(upbeat music) >> Hello and welcome to theCube's coverage of International Women's Day. I'm John Furrier, your host of "theCUBE." We've got great two remote guests coming into our Palo Alto Studios, some tech athletes, as we say, people that've been in the trenches, years of experience, Lena Smart, CISO at MongoDB, Cube alumni, and Tara Hernandez, VP of Developer Productivity at MongoDB as well. Thanks for coming in to this program and supporting our efforts today. Thanks so much. >> Thanks for having us. >> Yeah, everyone talk about the journey in tech, where it all started. Before we get there, talk about what you guys are doing at MongoDB specifically. MongoDB is kind of gone the next level as a platform. You have your own ecosystem, lot of developers, very technical crowd, but it's changing the business transformation. What do you guys do at Mongo? We'll start with you, Lena. >> So I'm the CISO, so all security goes through me. I like to say, well, I don't like to say, I'm described as the ones throat to choke. So anything to do with security basically starts and ends with me. We do have a fantastic Cloud engineering security team and a product security team, and they don't report directly to me, but obviously we have very close relationships. I like to keep that kind of church and state separate and I know I've spoken about that before. And we just recently set up a physical security team with an amazing gentleman who left the FBI and he came to join us after 26 years for the agency. So, really starting to look at the physical aspects of what we offer as well. >> I interviewed a CISO the other day and she said, "Every day is day zero for me." Kind of goofing on the Amazon Day one thing, but Tara, go ahead. Tara, go ahead. What's your role there, developer productivity? What are you focusing on? >> Sure. Developer productivity is kind of the latest description for things that we've described over the years as, you know, DevOps oriented engineering or platform engineering or build and release engineering development infrastructure. It's all part and parcel, which is how do we actually get our code from developer to customer, you know, and all the mechanics that go into that. It's been something I discovered from my first job way back in the early '90s at Borland. And the art has just evolved enormously ever since, so. >> Yeah, this is a very great conversation both of you guys, right in the middle of all the action and data infrastructures changing, exploding, and involving big time AI and data tsunami and security never stops. Well, let's get into, we'll talk about that later, but let's get into what motivated you guys to pursue a career in tech and what were some of the challenges that you faced along the way? >> I'll go first. The fact of the matter was I intended to be a double major in history and literature when I went off to university, but I was informed that I had to do a math or a science degree or else the university would not be paid for. At the time, UC Santa Cruz had a policy that called Open Access Computing. This is, you know, the late '80s, early '90s. And anybody at the university could get an email account and that was unusual at the time if you were, those of us who remember, you used to have to pay for that CompuServe or AOL or, there's another one, I forget what it was called, but if a student at Santa Cruz could have an email account. And because of that email account, I met people who were computer science majors and I'm like, "Okay, I'll try that." That seems good. And it was a little bit of a struggle for me, a lot I won't lie, but I can't complain with how it ended up. And certainly once I found my niche, which was development infrastructure, I found my true love and I've been doing it for almost 30 years now. >> Awesome. Great story. Can't wait to ask a few questions on that. We'll go back to that late '80s, early '90s. Lena, your journey, how you got into it. >> So slightly different start. I did not go to university. I had to leave school when I was 16, got a job, had to help support my family. Worked a bunch of various jobs till I was about 21 and then computers became more, I think, I wouldn't say they were ubiquitous, but they were certainly out there. And I'd also been saving up every penny I could earn to buy my own computer and bought an Amstrad 1640, 20 meg hard drive. It rocked. And kind of took that apart, put it back together again, and thought that could be money in this. And so basically just teaching myself about computers any job that I got. 'Cause most of my jobs were like clerical work and secretary at that point. But any job that had a computer in front of that, I would make it my business to go find the guy who did computing 'cause it was always a guy. And I would say, you know, I want to learn how these work. Let, you know, show me. And, you know, I would take my lunch hour and after work and anytime I could with these people and they were very kind with their time and I just kept learning, so yep. >> Yeah, those early days remind me of the inflection point we're going through now. This major C change coming. Back then, if you had a computer, you had to kind of be your own internal engineer to fix things. Remember back on the systems revolution, late '80s, Tara, when, you know, your career started, those were major inflection points. Now we're seeing a similar wave right now, security, infrastructure. It feels like it's going to a whole nother level. At Mongo, you guys certainly see this as well, with this AI surge coming in. A lot more action is coming in. And so there's a lot of parallels between these inflection points. How do you guys see this next wave of change? Obviously, the AI stuff's blowing everyone away. Oh, new user interface. It's been called the browser moment, the mobile iPhone moment, kind of for this generation. There's a lot of people out there who are watching that are young in their careers, what's your take on this? How would you talk to those folks around how important this wave is? >> It, you know, it's funny, I've been having this conversation quite a bit recently in part because, you know, to me AI in a lot of ways is very similar to, you know, back in the '90s when we were talking about bringing in the worldwide web to the forefront of the world, right. And we tended to think in terms of all the optimistic benefits that would come of it. You know, free passing of information, availability to anyone, anywhere. You just needed an internet connection, which back then of course meant a modem. >> John: Not everyone had though. >> Exactly. But what we found in the subsequent years is that human beings are what they are and we bring ourselves to whatever platforms that are there, right. And so, you know, as much as it was amazing to have this freely available HTML based internet experience, it also meant that the negatives came to the forefront quite quickly. And there were ramifications of that. And so to me, when I look at AI, we're already seeing the ramifications to that. Yes, are there these amazing, optimistic, wonderful things that can be done? Yes. >> Yeah. >> But we're also human and the bad stuff's going to come out too. And how do we- >> Yeah. >> How do we as an industry, as a community, you know, understand and mitigate those ramifications so that we can benefit more from the positive than the negative. So it is interesting that it comes kind of full circle in really interesting ways. >> Yeah. The underbelly takes place first, gets it in the early adopter mode. Normally industries with, you know, money involved arbitrage, no standards. But we've seen this movie before. Is there hope, Lena, that we can have a more secure environment? >> I would hope so. (Lena laughs) Although depressingly, we've been in this well for 30 years now and we're, at the end of the day, still telling people not to click links on emails. So yeah, that kind of still keeps me awake at night a wee bit. The whole thing about AI, I mean, it's, obviously I am not an expert by any stretch of the imagination in AI. I did read (indistinct) book recently about AI and that was kind of interesting. And I'm just trying to teach myself as much as I can about it to the extent of even buying the "Dummies Guide to AI." Just because, it's actually not a dummies guide. It's actually fairly interesting, but I'm always thinking about it from a security standpoint. So it's kind of my worst nightmare and the best thing that could ever happen in the same dream. You know, you've got this technology where I can ask it a question and you know, it spits out generally a reasonable answer. And my team are working on with Mark Porter our CTO and his team on almost like an incubation of AI link. What would it look like from MongoDB? What's the legal ramifications? 'Cause there will be legal ramifications even though it's the wild, wild west just now, I think. Regulation's going to catch up to us pretty quickly, I would think. >> John: Yeah, yeah. >> And so I think, you know, as long as companies have a seat at the table and governments perhaps don't become too dictatorial over this, then hopefully we'll be in a good place. But we'll see. I think it's a really interest, there's that curse, we're living in interesting times. I think that's where we are. >> It's interesting just to stay on this tech trend for a minute. The standards bodies are different now. Back in the old days there were, you know, IEEE standards, ITF standards. >> Tara: TPC. >> The developers are the new standard. I mean, now you're seeing open source completely different where it was in the '90s to here beginning, that was gen one, some say gen two, but I say gen one, now we're exploding with open source. You have kind of developers setting the standards. If developers like it in droves, it becomes defacto, which then kind of rolls into implementation. >> Yeah, I mean I think if you don't have developer input, and this is why I love working with Tara and her team so much is 'cause they get it. If we don't have input from developers, it's not going to get used. There's going to be ways of of working around it, especially when it comes to security. If they don't, you know, if you're a developer and you're sat at your screen and you don't want to do that particular thing, you're going to find a way around it. You're a smart person. >> Yeah. >> So. >> Developers on the front lines now versus, even back in the '90s, they're like, "Okay, consider the dev's, got a QA team." Everything was Waterfall, now it's Cloud, and developers are on the front lines of everything. Tara, I mean, this is where the standards are being met. What's your reaction to that? >> Well, I think it's outstanding. I mean, you know, like I was at Netscape and part of the crowd that released the browser as open source and we founded mozilla.org, right. And that was, you know, in many ways kind of the birth of the modern open source movement beyond what we used to have, what was basically free software foundation was sort of the only game in town. And I think it is so incredibly valuable. I want to emphasize, you know, and pile onto what Lena was saying, it's not just that the developers are having input on a sort of company by company basis. Open source to me is like a checks and balance, where it allows us as a broader community to be able to agree on and enforce certain standards in order to try and keep the technology platforms as accessible as possible. I think Kubernetes is a great example of that, right. If we didn't have Kubernetes, that would've really changed the nature of how we think about container orchestration. But even before that, Linux, right. Linux allowed us as an industry to end the Unix Wars and as someone who was on the front lines of that as well and having to support 42 different operating systems with our product, you know, that was a huge win. And it allowed us to stop arguing about operating systems and start arguing about software or not arguing, but developing it in positive ways. So with, you know, with Kubernetes, with container orchestration, we all agree, okay, that's just how we're going to orchestrate. Now we can build up this huge ecosystem, everybody gets taken along, right. And now it changes the game for what we're defining as business differentials, right. And so when we talk about crypto, that's a little bit harder, but certainly with AI, right, you know, what are the checks and balances that as an industry and as the developers around this, that we can in, you know, enforce to make sure that no one company or no one body is able to overly control how these things are managed, how it's defined. And I think that is only for the benefit in the industry as a whole, particularly when we think about the only other option is it gets regulated in ways that do not involve the people who actually know the details of what they're talking about. >> Regulated and or thrown away or bankrupt or- >> Driven underground. >> Yeah. >> Which would be even worse actually. >> Yeah, that's a really interesting, the checks and balances. I love that call out. And I was just talking with another interview part of the series around women being represented in the 51% ratio. Software is for everybody. So that we believe that open source movement around the collective intelligence of the participants in the industry and independent of gender, this is going to be the next wave. You're starting to see these videos really have impact because there are a lot more leaders now at the table in companies developing software systems and with AI, the aperture increases for applications. And this is the new dynamic. What's your guys view on this dynamic? How does this go forward in a positive way? Is there a certain trajectory you see? For women in the industry? >> I mean, I think some of the states are trying to, again, from the government angle, some of the states are trying to force women into the boardroom, for example, California, which can be no bad thing, but I don't know, sometimes I feel a bit iffy about all this kind of forced- >> John: Yeah. >> You know, making, I don't even know how to say it properly so you can cut this part of the interview. (John laughs) >> Tara: Well, and I think that they're >> I'll say it's not organic. >> No, and I think they're already pulling it out, right. It's already been challenged so they're in the process- >> Well, this is the open source angle, Tara, you are getting at it. The change agent is open, right? So to me, the history of the proven model is openness drives transparency drives progress. >> No, it's- >> If you believe that to be true, this could have another impact. >> Yeah, it's so interesting, right. Because if you look at McKinsey Consulting or Boston Consulting or some of the other, I'm blocking on all of the names. There has been a decade or more of research that shows that a non homogeneous employee base, be it gender or ethnicity or whatever, generates more revenue, right? There's dollar signs that can be attached to this, but it's not enough for all companies to want to invest in that way. And it's not enough for all, you know, venture firms or investment firms to grant that seed money or do those seed rounds. I think it's getting better very slowly, but socialization is a much harder thing to overcome over time. Particularly, when you're not just talking about one country like the United States in our case, but around the world. You know, tech centers now exist all over the world, including places that even 10 years ago we might not have expected like Nairobi, right. Which I think is amazing, but you have to factor in the cultural implications of that as well, right. So yes, the openness is important and we have, it's important that we have those voices, but I don't think it's a panacea solution, right. It's just one more piece. I think honestly that one of the most important opportunities has been with Cloud computing and Cloud's been around for a while. So why would I say that? It's because if you think about like everybody holds up the Steve Jobs, Steve Wozniak, back in the '70s, or Sergey and Larry for Google, you know, you had to have access to enough credit card limit to go to Fry's and buy your servers and then access to somebody like Susan Wojcicki to borrow the garage or whatever. But there was still a certain amount of upfrontness that you had to be able to commit to, whereas now, and we've, I think, seen a really good evidence of this being able to lease server resources by the second and have development platforms that you can do on your phone. I mean, for a while I think Africa, that the majority of development happened on mobile devices because there wasn't a sufficient supply chain of laptops yet. And that's no longer true now as far as I know. But like the power that that enables for people who would otherwise be underrepresented in our industry instantly opens it up, right? And so to me that's I think probably the biggest opportunity that we've seen from an industry on how to make more availability in underrepresented representation for entrepreneurship. >> Yeah. >> Something like AI, I think that's actually going to take us backwards if we're not careful. >> Yeah. >> Because of we're reinforcing that socialization. >> Well, also the bias. A lot of people commenting on the biases of the large language inherently built in are also problem. Lena, I want you to weigh on this too, because I think the skills question comes up here and I've been advocating that you don't need the pedigree, college pedigree, to get into a certain jobs, you mentioned Cloud computing. I mean, it's been around for you think a long time, but not really, really think about it. The ability to level up, okay, if you're going to join something new and half the jobs in cybersecurity are created in the past year, right? So, you have this what used to be a barrier, your degree, your pedigree, your certification would take years, would be a blocker. Now that's gone. >> Lena: Yeah, it's the opposite. >> That's, in fact, psychology. >> I think so, but the people who I, by and large, who I interview for jobs, they have, I think security people and also I work with our compliance folks and I can't forget them, but let's talk about security just now. I've always found a particular kind of mindset with security folks. We're very curious, not very good at following rules a lot of the time, and we'd love to teach others. I mean, that's one of the big things stem from the start of my career. People were always interested in teaching and I was interested in learning. So it was perfect. And I think also having, you know, strong women leaders at MongoDB allows other underrepresented groups to actually apply to the company 'cause they see that we're kind of talking the talk. And that's been important. I think it's really important. You know, you've got Tara and I on here today. There's obviously other senior women at MongoDB that you can talk to as well. There's a bunch of us. There's not a whole ton of us, but there's a bunch of us. And it's good. It's definitely growing. I've been there for four years now and I've seen a growth in women in senior leadership positions. And I think having that kind of track record of getting really good quality underrepresented candidates to not just interview, but come and join us, it's seen. And it's seen in the industry and people take notice and they're like, "Oh, okay, well if that person's working, you know, if Tara Hernandez is working there, I'm going to apply for that." And that in itself I think can really, you know, reap the rewards. But it's getting started. It's like how do you get your first strong female into that position or your first strong underrepresented person into that position? It's hard. I get it. If it was easy, we would've sold already. >> It's like anything. I want to see people like me, my friends in there. Am I going to be alone? Am I going to be of a group? It's a group psychology. Why wouldn't? So getting it out there is key. Is there skills that you think that people should pay attention to? One's come up as curiosity, learning. What are some of the best practices for folks trying to get into the tech field or that's in the tech field and advancing through? What advice are you guys- >> I mean, yeah, definitely, what I say to my team is within my budget, we try and give every at least one training course a year. And there's so much free stuff out there as well. But, you know, keep learning. And even if it's not right in your wheelhouse, don't pick about it. Don't, you know, take a look at what else could be out there that could interest you and then go for it. You know, what does it take you few minutes each night to read a book on something that might change your entire career? You know, be enthusiastic about the opportunities out there. And there's so many opportunities in security. Just so many. >> Tara, what's your advice for folks out there? Tons of stuff to taste, taste test, try things. >> Absolutely. I mean, I always say, you know, my primary qualifications for people, I'm looking for them to be smart and motivated, right. Because the industry changes so quickly. What we're doing now versus what we did even last year versus five years ago, you know, is completely different though themes are certainly the same. You know, we still have to code and we still have to compile that code or package the code and ship the code so, you know, how well can we adapt to these new things instead of creating floppy disks, which was my first job. Five and a quarters, even. The big ones. >> That's old school, OG. There it is. Well done. >> And now it's, you know, containers, you know, (indistinct) image containers. And so, you know, I've gotten a lot of really great success hiring boot campers, you