management layer that that integrates all these different systems and provides kind of a unified view. Control, I reporting et cetera. Right >> Exactly. Then can plug in and integrate, you know, third party tools. I had to do some strategic function. >> I'm just I'm just >> curious is one of the themes that we here out in the press right now is this is this kind of pull back of public cloud app. Some of them are coming back. Or maybe it was, you know, kind of a rush. Maybe a little bit too aggressively. What are some of the reasons why people are pulling stuff back out of public clouds, that just with the wrong it was just the wrong application? The costs were not what we anticipated to be. We find it, you know, what are some of the reasons that you see after coming back in house? Yeah, >> I think it's >> a variety of factors. I mean, it's certainly cost, I think is one. So as there are multiple private options and you know, we don't talk about this, but the hyper skills themselves are coming out with their own different private options, like Aunt Ours and out pulls and other stack and on. And Ali Baba has obsessed I and so on. So you see a proliferation of that and you see many more options around private cloud. So I think the cost is certainly a factor. The second is I think data gravity is, I think, a very important point because as you're starting to see how different applications have to work together, then that becomes a very important point. The third is just about compliance, and, you know, the regulatory environment. As we look across the globe, you know, even outside the U. S. We look at Europe and other parts of Asia as clients and moving more to the cloud. You know, that becomes an important factor. So as you start to balance these things, I think you have to take a very application centric view. You see some of those some some maps moving back, and and I think that's the part of the hybrid world is that you know, you can have a nap running on the private cloud and then tomorrow you can move this. Since it's been containerized to run on public and it's, you know, it's all managed that look >> e. I mean, cost is a big factor if you actually look at it. Most of our clients, you know, they typically you were big cap ex businesses, and all of a sudden they're using this consumption consumption model. And they weren't really They didn't have a function to go and look at the thousands or millions of lines of it, right? You know, as your statement, exactly think they misjudged, you know, some of the scale on B e e. I mean, that's one of the reasons we started. It's got to be an application lead modernization that really that will dictate that. And I think in many cases, people didn't may not have thought through which application. What data? There The data, gravity data. Gravity's a conversation I'm having just by with every client right now. You know, I've got a 64 terabyte hana, and that's the core. My crown jewels. That data, you know, how do I get that to tensorflow? How'd I get that >> right? But if Andy was >> here, though, Andy would say, we'll send down the snow. The snow came from which virgin snow plows Snowball snowball. Well, they're snowballs. But we've seen the >> hold of a truck killer >> that comes out and he'd say, Take that and stick it in the cloud. Because if you've got that data in a single source right now, you can apply multitude of applications across that thing. So they you know they're pushing. Get that date end in this single source course than to move it, change it, you know you run it. All these micro lines of billing statement take >> the hotel. I mean, their data stolen the mainframe. So if they may want need to expose it? Yeah, they have a database cash, and they move it out. You know, the particulars of data sets get larger, it becomes, you know, the data. Gravity becomes a big issue. Because no matter how much you know, while Moore's law might be might have elongated from 18 to 24 months, the network will always be the bottle, Mac. So ultimately, we're seeing, you know, a CZ. We proliferate more and more data, all data sets get bigger and better than network becomes more of a bottleneck. Conned. That's a lot of times you gotta look at your applications. They have. I've got some legacy database I need to get. Thio. I need this to be approximately somewhere where I don't have, you know, high bandwith o r. Right Or, you know, highlight and see type or so egress costs a pretty big deals. My date is up in the cloud, and I'm gonna get charged for pulling it off. You know that That's been a big issue. >> You know, it's funny, I think, and I think a lot of the issue, obviously complexity building. It's a totally different building model, but I think to a lot of people will put stuff in a public cloud and then operated as if they bought it. And they're running in the data center in this kind of this. Turn it on, turn it off when you need it. Everyone turns. Everyone loves to talk about the example turning it on when you need it. But nobody ever talks about turning it off when you don't. But but the kind of clothes on our conversation I won't talk about a I and applied a I. CoSine is a lot of talk in the market place, but a time machine learning. But as you guys know pride better than anybody, it's the application of a I and specific applications, which really on unlocks the value. And as we're sitting here talking about this complexity, I can't help but think that, you know, applied a I in a management layer like your run differently, set up to actually know when to turn things on, when to turn things off when you moved in but not moved, it's gonna have to be machines running that right cause the data sets and the complexity of these systems is going to be just overwhelming. Yeah, yeah, >> absolutely completely agree with you in fact. Ah, essential. We actually referred to the Seoul area as Applied intelligence. Ah, and that's our guy, right? And, uh, it is absolutely to add more and more automation Move everything Maur toe where it's being run by the machine rather than, you know, having people really working on these things >> yet, e I mean, if you think you hit the nail on the head, we're gonna a eyes e. I mean, given how things getting complex, more ephemeral, you think about kubernetes et cetera. We're gonna have to leverage a humans or not to be able to get, you know, manage this. The environment is important, right? What's interesting way we've used quite effectively for quite some time. But it's good at some stuff, not good at others. So we find it's very good at, like, ticket triage, like ticket triage, chicken routing, et cetera. You know, any time we take over account, we tune our AI ai engines. We have ticket advisers, etcetera. That's what probably got the most, you know, most bang for the buck. We tried in the network space. Less success to start even with, you know, commercial products that were out there. I think where a I ultimately bails us out of this is if you look at the problem. You know, a lot of times we talked about optimizing around cost, but then performance. I mean, and it's they they're somewhat, you know, you gotta weigh him off each other. So you've got a very multi dimensional problem on howto I optimize my workloads, particularly. I gotta kubernetes cluster and something on Amazon, you know, sums running on my private cloud, etcetera. So we're gonna get some very complex environment. And the only way you're gonna be ableto optimize across multi dimensions that cost performance service levels, you know, and then multiple options don't do it public private, You know, what's my network costs etcetera. Isn't a I engine tuning that ai ai engines? So ultimately, I mean, you heard me earlier on the operators. I think you know, they write the analytic albums, they do the automation scripts, but they're the ultimate ones who then tune the aye aye engines that will manage our environment, right. And I think it kubernetes will be interesting because it becomes a link to the control plane optimize workload placement between >> when the best thing to you. Then you have dynamic optimization can. You might be up to my tanks at us right now, but you might be optimizing for output the next day. So exists really a you know, kind of Ah, never ending >> when you got you got to see them >> together with it. And multi dimension optimization is very difficult. So I mean, you know, humans can't get their head around. Machines can, but they need to be trained. >> Well, Prasad, Larry, Lots of great opportunities for for centuries bring that expertise to the table. So thanks for taking a few minutes to walk through some of these things. Our pleasure. Thank you. Raise Prasad is Larry. I'm Jeff. You're watching the Cube. We are high above San Francisco in the Salesforce Tower. Theis Center. Innovation have in San Francisco. Thanks for watching. We'll see you next time

>> Hey, welcome back. Your body, Jefe Rick here from the Cube were high atop San Francisco in the century innovation hub. It's in the middle of the Salesforce Tower. It's a beautiful facility. They think you had it. The grand opening about six months ago. We're here for the grand opening. Very cool space. I got maker studios. They've got all kinds of crazy stuff going on. But we're here today to talk about Cloud in this continuing evolution about cloud in the enterprise and hybrid cloud and multi cloud in Public Cloud and Private Cloud. And we're really excited to have a couple of guys who really helping customers make this journey, cause it's really tough to do by yourself. CEOs are super busy. There were about security and all kinds of other things, so centers, often a trusted partner. We got two of the leaders from center joining us today's Prasad Sankaran. He's the senior managing director of Intelligent Cloud infrastructure for Center Welcome and Larry Soccer, the global managing director. Intelligent cloud infrastructure offering from central gentlemen. Welcome. I love it. It intelligent cloud. What is an intelligent cloud all about? Got it in your title. It must mean something pretty significant. >> Yeah, I think First of all, thank you for having us, but yeah, absolutely. Everything's around becoming more intelligent around using more automation. And the work that, you know we delivered to our clients and cloud, as you know, is the platform to reach. All of our clients are moving. So it's all about bringing the intelligence not only into infrastructure, but also into cloud generally. And it's all driven by software, >> right? It's just funny to think where we are in this journey. We talked a little bit before we turn the cameras on and there you made an interesting comment when I said, You know, when did this cloud for the Enterprise start? And you took it back to sass based applications, which, >> you know you were sitting in the sales force builder. >> That's true. It isn't just the tallest building in >> everyone's, you know, everyone's got a lot of focus on AWS is rise, etcetera. But the real start was really getting into sass. I mean, I remember we used to do a lot of Siebel deployments for CR M, and we started to pivot to sales, for some were moving from remedy into service now. I mean, we've went through on premise collaboration, email thio 3 65 So So we've actually been at it for quite a while in the particularly the SAS world. And it's only more recently that we started to see that kind of push to the, you know, the public pass, and it's starting to cloud native development. But But this journey started, you know, it was that 78 years ago that we really started. See some scale around it. >> And I think and tell me if you agree, I think really, what? The sales forces of the world and and the service now is of the world office 3 65 kind of broke down some of those initial beers, which are all really about security and security, security, security, Always to hear where now security is actually probably an attributes and loud can brink. >> Absolutely. In fact, I mean, those barriers took years to bring down. I still saw clients where they were forcing salesforce tor service Now to put, you know, instances on prime and I think I think they finally woke up toe. You know, these guys invested ton in their security organizations. You know there's a little of that needle in the haystack. You know, if you breach a data set, you know what you're getting after. But when Europe into sales force, it's a lot harder. And so you know. So I think that security problems have certainly gone away. We still have some compliance, regulatory things, data sovereignty. But I think security and not not that it sold by any means that you know, it's always giving an ongoing problem. But I think they're getting more comfortable with their data being up in the in the public domain, right? Not public. >> And I think it also helped them with their progress towards getting cloud native. So, you know, you pick certain applications which were obviously hosted by sales force and other companies, and you did some level of custom development around it. And now I think that's paved the way for more complex applications and different workloads now going