know, career transitioners. Because they bring a lot experience in addition to the technical skills. I think the most important thing is to experiment and figuring out what do you like, because, you know, maybe you are really into security or maybe you're really into like deep level coding and you want to go back, you know, try to go to school to get a degree where you would actually want that level of learning. Or maybe you're a front end engineer, you want to be full stacked. Like there's so many different things, data science, right. Maybe you want to go learn R right. You know, I think it's like figure out what you like because once you find that, that in turn is going to energize you 'cause you're going to feel motivated. I think the worst thing you could do is try to force yourself to learn something that you really could not care less about. That's just the worst. You're going in handicapped. >> Yeah and there's choices now versus when we were breaking into the business. It was like, okay, you software engineer. They call it software engineering, that's all it was. You were that or you were in sales. Like, you know, some sort of systems engineer or sales and now it's,- >> I had never heard of my job when I was in school, right. I didn't even know it was a possibility. But there's so many different types of technical roles, you know, absolutely. >> It's so exciting. I wish I was young again. >> One of the- >> Me too. (Lena laughs) >> I don't. I like the age I am. So one of the things that I did to kind of harness that curiosity is we've set up a security champions programs. About 120, I guess, volunteers globally. And these are people from all different backgrounds and all genders, diversity groups, underrepresented groups, we feel are now represented within this champions program. And people basically give up about an hour or two of their time each week, with their supervisors permission, and we basically teach them different things about security. And we've now had seven full-time people move from different areas within MongoDB into my team as a result of that program. So, you know, monetarily and time, yeah, saved us both. But also we're showing people that there is a path, you know, if you start off in Tara's team, for example, doing X, you join the champions program, you're like, "You know, I'd really like to get into red teaming. That would be so cool." If it fits, then we make that happen. And that has been really important for me, especially to give, you know, the women in the underrepresented groups within MongoDB just that window into something they might never have seen otherwise. >> That's a great common fit is fit matters. Also that getting access to what you fit is also access to either mentoring or sponsorship or some sort of, at least some navigation. Like what's out there and not being afraid to like, you know, just ask. >> Yeah, we just actually kicked off our big mentor program last week, so I'm the executive sponsor of that. I know Tara is part of it, which is fantastic. >> We'll put a plug in for it. Go ahead. >> Yeah, no, it's amazing. There's, gosh, I don't even know the numbers anymore, but there's a lot of people involved in this and so much so that we've had to set up mentoring groups rather than one-on-one. And I think it was 45% of the mentors are actually male, which is quite incredible for a program called Mentor Her. And then what we want to do in the future is actually create a program called Mentor Them so that it's not, you know, not just on the female and so that we can live other groups represented and, you know, kind of break down those groups a wee bit more and have some more granularity in the offering. >> Tara, talk about mentoring and sponsorship. Open source has been there for a long time. People help each other. It's community-oriented. What's your view of how to work with mentors and sponsors if someone's moving through ranks? >> You know, one of the things that was really interesting, unfortunately, in some of the earliest open source communities is there was a lot of pervasive misogyny to be perfectly honest. >> Yeah. >> And one of the important adaptations that we made as an open source community was the idea, an introduction of code of conducts. And so when I'm talking to women who are thinking about expanding their skills, I encourage them to join open source communities to have opportunity, even if they're not getting paid for it, you know, to develop their skills to work with people to get those code reviews, right. I'm like, "Whatever you join, make sure they have a code of conduct and a good leadership team. It's very important." And there are plenty, right. And then that idea has come into, you know, conferences now. So now conferences have codes of contact, if there are any good, and maybe not all of them, but most of them, right. And the ideas of expanding that idea of intentional healthy culture. >> John: Yeah. >> As a business goal and business differentiator. I mean, I won't lie, when I was recruited to come to MongoDB, the culture that I was able to discern through talking to people, in addition to seeing that there was actually women in senior leadership roles like Lena, like Kayla Nelson, that was a huge win. And so it just builds on momentum. And so now, you know, those of us who are in that are now representing. And so that kind of reinforces, but it's all ties together, right. As the open source world goes, particularly for a company like MongoDB, which has an open source product, you know, and our community builds. You know, it's a good thing to be mindful of for us, how we interact with the community and you know, because that could also become an opportunity for recruiting. >> John: Yeah. >> Right. So we, in addition to people who might become advocates on Mongo's behalf in their own company as a solution for themselves, so. >> You guys had great successful company and great leadership there. I mean, I can't tell you how many times someone's told me "MongoDB doesn't scale. It's going to be dead next year." I mean, I was going back 10 years. It's like, just keeps getting better and better. You guys do a great job. So it's so fun to see the success of developers. Really appreciate you guys coming on the program. Final question, what are you guys excited about to end the segment? We'll give you guys the last word. Lena will start with you and Tara, you can wrap us up. What are you excited about? >> I'm excited to see what this year brings. I think with ChatGPT and its copycats, I think it'll be a very interesting year when it comes to AI and always in the lookout for the authentic deep fakes that we see coming out. So just trying to make people aware that this is a real thing. It's not just pretend. And then of course, our old friend ransomware, let's see where that's going to go. >> John: Yeah. >> And let's see where we get to and just genuine hygiene and housekeeping when it comes to security. >> Excellent. Tara. >> Ah, well for us, you know, we're always constantly trying to up our game from a security perspective in the software development life cycle. But also, you know, what can we do? You know, one interesting application of AI that maybe Google doesn't like to talk about is it is really cool as an addendum to search and you know, how we might incorporate that as far as our learning environment and developer productivity, and how can we enable our developers to be more efficient, productive in their day-to-day work. So, I don't know, there's all kinds of opportunities that we're looking at for how we might improve that process here at MongoDB and then maybe be able to share it with the world. One of the things I love about working at MongoDB is we get to use our own products, right. And so being able to have this interesting document database in order to put information and then maybe apply some sort of AI to get it out again, is something that we may well be looking at, if not this year, then certainly in the coming year. >> Awesome. Lena Smart, the chief information security officer. Tara Hernandez, vice president developer of productivity from MongoDB. Thank you so much for sharing here on International Women's Day. We're going to do this quarterly every year. We're going to do it and then we're going to do quarterly updates. Thank you so much for being part of this program. >> Thank you. >> Thanks for having us. >> Okay, this is theCube's coverage of International Women's Day. I'm John Furrier, your host. Thanks for watching. (upbeat music)

>>Hey everyone. Welcome back to the Cube's live coverage of snowflake summit 22 live from Las Vegas. Caesar's forum. Lisa Martin here with Dave Valante. We've got a couple of guests here. We're gonna be talking about every day. AI. You wanna know what that means? You're in the right spot. Kurt UL joins us, the chief customer officer at data ICU and the mod Conn, the head of AI and ML strategy at snowflake guys. Great to have you on the program. >>It's wonderful to be here. Thank you so much. >>So we wanna understand Kurt what everyday AI means, but before we do that for the audience who might not be familiar with data, I could give them a little bit of an overview. What about what you guys do your mission and maybe a little bit about the partnership? >>Yeah, great. Uh, very happy to do so. And thanks so much for this opportunity. Um, well, data IKU, we are a collaborative platform, uh, for enterprise AI. And what that means is it's a software, you know, that sits on top of incredible infrastructure, notably snowflake that allows people from different backgrounds of data, analysts, data, scientists, data, engineers, all to come together, to work together, to build out machine learning models and ultimately the AI that's gonna be the future, uh, of their business. Um, and so we're very excited to, uh, to be here, uh, and you know, very proud to be a, a, a very close partner of snowflake. >>So Amad, what is Snowflake's AI strategy? Is it to, is it to partner? Where do, where do you pick up? And Frank said today, we, we're not doing it all. Yeah. The ecosystem by design. >>Yeah. Yeah, absolutely. So we believe in the best of breed look. Um, I think, um, we, we think that we're the best data platform and for data science and machine learning, we want our customers to really use the best tool for their use cases. Right. And, you know, data ICU is, is our leading partner in that space. And so, you know, when, when you talk about, uh, machine learning and data science, people talk about training a model, but it's really the difficult part and challenges are really, before you train the model, how do you get access to the right data? And then after you train the model, how do you then run the model? And then how do you manage the model? Uh, that's very, very important. And that's where our partnership with, with data, uh, IKU comes in place. Snowflake provides the platform that can process data at scale for the pre-processing bit and, and data IKU comes in and really, uh, simplifies the process for deploying the models and managing the model. >>Got it. Thank >>You. You talk about KD data. Aico talks about everyday AI. I wanna break that down. What do you mean by that? And how is this partnership with snowflake empowering you to deliver that to companies? >>Yeah, absolutely. So everyday AI for us is, uh, you know, kind of a future state that we are building towards where we believe that AI will become so pervasive in all of the business processes, all the decision making that organizations have to go through that it's no longer this special thing that we talk about. It's just the, the day to day life of, uh, of our businesses. And we can't do that without partners like snowflake and, uh, because they're bringing together all of that data and ensuring that there is the, uh, the computational horsepower behind that to drive that we heard that this morning in some of the keynote talking about that broad democratization and the, um, let's call it the, uh, you know, the pressure that that's going to put on the underlying infrastructure. Um, and so ultimately everyday AI for us is where companies own that AI capability. They're building it themselves very broad, uh, participation in the development of that. And all that work then is being pushed down into best of breed, uh, infrastructure, notably of course, snowflake. Well, >>You said push down, you, you guys, you there's a term in the industry push down optimization. What does that mean? How is it evolving? Why is it so important? >>So Amma, do you want to take a first step at that? >>Yeah, absolutely. So, I mean, when, when you're, you know, processing data, so saying data, um, before you train a, uh, a model, you have to do it at scale, that that, that data is, is coming from all different sources. It's human generated machine generated data, we're talking millions and billions of rows of data. Uh, and you have to make sense of it. You have to transform that data into the right kind of features into the right kind of signals that inform the machine learning model that you're trying to, uh, train. Uh, and so that's where, you know, any kind of large scale data processing is automatically pushed down by data IQ, into snowflakes, scalable infrastructure. Um, so you don't get into like memory issues. You don't get into, um, uh, situations where you're where your pipeline is running overnight, and it doesn't finish in time. Right? And so, uh, you can really take advantage of the scalable nature of cloud computing, uh, using Snowflake's infrastructure. So a lot of that processing is actually getting pushed down from data I could down into the scalable snowflake compute engine. How >>Does this affect the life of a data scientist? You always hear a data scientist spend 80% of the time wrangling data. Uh, I presume there's an infrastructure component around that you trying, we heard this morning, you're making infrastructure, my words, infrastructure, self serve, uh, does this directly address that problem and, and talk about that. And what else are you doing to address that 80% problem? >>It, it certainly does, right? Uh, that's how you solve for, uh, data scientists needing to have on demand access to computing resources, or of course, to the, uh, to the underlying data, um, is by ensuring that that work doesn't have to run on their laptop, doesn't have to run on some, you know, constrained, uh, physical machines, uh, in, in a data center somewhere. Instead it gets pushed down into snowflake and can be executed at scale with incredible parallelization. Now what's really, uh, I important is the ongoing development, uh, between the two products, uh, and within that technology. And so today snowflake, uh, announced the introduction of Python within snow park, um, which is really, really exciting, uh, because that really opens up this capability to a much wider audience. Now DataCo provides that both through a visual interface, um, in historically, uh, since last year through Java UDFs, but that's kind of the, the two extremes, right? You have people who don't code on one side, you know, very no code or a low code, uh, population, and then a very high code population. On the other side, this Python, uh, integration really allows us to, to touch really kind the, the fat center of the data science population, who, uh, who, for whom, you know, Python really is the lingua franca that they've been learning for, uh, for decades now. Sure. So >>Talking about the data scientist, I wanna elevate that a little bit because you both are enterprise customers, data ICO, and snowflake Kurt as the chief customer officer, obviously you're with customers all the time. If we look at the macro environment of all the challenges, companies have to be a data company these days, if you're not, you're not gonna be successful. It's how do we do that? Extract insights, value, action, take it. But I'm just curious if your customer conversations are elevating up to the C-suite or, or the board in terms of being able to get democratize access to data, to be competitive, new products, new services, we've seen tremendous momentum, um, on, on the, the part of customer's growth on the snowflake side. But what are you hearing from customers as they're dealing with some of these current macro pains? >>Yeah, no, I, I think it is the conversation today, uh, at that sea level is not only how do we, you know, leverage, uh, new infrastructure, right. You know, they they're, you know, most of them now are starting to have snowflake. I think Frank said, uh, you know, 50% of the, uh, fortune 500, so we can say most, um, have that in place. Um, but now the question is, how do we, how do we ensure that we're getting access to that data, to that, to that computational horsepower, to a broader group of people so that it becomes truly a transformational initiative and not just an it initiative, not just a technology initiative, but really a core business initiative. And that, that really has been a pivot. You know, I've been, you know, with my company now for almost eight years, right. Uh, and we've really seen a change in that discussion going from, you know, much more niche discussions at the team or departmental level now to truly corporate strategic level. How do we build AI into our corporate strategy? How do we really do that in practice? And >>We hear a lot about, Hey, I want to inject data into apps, AI, and machine intelligence into applications. And we've talked about, those are separate stacks. You got the data stack and analytics stack over here. You got the application development, stack the databases off in the corner. And so we see you guys bringing those worlds together. And my question is, what does that stack look like? I took a snapshot. I think it was Frank's presentation today. He had infrastructure at the lowest level live data. So infrastructure's cloud live data. That's multiple data sources coming in workload execution. You made some announcements there. Mm-hmm, <affirmative>, uh, to expend expand that application development. That's the tooling that is needed. Uh, and then marketplace, that's how you bring together this ecosystem. Yes. Monetization is how you turn data into data products and make money. Is that the stack, is that the new stack that's emerging here? Are you guys defining that? >>Absolutely. Absolutely. You talked about like the 80% of the time being spent by data scientists and part of that is actually discovering the right data. Right. Um, being able to give the right access to the right people and being able to go and discover that data. And so you, you, you go from that angle all the way to processing, training a model. And then all those predictions that are insights that are coming out of the model are being consumed downstream by data applications. And so the two major announcements I'm super excited about today is, is the ability to run Python, which is snow park, uh, in, in snowflake. Um, that will do, you know, you can now as a Python developer come and bring the processing to where the data lives rather than move the data out to where the processing lives. Right. Um, so both SQL developers, Python developers, fully enabled. Um, and then the predictions that are coming out of models that are being trained by data ICU are then being used downstream by these data applications for most of our customers. And so that's where number, the second announcement with streamlet is super exciting. I can write a complete data application without writing a single line of JavaScript CSS or HTML. I can write it completely in Python. It's it makes me super excited as, as a Python developer, myself >>And you guys have joint customers that are headed in this direction, doing this today. Where, where can you talk about >>That? Yeah, we do. Uh, you know, there's a few that we're very proud of. Um, you know, company, well known companies like, uh, like REI or emeritus. Um, but one that was mentioned today, uh, this morning by Frank again, uh, Novartis, uh, pharmaceutical company, you know, they have been extremely successful, uh, in accelerating their AI and ML development by expanding access to their data. And that's a combination of, uh, both the data ICU, uh, layer, you know, allowing for that work to be developed in that, uh, in that workspace. Um, but of course, without, you know, the, the underlying, uh, uh, platform of snowflake, right, they, they would not have been able to, to have re realized those, uh, those gains. And they were talking about, you know, very, very significant increases in inefficiency everything from data access to the actual model development to the deployment. Um, it's just really, really honestly inspiring to see. >>And it was great to see Novartis mentioned on the main stage, massive time to value there. We've actually got them on the program later this week. So that was great. Another joint customer, you mentioned re I we'll let you go, cuz you're off to do a, a session with re I, is that right? >>Yes, that's exactly right. So, uh, so we're going to be doing a fireside chat, uh, talking about, in fact, you know, much of the same, all of the success that they've had in accelerating their, uh, analytics, workflow development, uh, the actual development of AI capabilities within, uh, of course that, uh, that beloved brand. >>Excellent guys, thank you so much for joining Dave and me talking about everyday AI, what you're doing together, data ICO, and snowflake to empower organizations to actually achieve that and live it. We appreciate your insights. Thank you both. You guys. Thank you for having us for our guests and Dave ante. I'm Lisa Martin. You're watching the Cube's live coverage of snowflake summit 22 from Las Vegas. Stick around our next guest joins us momentarily.

>> Narrator: The cube presents, the Kubecon and Cloudnativecon Europe, 2022 brought to you by Red Hat, the cloud native computing foundation and its ecosystem partners. >> Welcome to Valencia, Spain in Kubecon and Cloudnativecon Europe, 2022. I'm your host Keith Townsend. It's been a amazing day, three days of coverage 7,500 people, 170 sponsors, a good mix of end user organizations, vendors, just people with open source at large. I've loved the conversations. We're not going to stop that coverage just because this is the last session of the conference. Colin Murphy, senior software engineer, Adobe, >> Adobe. >> Oh, wow. This is going to be fun. And then Liam Randall, the chair of CNCF Cloud Native WebAssembly Day. >> That's correct. >> And CNCF & CEO of Cosmonic. >> That's right. >> All right. First off, let's talk about the show. How has this been different than other, if at all of other Kubecons? >> Well, first I think we all have to do a tremendous round of applause, not only for the vendors, but the CNC staff and all the attendees for coming out. And you have to say, Kubecon is back. The online experiences have been awesome but this was the first one, where Hallwaycon was in full effect. And you had the opportunity to sit down and meet with so many intelligent and inspiring peers and really have a chance to learn about all the exciting innovations that have happened over the last year. >> Colin. >> Yeah, it's been my most enjoyable Kubecon I've ever been to. And I've been to a bunch of them over the last few years. Just the quality of people. The problems that we're solving right now, everywhere from this newer stuff that we're talking about today with WebAssembly but then all these big enterprises trying to getting involved in Kubernetes >> Colin, to your point about the problems that we're solving, in many ways the pandemic has dramatically accelerated the pace of innovation, especially inside the CNCF, which is by far the most critical repository of open source projects that enterprises, governments and individuals rely on around the world, in order to deliver new experiences and to have coped and scaled out within the pandemic over the last few years. >> Yeah, I'm getting this feel, this vibe of the overall show that feels like we're on the cuff for something. There's other shows throughout the year, that's more vendor focused that talk about cloud native. But I think this is going to be the industry conference where we're just getting together and talking about it and it's going to probably be, in the next couple of years, the biggest conference of the year, that's just my personal opinion. >> I actually really strongly agree with you. And I think that the reason for that is the diversity that we get from the open source focus of Kubecon Kubecon has started where the industry really started which was in shared community projects. And I was the executive at Capital One that led the donation of cloud custodian into the CNCF. And I've started and put many projects here. And one of the reasons that you do that is so that you can build real scalable communities, Vendors that oftentimes even have competing interest but it gives us a place where we can truly collaborate where we can set aside our personal agendas and our company's agendas. And we can focus on the problems at hand. And how do we really raise the bar for technology for everybody. >> Now you two are representing a project that, you know as we look at kind of, how the web has evolved the past few decades, there's standards, there's things that we know that work, there's things that we know that don't work and we're beyond cloud native, we're kind of resistant to change. Funny enough. >> That's right. >> So WebAssembly, talk to me about what problem is WebAssembly solving that need solving? >> I think it's fitting that here on the last day of Kubecon, we're starting with the newest standard for the web and for background, there's only four languages that make up what we think of as the modern web. There's JavaScript, there's HTML, there's CSS, and now there's a new idea that's WebAssembly. And it's maybe not a new idea but it's certainly a new standard, that's got massive adoption and acceleration. WebAssembly is best thought of as almost like a portable little virtual machine. And like a lot of great ideas like JavaScript, it was originally designed to bring new experiences to browsers everywhere. And as organizations looked at the portability and security value props that come from this tiny little virtual machine, it's made a wonderful addition to backend servers and as a platform for portability to bring solutions all the way out to the edge. >> So what are some of the business cases for WebAssembly? Like what problem, what business problem are we solving? >> So it, you know, we would not have been able to bring Photoshop to the web without WASM. >> Wow. >> And just to be clear, I had nothing to do with that effort. So I want to make sure everybody understands, but if you have a lot of C++ or C code and you want to bring that experience to the web browser which is a great cost savings, cause it's running on the client's machines, really low latency, high performance experiences in the browser, WASM, really the only way to go. >> So I'm getting hints of fruit berry, Java. >> Liam: Yeah, absolutely. >> Colin: Definitely. >> You know, the look, WebAssembly sounds similar to promises you've heard before, right ones, run anywhere. The difference is, is that WebAssembly is not driven by any one particular vendor. So there's no one vendor that's trying to bring a plug in to every single device. WebAssembly was a recognition, much like Kubecon, the point that we started with around the diversity of thought ideas and representation of shared interest, of how do we have a platform that's polyglot? Many people can bring languages to it, and solutions that we can share and then build from there. And it is unlocking some of the most amazing and innovative experiences, both on the web backend servers and all the way to the edge. Because WebAssembly is a tiny little virtual machine that runs everywhere. Adobe's leadership is absolutely incredible with the things that they're doing with WebAssembly. They did this awesome blog post with the Google Chrome team that talked about other performance improvements that were brought into Chrome and other browsers, in order to enable that kind of experience. >> So I get the general concept of WebAssembly and it's one of those things that I have to ask the question, and I appreciate that Adobe uses it but without the community, I mean, I've dedicated some of my team's resources over the years to some really cool projects and products that just died on the buying cause there was no community around. >> Yeah. >> Who else uses WebAssembly? >> Yeah, I think so. We actually, inside the CNCF now, have an entire day devoted just to WebAssembly and as the co-chair of the CNCF Cloud Native WebAssembly Day, we really focus on bringing those case studies to the forefront. So some of the more interesting talks that we had here and at some of the precursor weekend conferences were from BMW, for example, they talked about how they were excited about not only WebAssembly, but a framework that they use on WebAssembly called WASM cloud, that lets them a flexibly scale machine learning models from their own edge, in their own vehicles through to their developer's workstations and even take that data onto their regular cloud Kubernetes and scale analysis and analytics. They invested and they just released a machine learning framework for one of the many great WebAssembly projects called WASM cloud, which is a CNCF project, a member project here in the CNCF. >> So how does that fit in overall landscape? >> So think of WebAssembly, like you think of HTML. It's a technology that gives you a lot of concept and to accelerate your journey on those technologies, people create frameworks. For example, if you were going to write a UI, you would not very likely start with an empty document you'd start with a react or view. And in a similar vein, if you were going to start a new microservice or backend application, project for WebAssembly, you might use WASM cloud or you might use ATMO or you might use a Spin. Those are three different types of projects. They all have their own different value props and their own different opinions that they bring to them. But the point is is that this is a quickly evolving space and it's going to dramatically change the type of experiences that we bring, not only to web browsers but to servers and edges everywhere. >> So Colin, you mentioned C+ >> Colin: Yeah. >> And other coding. Well , talk to me about the ramp up. >> Oh, well, so, yeah, so, C++ there was a lot of work done in scripting, at Adobe. Taking our C++ code and bringing it into the browser. A lot of new instructions, Cimdi, that were brought to make a really powerful experience, but what's new now is the server side aspect of things. So, just what kind of, what Liam was talking about. Now we can run this stuff in the data center. It's not just for people's browsers anymore. And then we can also bring it out to the edge too, which is a new space that we can take advantage of really almost only through WebAssembly and some JavaScript. >> So wait, let me get this kind of under hook. Before, if I wanted a rich experience, I have to run a heavy VDI instance on the back end so that I'm basically getting remote desktop calls from a light thin client back to my backend server, that's heavy. >> That is heavy. >> WebAssembly is alternative to that? >> Yes, absolutely. Think of WebAssembly as a tiny little CPU that is a shim, that we can take the places that don't even traditionally have a concept of a processor. So inside the browser, for example, traditionally cloud native development on the backend has been dominated by things like Docker and Docker is a wonderful technology and Container is a wonderful technology that really drove the last 10 years of cloud native with the great lift and shift, if you will. Take our existing applications, package them up in this virtual desktop and then deliver them. But to deliver the next 10 years of experiences, we need solutions that let us have portability first and a security model that's portable across the entire landscape. So this isn't just browsers and servers on the back end, WebAssembly creates an a layer of equality from truly edge to edge. It's can transcend different CPUs, different operating systems. So where containers have this lower bound off you need to be running Linux and you need to be in a place where you're going to bring Kubernetes. WebAssembly is so small and portable, it transcends that lower bound. It can go to places like iOS. It can go to places like web browsers. It can even go to teeny tiny CPUs that don't even traditionally have a full on operating systems inside them. >> Colin: Right, places where you can't run Docker. >> So as I think about that, and I'm a developer and I'm running my back end and I'm running whatever web stack that I want, how does this work? Like, how do I get started with it? >> Well, there's some great stuff Liam already mentioned with WASM cloud and Frmion Spin. Microsoft is heavily involved now on providing cloud products that can take advantage of WebAssembly. So we've got a lot of languages, new languages coming in.net and Ruby, Rust is a big one, TinyGo, really just a lot of places to get involved. A lot of places to get started. >> At the highest level Finton Ryan, when he was at Gartner, he's a really well known analyst. He wrote something profound a few years ago. He said, WebAssembly is the one technology, You don't need a strategy to adopt. >> Mm. >> Because frankly you're already using it because there's so many wonderful experiences and products that are out there, like what Adobe's doing. This virtual CPU is not just a platform to run on cloud native and to build applications towards the edge. You can embed this virtual CPU inside of applications. So cases where you would want to allow your users to customize an application or to extend functionality. Give you an example, Shopify is a big believer in WebAssembly because while their platform covers, two standard deviations or 80% of the use cases, they have a wonderful marketplace of extensions that folks can use in order to customize the checkout process or apply specialized discounts or integrate into a partner ecosystem. So when you think about the requirements for those scenarios, they line up to the same requirements that we have in browsers and servers. I want real security. I want portability. I want reuseability. And ultimately I want to save money and go faster. So organizations everywhere should take a few minutes and do a heads up and think about one, where WebAssembly is already in their environment, inside of places like Envoy and Istio, some of the most popular projects in the cloud native ecosystem, outside of Kubernetes. And they should perhaps consider studying, how WebAssembly can help them to transform the experiences that they're delivering for their customers. This may be the last day of Kubecon, but this is certainly not the last time we're going to be talking about WebAssembly, I'll tell you that. >> So, last question, we've talked a lot about how to get started. How about day two, when I'm thinking about performance troubleshooting and ensuring clients have a great experience what's day two operation like? >> That's a really good question. So there's, I know that each language kind of brings their own tool chain and their, and you know we saw some great stuff on, on WASM day. You can look it up around the .net experience for debugging, They really tried to make it as seamless and the same as it was for native code. So, yeah, I think that's a great question. I mean, right now it's still trying to figure out server side, It's still, as Liam said, a shifting landscape. But we've got some great stuff out here already >> You know, I'd make an even bigger call than that. When I think about the last 20 years as computing has evolved, we've continued to move through these epics of tech that were dominated by a key abstraction. Think about the rise of virtualization with VMware and the transition to the cloud. The rise of containerization, we virtualized to OS. The rise of Kubernetes and CNCF itself, where we virtualize cloud APIs. I firmly believe that WebAssembly represents the next epic of tech. So I think that day two WebAssembly continues to become one of the dominant themes, not only across cloud native but across the entire technical computing landscape. And it represents a fundamentally gigantic opportunity for organizations such as Adobe, that are always market leading and at the cutting edge of tech, to bring new experiences to their customers and for vendors to bring new platforms and tools to companies that want to execute on that opportunity. >> Colin Murphy, Liam Randall, I want to thank you for joining the Cube at Kubecon Cloudnativecon 2022. I'm now having a JavaScript based app that I want to re-look at, and maybe re-platforming that to WebAssembly. It's some lot of good stuff there. We want to thank you for tuning in to our coverage of Kubecon Cloudnativecon. And we want to thank the organization for hosting us, here from Valencia, Spain. I'm Keith Townsend, and you're watching the Cube, the leader in high tech coverage. (bright music)

(gentle melody) >> Welcome back to theCUBE's live coverage of AWS Summit in San Francisco, California. Events are back. AWS Summit in New York City this summer, theCUBE will be there as well. Check us out there. I'm glad to have events back. It's great to have of everyone here. I'm John Furrier, host of theCUBE. Dr. Matt Wood is with me, CUBE alumni, now VP of Business Analytics Division of AWS. Matt, great to see you. >> Thank you, John. It's great to be here. I appreciate it. >> I always call you Dr. Matt Wood because Andy Jackson always says, "Dr. Matt, we would introduce you on the arena." (Matt laughs) >> Matt: The one and only. >> The one and only, Dr. Matt Wood. >> In joke, I love it. (laughs) >> Andy style. (Matt laughs) I think you had walk up music too. >> Yes, we all have our own personalized walk up music. >> So talk about your new role, not a new role, but you're running the analytics business for AWS. What does that consist of right now? >> Sure. So I work. I've got what I consider to be one of the best jobs in the world. I get to work with our customers and the teams at AWS to build the analytics services that millions of our customers use to slice dice, pivot, better understand their data, look at how they can use that data for reporting, looking backwards. And also look at how they can use that data looking forward, so predictive analytics and machine learning. So whether it is slicing and dicing in the lower level of Hadoop and the big data engines, or whether you're doing ETL with Glue, or whether you're visualizing the data in QuickSight or building your models in SageMaker. I got my fingers in a lot of pies. >> One of the benefits of having CUBE coverage with AWS since 2013 is watching the progression. You were on theCUBE that first year we were at Reinvent in 2013, and look at how machine learning just exploded onto the scene. You were involved in that from day one. It's still day one, as you guys say. What's the big thing now? Look at just what happened. Machine learning comes in and then a slew of services come in. You've got SageMaker, became a hot seller right out of the gate. The database stuff was kicking butt. So all this is now booming. That was a real generational change over for database. What's the perspective? What's your perspective on that's evolved? >> I think it's a really good point. I totally agree. I think for machine learning, there's sort of a Renaissance in machine learning and the application of machine learning. Machine learning as a technology has been around for 50 years, let's say. But to do machine learning right, you need like a lot of data. The data needs to be high quality. You need a lot of compute to be able to train those models and you have to be able to evaluate what those models mean as you apply them to real world problems. And so the cloud really removed a lot of the constraints. Finally, customers had all of the data that they needed. We gave them services to be able to label that data in a high quality way. There's all the compute you need to be able to train the models. And so where you go? And so the cloud really enabled this Renaissance with machine learning. And we're seeing honestly a similar Renaissance with data and analytics. If you look back five to ten years, analytics was something you did in batch, your data warehouse ran an analysis to do reconciliation at the end of the month, and that was it. (John laughs) And so that's when you needed it. But today, if your Redshift cluster isn't available, Uber drivers don't turn up, DoorDash deliveries don't get made. Analytics is now central to virtually every business, and it is central to virtually every business's digital transformation. And being able to take that data from a variety of sources, be able to query it with high performance, to be able to actually then start to augment that data with real information, which usually comes from technical experts and domain experts to form wisdom and information from raw data. That's kind of what most organizations are trying to do when they kind of go through this analytics journey. >> It's interesting. Dave Velanta and I always talk on theCUBE about the future. And you look back, the things we're talking about six years ago are actually happening now. And it's not hyped up statement to say digital transformation is actually happening now. And there's also times when we bang our fists on the table saying, say, "I really think this is so important." And David says, "John, you're going to die on that hill." (Matt laughs) And so I'm excited that this year, for the first time, I didn't die on that hill. I've been saying- >> Do all right. >> Data as code is the next infrastructure as code. And Dave's like, "What do you mean by that?" We're talking about how data gets... And it's happening. So we just had an event on our AWS startups.com site, a showcase for startups, and the theme was data as code. And interesting new trends emerging really clearly, the role of a data engineer, right? Like an SRE, what an SRE did for cloud, you have a new data engineering role because of the developer onboarding is massively increasing, exponentially, new developers. Data science scientists are growing, but the pipelining and managing and engineering as a system, almost like an operating system. >> Kind of as a discipline. >> So what's your reaction to that about this data engineer, data as code? Because if you have horizontally scalable data, you've got to be open, that's hard (laughs), okay? And you got to silo the data that needs to be siloed for compliance and reason. So that's a big policy around that. So what's your reaction to data's code and the data engineering phenomenon? >> It's a really good point. I think with any technology project inside of an organization, success with analytics or machine learning, it's kind of 50% technology and then 50% cultural. And you have often domain experts. Those could be physicians or drug design experts, or they could be financial experts or whoever they might be, got deep domain expertise, and then you've got technical implementation teams. And there's kind of a natural, often repulsive force. I don't mean that rudely, but they just don't talk the same language. And so the more complex a domain and the more complex the technology, the stronger their repulsive force. And it can become very difficult for domain experts to work closely with the technical experts to be able to actually get business decisions made. And so what data engineering does and data engineering is, in some cases a team, or it can be a role that you play. It's really allowing those two disciplines to speak the same language. You can think of it as plumbing, but I think of it as like a bridge. It's a bridge between the technical implementation and the domain experts, and that requires a very disparate range of skills. You've got to understand about statistics, you've got to understand about the implementation, you got to understand about the data, you got to understand about the domain. And if you can put all of that together, that data engineering discipline can be incredibly transformative for an organization because it builds the bridge between those two groups. >> I was advising some young computer science students at the sophomore, junior level just a couple of weeks ago, and I told them I would ask someone at Amazon this question. So I'll ask you, >> Matt: Okay. since you've been in the middle of it for years, they were asking me, and I was trying to mentor them on how do you become a data engineer, from a practical standpoint? Courseware, projects to work on, how to think, not just coding Python, because everyone's coding in Python, but what else can they do? So I was trying to help them. I didn't really know the answer myself. I was just trying to kind of help figure it out with them. So what is the answer, in your opinion, or the thoughts around advice to young students who want to be data engineers? Because data scientists is pretty clear on what that is. You use tools, you make visualizations, you manage data, you get answers and insights and then apply that to the business. That's an application. That's not the standing up a stack or managing the infrastructure. So what does that coding look like? What would your advice be to folks getting into a data engineering role? >> Yeah, I think if you believe this, what I said earlier about 50% technology, 50 % culture, the number one technology to learn as a data engineer is the tools in the cloud which allow you to aggregate data from virtually any source into something which is incrementally more valuable for the organization. That's really what data engineering is all about. It's about taking from multiple sources. Some people call them silos, but silos indicates that the storage is kind of fungible or undifferentiated. That's really not the case. Success requires you to have really purpose built, well crafted, high performance, low cost engines for all of your data. So understanding those tools and understanding how to use them, that's probably the most important technical piece. Python and programming and statistics go along with that, I think. And then the most important cultural part, I think is... It's just curiosity. You want to be able to, as a data engineer, you want to have a natural curiosity that drives you to seek the truth inside an organization, seek the truth of a particular problem, and to be able to engage because probably you're going to some choice as you go through your career about