into, you know, the public cloud and the private cloud. But that's the next part of the journey, >> right? So let's back up 1/2 a step, because then, as you said, a bunch of stuff then went into public cloud, right? Everyone's putting in AWS and Google. Um, IBM has got a public how there was a lot more. They're not quite so many as there used to be, Um, but then we ran into a whole new host of issues, right, which is kind of opened up this hybrid cloud. This multi cloud world, which is you just can't put everything into a public clouds. There's certain attributes is that you need to think about and yet from the application point of view before you decide where you deploy that. So I'm just curious. If you can share now, would you guys do with clients? How should they think about applications? How should they think about what to deploy where I think >> I'll start in? The military has a lot of expertise in this area. I think you know, we have to obviously start from an application centric perspective. You go to take a look at you know where your applications have to live water. What are some of the data implications on the applications, or do you have by way of regulatory and compliance issues, or do you have to do as faras performance because certain applications have to be in a high performance environment. Certain other applications don't think a lot of these factors will. Then Dr where these applications need to recite and then what we think in today's world is really accomplish. Complex, um, situation where you have a lot of legacy. But you also have private as well as public cloud. So you approach it from an application perspective. >> Yeah. I mean, if you really take a look at Army, you look at it centers clients, and we were totally focused on up into the market Global 2000 savory. You know how clients typically have application portfolios ranging from 520,000 applications? And really, I mean, if you think about the purpose of cloud or even infrastructure for that, they're there to serve the applications. No one cares if your cloud infrastructure is not performing the absolute. So we start off with an application monetization approach and ultimately looking, you know, you know, with our tech advisory guys coming in, there are intelligent engineering service is to do the cloud native and at mod work our platforms, guys, who do you know everything from sales forward through ASAP. They should drive a strategy on how those applications gonna evolve with its 520,000 and determined hey, and usually using some, like the six orders methodology. And I'm I am I going to retire this Am I going to retain it? And, you know, I'm gonna replace it with sass. Am I gonna re factor in format? And it's ultimately that strategy that's really gonna dictate a multi and, you know, every cloud story. So it's based on the applications data, gravity issues where they gonna reside on their requirements around regulatory, the requirements for performance, etcetera. That will then dictate the cloud strategies. I'm you know, not a big fan of going in there and just doing a multi hybrid cloud strategy without a really good up front application portfolio approach, right? How we gonna modernize that >> it had. And how do you segment? That's a lot of applications. And you know, how do you know the old thing? How do you know that one by that time, how do you help them pray or size where they should be focusing on us? >> So typically what we do is work with our clients to do a full application portfolio analysis, and then we're able to then segment the applications based on, you know, important to the business and some of the factors that both of us mentioned. And once we have that, then we come up with an approach where certain sets of applications he moved to sass certain other applications you move to pass. So you know, you're basically doing the re factoring and the modernization and then certain others you know, you can just, you know, lift and shift. So it's really a combination off both modernization as well as migration. It's a combination off that, but to do that, you have to initially look at the entire set of applications and come up with that approach. >> I'm just curious where within that application assessment, um, where is cost savings? Where is, uh, this is just old. And where is opportunities to innovate faster? Because we know a lot of lot of talk really. Days has cost savings, but what the real advantages is execution speed if you can get it. If >> you could go back through four years and we had there was a lot of CEO discussions around cost savings, I'm not really have seen our clients shift. It costs never goes away, obviously right. But there's a lot greater emphasis now on business agility. You know, howto innovate faster, get getting your capabilities to market faster, to change my customer experience. So So it's really I t is really trying to step up and, you know, enabled the business toe to compete in the marketplace. We're seeing a huge shift in emphasis or focus at least starting with, you know, how'd I get better business agility outta leverage to cloud and cloud native development to get their upper service levels? Actually, we started seeing increase on Hey, you know, these applications need to work. It's actress. So So Obviously, cost still remains a factor, but we seem much more for, you know, much more emphasis on agility, you know, enabling the business on, given the right service levels of right experience to the user, little customers. Big pivot there, >> Okay. And let's get the definitions out because you know a lot of lot of conversation about public clouds, easy private clouds, easy but hybrid cloud and multi cloud and confusion about what those are. How do you guys define him? How do you help your customers think about the definition? Yes, >> I think it's a really good point. So what we're starting to see is there were a lot of different definitions out there. But I think as I talked more clients and our partners, I think we're all starting to, you know, come to ah, you know, the same kind of definition on multi cloud. It's really about using more than one cloud. But hybrid, I think, is a very important concept because hybrid is really all about the placement off the workload or where your application is going to run on. And then again, it goes to all of these points that we talked about data, gravity and performance and other things. Other factors. But it's really all about where do you place the specific look >> if you look at that, so if you think about public, I mean obviously gives us the innovation of the public providers. You look at how fast Amazon comes out with new versions of Lambda etcetera. So that's the innovations there obviously agility. You could spend up environments very quickly, which is, you know, one of the big benefits of it. The consumption, economic models. So that is the number of drivers that are pushing in the direction of public. You know, on the private side, they're still it's quite a few benefits that don't get talked about as much. Um, so you know, if you look at it, um, performance if you think the public world, you know, Although they're scaling up larger T shirts, et cetera, they're still trying to do that for a large array of applications on the private side, you can really Taylor somethingto very high performance characteristics. Whether it's you know, 30 to 64 terabyte Hana, you can get a much more focused precision environment for business. Critical workloads like that article, article rack, the Duke clusters, everything about fraud analysis. So that's a big part of it. Related to that is the data gravity that Prasad just mentioned. You know, if I've got a 64 terabyte Hana database you know, sitting in my private cloud, it may not be that convenient to go and put get that data shared up in red shift or in Google's tensorflow. So So there's some data gravity out. Networks just aren't there. The laden sea of moving that stuff around is a big issue. And then a lot of people of investments in their data centers. I mean, the other piece, that's interesting. His legacy, you know, you know, as we start to look at the world a lot, there's a ton of code still living in, You know, whether it's you, nick system, just IBM mainframes. There's a lot of business value there, and sometimes the business cases aren't aren't necessarily there toe to replace them. Right? And in world of digital, the decoupling where I can start to use micro service is we're seeing a lot of trends. We worked with one hotel to take their reservation system. You know, Rapid and Micro Service is, um, we then didn't you know, open shift couch base, front end. And now, when you go against, you know, when you go and browsing properties, you're looking at rates you actually going into distributed database cash on, you know, in using the latest cloud native technologies that could be dropped every two weeks or everything three or four days for my mobile application. And it's only when it goes, you know, when the transaction goes back, to reserve the room that it goes back there. So we're seeing a lot of power with digital decoupling, But we still need to take advantage of, you know, we've got these legacy applications. So So the data centers air really were trying to evolve them. And really, just, you know, how do we learn everything from the world of public and struck to bring those saints similar type efficiencies to the to the world of private? And really, what we're seeing is this emerging approach where I can start to take advantage of the innovation cycles. The land is that, you know, the red shifts the functions of the public world, but then maybe keep some of my more business critical regulated workloads. You know, that's the other side of the private side, right? I've got G X p compliance. If I've got hip, a data that I need to worry about GDP are there, you know, the whole set of regular two requirements. Now, over time, we do anticipate the public guys will get much better and more compliant. In fact, they made great headway already, but they're still not a number of clients are still, you know, not 100% comfortable from my client's perspective. >> Gotta meet Teresa Carlson. She'll change him, runs that AWS public sector is doing amazing things, obviously with big government contracts. But but you raise real inching point later. You almost described what I would say is really a hybrid application in this in this hotel example that you use because it's is, you know, kind of breaking the application and leveraging micro service is to do things around the core that allowed to take advantage of some this agility and hyper fast development, yet still maintain that core stuff that either doesn't need to move. Works fine, be too expensive. Drea Factor. It's a real different weight. Even think about workloads and applications into breaking those things into bits. >> And we see that pattern all over the place. I'm gonna give you the hotel Example Where? But finance, you know, look at financial service. Is retail banking so open banking a lot. All those rito applications are on the mainframe. I'm insurance claims and and you look at it the business value of replicating a lot of like the regulatory stuff, the locality stuff. It doesn't make sense to write it. There's no rule inherent business values of I can wrap it, expose it and in a micro service's architecture now D'oh cloud native front end. That's gonna give me a 360 view a customer, Change the customer experience. You know, I've got a much you know, I can still get that agility. The innovation cycles by public. Bye bye. Wrapping my legacy environment >> and percent you raided, jump in and I'll give you something to react to, Which is which is the single planet glass right now? How do I How did I manage all this stuff now? Not only do I have distributed infrastructure now, I've got distributed applications in the and the thing that you just described and everyone wants to be that single pane of glass. Everybody wants to be the app that's upon everybody. Screen. How are you seeing people deal with the management complexity of these kind of distributed infrastructures? If you will Yeah, >> I think that that's that's an area that's, ah, actually very topical these days because, you know, you're starting to see more and more workers go to private cloud. And so you've got a hybrid infrastructure you're starting to see move movement from just using the EMS to, you know, cantinas and Cuba needs. And, you know, we talked about Serval s and so on. So all of our clients are looking for a way, and you have different types of users as well. Yeah, developers. You have data scientists. You have, you know, operators and so on. So they're all looking for that control plane that allows them access and a view toe everything that is out there that is being used in the enterprise. And that's where I think you know, a company like Accenture were able to use the best of breed toe provide that visibility to our clients, >> right? Yeah. I mean, you hit the nail on the head. It's becoming, you know, with all the promises, cloud and all the power. And these new architectures is becoming much more