which domain you end up in. Maybe you're really passionate about healthcare, or you're really just passionate about transportation or media, whatever it might be. And you can allow that to drive a certain amount of curiosity. But within those roles, the domains are so broad you kind of got to allow your curiosity to develop and lead you to ask the right questions and engage in the right way with your teams, because you can have all the technical skills in the world. But if you're not able to help the team's truth seek through that curiosity, you simply won't be successful. >> We just had a guest, 20 year old founder, Johnny Dallas who was 16 when he worked at Amazon. Youngest engineer- >> Johnny Dallas is a great name, by the way. (both chuckle) >> It's his real name. It sounds like a football player. >> That's awesome. >> Rock star. Johnny CUBE, it's me. But he's young and he was saying... His advice was just do projects. >> Matt: And get hands on. Yeah. >> And I was saying, hey, I came from the old days where you get to stand stuff up and you hugged on for the assets because you didn't want to kill the project because you spent all this money. And he's like, yeah, with cloud you can shut it down. If you do a project that's not working and you get bad data no one's adopting it or you don't like it anymore, you shut it down, just something else. >> Yeah, totally. >> Instantly abandon it and move on to something new. That's a progression. >> Totally! The blast radius of decisions is just way reduced. We talk a lot about in the old world, trying to find the resources and get the funding is like, all right, I want to try out this kind of random idea that could be a big deal for the organization. I need $50 million and a new data center. You're not going to get anywhere. >> And you do a proposal, working backwards, documents all kinds of stuff. >> All that sort of stuff. >> Jump your hoops. >> So all of that is gone. But we sometimes forget that a big part of that is just the prototyping and the experimentation and the limited blast radius in terms of cost, and honestly, the most important thing is time, just being able to jump in there, fingers on keyboards, just try this stuff out. And that's why at AWS, we have... Part of the reason we have so many services, because we want, when you get into AWS, we want the whole toolbox to be available to every developer. And so as your ideas develop, you may want to jump from data that you have that's already in a database to doing realtime data. And then you have the tools there. And when you want to get into real time data, you don't just have kinesis, you have real time analytics, and you can run SQL against that data. The capabilities and the breadth really matter when it comes to prototyping. >> That's the culture piece, because what was once a dysfunctional behavior. I'm going to go off the reservation and try something behind my boss' back, now is a side hustle or fun project. So for fun, you can just code something. >> Yeah, totally. I remember my first Hadoop projects. I found almost literally a decommissioned set of servers in the data center that no one was using. They were super old. They're about to be literally turned off. And I managed to convince the team to leave them on for me for another month. And I installed Hadoop on them and got them going. That just seems crazy to me now that I had to go and convince anybody not to turn these servers off. But what it was like when you- >> That's when you came up with Elastic MapReduce because you said this is too hard, we got to make it easier. >> Basically yes. (John laughs) I was installing Hadoop version Beta 9.9 or whatever. It was like, this is really hard. >> We got to make it simpler. All right, good stuff. I love the walk down memory Lane. And also your advice. Great stuff. I think culture is huge. That's why I like Adam's keynote at Reinvent, Adam Selipsky talk about Pathfinders and trailblazers, because that's a blast radius impact when you can actually have innovation organically just come from anywhere. That's totally cool. >> Matt: Totally cool. >> All right, let's get into the product. Serverless has been hot. We hear a lot of EKS is hot. Containers are booming. Kubernetes is getting adopted, still a lot of work to do there. Cloud native developers are booming. Serverless, Lambda. How does that impact the analytics piece? Can you share the hot products around how that translates? >> Absolutely, yeah. >> Aurora, SageMaker. >> Yeah, I think it's... If you look at kind of the evolution and what customers are asking for, they don't just want low cost. They don't just want this broad set of services. They don't just want those services to have deep capabilities. They want those services to have as low an operating cost over time as possible. So we kind of really got it down. We got built a lot of muscle, a lot of services about getting up and running and experimenting and prototyping and turning things off and turning them on and turning them off. And that's all great. But actually, you really only in most projects start something once and then stop something once, and maybe there's an hour in between or maybe there's a year. But the real expense in terms of time and operations and complexity is sometimes in that running cost. And so we've heard very loudly and clearly from customers that running cost is just undifferentiated to them. And they want to spend more time on their work. And in analytics, that is slicing the data, pivoting the data, combining the data, labeling the data, training their models, running inference against their models, and less time doing the operational pieces. >> Is that why the service focuses there? >> Yeah, absolutely. It dramatically reduces the skill required to run these workloads of any scale. And it dramatically reduces the undifferentiated heavy lifting because you get to focus more of the time that you would have spent on the operations on the actual work that you want to get done. And so if you look at something just like Redshift Serverless, that we launched a Reinvent, we have a lot of customers that want to run the cluster, and they want to get into the weeds where there is benefit. We have a lot of customers that say there's no benefit for me, I just want to do the analytics. So you run the operational piece, you're the experts. We run 60 million instant startups every single day. We do this a lot. >> John: Exactly. We understand the operations- >> I just want the answers. Come on. >> So just give me the answers or just give me the notebook or just give me the inference prediction. Today, for example, we announced Serverless Inference. So now once you've trained your machine learning model, just run a few lines of code or you just click a few buttons and then you got an inference endpoint that you do not have to manage. And whether you're doing one query against that end point per hour or you're doing 10 million, we'll just scale it on the back end. I know we got not a lot of time left, but I want to get your reaction on this. One of the things about the data lakes not being data swamps has been, from what I've been reporting and hearing from customers, is that they want to retrain their machine learning algorithm. They need that data, they need the real time data, and they need the time series data. Even though the time has passed, they got to store in the data lake. So now the data lake's main function is being reusing the data to actually retrain. It works properly. So a lot of post mortems turn into actually business improvements to make the machine learnings smarter, faster. Do you see that same way? Do you see it the same way? >> Yeah, I think it's really interesting >> Or is that just... >> No, I think it's totally interesting because it's convenient to kind of think of analytics as a very clear progression from point A to point B. But really, you're navigating terrain for which you do not have a map, and you need a lot of help to navigate that terrain. And so having these services in place, not having to run the operations of those services, being able to have those services be secure and well governed. And we added PII detection today. It's something you can do automatically, to be able to use any unstructured data, run queries against that unstructured data. So today we added text queries. So you can just say, well, you can scan a badge, for example, and say, well, what's the name on this badge? And you don't have to identify where it is. We'll do all of that work for you. It's more like a branch than it is just a normal A to B path, a linear path. And that includes loops backwards. And sometimes you've got to get the results and use those to make improvements further upstream. And sometimes you've got to use those... And when you're downstream, it will be like, "Ah, I remember that." And you come back and bring it all together. >> Awesome. >> So it's a wonderful world for sure. >> Dr. Matt, we're here in theCUBE. Just take the last word and give the update while you're here what's the big news happening that you're announcing here at Summit in San Francisco, California, and update on the business analytics group. >> Yeah, we did a lot of announcements in the keynote. I encourage everyone to take a look at, that this morning with Swami. One of the ones I'm most excited about is the opportunity to be able to take dashboards, visualizations. We're all used to using these things. We see them in our business intelligence tools, all over the place. However, what we've heard from customers is like, yes, I want those analytics, I want that visualization, I want it to be up to date, but I don't actually want to have to go from my tools where I'm actually doing my work to another separate tool to be able to look at that information. And so today we announced 1-click public embedding for QuickSight dashboard. So today you can literally as easily as embedding a YouTube video, you can take a dashboard that you've built inside QuickSight, cut and paste the HTML, paste it into your application and that's it. That's what you have to do. It takes seconds. >> And it gets updated in real time. >> Updated in real time. It's interactive. You can do everything that you would normally do. You can brand it, there's no power by QuickSight button or anything like that. You can change the colors, fit in perfectly with your application. So that's an incredibly powerful way of being able to take an analytics capability that today sits inside its own little fiefdom and put it just everywhere. Very transformative. >> Awesome. And the business is going well. You got the Serverless detail win for you there. Good stuff. Dr. Matt Wood, thank you for coming on theCUBE. >> Anytime. Thank you. >> Okay, this is theCUBE's coverage of AWS Summit 2022 in San Francisco, California. I'm John Furrier, host of theCUBE. Stay with us for more coverage of day two after this short break. (gentle music)

>>from around the globe. It's the Cube presenting Cuban cloud brought >>to you by silicon angle. Okay, we're back. Here. Live Cuban Cloud. And this is Dave. Want with my co host, John Ferrier Were all remote. We're getting into the analyst power half hour. Really pleased to have Maribel Lopez here. She's the principal and founder of Lopez Research and Zias Caraballo, who is the principal and founder of ZK research. Guys, great to see you. Let's get into it. How you doing? >>Great. How you been? Good, >>thanks. Really good. John's hanging in there quarantining and, uh, all healthy, So I hope you guys are too. Hey, Mary, But let's start with you. You know, here we are on 2021 you know, just exited one of the strangest years, if not the strangest year of our lives. But looking back in the past decade of cloud and we're looking forward. How do you see that? Where do we come from? Where we at and where we going >>When we obviously started with the whole let's build a public cloud and everything was about public cloud. Uh, then we went thio the notion of private cloud than we had hybrid cloud and multi cloud. So we've done a lot of different clouds right now. And I think where we are today is that there's a healthy recognition on the cloud computing providers that you need to give it to the customers the way they want it, not the way you've decided to build it. So how do you meet them where they are so that they can have a cloud like experience wherever they want their data to be? >>Yes and yes, you've, you know, observed, This is well, in the early days of cloud, you heard a lot of rhetoric. It was private cloud And and then now we're, you know, hearing a lot of multi cloud and so forth. But initially, a lot of the traditional vendors kind of pooh poohed it. They called us analysts. We said we were all cloud crazy, but they seem to have got their religion. >>Well, everything. Everyone's got a definition of cloud, but I actually think we are right in the midst of another transformation of clouds Miracle talked about. We went from, you know, private clouds, which is really hosting the public cloud to multi cloud hybrid cloud. And if you look at the last post that put on Silicon Angle, which was talking about five acquisition of Volterra, I actually think we're in the midst of the transition to what's called distributed Club, where if you look at modernized cloud apps today, they're actually made up of services from different clouds on also distributed edge locations. And that's gonna have a pretty profound impact on the way we build out, because those distributed edges be a telco edge, cellular vagina. Th whatever the services that lived there are much more ephemeral in nature, right? So the way we secure the way we connect changes quite a bit. But I think that the great thing about Cloud is we've seen several several evolutionary changes. So what the definition is and we're going through that now, which is which is pretty cool to think about, right? It's not a static thing. Um, it's, uh, you know, it's a it's an ongoing transition. But I think, uh, you know, we're moving into this distributed Cloudera, which to me is a lot more complex than what we're dealing with in the Palace. >>I'm actually pretty excited about that because I think that this move toe edge and the distribution that you've talked about, it's like we now have processing everywhere. We've got it on devices, we've got it in, cars were moving, the data centers closer and closer to where the action's happening. And I think that's gonna be a huge trend for 2021. Is that distributed that you were talking about a lot of edge discussion? You >>know what? The >>reason we're doing This, too, is we want. It's not just we're moving the data closer to the user, right? And some. If you think you brought up the autonomous vehicle right in the car being an edge, you think of the data that generates right? There's some things such as the decision to stop or not right that should be done in car. I don't wanna transport that data all the way back to Google him back to decide whether I want to stop. You could also use the same data determine whether drivers driving safely for insurance purposes, right? So the same data give me located at the edge or in a centralized cloud for different purposes, and I think that's what you know, kind of cool about this is we're being able to use our data and much different ways. Now. >>You know, it's interesting is it's so complex. It's mind blowing because this is distributed computing. Everyone kind of agrees this is where it is. But if you think about the complexity and I want to get your guys reaction to this because you know some of the like side fringe trend discussions are data sovereignty, misinformation as a vulnerability. Okay, you get the chips now you got gravitas on with Amazon in front. Apple's got their own chips. Intel is gonna do a whole new direction. So you've got tons of computer. And then you mentioned the ephemeral nature. How do you manage those? What's the observe ability look like? They're what's the trust equation? So all these things kind of play into it. It sounds almost mind blowing, just even thinking about it. But how do you guys, this analyst tryto understand where someone's either blowing bullshit or kind of like has the real deal? Because all those things come into play? I mean, you could have a misinformation campaign targeting the car. Let's say Hey, you know that that data is needs to be. This is this is misinformation who's a >>in a lot of ways, this creates almost unprecedented opportunity now for for starts and for companies to transform right. The fundamental tenet of my research has always been share shifts happen when markets transition and we're in the middle of the big one. If the computer resource is we're using, John and the application resource will be using or ephemeral nature than all the things that surrounded the way we secured the way we connect. Those also have to be equal, equally agile, right, So you can't have, you know, you think of a micro services based application being secured with traditional firewalls, right? Just the amount of, or even virtual the way that the length of time it takes to spend those things up is way too long. So in many ways, this distributed cloud change changes everything in I T. And that that includes all of the services in the the infrastructure that we used to secure and connect. And that's a that is a profound change, and you mentioned the observe ability. You're right. That's another thing that the traditional observe ability tools are based on static maps and things and, you know, traditional up, down and we don't. Things go up and down so quickly now that that that those don't make any sense. So I think we are going to see quite a rise in different types of management tools and the way they look at things to be much more. I suppose you know Angela also So we can measure things that currently aren't measurable. >>So you're talking about the entire stack. Really? Changing is really what you're inferring anyway from your commentary. And that would include the programming model as well, wouldn't it? >>Absolutely. Yeah. You know, the thing that is really interesting about where we have been versus where we're going is we spent a lot of time talking about virtual izing hardware and moving that around. And what does that look like? And that, and creating that is more of a software paradigm. And the thing we're talking about now is what is cloud is an operating model look like? What is the manageability of that? What is the security of that? What? You know, we've talked a lot about containers and moving into a different you know, Dev suck ups and all those different trends that we've been talking about, like now we're doing them. So we've only got into the first crank of that. And I think every technology vendor we talked to now has to address how are they going to do a highly distributed management and security landscape? Like, what are they gonna layer on top of that? Because it's not just about Oh, I've taken Iraq of something server storage, compute and virtualized it. I now have to create a new operating model around it. In a way, we're almost redoing what the OS I stack looks like and what the software and solutions are for that. >>So >>it was really Hold on, hold on, hold on their lengthened. Because that side stack that came up earlier today, Mayor. But we're talking about Yeah, we were riffing on the OSC model, but back in the day and we were comparing the S n a definite the, you know, the proprietary protocol stacks that they were out there and someone >>said Amazon's S N a. Is that recall? E think that's what you said? >>No, no. Someone in the chest. That's a comment like Amazon's proprietary meaning, their scale. And I said, Oh, that means there s n a But if you think about it, that's kind of almost that can hang. Hang together. If the kubernetes is like a new connective tissue, is that the TCP pipe moment? Because I think Os I kind of was standardizing at the lower end of the stack Ethernet token ring. You know, the data link layer physical layer and that when you got to the TCP layer and really magic happened right to me, that's when Cisco's happened and everything started happening then and then. It kind of stopped because the application is kinda maintain their peace there. A little history there, but like that's kind of happening now. If you think about it and then you put me a factor in the edge, it just kind of really explodes it. So who's gonna write that software? E >>think you know, Dave, your your dad doesn't change what you build ups. It's already changed in the consumer world, you look atyou, no uber and Waze and things like that. Those absolute already highly decomposed applications that make a P I calls and DNS calls from dozens of different resource is already right. We just haven't really brought that into the enterprise space. There's a number, you know, what kind of you know knew were born in the cloud companies that have that have done that. But they're they're very few and far between today. And John, your point about the connectivity. We do need to think about connectivity at the network layer. Still, obviously, But now we're creating that standardization that standardized connectivity all the way a player seven. So you look at a lot of the, you know, one of the big things that was a PDP. I calls right, you know, from different cloud services. And so we do need to standardize in every layer and then stitch that together. So that does make It does make things a lot more complicated. Now I'm not saying Don't do it because you can do a whole lot more with absolute than you could ever do before. It's just that we kind of cranked up the level of complexity here, and flowered isn't just a single thing anymore, right? That's that. That's what we're talking about here It's a collection of edges and private clouds and public clouds. They all have to be stitched together at every layer in orderto work. >>So I was I was talking a few CEOs earlier in the day. We had we had them on, I was asking them. Okay, So how do you How do you approach this complexity? Do you build that abstraction layer? Do you rely on someone like Microsoft to build that abstraction layer? Doesn't appear that Amazon's gonna do it, you know? Where does that come from? Or is it or is it dozens of abstraction layers? And one of the CEO said, Look, it's on us. We have to figure out, you know, we get this a p I economy, but But you guys were talking about a mawr complicated environment, uh, moving so so fast. Eso if if my enterprise looks like my my iPhone APs. Yes, maybe it's simpler on an individual at basis, but its app creep and my application portfolio grows. Maybe they talk to each other a little bit better. But that level of complexity is something that that that users are gonna have to deal >>with what you thought. So I think quite what Zs was trying to get it and correct me if I'm wrong. Zia's right. We've got to the part where we've broken down what was a traditional application, right? And now we've gotten into a P. I calls, and we have to think about different things. Like we have to think about how we secure those a p I s right. That becomes a new criteria that we're looking at. How do we manage them? How do they have a life cycle? So what was the life cycle of, say, an application is now the life cycle of components and so that's a That's a pretty complex thing. So it's not so much that you're getting app creep, but you're definitely rethinking how you want to design your applications and services and some of those you're gonna do yourself and a lot of them are going to say it's too complicated. I'm just going to go to some kind of SAS cloud offering for that and let it go. But I think that many of the larger companies I speak to are looking for a larger company to help them build some kind of framework to migrate from what they've used with them to what they need tohave going forward. >>Yeah, I think. Where the complexities. John, You asked who who creates the normalization layer? You know, obviously, if you look to the cloud providers A W s does a great job of stitching together all things AWS and Microsoft does a great job of stitching together all things Microsoft right in saying with Google. >>But >>then they don't. But if if I want to do some Microsoft to Amazon or Google Toe Microsoft, you know, connectivity, they don't help so much of that. And that's where the third party vendors that you know aviatrix on the network side will tear of the security side of companies like that. Even Cisco's been doing a lot of work with those companies, and so what we what we don't really have And we probably won't for a while if somebody is gonna stitch everything together at every >>you >>know, at every layer. So Andi and I do think we do get after it. Maribel, I think if you look at the world of consumer APS, we moved to a lot more kind of purpose built almost throwaway apps. They serve a purpose or to use them for a while. Then you stop using them. And in the enterprise space, we really haven't kind of converted to them modeling on the mobile side. But I think that's coming. Well, >>I think with micro APS, right, that that was kind of the issue with micro APS. It's like, Oh, I'm not gonna build a full scale out that's gonna take too long. I'm just gonna create this little workflow, and we're gonna have, like, 200 work flows on someone's phone. And I think we did that. And not everybody did it, though, to your point. So I do think that some people that are a little late to the game might end up in in that app creep. But, hey, listen, this is a fabulous opportunity that just, you know, throw a lot of stuff out and do it differently. What What? I think what I hear people struggling with ah lot is be to get it to work. It typically is something that is more vertically integrated. So are you buying all into a Microsoft all you're buying all into an Amazon and people are starting to get a little fear about doing the full scale buy into any specific platform yet. In absence of that, they can't get anything to work. >>Yeah, So I think again what? What I'm hearing from from practitioners, I'm gonna put a micro serve. And I think I think, uh, Mirabelle, this is what you're implying. I'm gonna put a micro services layer. Oh, my, my. If I can't get rid of them, If I can't get rid of my oracle, you know, workloads. I'm gonna connect them to my modernize them with a layer, and I'm gonna impart build that. I'm gonna, you know, partner to get that done. But that seems to be a a critical path forward. If I don't take that step, gonna be stuck in the path in the past and not be able to move forward. >>Yeah, absolutely. I mean, you do have to bridge to the past. You you aren't gonna throw everything out right away. That's just you can't. You can't drive the bus and take the wheels off that the same time. Maybe one wheel, but not all four of them at the same time. So I think that this this concept of what are the technologies and services that you use to make sure you can keep operational, but that you're not just putting on Lee new workloads into the cloud or new workloads as decomposed APS that you're really starting to think about. What do I want to keep in whatever I want to get rid of many of the companies you speak Thio. They have thousands of applications. So are they going to do this for thousands of applications? Are they gonna take this as an opportunity to streamline? Yeah, >>well, a lot of legacy never goes away, right? And I was how companies make this transition is gonna be interesting because there's no there's no really the fact away I was I was talking to this one company. This is New York Bank, and they've broken their I t division down into modern I t and legacy I t. And so modern. Everything is cloud first. And so imagine me, the CEO of Legacy i e 02 miracles. But what they're doing, if they're driving the old bus >>and >>then they're building a new bus and parallel and eventually, you know, slowly they take seats out of the old bus and they take, you know, the seat and and they eventually start stripping away things. That old bus, >>But >>that old bus is going to keep running for a long time. And so stitching the those different worlds together is where a lot of especially big organizations that really can't commit to everything in the cloud are gonna struggle. But it is a It is a whole new world. And like I said, I think it creates so much opportunity for people. You know, e >>whole bus thing reminds me that movie speed when they drive around 55 miles an hour, just put it out to the airport and just blew up E >>got But you know, we all we all say that things were going to go away. But to Zia's point, you know, nothing goes away. We're still in 2021 talking about mainframes just as an aside, right? So I think we're going to continue tohave some legacy in the network. But the But the issue is ah, lot will change around that, and they're gonna be some people. They're gonna make a lot of money selling little startups that Just do one specific piece of that. You know, we just automation of X. Oh, >>yeah, that's a great vertical thing. This is the This is the distributed network argument, right? If you have a note in the network and you could put a containerized environment around it with some micro services um, connective tissue glue layer, if you will software abstract away some integration points, it's a note on the network. So if in mainframe or whatever, it's just I mean makes the argument right, it's not core. You're not building a platform around the mainframe, but if it's punching out, I bank jobs from IBM kicks or something, you know, whatever, Right? So >>And if those were those workloads probably aren't gonna move anywhere, right, they're not. Is there a point in putting those in the cloud? You could say Just leave them where they are. Put a connection to the past Bridge. >>Remember that bank when you talk about bank guy we interviewed in the off the record after the Cube interviews like, Yeah, I'm still running the mainframe, so I never get rid of. I love it. Run our kicks job. I would never think about moving that thing. >>There was a large, large non US bank who said I buy. I buy the next IBM mainframe sight unseen. Andi, he's got no choice. They just write the check. >>But milliseconds is like millions of dollars of millisecond for him on his back, >>so those aren't going anywhere. But then, but then, but they're not growing right. It's just static. >>No, no, that markets not growing its's, in fact. But you could make a lot of money and monetizing the legacy, right? So there are vendors that will do that. But I do think if you look at the well, we've already seen a pretty big transition here. If you look at the growth in a company like twilio, right, that it obviates the need for a company to rack and stack your own phone system to be able to do, um, you know, calling from mobile lapse or even messaging. Now you just do a P. I calls. Um, you know, it allows in a lot of ways that this new world we live in democratizes development, and so any you know, two people in the garage can start up a company and have a service up and running another time at all, and that creates competitiveness. You know much more competitiveness than we've ever had before, which is good for the entire industry. And, you know, because that keeps the bigger companies on their toes and they're always looking over their shoulder. You know what, the banks you're looking at? The venues and companies like that Brian figure out a way to monetize. So I think what we're, you know well, that old stuff never going away. The new stuff is where the competitive screen competitiveness screen. >>It's interesting. Um IDs Avery. Earlier today, I was talking about no code in loco development, how it's different from the old four g l days where we didn't actually expand the base of developers. Now we are to your point is really is democratizing and, >>well, everybody's a developer. It could be a developer, right? A lot of these tools were written in a way that line of business people create their own APs to point and click interface is, and so the barrier. It reminds me of when, when I started my career, I was a I. I used to code and HTML build websites and then went to five years. People using drag and drop interface is right, so that that kind of job went away because it became so easy to dio. >>Yeah, >>sorry. A >>data e was going to say, I think we're getting to the part. We're just starting to talk about data, right? So, you know, when you think of twilio, that's like a service. It's connecting you to specific data. When you think of Snowflake, you know, there's been all these kinds of companies that have crept up into the landscape to feel like a very specific void. And so now the Now the question is, if it's really all about the data, they're going to be new companies that get built that are just focusing on different aspects of how that data secured, how that data is transferred, how that data. You know what happens to that data, because and and does that shift the balance of power about it being out of like, Oh, I've created these data centers with large recommend stack ums that are virtualized thio. A whole other set of you know this is a big software play. It's all about software. >>Well, we just heard from Jim Octagon e You guys talking earlier about just distributed system. She basically laid down that look. Our data architectures air flawed there monolithic. And data by its very nature is distributed so that she's putting forth the whole new paradigm around distributed decentralized data models, >>which Howie shoe is just talking about. Who's gonna build the visual studio for data, right? So programmatic. Kind of thinking around data >>I didn't >>gathering. We didn't touch on because >>I do think there's >>an opportunity for that for, you know, data governance and data ownership and data transport. But it's also the analytics of it. Most companies don't have the in house, um, you know, data scientists to build on a I algorithms. Right. So you're gonna start seeing, you know, cos pop up to do very specific types of data. I don't know if you saw this morning, um, you know, uniforms bought this company that does, you know, video emotion detection so they could tell on the video whether somebody's paying attention, Not right. And so that's something that it would be eso hard for a company to build that in house. But I think what you're going to see is a rise in these, you know, these types of companies that help with specific types of analytics. And then you drop you pull those in his resource is into your application. And so it's not only the storage and the governance of the data, but also the analytics and the analytics. Frankly, there were a lot of the, uh, differentiation for companies is gonna come from. I know Maribel has written a lot on a I, as have I, and I think that's one of the more exciting areas to look at this year. >>I actually want to rip off your point because I think it's really important because where we left off in 2020 was yes, there was hybrid cloud, but we just started to see the era of the vertical eyes cloud the cloud for something you know, the cloud for finance, the cloud for health care, the telco and edge cloud, right? So when you start doing that, it becomes much more about what is the specialized stream that we're looking at. So what's a specialized analytic stream? What's a specialized security stack stream? Right? So until now, like everything was just trying to get to what I would call horizontal parody where you took the things you had before you replicated them in a new world with, like, some different software, but it was still kind of the same. And now we're saying, OK, let's try Thio. Let's try to move out of everything, just being a generic sort of cloud set of services and being more total cloud services. >>That is the evolution of everything technology, the first movement. Everything doing technology is we try and make the old thing the new thing look like the old thing, right? First PCs was a mainframe emulator. We took our virtual servers and we made them look like physical service, then eventually figure out, Oh, there's a whole bunch of other stuff that I could do then I couldn't do before. And that's the part we're trying to hop into now. Right? Is like, Oh, now that I've gone cloud native, what can I do that I couldn't do before? Right? So we're just we're sort of hitting that inflection point. That's when you're really going to see the growth takeoff. But for whatever reason, and i t. All we ever do is we're trying to replicate the old until we figure out the old didn't really work, and we should do something new. >>Well, let me throw something old and controversial. Controversial old but old old trope out there. Consumerism ation of I t. I mean, if you think about what year was first year you heard that term, was it 15 years ago? 20 years ago. When did that first >>podcast? Yeah, so that was a long time ago >>way. So if you think about it like, it kind of is happening. And what does it mean, right? Come. What does What does that actually mean in today's world Doesn't exist. >>Well, you heard you heard. Like Fred Luddy, whose founder of service now saying that was his dream to bring consumer like experiences to the enterprise will. Well, it didn't really happen. I mean, service not pretty. Pretty complicated compared toa what? We know what we do here, but so it's It's evolving. >>Yeah, I think there's also the enterprise ation of consumer technology that John the companies, you know, you look a zoom. They came to market with a highly consumer facing product, realized it didn't have the security tools, you know, to really be corporate great. And then they had to go invest a bunch of money in that. So, you know, I think that waken swing the pendulum all the way over to the consumer side, but that that kind of failed us, right? So now we're trying to bring it back to center a little bit where we blend the two together. >>Cloud kind of brings that I never looked at that way. That's interesting and surprising of consumer. Yeah, that's >>alright, guys. Hey, we gotta wrap Zs, Maribel. Always a pleasure having you guys on great great insights from the half hour flies by. Thanks so much. We appreciate it. >>Thank >>you guys. >>Alright, keep it right there. Mortgage rate content coming from the Cuban Cloud Day Volonte with John Ferrier and a whole lineup still to come Keep right there.

(upbeat music) >> From ''theCUBE studios,'' in Palo Alto, in Boston, connecting with thought leaders all around the world. This is ''theCUBE Conversation.'' >> Hi, I'm John Walls. And as we're all aware, technology continues to evolve these days at an incredible pace and it's changing the way industries are doing their business all over the world and that's certainly true in telecommunications, CSPs all around the globe are developing plans on how to leverage the power of 5G technology and their network operations are certainly central to that mission. That is the genesis of ''IBM's Cloud for Telecommunications Service.'' That's a unified open hybrid architecture, that was recently launched and was developed to provide telecoms with the solutions they need to meet their very unique network demands and needs. I want us to talk more about that. I'm joined by Steve Canepa, who is the Global GM and Managing Director of the communication sector at IBM. Steve, good to see you today. >> Yeah, you too, John. >> And Jeffrey Hammond. So, he's the Principal Analyst and Vice President at Forrester. Jeffrey, thank you for your time as well today. Good to see you. >> Thanks a lot. It's great to be here. >> Yeah, Steve, let's just jump right in. First off, I mean, to me, the overarching question is, why telecom, I know that IBM has been very focused on providing these kinds of industries specific services, you've done very well in finance, now you're shifting over to telecom. What was the driver there? >> First, great to be with you today, John, and, you know, if we look at the marketplace, especially in 2020, I think the one thing that's, everyone can agree with, is that the rate and pace of change is just really accelerating and is a very, very dynamic marketplace. And so, if we look at the way both our personal lives are now guided by connectivity, and the use of multiple devices throughout the day, the same with our professional lives. So, connectivity really sits at the heart of how value and solutions are delivered and for businesses, this is becoming a critical issue. So, as we work with the telecommunication providers around the world, we're helping them transform their business to make it much more agile, to make it open and make them deliver new services much more quickly and to engage digitally with their clients to bring that kind of experience that we all expect now, so, that the rate pace of change, and the need for the telecommunications industry to bring new value, is really driving a tremendous opportunity for us to work with them. >> Jeffrey what's happening in the telecom space? That, I mean, these aren't just small trends, right? These are tectonic shifts that are going on in terms of their new capabilities and their needs. I'm sure this digital transformation has been driven in some part by COVID, but there are other forces going on here, I would assume too. What do you see from your analyst seat? >> Yeah, I look at it, you know, from a glass half full and a glass half empty approach. From a half empty approach, the shifts to remote work and remote learning, and from traditional retail channels, brick and mortar channels to digital ones, have really put a strain on the existing networking infrastructure, especially, at the Edge, but they've also demonstrated just how critical it is to get that right. You know, as an example, I'm actually talking to you today over my hotspot on my iPhone. So, I think a lot more about the performance of my local cell tower now than I ever did a year ago. and I want it to be as good as it can possibly be and give me as many capabilities as it can. From a glass half full perspective, the opportunities that a modernized network infrastructure gives us are, I think, more readily apparent than ever, you know, most of my wife's doctor's appointments have shifted to remote appointments and every time she calls up to connect, I kind of cringe in the other room and it's like, are they going to get video working? Are they going to get audio working? Are they actually going to have to shift to an old-style phone call to make this happen? Well, things like 5G really are poised to solve those kinds of challenges. They promise, 5G promises, exponential improvements in connectivity speed, capacity, and reductions in latency that are going to allow us to look at some really interesting workloads, IOT workloads, automation workloads, and a lot of Edge use cases. I think 5G sets the stage or Edge compute. Expanding Edge compute scenarios, make it possible to distribute data and services where businesses can best optimize their outcomes, whether it's IOT enabled assets, whether it's connected environments, whether it's personalization, whether it's rich content, AI, or even extended reality workloads. So, you might seem like, that's what a little over the horizon, but it's actually not that far away. And as companies gain the ability to manage and analyze and localize their data, and unlocks real-time insights in a way that they just haven't had before, it can drive expanded engagement and automation in close proximity to the end point devices and customers. And none of that happens without the telco providers and the infrastructure that they own being on board and providing the capabilities for developers like me to take advantage of the infrastructure that they've put in place. So, my perspective on it is, that transformation, that digital transformation, is not going to happen on its own. Someone's got to provision the infrastructure, someone's got to write the code, someone's got to get the services as close to my cell tower or to the Edge as possible and so, that's one of the reasons that when we ask decision makers in the telco space about their priorities from a business perspective, what they tell us is, one of their top three priorities is, we need to improve our ability to innovate and the other two are, we need to grow our revenue and we need to improve our product and services. What's going on from a software perspective in the telco space, is set to make all three of those possible, from my perspective. >> You know, Steve, Jeffrey just unpacked an awful lot there, did a really nice job of that. So, let's talk about first off, that telco relationship IBM's had, or has. You work with data, the 10 largest communication service providers in the world, and I'm sure you're on this journey with them, right? They've been telling you about their challenges and you recognize their needs. This is, you have had maybe some specific examples of that dialogue, that has progressed as your relationship has matured and you provide a different service to them. What are they telling you? What did they tell you say, '' This is where we have got to get better. We've got to get a little sharper, a little leaner.'' And then how did IBM respond to that? >> Yeah, I mean, critical to what Jeffrey just shared is under the covers. You know, 5G is going to take five times the cost that 4G took to deploy. So, if you're a telco, you have to get much more efficient. You have to drive a much more effective TCO into cost of deploying and managing and running that network architecture. When the network becomes a software defined platform, it opens up the opportunity to use open source, open technology, and to drive a tremendous ecosystem of innovation that you can then capture that value onto that open software network. And as the Edge emerged as compute and storage and connectivity, both to the Edge as Jeffrey described, then the opportunity to deliver B2B use cases to take advantage of the latency improvements with 5G, take advantage of the bandwidth capabilities that you have moving video and AI out to the Edge, so, you can create insights as a service. These are the underlying transformations that the telcos are making right now to capture this value. And in fact, we have an institute for business value on our website. You can see some of the surveys and analysis we've done but 84% of the telco clients say, you know, '' Improving the automation and the intelligence of this network platform becomes critical.'' So, from our standpoint, we see a tremendous opportunity to create an open architecture to allow the telcos to regain control of their architecture so that they can pick the solutions and services that work best for them to create value for their customers and then allows them to deploy them incredibly quickly. In fact, just this last week, we announced a milestone with Bharti, a project that we're doing in India, already has over 300 million subscribers. We've taken their ability to deploy their run environment, one of the core domains of the network, where you actually do the access over the cell towers. We've improved that from weeks down to a few days. In fact, our objective is to get to a few minutes. Applying that kind of automation dramatically improves the kind of service they can deliver. When we talk about relationships we have with Vodafone, AT$T, Verizon, about working with them on their mobile Edge compute platforms, it will allow them to extend their network. In fact, with our cloud announcement that you highlighted at the top, we announced a capability called the IBM Cloud Satellite and what IBM Cloud Satellite does is, it's built with Red Hat, so, it's open architecture, it takes advantage of the millions and millions of upstream developers, that are developing every single day to build a foundational shift architecture that allows us to deploy these services so quickly and we can move that capability right now to the Edge. What that means for a telco, is they can deploy those services wherever they want to deploy them, on their private infrastructure or on a public cloud, on a customer's premise, that gives them the flexibility. The automation allows them to do it smartly and very quickly and then in partnering with clients, they can create new end Edge services, things like, you know, manufacturing 4.0 you may have heard of or as you mentioned, advanced healthcare services. Every single industry is going to take advantage of these changes and we're really excited about the opportunity to work in combination with the telcos and speed the pace of innovation in the market. >> Jeffrey, I'd like to go back to the Bharti there. I was going to get into it a little bit later but Steve brought it up. This major Indian CSP, as you mentioned, 300 million subs, 400 million around the world. What does that say to you in terms of its commitment and its, the needs that are being addressed and how it's going to fundamentally change the way it is doing business as far as setting the pace in the telecom industry? >> Well, I think, one of the things that highlights it is, you know, this isn't just a U.S phenomenon or a European phenomenon. Indeed, in some cases we're seeing countries outside the U.S in advance, moving faster, Switzerland, as an example. We expect 90% of the population in Germany to be covered by 5G By 2025, we expect 90% of the population in South Korea to be covered by 2026, 160 million connections in in China as well. So, in some ways, what's happening in the telco world is mirroring what has happened in the public cloud world, which is the world's gone flat. And that's great from a developer perspective because that means that I don't have to learn specialized technologies or specialized services, in order to look at these network infrastructure platforms as part of the addressable surface that