dynamic, ephemeral, with containers and kubernetes with service computing that that that one application for the hotel, they're actually started in. They've got some, actually, now running a native us of their containers and looking at surveillance. So you're gonna even a single application can span that. And one of things we've seen is is first, you know, a lot of our clients used to look at, you know, application management, you know, different from their their infrastructure. And the lines are now getting very blurry. You need to have very tight alignment. You take that single application, if any my public side goes down or my mid tier with my you know, you know, open shipped on VM, where it goes down on my back and mainframe goes down. Or the networks that connected to go down the devices that talk to it. It's a very well. Despite the power, it's a very complex environment. So what we've been doing is first we've been looking at, you know, how do we get better synergy across what we you know, Application Service's teams that do that Application manager, an optimization cloud infrastructure. How do we get better alignment that are embedded security, You know, how do you know what are managed to security service is bringing those together. And then what we did was we looked at, you know, we got very aggressive with cloud for a strategy and, you know, how do we manage the world of public? But when looking at the public providers of hyper scale, er's and how they hit Incredible degrees of automation. We really looked at, said and said, Hey, look, you gotta operate differently in this new world. What can we learn from how the public guys we're doing that We came up with this concept. We call it running different. You know, how do you operate differently in this new multi speed? You know, you know, hot, very hybrid world across public, private demon, legacy, environment, and start a look and say, OK, what is it that they do? You know, first they standardize, and that's one of the big challenges you know, going to almost all of our clients in this a sprawl. And you know, whether it's application sprawl, its infrastructure, sprawl >> and my business is so unique. The Larry no business out there has the same process that way. So >> we started make you know how to be standardized like center hybrid cloud solution important with hp envy And where we how do we that was an example of so we can get to you because you can't automate unless you standardise. So that was the first thing you know, standardizing our service catalog. Standardizing that, um you know, the next thing is the operating model. They obviously operate differently. So we've been putting a lot of time and energy and what I call a cloud and agile operating model. And also a big part of that is truly you hear a lot about Dev ops right now. But truly putting the security and and operations into Deb said cops are bringing, you know, the development in the operations much tied together. So spending a lot of time looking at that and transforming operations re Skilling the people you know, the operators of the future aren't eyes on glass there. Developers, they're writing the data ingestion, the analytic algorithms, you know, to do predictive operations. They're riding the automation script to take work, you know, test work out right. And over time they'll be tuning the aye aye engines to really optimize environment. And then finally, has Prasad alluded to Is that the platforms that control planes? That doing that? So, you know what we've been doing is we've had a significant investments in the eccentric cloud platform, our infrastructure automation platforms, and then the application teams with it with my wizard framework, and we started to bring that together you know, it's an integrated control plane that can plug into our clients environments to really manage seamlessly, you know, and provide. You know, it's automation. Analytics. Aye, aye. Across APS, cloud infrastructure and even security. Right. And that, you know, that really is a I ops, right? I mean, that's delivering on, you know, as the industry starts toe define and really coalesce around, eh? I ops. That's what we you A ups. >> So just so I'm clear that so it's really your layer your software layer kind of management layer that that integrates all these different systems and provides kind of a unified view. Control? Aye, aye. Reporting et cetera. Right? >> Exactly. Then can plug in and integrate, you know, third party tools to do straight functions. >> I'm just I'm just curious is one of the themes that we here out in the press right now is this is this kind of pull back of public cloud app, something we're coming back. Or maybe it was, you know, kind of a rush. Maybe a little bit too aggressively. What are some of the reasons why people are pulling stuff back out of public clouds that just with the wrong. It was just the wrong application. The costs were not what we anticipated to be. We find it, you know, what are some of the reasons that you see after coming back in house? Yeah, I think it's >> a variety of factors. I mean, it's certainly cost, I think is one. So as there are multiple private options and you know, we don't talk about this, but the hyper skills themselves are coming out with their own different private options like an tars and out pulls an actor stack and on. And Ali Baba has obsessed I and so on. So you see a proliferation of that, then you see many more options around around private cloud. So I think the cost is certainly a factor. The second is I think data gravity is, I think, a very important point because as you're starting to see how different applications have to work together, then that becomes a very important point. The third is just about compliance, and, you know, the regulatory environment. As we look across the globe, even outside the U. S. We look at Europe and other parts of Asia as clients and moving more to the cloud. You know that becomes an important factor. So as you start to balance these things, I think you have to take a very application centric view. You see some of those some some maps moving back, and and I think that's the part of the hybrid world is that you know, you can have a nap running on the private cloud and then tomorrow you can move this. Since it's been containerized to run on public and it's, you know, it's all managed. That left >> E. I mean, cost is a big factor if you actually look at it. Most of our clients, you know, they typically you were a big cap ex businesses, and all of a sudden they're using this consumption, you know, consumption model. And they went, really, they didn't have a function to go and look at be thousands or millions of lines of it, right? You know, as your statement Exactly. I think they misjudged, you know, some of the scale on Do you know e? I mean, that's one of the reasons we started. It's got to be an application led, you know, modernization, that really that will dictate that. And I think In many cases, people didn't. May not have thought Through which application. What data? There The data, gravity data. Gravity's a conversation I'm having just by with every client right now. And if I've got a 64 terabyte Hana and that's the core, my crown jewels that data, you know, how do I get that to tensorflow? How'd I get that? >> Right? But if Andy was here, though, and he would say we'll send down the stove, the snow came from which virgin snow plows? Snowball Snowball. Well, they're snowballs. But I have seen the whole truck killer that comes out and he'd say, Take that and stick it in the cloud. Because if you've got that data in a single source right now, you can apply multitude of applications across that thing. So they, you know, they're pushing. Get that date end in this single source. Of course. Then to move it, change it. You know, you run into all these micro lines of billing statement, take >> the hotel. I mean, their data stolen the mainframe, so if they anyone need to expose it, Yeah, they have a database cash, and they move it out, You know, particulars of data sets get larger, it becomes, you know, the data. Gravity becomes a big issue because no matter how much you know, while Moore's Law might be might have elongated from 18 to 24 months, the network will always be the bottle Mac. So ultimately, we're seeing, you know, a CZ. We proliferate more and more data, all data sets get bigger and better. The network becomes more of a bottleneck. And that's a It's a lot of times you gotta look at your applications. They have. I've got some legacy database I need to get Thio. I need this to be approximately somewhere where I don't have, you know, high bandwith. Oh, all right. Or, you know, highlight and see type. Also, egress costs a pretty big deals. My date is up in the cloud, and I'm gonna get charged for pulling it off. You know, that's being a big issue, >> you know, it's funny, I think, and I think a lot of the the issue, obviously complexity building. It's a totally from building model, but I think to a lot of people will put stuff in a public cloud and then operated as if they bought it and they're running in the data center in this kind of this. Turn it on, Turn it off when you need it. Everyone turns. Everyone loves to talk about the example turning it on when you need it. But nobody ever talks about turning it off when you don't. But it kind of close on our conversation. I won't talk about a I and applied a Iot because he has a lot of talk in the market place. But, hey, I'm machine learning. But as you guys know pride better than anybody, it's the application of a I and specific applications, which really on unlocks the value. And as we're sitting here talking about this complexity, I can't help but think that, you know, applied a I in a management layer like your run differently, set up to actually know when to turn things on, when to turn things off when you moved in but not moved, it's gonna have to be machines running that right cause the data sets and the complexity of these systems is going to be just overwhelming. Yeah, yeah, >> absolutely. Completely agree with you. In fact, attack sensual. We actually refer to this whole area as applied intelligence on That's our guy, right? And it is absolutely to add more and more automation move everything Maur toe where it's being run by the machine rather than you know, having people really working on these things >> yet, e I mean, if you think you hit the nail on the head, we're gonna a eyes e. I mean, given how things getting complex, more ephemeral, you think about kubernetes et cetera. We're gonna have to leverage a humans or not to be able to get, you know, manage this. The environments comported right. What's interesting way we've used quite effectively for quite some time. But it's good at some stuff, not good at others. So we find it's very good at, like, ticket triage, like ticket triage, chicken rounding et cetera. You know, any time we take over account, we tune our AI ai engines. We have ticket advisers, etcetera. That's what probably got the most, you know, most bang for the buck. We tried in the network space, less success to start even with, you know, commercial products that were out there. I think where a I ultimately bails us out of this is if you look at the problem. You know, a lot of times we talked about optimizing around cost, but then performance. I mean, and it's they they're somewhat, you know, you gotta weigh him off each other. So you've got a very multi dimensional problem on howto I optimize my workloads, particularly. I gotta kubernetes cluster and something on Amazon, you know, sums running on my private cloud, etcetera. So we're gonna get some very complex environment. And the only way you're gonna be ableto optimize across multi dimensions that cost performance service levels, you know, And then multiple options don't do it public private, You know, what's my network costs etcetera. Isn't a I engine tuning that ai ai engines? So ultimately, I mean, you heard me earlier on the operators. I think you know, they write the analytic albums, they do the automation scripts, but they're the ultimate one too. Then tune the aye aye engines that will manage our environment. And I think it kubernetes will be interesting because it becomes a link to the control plane optimize workload placement. You know, between >> when the best thing to you, then you have dynamic optimization. Could you might be optimizing eggs at us right now. But you might be optimizing for output the next day. So exists really a you know, kind of Ah, never ending when you got me. They got to see them >> together with you and multi dimension. Optimization is very difficult. So I mean, you know, humans can't get their head around. Machines can, but they need to be trained. >> Well, Prasad, Larry, Lots of great opportunities for for centuries bring that expertise to the tables. So thanks for taking a few minutes to walk through some of these things. Our pleasure. Thank you, Grace. Besides Larry, I'm Jeff. You're watching the Cube. We are high above San Francisco in the Salesforce Tower, Theis Center, Innovation hub in San Francisco. Thanks for watching. We'll see you next time.