I have. That's one of the things that I think has always held the larger developer population back and has kept them from taking advantage of the telco networks. Is, they've always been bit of a black box to the vast majority of developers, you know, IP goes in, IP comes out but that's about all the control I have, unless I want to go and dig deep into those, you know, industry specific specifications. I was cleaning out my office last week because I'm in the process of moving and I came across my '' IMS Explained Handbook from 2006,'' and I remember going deep into that because, you know, we were told that that's going to make it so that IT infrastructure and telco infrastructure is going to converge and it did to a little bit, but not in a way that all the developers out there could really take advantage of telco infrastructure. And then I remember the next thing was like, well, '' Java Amiens on the front end with mobile clients, that's going to make everything different and we're going to be able to build apps everywhere.'' What ended up being was we would write once and test everywhere, across all the different devices that we had to support. And you know, what really drove you equity? Was the iPhone and apps that we could use HTML like technology or that we could use Java to build and it exploded. And we got millions of applications on the front end of the network. What I see potentially happening now, is the same thing on the backend infrastructure side, because the reality is for any developer that is trying to build modern applications, that's trying to take advantage of cloud native technologies, things start with containers and specifically, OCI compliant containers. That is the basis for how we think about building services and handing them off to operators to run them for us. And with what's going on here, by building on top of OpenShift, you take that, you know, essentially de facto standard of containers as the way that we communicate on the infrastructure side globally, from a software development perspective and you make that the entry point for developers into the modern telco outcome system. And so, basically, it means that if I want to push all the way out to the Edge and I want to get as close as I possibly can, as long as I can give you a container to execute that capability, I'm well on the way to making that a reality, that's a game changer in my opinion. >> Yeah, I was on. >> Just to pick it, just if I could, just to pick up on that because I think Jeffrey made a really important point. So, it's kind of like, in a way, an auntie to the ball here is this open architecture because it empowers the entire ecosystem and it allows the telcos to take advantage of enormous innovation that's happening in the marketplace. And that's why, you know, the 35 ecosystem partners that we announced when we announced the IBM Cloud for telco, that's why they're so important because it allows you to have choice. But the other piece, which he hinted at, I wanted to just underscore, is today, in it kind of the first wave of cloud, only about 20% of the applications move to cloud. They were mostly funny digital applications. In fact, we moved our funny digital applications as well into Watson, we have over 1.5 billion customers of telcos today around the world that can access Watson, through our various chatbot and call center or an agent assist solutions we've deployed. But the 80% of applications that haven't moved yet, haven't moved because it's tough to move them, because they're mission critical, they need, you know, regulatory controls, they have to have world-class security, they need to be able to provide data sovereignty as you're operating in different countries around the world and you have to make sure that you have the data in places that you need, these are the attributes, that kind of open up the opportunity for all these other workloads to move. And those are the exact kind of capabilities that we've built into the IBM Cloud for telco, so that we can enable telcos to move their applications into this environment safely, securely, and do it, as Jeffrey described, on an open architecture that gives them that agility and flexibility. And we're seeing it happen real time, you know, I'll just give you another quick example, Vodafone India, their CTO has said publicly and moving to this cloud architecture, he sees it as a universal cloud architecture, so, they're going to run not just their internal it workloads, not just their network services, their voice data and multimedia network services workloads, but also their B2B enterprise workloads, as Jeffrey was starting to describe. Those workloads that are going to move out to the Edge. And by being able to run on a common platform, he's said publicly that they're seeing an 80% improvement in their CapEx, a 50% improvement in their OPEX, and then 90% improvement in the cost to get productions and services deployed. So, the ability to embrace this open architecture and to have the underlying capabilities and attributes in a cloud platform that responds to the specific needs of telco and enterprise workloads, we think is a really powerful combination. >> Steve, the ecosystem, Jeffrey, you brought it up as well. So, I'd like, just to give you a moment to talk about that a little bit, not a small point, by any means you have nearly 40 partners lined up in this respect, from a hardware vendor, software vendors, SAS providers. I mean, it's a pretty impressive lineup and what kind of a statement is that in your, from your perspective, that you're making to the marketplace when you bring that kind of breadth and depth, that kind of bench, basically the game? >> From our view, it's exciting, and we're only getting started. I mean, we literally have not made the announcement, just a matter of a couple of months ago, and every day that passes, we have additional partners that see the power in joining this open architecture approach that we've put in place. The reason that it delivers such values for all the players, you know, one of the hallmarks of a platform approach is that for every player that joins the platform, it brings value to all the players on the cloud. So as we build this ecosystem and we take the leverage of the open source community, and we build on the power of OpenShift and containers, as Jeffrey was saying, we're creating momentum in the marketplace and back to my very first point I made, when the market's moving really quickly, you've got to be agile. And to be agile in today's market, you have to infuse automation at scale, you have to infuse security at scale and you have to infuse intelligence at scale. And that's exactly what we can help the telcos do, and do it in partnership with these enterprise clients. Instinctively >> One of the values of that is that, you know, we're seeing the larger trend in the cloud native space of folks that used to build packaged software services, is essentially taking advantage of these architectural capabilities and containerizing their applications as part of their future strategy. I mean, just two weeks ago, Salesforce basically said, we're reinvisioning Salesforce as a set of containerized workloads that we deliver, SAP is going in very much the same direction. So as you think about these business workloads, where you get data coming from the infrastructure and you want to go all the way back to the back office and you want to make sure that data gets updated in your supply chain management system, being able to do that with a consistent architecture makes these integration challenges just an order of magnitude easier. I actually want to drill in on that data point for a minute because I think that that's also key to understanding what's going on here, because, you know, during the early days of the public cloud and even WebDuo before that, one of the things that drove WebDuo was the idea that data is the new Intel inside and in some ways that was around centralized data because we had 40 or 50 years to get all the data into the data centers and into the, and then put it in the public cloud. But that's not what is happening today. So much of the new data is actually originating at the Edge and increasingly it needs to stay at the Edge if for no other reason than to make sure that the folks that are trying to use it well aren't running up huge ingestion costs, trying to move it all back to the public cloud providers, analyze it and then push it back out and do that within the realm of the laws of physics. So, you know, one of the big things that's driving the Edge is, in the move toward the Edge, and the interest in 5G is that allows us to do more with data where the data originates. So, as an example, a manufacturer that I've been working with that basically came across exactly that problem, as they stood up more and more connected devices, they were seeing their data ingestion volume spiking and kind of running ahead of their budgets for data ingestion but they were like, well, we can't just leave this data and discard it at the Edge, because what happens if it turns out to be valuable for the maintenance, preventative maintenance use cases that we want to run, or for the machine wear characteristics that we want to run. So, we need to find a way to get our models out close to the data so we don't have to bring it all back to the core. In retailing, personalization is something that a lot of folks are looking at right now and even clientelling and that's, again, another situation where you want to get the data close to where the customer actually lives from a geographic basis and into the hands of the person that's in the store but you don't want to necessarily have to go and install a lot of complex hardware in the retail outlet because then somebody has to manage, you know, those servers and manage all those capabilities. So, you know, in the case of the retailer that I was working with, what they wanted was to get that capability as close as possible to the store, but no closer. And the idea of essentially a virtual back office that they could stand up whenever they opened up a new retail outlet, or even had a franchisee open up an outlet, was an extremely powerful concept and that's the kind of thing that you can do when you're saying,'' Well it's just a set of containers and if I have a, you know, essentially a control plane that I deploy it to, then I can do that on top of that telco provider that they sign up to be a strategic services provider.'' There are lots of other interesting scenarios, tourism, if you think about, you know, the tourist economies that we have around the world and the data that, you know, mobile devices throw off that let us get anonymized information about who's coming, where they're going, what they're spending, how long they're staying, there's a huge set of data there that you can use to grow revenue. You know, other types of use cases, transportation? We see, you know, municipal governments kind of looking at how they can use anonymized data around commute patterns to impact their planning. That's all data that's coming from the the telco infrastructure. >> You know, when we're talking about these massive advantages, right, as this hybrid cloud approach about skill ones, build one's, easy management, efficient management, all of these things, Steve, I think we almost, we'd be derelict to duty if we didn't talk about security a little bit. Just ultimately at the end of the day, you've got to provide this as you pointed out, world-class secure environment. And so, in terms of the hybrid approach, what kind of considerations do you have to make that are special to that and that are being deployed and have been considered >> You know, that's a great point. One of the benefits to Comms from moving to an open architecture, is that you componentize the framework of that architecture, and you have suppliers supplying applications for the various different services that we just talked through. And the ability then to integrate security is essentially a foundational element to the entire Premack architecture. We've stayed very compliant with the Nanci framework architecture and the way that we've worked with the telcos and bringing forth a solution, because we specifically want them to have the choice but how is that choice being married with the kind of security you just talked about. And to Jeffrey's point, you know, when you move those applications out to the Edge and that data, you know, many of the analysts are saying now by 2025, as much as 75% of the data created in the world will happen at the Edge. So, this is a massive shift. And when that shift occurs, you have to have the security to make sure that you're going to take care of that data in the way that it should be and that meets all regulatory, you know, governance already rules and regulations. So, that becomes really critical. The other piece though, is just the amount of value that gets created. The reason that data is at the Edge is because now you can act on it at the Edge, you can extract insights and in fact, most of the analysts will say,'' In the next three years, we'll see $675 billion of new value created at the Edge with these kinds of applications.'' And going back on the manufacturing example, I mean, we're already working today with manufacturers and they already had, you know, hundreds of IOT sensors deployed in the factory and we have an Edge application manager that extends right out to the far Edge, if you will, right out onto that factory floor to help get intelligence from those devices. But now think about adding to that the AI capabilities, the video capabilities, watching that manufacturing line to make sure every product that comes off that line is absolutely perfect, Watching the employees to make sure they're staying in safety zones, you know, watching the actual equipment itself to make sure it is performing the way it's supposed to, maybe using an analytics and AI capabilities to predict, you know, issues that might arise before they even happen, so you can take preventative action. This kind of intelligence, you know, makes the business run smarter, faster, more effective. So, that's where we see tremendous service. So, it's not just the fact that data will be created and it will be higher fidelity data to include the analytics, AI, you don't include unstructured data like video data and image data, audio data, but the ability to then extract insights and value out of it. And this is why we believe the ecosystem we talked about earlier, our partnership with the telco's and the ability to bring ecosystem partners and they can add value is just a tremendous momentum that we're going to build. >> Well, the market opportunity is certainly great. As you pointed out, a lot of additional value yet to be created, significant value and obviously, a lot of money to be spent as well by telcos, by some estimates, a hundred billion plus, just by the year 2022 and getting this new software defined platforms up and running. So, congratulations to IBM for this launch and we wish you continued success, Steve, in that endeavor and thank you for your time and Jeffrey, thank you as well for your insights from Forester. >> Always a pleasure. (upbeat music)

>> Narrator: From theCUBE Studios in Palo Alto in Boston, connecting with thought leaders all around the world, this is a CUBE conversation. >> Hi, I'm Stu Miniman, the host of Cloud Native Insights. And when we kicked off this program, Cloud Native Insights, we wanted to talk about the innovation and agility that's happening, not just Cloud as a location. We're going to draw down a little bit into one of the very important pieces of a company and that's their websites and their applications, that live in that environment. And of course, that comes from a lot of changes over the years. Any of us that have been in tech for a couple of decades have worked from the early days, to of course today's multimedia globally distributed environment and everyone during the global pandemic, of course, has been (indistinct) straining their use of the internet. So really excited to welcome to the program the two co-founders of Netlify. I have Matt Biilmann, who is the CEO, and his co-founder Christian Bach, who is the president both of Netlify really the company behind Jamstack, which we're going to explain and talk about a bit. Matt and Chris, thank you so much for joining us. >> Thanks for having us. >> Thank you for having us >> All right so, let's start with just some of the basics. I expect that some of our audience is not familiar with Jamstack. You do a quick Google search and it's JavaScript, its APIs, its markup. And you say, okay, I understand what a bunch of that means. But, yeah, if you could give us kind of a compare contrast to what web development was before and how Jamstack's really helping to revolutionize what's happening in this space. >> Yes, so for many years, we built websites and web applications with an application based architecture, where every website or every application would be this monolithic application with typically like a load balancer, a set of web servers, application servers, and that database and every request through a page would go through this whole stack it would pass through the application layer, talk to the database, fetch template, merge data and template, build HTML on the fly and send it back to the user. And basically what we saw happening and what's been happening with the Jamstack is this decoupling of the actual front-end presentation layer of the websites and web applications and then the back-end layer. And the advantages there is that if you can really pre-build the front-end application layer, you can take the actual HTML, or an application shell and distribute it across a globally distributed network, you can get it into the hands of the user's browser very quickly. And then the back end, what we've seen happening there is that it's split up to all these different APIs and services you no longer have your one monolithic back end you have all these different services. Where some of your own but a lot of them are other people's services like Stripe or Twilio or Algolia or Contentful. So we've seen this shift to this architecture, where we're considered in a way that the stack has moved up a little from the old tooling where something like the LAMP stack would be common in really naming the programming language, the specific web server, the Linux server, the operating system, and so on right? And then up to a level where it's really about getting an application into the browser, using JavaScript as the runtime and talking to this whole new economy of APIs and services. >> Yeah, Chris I wonder if you could bring us inside your customers and the companies that you talk to. I think about for the longest time it was, maybe I just outsource my web development, but website is one of those key components that I share my value, I share what's going on, I want to be able to change it pretty often and there's so much more that I can do today than I could have done 10 years ago. We've watched that mark. So, help us understand, what skill sets do people need to have? what type of companies are using Jamstack? And, bring in if you can, Netlify. How is this a business and not just, an open source standards movement, that's helping to revolutionize what's happening? >> Absolutely, I mean, First of all, people using this and companies use this is extremely wide. Wide vertical, right? Its very horizontal. This is anyone with a digital property basically, right? I think what we've seen all the time is that, that we have a lot more channels than we used to have, right? So we started off just maybe having the one dot com, right? With limited functionality. And today, you have a multiple channels, right? You have the landing pages, you have the domains, you have lots of activities online. You have mobile apps and commerce is often a big part of it, and I would say especially the last few months, there's a lot of people that had the digital convergence points as one of many. And now it's the only ones, right? So I think it's become extremely important. I also think that when you look at your web infrastructure in general, it has been very complex, right? And you need a lot of different people, right? And you need to maintain staging environments, production lines, development environments. You need to, have a wide set of skills to maintain these things, right? And if a web developer wanted to do a lot of things, right? They have to go and tap DevOps and so on on the shoulder, right? And I think what the Jamstack is about saying, hey, you can get so much further as a web developer. Now, if you take the modern built tools, you can take the Git workflows, and you wrap around the browser that has become a full-fledged operating system and the API economy as Matt was just talking about. You have these workflows, or you potentially have these workflows, where you can get so much further, right? And that's very much Netlify submission. So Netlify saw this opportunity of decoupling the front end from the back end of the building from the hosting of creating an approach to making websites that would be many times faster, 'cause you have multiple points of origin and you don't feel fredurous. It's many times safer. There's not that huge surface area of attack. It's much more scalable, and so on. It was sort of a win-win-win. But the problem was, there was no viable workflow. If you take a traditional CDN, and you put it in, it doesn't matter really, if it's one or the other. As good as they (indistinct) services, they're all meant to sit in front of an origin, right? They're meant to buffer something. And if you have the gems, there's no origin in that way, right? The network in itself has to be an origin so it has to be architectured quite differently. And then there's a lot of things around CDCI and how you server lists and so on. That all had to be sort of re-merged . And Netlify is that glue, it is that platform that takes you from local development all the way out to edge nodes. But allows you to mix and match any tool. So it's not program independent. So you can say, well, we use a build tool, and that's PHP or Ruby or JavaScript, the react or Next or whatever it might be, right? And we use these APIs for this server, for this property. Over here we have a commerce site. Over here, we have a dotcom, that needs a huge enterprise CMS with tons of stakeholders. But the thing is that all of those now becomes something that plugs into your website. Rather than have to drive the website itself. And that's sort of frees up the silos. So when we see people using Netlify, we have companies using Netlify. Big Fitness Company, for example, that own fitness company that uses us for developer documentation, or their marketing sites, but also for their dotcom. But even if you go to the equipment that people have at home, and you log in, that's actually using some very nifty identity and remote based access control for Netlify and if you watch the video there, it's also going through a Netlify player, all right? We have fast food chains that has their dotcom and their marketing sites, but also the kiosks down in the store like the menus, the screens there. Rather than being an old Windows NT server running some .NET application in a dusty corner, why not have it like that? And so, both the category but also Netlify sort of brings in a solution and because it's decoupled from all those architectural choices, that means that you can now use the solution in a much, much wider setting. And we were sort of first to market doing this. They get serverless approach where you just push your serverless functions to get better Netlify. First Feature Deploy Previews Were invented by us and so on. So the Jamstack is an extremely wide fundamental architectural approach that matches basically anyone that wants to build web properties. Netlify is the segnostic wide platform that just makes it possible. >> Yeah, good Chris actually, I saw the Peloton use case up on the website and you're right, a very different experience rather than I bring my device, is it synced? Does it work with it? Really integrates those solutions. And you just brought up serverless, which is actually how I got connected to talk in Netlify. So, Matt, sorry, I think you wanted to jump in there but I was wondering if you could help us. I've looked at serverless and what the promise of serverless of course, is that I don't need to think about that underlying infrastructure. I just like developers build our applications. Well, feels like that's really the same mission that you have. And they're serverless is a piece of your story. So, maybe explain (indistinct) that out a little for us. >> Absolutely, I think it ties in, right? Basically, what we saw just from a architectural perspective was this approach of really decoupling front end and back end and so on and working in a new way that gave a lot of benefits to the inducers in performance and security and so on right? But on the other hand, early on, what we saw was that to adopt that approach, like developers had to deal with lot of different moving pieces like CICD, CDN. What to do about the API endpoints that didn't need to be dynamic, and so on. And as Netlify, what we saw was that we could give one intro and workflow for all of this and make it extremely easy for developers to work with this thing. And serverless plays a really important piece there, right? Because when Amazon pioneered AWS Lambda and took it to the world, right? I think the promise also for the front-end web developers of being able to simply write code and then not have to worry at all about where is it actually running? How are we scaling it? How are we operating it and so on, right? That's a really powerful promise, right? But at the same time, in the same way, what we saw earlier on was that for a front-end team to actually adopt serverless functions as part of the Jamstack, it introduced another level of complexity of now having to manage your serverless functions independent from your front end figuring out API Gateway endpoints for every one of them. And how about deployment pipeline for your functions layer versus deployment pipelines for the actual front end layer that's supposed to talk to those front ends. How about staging environments versus to production environments? How do you manage all that, right? So we saw that there was this inherent incredible potential, but also a lot of complexity, right? And as Netlify we saw that if we could give front end developers a web developers in general, an ene-to-end workflow, where they can work both with the front-end framework, write the code that will get deployed into the browser, but also just have a folder where they can write this serverless functions and then know that Netlify will take care of all of the wiring, right? When you open a pull request and get with new function we'll give you a URL on our globally distributed CDN where you can view both the whole front end, but also the function and sidestep sort of all of the complexities of linking together API Gateways, to functions of managing CICD pipelines and test environments and so on. And in the end, the serverless functions starts becoming a really important part of this Jamstack approach, right? Because you have this world where you have a front end that's often talking to many different APIs and services where again, some of your own and some other people's services. But really often you need some place to glue those together or to build your own custom API endpoint that talks to a couple of them and it has access to server site secrets and so on, right? And this idea of not having to suddenly operate and manage a whole set of servers and infrastructure just for that part of it, but simply just writing the code and then knowing, that you don't have to worry about the operation scalability or anything around that code. That's a really powerful paradigm. >> Yeah, that's one of the real challenges of the Cloud as you talk about the Paradox of Choice. There's so many ways to do things. Not necessarily... It's simple anybody... I was a blogger for many years and it was like, well, I'll just use the self-hosted WordPress, because I don't want to have to worry about that piece of it. Matt, I watched it you did a presentation talking about if I wanted to do WordPress hosted in a AWS that absolutely is not simple. I heard a podcast from one of your board members, Tom Preston Werner, talking about we need to be more opinionated. We need to be able to give more guidance to developers, maybe Chris if you could, how are we when the proliferation of choice, keeps increasing, making sure that people can... How do I make that decision tree? And how do we try to keep it simple? >> Absolutely, I mean, and I actually think that, that's a super relevant question, because you have a lot of choice as a web developer today. Front-end developers used to cut out Photoshop files and turn them into HTML, right? Now with the new advanced markup, and they have all these frameworks and flavors of JavaScript to choose between and there's these powerful build tools, And all those workflows and the browser can do everything you can imagine, right? And so yeah, there is a lot of choice out there, right? And I think, for Netlify what's extremely important is that we are opinionated in the right places. And so when it comes to, for example, a front-end tool and built tools and these things that web developers often face with having to choose between. Our role is to make it as simple as possible to use any of them. But also give you the opportunity of saying, well, this new paradigm allows you to actually mix and match, right? It allows you to use this tool for this property and this tool for this property and gives you a ton of flexibility. But still, come under one roof of a platform like Netlify. And I think that is very powerful. And so we also don't want to choose for you, we want to inform your choices and we want to make it as easy as possible to go and say, hey, these are my needs, what direction should I be going? And of course, we work with enterprise clients, so on migration services, and so on, right? And where we help them a lot with that. But if we locked down on a single flavor, or a single bill tool or a single front end framework, then we also limit the application of what we bring to market and we want to remain a little more open-ended there. But I think there's a lot complexity, a platform like Netlify is all about simplification. So all that wiring that Matt just mentioned, that at least goes, right? You don't spend hours configuring bondage caching and trying to find those edge cases, it just works. And that's a huge game changer for a lot of people, right? But there's definitely parts of the ecosystem that has a lot of choice. And we do our best to inform. And I think, under hand holding part, adjacent to that is the story of, well, do we then start using content management systems? Is this a whole new? Is it out with the old and in with the new? And I would say, you still have a lot of those needs, right? You still have non-technical people, for example, that needs to be able to update and create moves and content, and so on, right? And create content. And so you very often will need and an E-commerce solution or content management systems and so on. But what we're seeing there, is that we're speaking basically with every single major CMS out there. That are saying we're working on a headless system, or we already have a headless version, or we just gone full headless, that means that we work decoupled. So we don't no longer need to build the site. But we just provide like an independent source of content. And then it plugs into a platform like Netlify. So that can bring a lot of simplicity. And now you just have to maintain your content, but you don't have to worry about all the different environments and what is up to date and how does some of the infrastructure look like you press a button that commits to get a default preview, and it looks the same everywhere. >> I'm curious, what impact the current global pandemic has had on Netlify, and your customers. I saw you've got a COVID tracking project that you've done. But also now just there's different considerations when I think about what services I need to access from the web and what kind of connectivity the ultimate end user would have. So, what learnings have you had? What's involved there? >> In, obviously we, it depends a lot on, as Chris mentioned, right? The game circus is adopted horizontally across all kinds of areas and businesses and so on, right? So, we've of course seen businesses in sectors that are having a hard time and on the other hand, we've seen businesses and sectors that are exploding, right? We did immediately when the lockdown started happening and the pandemic started happening we set aside like a free plan for projects working in the space of tackling the information sharing around COVID and finding solutions and so on. And that was really interesting to see you mention the COVID tracking project, right? Which was a project like built a short time by small group of distributed incredibly talented front end developers and scientists and so on, right? And I think it was interesting to see that, how the Jamstack and our tooling and so on also really made it possible for them to build as a small distributed team the set of data information and tooling to a global audience, right? Seeing huge traffic peaks at time and just knowing that their architecture and our infrastructure could handle it for them. >> All right. Chris, I've got one, a little bit off to the side here. When I look at what Netlify is doing, you talk about having an open and independent web. And while we are fully supportive of that, we're a little concerned sometimes. If you look at what's happening across the globe, there's a lot of discussions. Will the internet actually fragment? Will certain countries wall off certain environments? Any concerns there? What do you look at? What are you hearing from your customers when you talk about that mission? >> It's one of the big challenges of all time, right? I think we all maybe took for given the Internet as the standard it became right? The way that you can publish without permission is pretty magnificent, right? And it would be indescribably painful for civilization if we lost that, right? And I think fragmentation is something that we all have to sort of worry around. From the way we see it, is that the web, the traditional monolithic approach, right? To which led to as a web that wasn't secure enough and wasn't scalable enough and wasn't performing enough and that's, for example, what opened the door for mobile applications, right? Where it just didn't make sense to pull in the UI every time you turn the page. So we ended up with a form that's it. We prebuilt the application, you download it, and then you speak to service for anything then atmosphere come up with it, right. And that makes perfect sense. That's basically the same architecture that we're bringing to the web a very large scale. Of course, the problem is that now there are gatekeepers there, right? There people, you have to ask for permission to publish and so on. And, and there are other attempts to say, "Hey, we need a performing web." And there's a very big players out there that say, "Let's come over and just..." Do we even need to call it the Internet? Can we just call it our company website? I'm not going to name any names here, right? But leading down, it's what we've called walled gardens, that are great for absolutely no one except for the company. And what we believe is that if you have a web that is secure and is scalable, and it's performant enough to justify at least the architecture maintaining and not having to run into any walled gardens and still say no, you don't need to use a handful of commercial platforms if you want to be heard rather than have your own web properties on your own custom domains, right? I think that's the part of the open independent viable web that we're fighting for. Basically, one that adopts and keeps adopting an architecture that is something that levels the playing field. And then they would also say, why Netlify? I mean, a few years before we started, like, try configuring your own CDN. And like that was reserved for the very, very large tech players. Now you can comment, you can literally click a button on Netlify, you get custom domain and ACS post process site that's globally distributed, automatically integrated into get. And that's on the premium plan. And so as a startup, you can level set together with everyone else and be available widely across the globe without performance issues, immediately. And so in that way, I'm also seeing that's a democrat sensation of performance, right? That means that, that's great. And for places where you see developing economies, where you often have brownouts, where you often can't depend on having viable services and is locally and so on, this idea of having he cover that and having something that's just automatically, you know what, don't even worry about it, because it's already ready to go in all these packets all around the world. That's a huge game changer. That's actually what we see a lot of adoption of the gems they can never find in those places as well. Guess that's just such a promise to the architecture. So, I hear what you're saying and I'm also very concerned about a fragmented web for political reasons as well across the globe. And from our angle, the way we fight for this is to make sure that it retains using an architecture that makes it accessible for me. >> Yeah, I heard many years ago, a friend of mine said, if you're a technologist it means that in general you are a technology optimist, which I definitely try to be. So, I love Chris how you've just brought in some of the potential opportunity Matt, I want to give you just... People out there they hear like oh, 5G is coming, it's going to completely change the world. Anything that you're seeing on your side as to real opportunities that we will see, just a step function in what your company is using. Jamstack, partnering with Netlify in your ecosystem. What are some of the early things that you see that are exciting you down the line for this? >> Part of it is simply like the whole ecosystem around the gem stalk growing up and the tooling, the APIs, the frameworks available around it, and the level of innovation that's triggered. And especially how it's triggering in... Especially how we're seeing like the potential for small, distributed teams to work together and build things with a global impact in a short time. And I remember a couple of years ago, we did a hackathon with together with freeCodeCamp. And of course, like since it was with freeCodeCamp, it was mostly like teams were mostly fairly new to programming and so on, right? It was pretty amazing to see what over a weekend with this architecture and with this tooling, with the vendors that were present there and helping out and so on, what the small teams could actually get done in a weekend, right? Like I remember the winning team had an app where the whole room would see an image on the main stage screen and then on their phone, try to place that image on the map and you would real time see how people ranked, how close they got and get a winner and so on, right? And that was all just from combining APIs and tooling, like history, like Netlify, like Honor Bee, like Google Maps, and so on, right? And I think, in some way we shouldn't forget just how much this kind of ecosystem of readily available APIs and services around this front end stake. It's allowing people to build things that years ago would have taken a very big team probably like a year to build, and suddenly you can have a relatively small group of relatively new programmers built something really impressive, right? So I think that's a trend we'll see continue accelerating And me and Chris are personally involved in advising and helping out a lot of these new startups in the space that are trying to bring new tooling to the world that makes more and more of these things possible and accessible. >> Well, Chris and Matt, I really appreciate you both joining such an exciting space. Talk about the cloud, agility and innovation, such a robust ecosystem. Thank you so much for joining. >> Thanks for having us. >> Thanks for having us. >> And I'm Stu Miniman. Thank you for joining and look forward to hearing more about your CUBE insight. (soft music)

hello everybody thank you for joining us today from the virtual verdict of BBC 2020 today's breakout session is entitled putting complex data types to work I'm Jeff Healey I lead vertical marketing I'll be a host for this breakout session joining me is Deepak Magette II technical lead from verdict engineering but before we begin I encourage you to submit questions and comments during the virtual session you don't have to wait just type your question or comment and the question box below the slides and click Submit it won't be a Q&A session at the end of the presentation we'll answer as many questions were able to during that time any questions we don't address we'll do our best to answer them offline alternatively visit Vertica forms that formed up Vertica calm to post your questions there after the session engineering team is planning to join the forms conversation going and also as a reminder that you can maximize your screen by clicking a double arrow button in the lower right corner of the slides yes this virtual session is being recorded and will be available to view on demand this week we'll send you a notification as submits ready now let's get started over to you Deepak thanks yes make sure you talk about the complex a textbook they've been doing it wedeck R&D without further delay let's see why and how we should put completely aside to work in your data analytics so this is going to be the outline or overview of my talk today first I'm going to talk about what are complex data types in some use cases I will then quickly cover some file formats that support these complex website I will then deep dive into the current support for complex data types in America finally I'll conclude with some usage considerations and what is coming in are 1000 release and our future roadmap and directions for this project so what are complex stereotypes complex data types are nested data structures composed of tentative types community types are nothing but your int float and string war binary etc the basic types some examples of complex data types include struct also called row are a list set map and Union composite types can also be built by composing other complicated types computer types are very useful for handling sparse data we also make samples on this presentation on that use case and also they help simplify analysis so let's look at some examples of complex data types so the first example on the left you can see a simple customer which is of type struc with two fields namely make a field name of type string and field ID of type integer structs are nothing but a group of fields and each field is a type of its own the type can be primitive or another complex type and on the right we have some example data for this simple customer complex type so it's basically two fields of type string and integer so in this case you have two rows where the first row is Alex with name named Alex and ID 1 0 and the second row has name Mary with ID 2 0 0 2 the second complex type on the left is phone numbers of type array of data has the element type string so area is nothing but a collection of elements the elements could be again a primitive type or another complex type so in this example the collection is of type string which is a primitive type and on the right you have some example of this collection of a fairy type called phone numbers and basically each row has a set or the list or a collection of phone numbers on the first we have two phone numbers and second you have a single phone number in that array and the third type on the slide is the map data type map is nothing but a collection of key value pairs so each element is actually a key value and you have a collection of such elements the key is usually a primitive type however the value is can be a primitive or complex type so in this example the both the key and value are of type string and then if you look on the right side of the slide you have some sample data here we have HTTP requests where the key is the header type and the value is the header value so the for instance on the first row we have a key type pragma with value no cash key type host with value some hostname and similarly on the second row you have some key value called accept with some text HTML because yeah they actually have a collection of elements allison maps are commonly called as collections as a to talking to in mini documents so we saw examples of a one-level complex steps on this slide we have nested complex there types on the right we have the root complex site called web events of type struct script has a for field a session ID of type integer session duration of type timestamp and then the third and the fourth fields customer and history requests are further complex types themselves so customer is again a complex type of type struct with three fields where the first two fields name ID are primitive types however the third field is another complex type phone numbers which we just saw in the previous slide similarly history request is also the same map type that we just saw so in this example each complex types is independent and you can reuse a complex type inside other complex types for example you can build another type called orders and simply reuse the customer type however in a practical implementation you have to deal with complexities involving security ownership and like sets lifecycle dependencies so keeping complex types as independent has that advantage of reusing them however the complication with that is you have to deal with security and ownership and lifecycle dependencies so this is on this slide we have another style of declaring a nested complex type do is call inlined complex data type so we have the same web driven struct type however if you look at the complex sites that embedded into the parent type definition so customer and HTTP request definition is embedded in lined into this parent structure so the advantage of this is you won't have to deal with the security and other lifecycle dependency issues but with the downside being you can't reuse them so it's sort of a trade-off between the these two so so let's see now some use cases of these complex types so the first use case or the benefit of using complex stereotypes is that you'll be able to express analysis mode naturally compute I've simplified the expression of analysis logic thereby simplifying the data pipelines in sequel it feels as if you have tables inside table so let's look at an example on and say you want to list all the customers with more than one thousand website events so if you have complex types you can simply create a table called web events and with one column of type web even which is a complex step so we just saw that difference it has four fields station customer and HTTP request so you can basically have the entire schema or in one type if you don't have complex types you'll have to create four tables one essentially for each complex type and then you have to establish primary key foreign key dependencies across these tables now if you want to achieve your goal of of listing all the customers in more than thousand web requests if you have complex types you can simply use the dot notation to extract the name the contact and also use some special functions for maps that will give you the count of all the HTTP requests grid in thousand however if you don't have complex types you'll have to now join each table individually extract the results from sub query and again joined on the outer query and finally you can apply a predicate of total requests which are greater than thousand to basically get your final result so it's a complex steps basically simplify the query writing part also the execution itself is also simplified so you don't have to have joins if you have complex you can simply have a load step to load the map type and then you can apply the function on top of it directly however if you have separate tables you have to join all these data and apply the filter step and then finally another joint to get your results alright so the other advantage of complex types is that you can cross this semi structured data very efficiently for example if you have data from clique streams or page views the data is often sparse and maps are very well suited for such data so maps or semi-structured by nature and with this support you can now actually have semi structured data represented along with structured columns in in any database so maps have this nice of nice feature to cap encapsulated sparse data as an example the common fields of a kick stream click stream or page view data are pragma host and except if you don't have map types you will have to end up creating a column for each of this header or field types however if you have map you can basically embed as key value pairs for all the data so on the left here on the slide you can see an example where you have a separate column for each field you end up with a lot of nodes basically the sparse however if you can embed them into in a map you can put them into a single column and sort of yeah have better efficiency and better representation of spots they imagine if you have thousands of fields in a click stream or page view you will have thousands of columns you will need thousands of columns