>> Hey, welcome back. Your body, Jefe Rick here from the Cube were high atop San Francisco in the century innovation hub. It's in the middle of the Salesforce Tower. It's a beautiful facility. They think you had it. The grand opening about six months ago. We're here for the grand opening. Very cool space. I got maker studios. They've got all kinds of crazy stuff going on. But we're here today to talk about Cloud in this continuing evolution about cloud in the enterprise and hybrid cloud and multi cloud in Public Cloud and Private Cloud. And we're really excited to have a couple of guys who really helping customers make this journey, cause it's really tough to do by yourself. CEOs are super busy. There were about security and all kinds of other things, so centers, often a trusted partner. We got two of the leaders from center joining us today's Prasad Sankaran. He's the senior managing director of Intelligent Cloud infrastructure for Center Welcome and Larry Soccer, the global managing director. Intelligent cloud infrastructure offering from central gentlemen. Welcome. I love it. It intelligent cloud. What is an intelligent cloud all about? Got it in your title. It must mean something pretty significant. >> Yeah, I think First of all, thank you for having us, but yeah, absolutely. Everything's around becoming more intelligent around using more automation. And the work that, you know we delivered to our clients and cloud, as you know, is the platform to reach. All of our clients are moving. So it's all about bringing the intelligence not only into infrastructure, but also into cloud generally. And it's all driven by software, >> right? It's just funny to think where we are in this journey. We talked a little bit before we turn the cameras on and there you made an interesting comment when I said, You know, when did this cloud for the Enterprise start? And you took it back to sass based applications, which, >> you know you were sitting in the sales force builder. >> That's true. It isn't just the tallest building in >> everyone's, you know, everyone's got a lot of focus on AWS is rise, etcetera. But the real start was really getting into sass. I mean, I remember we used to do a lot of Siebel deployments for CR M, and we started to pivot to sales, for some were moving from remedy into service now. I mean, we've went through on premise collaboration, email thio 3 65 So So we've actually been at it for quite a while in the particularly the SAS world. And it's only more recently that we started to see that kind of push to the, you know, the public pass, and it's starting to cloud native development. But But this journey started, you know, it was that 78 years ago that we really started. See some scale around it. >> And I think and tell me if you agree, I think really, what? The sales forces of the world and and the service now is of the world office 3 65 kind of broke down some of those initial beers, which are all really about security and security, security, security, Always to hear where now security is actually probably an attributes and loud can brink. >> Absolutely. In fact, I mean, those barriers took years to bring down. I still saw clients where they were forcing salesforce tor service Now to put, you know, instances on prime and I think I think they finally woke up toe. You know, these guys invested ton in their security organizations. You know there's a little of that needle in the haystack. You know, if you breach a data set, you know what you're getting after. But when Europe into sales force, it's a lot harder. And so you know. So I think that security problems have certainly gone away. We still have some compliance, regulatory things, data sovereignty. But I think security and not not that it sold by any means that you know, it's always giving an ongoing problem. But I think they're getting more comfortable with their data being up in the in the public domain, right? Not public. >> And I think it also helped them with their progress towards getting cloud native. So, you know, you pick certain applications which were obviously hosted by sales force and other companies, and you did some level of custom development around it. And now I think that's paved the way for more complex applications and different workloads now going into, you know, the public cloud and the private cloud. But that's the next part of the journey, >> right? So let's back up 1/2 a step, because then, as you said, a bunch of stuff then went into public cloud, right? Everyone's putting in AWS and Google. Um, IBM has got a public how there was a lot more. They're not quite so many as there used to be, Um, but then we ran into a whole new host of issues, right, which is kind of opened up this hybrid cloud. This multi cloud world, which is you just can't put everything into a public clouds. There's certain attributes is that you need to think about and yet from the application point of view before you decide where you deploy that. So I'm just curious. If you can share now, would you guys do with clients? How should they think about applications? How should they think about what to deploy where I >> think I'll start in? The military has a lot of expertise in this area. I think you know, we have to obviously start from an application centric perspective. You go to take a look at you know where your applications have to live water. What are some of the data implications on the applications, or do you have by way of regulatory and compliance issues, or do you have to do as faras performance because certain applications have to be in a high performance environment. Certain other applications don't think a lot of these factors will. Then Dr where these applications need to recite and then what we think in today's world is really accomplish. Complex, um, situation where you have a lot of legacy. But you also have private as well as public cloud. So you approach it from an application perspective. >> Yeah. I mean, if you really take a look at Army, you look at it centers clients, and we were totally focused on up into the market Global 2000 savory. You know how clients typically have application portfolios ranging from 520,000 applications? And really, I mean, if you think about the purpose of cloud or even infrastructure for that, they're there to serve the applications. No one cares if your cloud infrastructure is not performing the absolute. So we start off with an application monetization approach and ultimately looking, you know, you know, with our tech advisory guys coming in, there are intelligent engineering service is to do the cloud native and at mod work our platforms, guys, who do you know everything from sales forward through ASAP. They should drive a strategy on how those applications gonna evolve with its 520,000 and determined hey, and usually using some, like the six orders methodology. And I'm I am I going to retire this Am I going to retain it? And, you know, I'm gonna replace it with sass. Am I gonna re factor in format? And it's ultimately that strategy that's really gonna dictate a multi and, you know, every cloud story. So it's based on the applications data, gravity issues where they gonna reside on their requirements around regulatory, the requirements for performance, etcetera. That will then dictate the cloud strategies. I'm you know, not a big fan of going in there and just doing a multi hybrid cloud strategy without a really good up front application portfolio approach, right? How we gonna modernize that >> it had. And how do you segment? That's a lot of applications. And you know, how do you know the old thing? How do you know that one by that time, how do you help them pray or size where they should be focusing on us? >> So typically what we do is work with our clients to do a full application portfolio analysis, and then we're able to then segment the applications based on, you know, important to the business and some of the factors that both of us mentioned. And once we have that, then we come up with an approach where certain sets of applications he moved to sass certain other applications you move to pass. So you know, you're basically doing the re factoring and the modernization and then certain others you know, you can just, you know, lift and shift. So it's really a combination off both modernization as well as migration. It's a combination off that, but to do that, you have to initially look at the entire set of applications and come up with that approach. >> I'm just curious where within that application assessment, um, where is cost savings? Where is, uh, this is just old. And where is opportunities to innovate faster? Because we know a lot of lot of talk really. Days has cost savings, but what the real advantages is execution speed if you can get it. If >> you could go back through four years and we had there was a lot of CEO discussions around cost savings, I'm not really have seen our clients shift. It costs never goes away, obviously right. But there's a lot greater emphasis now on business agility. You know, howto innovate faster, get getting your capabilities to market faster, to change my customer experience. So So it's really I t is really trying to step up and, you know, enabled the business toe to compete in the marketplace. We're seeing a huge shift in emphasis or focus at least starting with, you know, how'd I get better business agility outta leverage to cloud and cloud native development to get their upper service levels? Actually, we started seeing increase on Hey, you know, these applications need to work. It's actress. So So Obviously, cost still remains a factor, but we seem much more for, you know, much more emphasis on agility, you know, enabling the business on, given the right service levels of right experience to the user, little customers. Big pivot there, >> Okay. And let's get the definitions out because you know a lot of lot of conversation about public clouds, easy private clouds, easy but hybrid cloud and multi cloud and confusion about what those are. How do you guys define him? How do you help your customers think about the definition? Yes, >> I think it's a really good point. So what we're starting to see is there were a lot of different definitions out there. But I think as I talked more clients and our partners, I think we're all starting to, you know, come to ah, you know, the same kind of definition on multi cloud. It's really about using more than one cloud. But hybrid, I think, is a very important concept because hybrid is really all about the placement off the workload or where your application is going to run on. And then again, it goes to all of these points that we talked about data, gravity and performance and other things. Other factors. But it's really all about where do you place the specific look >> if you look at that, so if you think about public, I mean obviously gives us the innovation of the public providers. You look at how fast Amazon comes out with new versions of Lambda etcetera. So that's the innovations there obviously agility. You could spend up environments very quickly, which is, you know, one of the big benefits of it. The consumption, economic models. So that is the number of drivers that are pushing in the direction of public. You know, on the private side, they're still it's quite a few benefits that don't get talked about as much. Um, so you know, if you look at it, um, performance if you think the public world, you know, Although they're scaling up larger T shirts, et cetera, they're still trying to do that for a large array of applications on the private side, you can really Taylor somethingto very high performance characteristics. Whether it's you know, 30 to 64 terabyte Hana, you can get a much more focused precision environment for business. Critical workloads like that article, article rack, the Duke clusters, everything about fraud analysis. So that's a big part of it. Related to that is the data gravity that Prasad just mentioned. You know, if I've got a 64 terabyte Hana database you know, sitting in my private cloud, it may not be that convenient to go and put get that data shared up in red shift or in Google's tensorflow. So So there's some data gravity out. Networks just aren't there. The laden sea of moving that stuff around is a big issue. And then a lot of people of investments in their data centers. I mean, the other piece, that's interesting. His legacy, you know, you know, as we start to look at the world a lot, there's a ton of code still living in, You know, whether it's you, nick system, just IBM mainframes. There's a lot of business value there, and sometimes the business cases aren't aren't necessarily there toe to replace them. Right? And in world of digital, the decoupling where I can start to use micro service is we're seeing a lot of trends. We worked with one hotel to take their reservation system. You know, Rapid and Micro Service is, um, we then didn't you know, open shift couch base, front end. And now, when you go against, you know, when you go and browsing properties, you're looking at rates you actually going into distributed database cash on, you know, in using the latest cloud native technologies that could be dropped every two weeks or everything three or four days for my mobile application. And it's only when it goes, you know, when the transaction goes back, to reserve the room that it goes back there. So we're seeing a lot of power with digital decoupling, But we still need to take advantage of, you know, we've got these legacy applications. So So the data centers air really were trying to evolve them. And really, just, you know, how do we learn everything from the world of public and struck to bring those saints similar type efficiencies to the to the world of private? And really, what we're seeing is this emerging approach where I can start to take advantage of the innovation cycles. The land is that, you know, the red shifts the functions of the public world, but then maybe keep some of my more business critical regulated workloads. You know, that's the other side of the private side, right? I've got G X p compliance. If I've got hip, a data that I need to worry about GDP are there, you know, the whole set of regular two requirements. Now, over time, we do anticipate the public guys will get much better and more compliant. In fact, they made great headway already, but they're still not a number of clients are still, you know, not 100% comfortable from my client's perspective. >> Gotta meet Teresa Carlson. She'll change him, runs that AWS public sector is doing amazing things, obviously with big government contracts. But but you raise real inching point later. You almost described what I would say is really a hybrid application in this in this hotel example that you use because it's is, you know, kind of breaking the application and leveraging micro service is to do things around the core that allowed to take advantage of some this agility and hyper fast development, yet still maintain that core stuff that either doesn't need to move. Works fine, be too expensive. Drea Factor. It's a real different weight. Even think about workloads and applications into breaking those things into bits. >> And we see that pattern all over the place. I'm gonna give you the hotel Example Where? But finance, you know, look at financial service. Is retail banking so open banking a lot. All those rito applications are on the mainframe. I'm insurance claims and and you look at it the business value of replicating a lot of like the regulatory stuff, the locality stuff. It doesn't make sense to write it. There's no rule inherent business values of I can wrap it, expose it and in a micro service's architecture now D'oh cloud native front end. That's gonna give me a 360 view a customer, Change the customer experience. You know, I've got a much you know, I can still get that agility. The innovation cycles by public. Bye bye. Wrapping my legacy environment >> and percent you raided, jump in and I'll give you something to react to, Which is which is the single planet glass right now? How do I How did I manage all this stuff now? Not only do I have distributed infrastructure now, I've got distributed applications in the and the thing that you just described and everyone wants to be that single pane of glass. Everybody wants to be the app that's upon everybody. Screen. How are you seeing people deal with the management complexity of these kind of distributed infrastructures? If you >> will Yeah, I think that that's that's an area that's, ah, actually very topical these days because, you know, you're starting to see more and more workers go to private cloud. And so you've got a hybrid infrastructure you're starting to see move movement from just using the EMS to, you know, cantinas and Cuba needs. And, you know, we talked about Serval s and so on. So all of our clients are looking for a way, and you have different types of users as well. Yeah, developers. You have data scientists. You have, you know, operators and so on. So they're all looking for that control plane that allows them access and a view toe everything that is out there that is being used in the enterprise. And that's where I think you know, a company like Accenture were able to use the best of breed toe provide that visibility to our clients, >> right? Yeah. I mean, you hit the nail on the head. It's becoming, you know, with all the promises, cloud and all the power. And these new architectures is becoming much more dynamic, ephemeral, with containers and kubernetes with service computing that that that one application for the hotel, they're actually started in. They've got some, actually, now running a native us of their containers and looking at surveillance. So you're gonna even a single application can span that. And one of things we've seen is is first, you know, a lot of our clients used to look at, you know, application management, you know, different from their their infrastructure. And the lines are now getting very blurry. You need to have very tight alignment. You take that single application, if any my public side goes down or my mid tier with my you know, you know, open shipped on VM, where it goes down on my back and mainframe goes down. Or the networks that connected to go down the devices that talk to it. It's a very well. Despite the power, it's a very complex environment. So what we've been doing is first we've been looking at, you know, how do we get better synergy across what we you know, Application Service's teams that do that Application manager, an optimization cloud infrastructure. How do we get better alignment that are embedded security, You know, how do you know what are managed to security service is bringing those together. And then what we did was we looked at, you know, we got very aggressive with cloud for a strategy and, you know, how do we manage the world of public? But when looking at the public providers of hyper scale, er's and how they hit Incredible degrees of automation. We really looked at, said and said, Hey, look, you gotta operate differently in this new world. What can we learn from how the public guys we're doing that We came up with this concept. We call it running different. You know, how do you operate differently in this new multi speed? You know, you know, hot, very hybrid world across public, private demon, legacy, environment, and start a look and say, OK, what is it that they do? You know, first they standardize, and that's one of the big challenges you know, going to almost all of our clients in this a sprawl. And you know, whether it's application sprawl, its infrastructure, sprawl >> and my business is so unique. The Larry no business out there has the same process that way. So >> we started make you know how to be standardized like center hybrid cloud solution important with hp envy And where we how do we that was an example of so we can get to you because you can't automate unless you standardise. So that was the first thing you know, standardizing our service catalog. Standardizing that, um you know, the next thing is the operating model. They obviously operate differently. So we've been putting a lot of time and energy and what I call a cloud and agile operating model. And also a big part of that is truly you hear a lot about Dev ops right now. But truly putting the security and and operations into Deb said cops are bringing, you know, the development in the operations much tied together. So spending a lot of time looking at that and transforming operations re Skilling the people you know, the operators of the future aren't eyes on glass there. Developers, they're writing the data ingestion, the analytic algorithms, you know, to do predictive operations. They're riding the automation script to take work, you know, test work out right. And over time they'll be tuning the aye aye engines to really optimize environment. And then finally, has Prasad alluded to Is that the platforms that control planes? That doing that? So, you know what we've been doing is we've had a significant investments in the eccentric cloud platform, our infrastructure automation platforms, and then the application teams with it with my wizard framework, and we started to bring that together you know, it's an integrated control plane that can plug into our clients environments to really manage seamlessly, you know, and provide. You know, it's automation. Analytics. Aye, aye. Across APS, cloud infrastructure and even security. Right. And that, you know, that really is a I ops, right? I mean, that's delivering on, you know, as the industry starts toe define and really coalesce around, eh? I ops. That's what we you A ups. >> So just so I'm clear that so it's really your layer your software layer kind of management layer that that integrates all these different systems and provides kind of a unified view. Control? Aye, aye. Reporting et cetera. Right? >> Exactly. Then can plug in and integrate, you know, third party tools to do straight functions. >> I'm just I'm just curious is one of the themes that we here out in the press right now is this is this kind of pull back of public cloud app, something we're coming back. Or maybe it was, you know, kind of a rush. Maybe a little bit too aggressively. What are some of the reasons why people are pulling stuff back out of public clouds that just with the wrong. It was just the wrong application. The costs were not what we anticipated to be. We find it, you know, what are some of the reasons that you see after coming back in house? Yeah, I think it's >> a variety of factors. I mean, it's certainly cost, I think is one. So as there are multiple private options and you know, we don't talk about this, but the hyper skills themselves are coming out with their own different private options like an tars and out pulls an actor stack and on. And Ali Baba has obsessed I and so on. So you see a proliferation of that, then you see many more options around around private cloud. So I think the cost is certainly a factor. The second is I think data gravity is, I think, a very important point because as you're starting to see how different applications have to work together, then that becomes a very important point. The third is just about compliance, and, you know, the regulatory environment. As we look across the globe, even outside the U. S. We look at Europe and other parts of Asia as clients and moving more to the cloud. You know that becomes an important factor. So as you start to balance these things, I think you have to take a very application centric view. You see some of those some some maps moving back, and and I think that's the part of the hybrid world is that you know, you can have a nap running on the private cloud and then tomorrow you can move this. Since it's been containerized to run on public and it's, you know, it's all managed. That >> left E. I mean, cost is a big factor if you actually look at it. Most of our clients, you know, they typically you were a big cap ex businesses, and all of a sudden they're using this consumption, you know, consumption model. And they went, really, they didn't have a function to go and look at be thousands or millions of lines of it, right? You know, as your statement Exactly. I think they misjudged, you know, some of the scale on Do you know e? I mean, that's one of the reasons we started. It's got to be an application led, you know, modernization, that really that will dictate that. And I think In many cases, people didn't. May not have thought Through which application. What data? There The data, gravity data. Gravity's a conversation I'm having just by with every client right now. And if I've got a 64 terabyte Hana and that's the core, my crown jewels that data, you know, how do I get that to tensorflow? How'd I get that? >> Right? But if Andy was here, though, and he would say we'll send down the stove, the snow came from which virgin snow plows? Snowball Snowball. Well, they're snowballs. But I have seen the whole truck killer that comes out and he'd say, Take that and stick it in the cloud. Because if you've got that data in a single source right now, you can apply multitude of applications across that thing. So they, you know, they're pushing. Get that date end in this single source. Of course. Then to move it, change it. You know, you run into all these micro lines of billing statement, take >> the hotel. I mean, their data stolen the mainframe, so if they anyone need to expose it, Yeah, they have a database cash, and they move it out, You know, particulars of data sets get larger, it becomes, you know, the data. Gravity becomes a big issue because no matter how much you know, while Moore's Law might be might have elongated from 18 to 24 months, the network will always be the bottle Mac. So ultimately, we're seeing, you know, a CZ. We proliferate more and more data, all data sets get bigger and better. The network becomes more of a bottleneck. And that's a It's a lot of times you gotta look at your applications. They have. I've got some legacy database I need to get Thio. I need this to be approximately somewhere where I don't have, you know, high bandwith. Oh, all right. Or, you know, highlight and see type. Also, egress costs a pretty big deals. My date is up in the cloud, and I'm gonna get charged for pulling it off. You know, that's being a big issue, >> you know, it's funny, I think, and I think a lot of the the issue, obviously complexity building. It's a totally from building model, but I think to a lot of people will put stuff in a public cloud and then operated as if they bought it and they're running in the data center in this kind of this. Turn it on, Turn it off when you need it. Everyone turns. Everyone loves to talk about the example turning it on when you need it. But nobody ever talks about turning it off when you don't. But it kind of close on our conversation. I won't talk about a I and applied a Iot because he has a lot of talk in the market place. But, hey, I'm machine learning. But as you guys know pride better than anybody, it's the application of a I and specific applications, which really on unlocks the value. And as we're sitting here talking about this complexity, I can't help but think that, you know, applied a I in a management layer like your run differently, set up to actually know when to turn things on, when to turn things off when you moved in but not moved, it's gonna have to be machines running that right cause the data sets and the complexity of these systems is going to be just overwhelming. >> Yeah, yeah, absolutely. Completely agree with you. In fact, attack sensual. We actually refer to this whole area as applied intelligence on That's our guy, right? And it is absolutely to add more and more automation move everything Maur toe where it's being run by the machine rather than you know, having people really working on these things >> yet, e I mean, if you think you hit the nail on the head, we're gonna a eyes e. I mean, given how things getting complex, more ephemeral, you think about kubernetes et cetera. We're gonna have to leverage a humans or not to be able to get, you know, manage this. The environments comported right. What's interesting way we've used quite effectively for quite some time. But it's good at some stuff, not good at others. So we find it's very good at, like, ticket triage, like ticket triage, chicken rounding et cetera. You know, any time we take over account, we tune our AI ai engines. We have ticket advisers, etcetera. That's what probably got the most, you know, most bang for the buck. We tried in the network space, less success to start even with, you know, commercial products that were out there. I think where a I ultimately bails us out of this is if you look at the problem. You know, a lot of times we talked about optimizing around cost, but then performance. I mean, and it's they they're somewhat, you know, you gotta weigh him off each other. So you've got a very multi dimensional problem on howto I optimize my workloads, particularly. I gotta kubernetes cluster and something on Amazon, you know, sums running on my private cloud, etcetera. So we're gonna get some very complex environment. And the only way you're gonna be ableto optimize across multi dimensions that cost performance service levels, you know, And then multiple options don't do it public private, You know, what's my network costs etcetera. Isn't a I engine tuning that ai ai engines? So ultimately, I mean, you heard me earlier on the operators. I think you know, they write the analytic albums, they do the automation scripts, but they're the ultimate one too. Then tune the aye aye engines that will manage our environment. And I think it kubernetes will be interesting because it becomes a link to the control plane optimize workload placement. You know, between >> when the best thing to you, then you have dynamic optimization. Could you might be optimizing eggs at us right now. But you might be optimizing for output the next day. So exists really a you know, kind of Ah, never ending when you got me. They got to see them >> together with you and multi dimension. Optimization is very difficult. So I mean, you know, humans can't get their head around. Machines can, but they need to be trained. >> Well, Prasad, Larry, Lots of great opportunities for for centuries bring that expertise to the tables. So thanks for taking a few minutes to walk through some of these things. Our pleasure. Thank you, Grace. Besides Larry, I'm Jeff. You're watching the Cube. We are high above San Francisco in the Salesforce Tower, Theis Center, Innovation hub in San Francisco. Thanks for watching. We'll see you next time.

>> From Seattle Washington, it's theCUBE, covering AWS Imagine, nonprofit. Brought to you by Amazon Web Services. >> Hey welcome back everybody, Jeff Frick here with theCUBE. We're actually on the waterfront in Seattle at the AWS Imagine nonprofit event. We were here a couple weeks ago for the AWS Imagine education event. This is really about nonprofits and solving big, big problems. So Dave Levy and team have you know dedicated to some of these big problems. And one of the big problems in the world is human trafficking, and problems that people are encountering and all kinds of nasty situations all over the world. And we're really excited to have someone who's tackling that problem, and really trying to bring a voice to those people that wouldn't otherwise have a voice. And she's Hend Alhinnawai, she's the CEO of Humanitarian Tracker. Hend, good to see you. >> Thank you Jeff, good to be here. >> Absolutely. So before we jump into it, impressions on this event? >> Wonderful event bringing together technologists, people in nonprofits, really creating synergies for people to collaborate and talk to each other and network and learn how they can advance their organizations. >> Such important work. >> Yes. >> So give us kind of the background on what you're up to, what Humanitarian Tracker's all about. >> So Humanitarian Tracker's a nonprofit forum. It was created to connect and empower citizens using innovation and technology, but specifically for humanitarian events. We were among the first to combine crowdsourced reports with data mining and artificial intelligence and apply them to humanitarian disasters, conflicts, human rights violations, disease outbreak. All the way to tracking the UN's Sustainable Development Goals. Really giving a holistic view of what's happening. >> It's interesting, you know, it's probably like the middle eastern spring, I can't remember the exact term that people use, where it was kind of the first use of regular people using their mobile phones to kind of grab a ground swell of action. You're not looking at the politics specifically, you're looking more at humanitarian disasters. But pretty amazing kind of what a connected phone represents to anyone anywhere in the world now to communicate what's happening to them. To share that story. We really didn't have anything like that before. To get that personal event on the ground. >> No it's really a new way of consuming, creating and consuming information. So the cell phone has really given people on the ground a chance to tell their own story. But it's not enough. If you have an event that happens to you. Something happens to you. And you record it, it stops there. But the unique thing with Humanitarian Tracker is it gives people that forum to show the world and tell them what's happening to and around them. >> Right, but it's not just about the individual. And what you guys are doing is using cutting edge technology, obviously you're here as part of the AWS event. In terms of machine-learning and big data to grab a large number of these reported events and distill it into more of an overarching view of what is actually happening on the ground. How did you do that, where did you get that vision, how are you executing that? >> Well, we're all about empowering the citizen. And in our line of work we deal with a lot of data, a lot of information, most of it is unstructured, most of it is crowdsourced. So we use machine-learning to help us extract important details. Information on time. Event location, what is happening. And at the same time we really cared that this reporter, stays anonymous for their own safety. We, privacy and security is utmost importance to us. So that's always our focus. So in that space, we de-identify them. We take out any information that could be identifiable, that could lead to their arrest, or could lead to someone identifying that it was them that reported. >> And how do you get this information to the people that are suffering this activity ground? How do they know about you, how do they know that you are anonymizing their information so there's not going to be repercussions if they report. You know, how do, kind of I guess your go-to-market, to steal a business terms, in making sure that people know this tool's available for help? >> It depends on the situation. For example in the conflict situation, we rolled it out, and we kept it low key for awhile. Because we didn't want government attacks, we didn't want people to be arrested, or to be tried. So we rolled it out. And it was word of mouth that spreads. And people started submitting supports. Actually the first project we did with conflict, we weren't sure if we were going to get one report, zero reports. The first week we got nothing. And then slowly as people learned about it they started submitting their reports. And we see our job as really elevating the otherwise marginalized voice. So you submit a report to us, we then take it. We verify it. We make it public. And that, we welcome, we encourage, we want people to consume it. Whether you're a student, whether you're a journalist, whether you're a government, whether you work in a nonprofit, the UN. It's been used to address human rights violations, it's been used to identify humanitarian hotspots. The data's phenomenal, and what you get from it. It's not just collecting data. We're not just about collecting the data. We want to make sure it's meaningful, and we want to derive insights. So we want to know what is the data actually telling us? >> Right, right. So just to be clear for people that don't know, so you're making that data available, you're cleansing the data, you're running some AI on it to try to get a bigger picture, and anyone with a login, any kind of journalist can now access that data in support of whatever issue or topic or story they're chasing? >> That's it Jeff. >> That's phenomenal. And just kind of size and scope. You've been at this I think you said since 2011. You know kind of how many active, activities, crisis, I don't know, what the definition is of a bucket of these problems. Are you tracking historically at a given point in time? Give us some kind of basic sizing type of dimensions. >> It really ranges, because it could, when we were tracking conflict for example, we were really focused on one area, and the surrounding countries. Because you had refugee population, you had displacement, you had all sorts of issues. But it could be anywhere from five projects, it just depends. And we want to make sure that each project we're taking on we're giving it our full attention, full scope. And I like to run the organization like a two-team pizza team. And so I don't take on more than I could handle. >> Right, right. So then how did it morph from the conflict to the Global Sustainability Goal? So we've worked with Western Digital, they're doing a lot of work, ASP's doing a lot of work on kind of these global sustainability goals. How did you get involved in that, and how did the two kind of dovetail together? >> So the elasticity of the cloud has helped our operation scale tremendously. And in 2016 we were selected as a top 10 global innovation, that could be applied to the Sustainable Development Goals, and-- >> So they found you, the UN find you, or did you get nominated? How did that happen? >> We were nominated, and from over 1,000 solutions we were chosen. >> Congratulations. >> Thank you. And we were showcased at the Solutions Summit which is hosted at the United Nations. And just based on that experience of meeting people that were doing really cool things in their respective communities, we launched the Global Action Mosaic. Because we wanted to create one place where people that are doing projects in their communities could submit it, and have it showcased. And the goals are not only to crowdsource the SGD's, but to also be a part of the effort to track what's happening. Who's doing what where, make it easy for people to search say, Jeff you decided to get involved in a project with education. You can go onto our Global Action Mosaic, search projects on education in your community or in other parts of the world and then get involved in it. So it's really creating a centralized place where people can get information on the global goals. >> Awesome. So that's pretty much the Global Action Mosaic. It's pretty much focused on the UN global goals versus your core efforts around the Humanitarian Tracker. >> Yes. >> That's great. So we're here at AWS. Have you always been on AWS? Is this something new? How does being on kind of the AWS infrastructure help you do your mission better? >> We are, we've been partners in running AWS since we actually started. >> Since the beginning. >> Yes we have Yusheheedi as one of our partners, development partners, AWS. And because one of the core, one of the most important things to us is privacy and security, we want to make sure that whatever data is being handled and received is stored securely. >> Right, right. >> And that information transmitted, handled is also being done so in a secure way. Like I mentioned, the elasticity of the cloud has helped us scale our mission tremendously. It's affordable, we've been able to us it, we've learned their machine-learning stock to de-identify some of the data that comes in. So we're firm believers that AWS is essential to how we run our operation. >> Because do the individual conflicts kind of grow and shrink over time? Do you see it's really a collection of kind of firing up hotspots and then turning down versus one long, sustained, relatively flat, from kind of a utilization and capacity point of view? >> Yeah, no it definitely, it flares up and you'll have like a year, months, weeks sometimes where it's just focused on one area. But one of the things we focus on, it's not just. So what is the data actually telling us? So say you're focusing on point A. But just down the street in location B there is a dire humanitarian emergency that needs to be addressed. The crowdsourced reports, combined with the data mining and the AI, helps us identify those hotspots. So everybody could be focused here, but there could be an emergency down the street that needs to be addressed as well. It just depends. >> And do you have your own data scientists or do you, do other people take your data and run it through their own processes to try to find some of these insights? >> We have both. >> You have both. >> Yeah. >> So what's been the biggest surprise when you anonymize and aggregate the data around some of these hotspots? Is there a particular pattern that you see over and over? Is there some insight, that now that you've seen so much of it, from kind of the (muffled speaking) that you can share and reflect on? >> I think it' very unique to each project to do. But there is one thing that I strongly support, that I don't see enough of, and that's the sharing of data within the organizations. And so, for example just getting to that culture where sharing your data between organizations is encouraged and actually done. Could help create a, create a pool of knowledge. So, for example we worked with 13 different organizations that were all tackling humanitarian events. The same one, in Syria. And the 13 did not share data and did not talk to each other. And so we found that for example, they were all focused on one area. When just a few miles down, there was a need that wasn't being addressed. But because they don't share information, they had no idea. >> Right. >> It was only when we were able to take a look at it, kind of from the, from an overarching view, looking all their data, we were able to say you know, it would be helpful, it would actually, you could save on resources, and less time, and less effort, and you guys are tackling a small funding pool to begin with. If you shared information and tackled different things, instead of focusing on one area, because you don't know what the other guys doing. >> And were they using crowdsource data, is there source data, or were they just trying to collect their own from the field? >> They were collecting their own. >> So I assume that the depth, and the richness, and the broadness of data is nothing like you're collecting. >> Well you get a different kind of, you get different kind of information when the individuals actually telling you what's happening versus you asking a very direct question like, "Are you healthy? Yes or No?". Whereas you give them the chance, they might tell you that they haven't eaten, and their diabetic and you know, give you other pieces of information. Where they're living, are they refugees? Are they healthy? Are they not healthy? Do they go to school? Do their kids go to school? How many kids they have? Are they a female-run household? All this information could help guide development in the proper way. >> Right, right. All right. So give you the final word, how should people get involved if they want to help? >> You can go to humanitariantracker.org if you want to volunteer with us. And if you're doing a project that is related to the UN's Sustainable Development Goals, I would like you to go to globalactionmosaic.org, and map it there, and be part of our community. >> So Hend, thank you for taking a few minutes to share your story, and for all the good work that you're doing out there. >> Thank you Jeff it was a pleasure. >> All right, she's Hend, I'm Jeff, you're watching theCUBE, we're at AWS Imagine nonprofit. Thanks for watching we'll see you next time. (techno music)

>> From Cambridge, Massachusetts, it's theCUBE. Covering MIT Chief Data Officer and Information Quality Symposium 2019. Brought to you by SiliconANGLE Media. (futuristic music) >> Welcome back to Cambridge, Massachusetts everybody. You're watching theCUBE, the leader in live tech coverage. We go out to the events and we extract the signal from the noise. This is day two, we're sort of wrapping up the Chief Data Officer event. It's MIT CDOIQ, it started as an information quality event and with the ascendancy of big data the CDO emerged and really took center stage here. And it's interesting to know that it's kind of come full circle back to information quality. People are realizing all this data we have, you know the old saying, garbage in, garbage out. So the information quality worlds and this chief data officer world have really come colliding together. Robert Abate is here, he's the Vice President and CDO of Global IDS and also the co-chair of next year's, the 14th annual MIT CDOIQ. Robert, thanks for coming on. >> Oh, well thank you. >> Now you're a CDO by background, give us a little history of your career. >> Sure, sure. Well I started out with an Electrical Engineering degree and went into applications development. By 2000, I was leading the Ralph Lauren's IT, and I realized when Ralph Lauren hired me, he was getting ready to go public. And his problem was he had hired eight different accounting firms to do eight different divisions. And each of those eight divisions were reporting a number, but the big number didn't add up, so he couldn't go public. So he searched the industry to find somebody who could figure out the problem. Now I was, at the time, working in applications and had built this system called Service Oriented Architectures, a way of integrating applications. And I said, "Well I don't know if I could solve the problem, "but I'll give it a shot." And what I did was, just by taking each silo as it's own problem, which was what EID Accounting Firm had done, I was able to figure out that one of Ralph Lauren's policies was if you buy a garment, you can return it anytime, anywhere, forever, however long you own it. And he didn't think about that, but what that meant is somebody could go to a Bloomingdale's, buy a garment and then go to his outlet store and return it. Well, the cross channels were different systems. So the outlet stores were his own business, retail was a different business, there was a completely different, each one had their own AS/400, their own data. So what I quickly learned was, the problem wasn't the systems, the problem was the data. And it took me about two months to figure it out and he offered me a job, he said well, I was a consultant at the time, he says, "I'm offering you a job, you're going to run my IT." >> Great user experience but hard to count. >> (laughs) Hard to count. So that's when I, probably 1999 was when that happened. I went into data and started researching-- >> Sorry, so how long did it take you to figure that out? You said a couple of months? >> A couple of months, I think it was about two months. >> 'Cause jeez, it took Oracle what, 10 years to build Fusion with SOA? That's pretty good. (laughs) >> This was a little bit of luck. When we started integrating the applications we learned that the messages that we were sending back and forth didn't match, and we said, "Well that's impossible, it can't not match." But what didn't match was it was coming from one channel and being returned in another channel, and the returns showed here didn't balance with the returns on this side. So it was a data problem. >> So a forensics showdown. So what did you do after? >> After that I went into ICICI Bank which was a large bank in India who was trying to integrate their systems, and again, this was a data problem. But they heard me giving a talk at a conference on how SOA had solved the data challenge, and they said, "We're a bank with a wholesale, a retail, "and other divisions, "and we can't integrate the systems, can you?" I said, "Well yeah, I'd build a website "and make them web services and now what'll happen is "each of those'll kind of communicate." And I was at ICICI Bank for about six months in Mumbai, and finished that which was a success, came back and started consulting because now a lot of companies were really interested in this concept of Service Oriented Architectures. Back then when we first published on it, myself, Peter Aiken, and a gentleman named Joseph Burke published on it in 1996. The publisher didn't accept the book, it was a really interesting thing. We wrote the book called, "Services Based Architectures: A Way to Integrate Systems." And the way Wiley & Sons, or most publishers work is, they'll have three industry experts read your book and if they don't think what you're saying has any value, they, forget about it. So one guy said this is brilliant, one guy says, "These guys don't know what they're talking about," and the third guy says, "I don't even think what they're talking about is feasible." So they decided not to publish. Four years later it came back and said, "We want to publish the book," and Peter said, "You know what, they lost their chance." We were ahead of them by four years, they didn't understand the technology. So that was kind of cool. So from there I went into consulting, eventually took a position as the Head of Enterprise and Director of Enterprise Information Architecture with Walmart. And Walmart, as you know, is a huge entity, almost the size of the federal government. So to build an architecture that integrates Walmart would've been a challenge, a behemoth challenge, and I took it on with a phenomenal team. >> And when was this, like what timeframe? >> This was 2010, and by the end of 2010 we had presented an architecture to the CIO and the rest of the organization, and they came back to me about a week later and said, "Look, everybody agrees what you did was brilliant, "but nobody knows how to implement it. "So we're taking you away, "you're no longer Director of Information Architecture, "you're now Director of Enterprise Information Management. "Build it. "Prove that what you say you could do, you could do." So we built something called the Data CAFE, and CAFE was an acronym, it stood for: Collaborative Analytics Facility for the Enterprise. What we did was we took data from one of the divisions, because you didn't want to take on the whole beast, boil the ocean. We picked Sam's Club and we worked with their CFO, and because we had information about customers we were able to build a room with seven 80 inch monitors that surrounded anyone in the room. And in the center was the Cisco telecommunications so you could be a part of a meeting. >> The TelePresence. >> TelePresence. And we built one room in one facility, and one room in another facility, and we labeled the monitors, one red, one blue, one green, and we said, "There's got to be a way where we can build "data science so it's interactive, so somebody, "an executive could walk into the room, "touch the screen, and drill into features. "And in another room "the features would be changing simultaneously." And that's what we built. The room was brought up on Black Friday of 2013, and we were able to see the trends of sales on the East Coast that we quickly, the executives in the room, and these are the CEO of Walmart and the heads of Sam's Club and the like, they were able to change the distribution in the Mountain Time Zone and west time zones because of the sales on the East Coast gave them the idea, well these things are going to sell, and these things aren't. And they saw a tremendous increase in productivity. We received the 2014, my team received the 2014 Walmart Innovation Project of the Year. >> And that's no slouch. Walmart has always been heavily data-oriented. I don't know if it's urban legend or not, but the famous story in the '80s of the beer and the diapers, right? Walmart would position beer next to diapers, why would they do that? Well the father goes in to buy the diapers for the baby, picks up a six pack while he's on the way, so they just move those proximate to each other. (laughs) >> In terms of data, Walmart really learned that there's an advantage to understanding how to place items in places that, a path that you might take in a store, and knowing that path, they actually have a term for it, I believe it's called, I'm sorry, I forgot the name but it's-- >> Selling more stuff. (laughs) >> Yeah, it's selling more stuff. It's the way you position items on a shelf. And Walmart had the brilliance, or at least I thought it was brilliant, that they would make their vendors the data champion. So the vendor, let's say Procter & Gamble's a vendor, and they sell this one product the most. They would then be the champion for that aisle. Oh, it's called planogramming. So the planogramming, the way the shelves were organized, would be set up by Procter & Gamble for that entire area, working with all their other vendors. And so Walmart would give the data to them and say, "You do it." And what I was purporting was, well, we shouldn't just be giving the data away, we should be using that data. And that was the advent of that. From there I moved to Kimberly-Clark, I became Global Director of Enterprise Data Management and Analytics. Their challenge was they had different teams, there were four different instances of SAP around the globe. One for Latin America, one for North America called the Enterprise Edition, one for EMEA, Europe, Middle East, and Africa, and one for Asia-Pacific. Well when you have four different instances of SAP, that means your master data doesn't exist because the same thing that happens in this facility is different here. And every company faces this challenge. If they implement more than one of a system the specialty fields get used by different companies in different ways. >> The gold standard, the gold version. >> The golden version. So I built a team by bringing together all the different international teams, and created one team that was able to integrate best practices and standards around data governance, data quality. Built BI teams for each of the regions, and then a data science and advanced analytics team. >> Wow, so okay, so that makes you uniquely qualified to coach here at the conference. >> Oh, I don't know about that. (laughs) There are some real, there are some geniuses here. >> No but, I say that because these are your peeps. >> Yes, they are, they are. >> And so, you're a practitioner, this conference is all about practitioners talking to practitioners, it's content-heavy, There's not a lot of fluff. Lunches aren't sponsored, there's no lanyard sponsor and it's not like, you know, there's very subtle sponsor desks, you have to have sponsors 'cause otherwise the conference's not enabled, and you've got costs associated with it. But it's a very intimate event and I think you guys want to keep it that way. >> And I really believe you're dead-on. When you go to most industry conferences, the industry conferences, the sponsors, you know, change the format or are heavily into the format. Here you have industry thought leaders from all over the globe. CDOs of major Fortune 500 companies who are working with their peers and exchanging ideas. I've had conversations with a number of CDOs and the thought leadership at this conference, I've never seen this type of thought leadership in any conference. >> Yeah, I mean the percentage of presentations by practitioners, even when there's a vendor name, they have a practitioner, you know, internal practitioner presenting so it's 99.9% which is why people attend. We're moving venues next year, I understand. Just did a little tour of the new venue, so, going to be able to accommodate more attendees, so that's great. >> Yeah it is. >> So what are your objectives in thinking ahead a year from now? >> Well, you know, I'm taking over from my current peer, Dr. Arka Mukherjee, who just did a phenomenal job of finding speakers. People who are in the industry, who are presenting challenges, and allowing others to interact. So I hope could do a similar thing which is, find with my peers people who have real world challenges, bring them to the forum so they can be debated. On top of that, there are some amazing, you know, technology change is just so fast. One of the areas like big data I remember only five years ago the chart of big data vendors maybe had 50 people on it, now you would need the table to put all the vendors. >> Who's not a data vendor, you know? >> Who's not a data vendor? (laughs) So I would think the best thing we could do is, is find, just get all the CDOs and CDO-types into a room, and let us debate and talk about these points and issues. I've seen just some tremendous interactions, great questions, people giving advice to others. I've learned a lot here. >> And how about long term, where do you see this going? How many CDOs are there in the world, do you know? Is that a number that's known? >> That's a really interesting point because, you know, only five years ago there weren't that many CDOs to be called. And then Gartner four years ago or so put out an article saying, "Every company really should have a CDO." Not just for the purpose of advancing your data, and to Doug Laney's point that data is being monetized, there's a need to have someone responsible for information 'cause we're in the Information Age. And a CIO really is focused on infrastructure, making sure I've got my PCs, making sure I've got a LAN, I've got websites. The focus on data has really, because of the Information Age, has turned data into an asset. So organizations realize, if you utilize that asset, let me reverse this, if you don't use data as an asset, you will be out of business. I heard a quote, I don't know if it's true, "Only 10 years ago, 250 of the Fortune 10 no longer exists." >> Yeah, something like that, the turnover's amazing. >> Many of those companies were companies that decided not to make the change to be data-enabled, to make data decision processing. Companies still use data warehouses, they're always going to use them, and a warehouse is a rear-view mirror, it tells you what happened last week, last month, last year. But today's businesses work forward-looking. And just like driving a car, it'd be really hard to drive your car through a rear-view mirror. So what companies are doing today are saying, "Okay, let's start looking at this as forward-looking, "a prescriptive and predictive analytics, "rather than just what happened in the past." I'll give you an example. In a major company that is a supplier of consumer products, they were leading in the industry and their sales started to drop, and they didn't know why. Well, with a data science team, we were able to determine by pulling in data from the CDC, now these are sources that only 20 years ago nobody ever used to bring in data in the enterprise, now 60% of your data is external. So we brought in data from the CDC, we brought in data on maternal births from the national government, we brought in data from the Census Bureau, we brought in data from sources of advertising and targeted marketing towards mothers. Pulled all that data together and said, "Why are diaper sales down?" Well they were targeting the large regions of the country and putting ads in TV stations in New York and California, big population centers. Birth rates in population centers have declined. Birth rates in certain other regions, like the south, and the Bible Belt, if I can call it that, have increased. So by changing the marketing, their product sales went up. >> Advertising to Texas. >> Well, you know, and that brings to one of the points, I heard a lecture today about ethics. We made it a point at Walmart that if you ran a query that reduced a result to less than five people, we wouldn't allow you to see the result. Because, think about it, I could say, "What is my neighbor buying? "What are you buying?" So there's an ethical component to this as well. But that, you know, data is not political. Data is not chauvinistic. It doesn't discriminate, it just gives you facts. It's the interpretation of that that is hard CDOs, because we have to say to someone, "Look, this is the fact, and your 25 years "of experience in the business, "granted, is tremendous and it's needed, "but the facts are saying this, "and that would mean that the business "would have to change its direction." And it's hard for people to do, so it requires that. >> So whether it's called the chief data officer, whatever the data czar rubric is, the head of analytics, there's obviously the data quality component there whatever that is, this is the conference for, as I called them, your peeps, for that role in the organization. People often ask, "Will that role be around?" I think it's clear, it's solidifying. Yes, you see the chief digital officer emerging and there's a lot of tailwinds there, but the information quality component, the data architecture component, it's here to stay. And this is the premiere conference, the premiere event, that I know of anyway. There are a couple of others, perhaps, but it's great to see all the success. When I first came here in 2013 there were probably about 130 folks here. Today, I think there were 500 people registered almost. Next year, I think 600 is kind of the target, and I think it's very reasonable with the new space. So congratulations on all the success, and thank you for stepping up to the co-chair role, I really appreciate it. >> Well, let me tell you I thank you guys. You provide a voice at these IT conferences that we really need, and that is the ability to get the message out. That people do think and care, the industry is not thoughtless and heartless. With all the data breaches and everything going on there's a lot of fear, fear, loathing, and anticipation. But having your voice, kind of like ESPN and a sports show, gives the technology community, which is getting larger and larger by the day, a voice and we need that so, thank you. >> Well thank you, Robert. We appreciate that, it was great to have you on. Appreciate the time. >> Great to be here, thank you. >> All right, and thank you for watching. We'll be right back with out next guest as we wrap up day two of MIT CDOIQ. You're watching theCUBE. (futuristic music)