represent data if you don't have a map type correct so given these are the most commonly used complexity types let's see what are the file formats that actually support these complex data types so most of file formats popular ones support complex data types however they have different serve variations so for instance if you have JSON it supports arrays and objects which are complex data types however JSON data is schema-less it is row oriented and this text fits because it is Kimmel s it has to store it in encase on every job the second type of file format is Avro and Avro has records enums arrays Maps unions and a fixed type however Avro has a schema it is oriented and it is binary compressed the third category is basically the park' and our style of file formats where the columnar so parquet and arc have support for arrays maps and structs the hewa schema they are column-oriented unlike Avro which is oriented and they're also binary compressed and they support a very nice compression and encoding types additionally so the main difference between parquet and arc is only in terms of how they represent complex types parquet includes the complex type hierarchy as reputation deflation levels however orc uses a separate column at every parent of the complex type to basically the prisons are now less so that apart from that difference in how they represent complex types parking hogs have similar capabilities in terms of optimizations and other compression techniques so to summarize JSON has no schema has no binary format in this columnar so it is not columnar Avro has a schema because binary format however it is not columnar and parquet and art are have a schema have a binary format and are columnar so let's see how we can query these different kinds of complex types and also the different file formats that they can be present in in how we can basically query these different variations in Vertica so in Vertica we basically have this feature called flex tables to where you can load complex data types and analyze them so flex tables use a binary format called vemma to store data as key value pairs clicks tables are schema-less they are weak typed and they trade flexibility for performance so when I mean what I mean by schema-less is basically the keys provide the field name and each row can potentially have different keys and it is weak type because there's no type information at the column level we have some we will see some examples of of this week type in the following slides but basically there's no type information so so the data is stored in text format and because of the week type and schema-less nature of flex tables you can implement some optimum use cases like if you can trivially implement needs like schema evolution or keep the complex types types fluid if that is your use case then the weak tightness and schema-less nature of flex tables will help you a lot to get give you that flexibility however because you have this weak type you you have a downside of not getting the best possible performance so if you if your use case is to get the best possible performance you can use a new feature of the strongly-typed complex types that we started to introduce in Vertica so complex types here are basically a strongly typed complex types they have a schema and then they give you the best possible performance because the optimizer now has enough information from the schema and the type to implement optimization system column selection or all the nice techniques that Vertica employs to give you the best possible color performance can now be supported even for complex types so and we'll see some of the examples of these two types in these slides now so let's use a simple data called restaurants a restaurant data - as running throughout this poll excites to basically see all the different variations of flex and complex steps so on this slide you have some sample data with four fields and essentially two rows if you sort of loaded in if you just operate them out so the four fields are named cuisine locations in menu name in cuisine or of type watch are locations is essentially an array and menu array of a row of two fields item and price so if you the data is in JSON there is no schema and there is no type information so how do we process that in Vertica so in Vertica you can simply create a flex table called restaurants you can copy the restaurant dot J's the restaurants of JSON file into Vertica and basically you can now start analyzing the data so if you do a select star from restaurants you will see that all the data is actually in one column called draw and it also you have the other column called identity which is to give you some unique row row ID but the row column base again encapsulates all the data that gives in the restaurant so JSON file this tall column is nothing but the V map format the V map format is a binary format that encodes the data as key value pairs and RAW format is basically backed by the long word binary column type in Vertica so each key essentially gives you the field name and the values the field value and it's all in its however the values are in the text text representation so see now you want to get better performance of this JSON data flex tables has these nice functions to basically analyze your data or try to extract some schema and type information from your data so if you execute compute flex table keys on the restaurants table you will see a new table called public dot restaurants underscore keys and then that will give you some information about your JSON data so it was able to automatically infer that your data has four fields namely could be name cuisine locations in menu and could also get that the name in cuisine or watch are however since locations in menu are complex types themselves one is array and one is area for row it sort of uses the same be map format as ease to process them so it has four columns to two primitive of type watch R and 2 R P map themselves so now you can materialize these columns by altering the table definitions and adding columns of that particular type it inferred and then you can get better performance from this materialized columns and yeah it's basically it's not in a single column anymore you have four columns for the fare your restaurant data and you can get some column selection and other optimizations on on the data that Whittaker provides all right so that is three flex tables are basically helpful if you don't have a schema and if you don't have any type of permission however we saw earlier that some file formats like Parker and Avro have schema and have some type information so in those cases you don't have to do the first step of inputting the type so you can directly create the type external table definition of the type and then you can target it to the park a file and you can load it in by an external table in vertical so the same restaurants dot JSON if you call if you transfer it to a translations or park' format you can basically get the fields with look however the locations and menu are still in the B map format all right so the V map format also allows you to explode the data and it has some nice functions to yeah M extract the fields from P map format so you have this map items so the same restaurant later if you want to explode and you want to apply predicate on the fields of the RS and the address of pro you can have map items to export your data and then you can apply predicates on a particular field in the complex type data so on this slide is basically showing you how you can explode the entire data the menu items as well as the locations and basically give you the elements of each of these complex types up so as I mentioned the menus so if you go back to the previous slide the locations and menu items are still the bond binary or the V map format so the question is if you want what if you want to get perform better on the V map data so for primitive types you could materialize into the primitive style however if it's an array and array of row we will need some first-class complex type constructs and that is what we will see that are added in what is right now so Vertica has started to introduce complex stereotypes with where these complex types is sort of a strongly typed complex site so on this slide you have an example of a row complex type where so we create an external table called customers and you have a row type of twit to fields name and ID so the complex type is basically inlined into the tables into the column definition and on the second example you can see the create external table items which is unlisted row type so it has an item of type row which is so fast to peals name and the properties is again another nested row type with two fixed quantities label so these are basically strongly typed complex types and then the optimizer can now give you a better performance compared to the V map using the strongly typed information in their queries so we have support for pure rows and extra draws in external tables for power K we have support for arrays and nested arrays as well for external tables in power K so you can declare an external table called contacts with a flip phone number of array of integers similarly you can have a nested array of items of type integer we can declare a column with that strongly typed complex type so the other complex type support that we are adding in the thinner liz's support for optimized one dimensional arrays and sets for both ross and as well as RK external table so you can create internal table called phone numbers with a one-dimensional array so here you have phone numbers of array of type int you can have one dimensional you can have sets as well which is also one color one dimension arrays but sets are basically optimized for fast look ups they are have unique elements and they are ordered so big so you can get fast look ups using sets if that is a use case then set will give you very quick lookups for elements and we also implemented some functions to support arrays sets as well so you have applied min apply max which are scale out that you can apply on top of an array element and you can get the minimum element and so on so you can up you have support for additional functions as well so the other feature that is coming in ten o is the explored arrays of functionality so we have a implemented EU DX that will allow you to similar similar to the example you saw in the math items case you can extract elements from these arrays and you can apply different predicates or analysis on the elements so for example if you have this restaurant table with the column name watch our locations of each an area of archer and menu again an area watch our you can insert values using the array constructor into these columns so here we inserting three values lilies feed the with location with locations cambridge pittsburgh menu items cheese and pepperoni again another row with name restaurant named bob tacos location Houston and totila salsa and Patty on the third example so now you can basically explode the both arrays into and extract the elements out from these arrays so you can explode the location array and extract the location elements which is which are basically Houston Cambridge Pittsburgh New Jersey and also you can explode the menu items and extract individual elements and now you can sort of apply other predicates on the extruded data Kollek so so so let's see what are some usage considerations of these complex data types so complex data types as we saw earlier are nice if you have sparse data so if your data has clickstream or has some page view data then maps are very nice to have to represent your data and then you can sort of efficiently represent the in the space wise fashion for sparse data use a map types and compensate that as we saw earlier for the web request count query it will help you simplify the analysis as well you don't have to have joins and it will simplify your query analysis as I just mentioned if your use cases are for fast look ups then you can use a set type so arrays are nice but they have the ordering on them however if your primary use case to just look up for certain elements then we can use the set type also you can use the B map or the Flex functionality that we have in Vertica if you want flexibility in your complex set data type schema so like I mentioned earlier you can trivially implement needs like scheme evolution or even keep the complex types fluid so if you have multiple iterations of unit analysis and each iteration we are changing the fields because you're just exploring the data then we map and flex will give you that nice ease to change the fields within the complex type or across files and we can load fluid complex you can load complexity types with bit fluids is basically different fields in different Rho into V map and flex tables easily however if you're once you basically treated over your data you figured out what are the fields and the complex types that you really need you can use the strongly typed complex data types that we started to introduce in Vertica so you can use the array type the struct type in the map type for your data analysis so that's sort of the high level use cases for complex types in vertical so it depends on a lot on where your data analysis phase is fear early then your data is usually still fluid and you might want to use V Maps and flex to explore it once you finalize your schema you can use the strongly typed complex data types and to get the best possible performance holic so so what's coming in the following releases of Vertica so antenna which is coming in sometime now so yeah so we are adding which is the next release of vertical basically we're adding support for loading Park a complex data types to the V map format so parquet is a strongly typed file format basically it has the schema it also has the type information for each of the complex type however if you are exploring your data then you might have different park' files with different schemes so you can load them to the V map format first and then you can analyze your data and then you can switch to the strongly typed complex types we're also adding one dimensional optimized arrays and sets in growth and for parquet so yeah the complex sets are not just limited to parquet you can also store them in drawers however right now you only support one dimension arrays and set in rows we're also adding the Explorer du/dx for one-dimensional arrays in the in this release so you can as you saw in the previous example you can explode the data for of arrays in arrays and you can apply predicates on individual elements for the erase data so you can in it'll apply for set so you can cause them to milli to erase and Clinics code sets as well so what are the plans paths that you know release so we are going to continue both for strongly-typed computer types right now we don't have support for the full in the tail release we won't have support for the full all the combinations of complex types so we only have support for nested arrays sorriness listed pure arrays or nested pure rows and some are only limited to park a file format so we will continue to add more support for sub queries and nested complex sites in the following in the in following releases and we're also planning to add this B map data type so you saw in the examples that the V map data format is currently backed by the long word binary data format or the other column type because of this the optimizer really cannot distinguish which is a which is which data is actually a long wall binary or which is actually data and we map format so if we the idea is to basically add a type called V map and then the optimizer can now implement our support optimizations or even syntax such as dot notation and yeah if your data is columnar such as Parque then you can implement optimizations just keep push down where you can push the keys that are actually querying in your in your in your analysis and then only those keys should be loaded from parquet and built into the V map format so that way you get sort of the column selection optimization for complex types as well and yeah that's something you can achieve if you have different types for the V map format so that's something on the roadmap as well and then unless join is basically another nice to have feature right now if you want to explode and join the array elements you have to explode in the sub query and then in the outer query you have to join the data however if you have unless join till I love you to explode as well as join the data in the same query and on the fly you can do both and finally we are also adding support for this new feature called UD vector so that's on the plan too so our work for complex types is is essentially chain the fundamental way Vertica execute in the sense of functions and expression so right now all expressions in Vertica can return only a single column out acceptance in some cases like beauty transforms and so on but the scalar functions for instance if you take aut scalar you can get only one column out of it however if you have some use cases where you want to compute multiple computation so if you also have multiple computations on the same input data say you have input data of two integers and you want to compute both addition and multiplication on those two columns this is for example but in many many machine learning example use cases have similar patterns so say you want to do both these computations on the data at the same time then in the current approach you have to have one function for addition one function for multiplication and both of them will have to load the data once basically loading data twice to get both these computations turn however with the Uni vector support you can perform both these computations in the same function and you can return two columns out so essentially saving you the loading loading these columns twice you can only do it once and get both the results out so that's sort of what we are trying to implement with all the changes that we are doing to support complex data types in Vertica and also you don't have to use these over Clause like a uni transform so PD scale just like we do scalars you can have your a vector and you can have multiple columns returned from your computations so that sort of concludes my talk so thank you for listening to my presentation now we are ready for Q&A

(upbeat music) >> From our studios in the heart of Silicon Valley, Palo Alto, California, this is a CUBE Conversation. >> Hello, everyone. Welcome to this special Cube conversation here in theCUBE studios here in Palo Alto, California. I'm John Furrier, host of theCUBE. We have a special series we're starting called Demystifying Cloud-Native. And I'm joined with my cohost for this series, Dominik Tornow, Principal Engineer with Cisco Office of the CTO. Dominik, thanks for joining me, and thanks for agreeing to participate in this awesome series around demystifying cloud-native. >> Hey, thanks for having me. >> So, cloud-native is hot, but it's changing. It's super important. Some people have a definition here or there. What is your definition of cloud-native. >> Well for, to define cloud-native, let's use a mechanical approach, alright. So, we are talking about cloud-native applications. So, the first question there would be "what is cloud?" Alright. And I personally define the cloud as a service provider that allows a service consumer to dynamically acquire and release resources. Now, from that point, with that definition in mind, we can define three related concepts. That would be public cloud, private cloud, and hybrid cloud. So, the public cloud is a service provider outside of your organization, the private cloud is a service provider inside your organization, and the hybrid cloud is a union of both. So, with this definition, we can define a cloud application. And a cloud application then is any application that runs on a cloud provider, alright. But now, what is a cloud-native application, alright? If I take a classical application and put it on the cloud it it becomes a cloud application by definition, but it doesn't become a cloud-native application. If we want to grasp cloud-native applications, alright, we've got to grasp a concept that is responsiveness. Responsiveness is very close to availability, but the term availability is highly overloaded. So, I personally like to talk about responsiveness. And responsiveness is a ability of an application to hit its service level agreements. Typically it's response time, right. A typical service level agreement may be 90% of my requests need to be served within 250 milliseconds. So, that is the responsiveness of an application. And now, we can define scalability and reliability. Scalability is responsiveness under load, and reliability is responsiveness under failure. And now to close the loop, we can define cloud-native. And my definition of a cloud-native application is a cloud application that is scalable and reliable by construction. >> Dominik, what is your view on hybrid versus multi-cloud? Cause that's something that we a lot of in the industry around hybrid being public private, a union of that. And you mentioned that. But the talk of multi-cloud is being kicked around a lot. What's the reality of multi-cloud? Is that just I have multiple clouds? What's the impact to development teams and companies as they think about hybrid and multi-cloud? >> So, the hybrid cloud, right, is an instance of a multi-cloud. Because by definition you have multiple cloud providers that make up the multi-cloud, and in the hybrid cloud, you have at least one public and at least one private cloud. And, of course, the implications whether it's public to public or public to private cloud are huge. It does effect your application all the way from the architecture down to the way how you operate your application, alright. And when it comes to, when it comes to multi-cloud, we are looking at significant challenges when it comes to the operation, automation, and the federation between the clouds. >> What do you think about the role Kubernetes is going to play in the enterprise? Cause right now, it's really, I think, one of the most popular, if not the most defacto things I've seen in many, many years. I think it's--to me I think-- The only thing I can think of as impactible as Kubernetes is going way back to TCPIP and what that meant for internet working, which spawned massive change, massive wealth creation, massive computing capabilities. It essentially created networking subnets and, as we know, networking as we know it. Kubernetes has that same feel to it in a whole another kind of modern way. It seems to be something that people are getting behind in a defacto--it's not officially a standard, I guess. Well, it could be. How important--what's the big deal around Kubernetes? What's your thoughts on this? >> Oh, Kubernetes are so--Kubernetes is definitely something that is exciting in the ecosystem because it puts cloud-native in all of our reach, right. With Kubernetes, cloud-native is up for grabs, alright. A cloud--any application, when you just put it on Kubernetes, it won't become a cloud-native application just by containerization, alright. But Kubernetes provides so many primitives that actually allow you to address the challenge of scalability and allow you to address the challenge of reliability. And top of that, it has, as you mentioned, the energy in the ecosystem, alright. And with Kubernetes, if you architect your application right, you do have a chance to efficiently, cost efficiently and also effort efficiently have a cloud-native application that is scalable and reliable by construction. And if you think about it, scalable and reliable by construction, that requires your application to be able to A, detect load and failure and B, mitigate load and failure. And now, if you take Kubernetes and you take it apart and you look under the hood, you see that the Kubernetes primitives are actually designed for that, alright. They allow you to-- They allow the application to scale itself. They allow the application to actually recover from failure. You do have to up and architect your application that way. If your application cannot handle partial failure, your container comes down and with your container you are actually losing vital state in your application. Kubernetes cannot help you with that. But if you architect it correctly, Kubernetes will never stop trying to actually meet your demands. >> That's a great point. How has Kubernetes changed the relationship between the application and the application developers' requirements. Because I think a lot of people see Kubernetes as this silver bullet. Oh my god, Kubernetes's going to solve all my problems. But that's not really what it is there for. You're kind of getting at that. Detecting failure, understanding the events... These are things that are super important. but the application folks have to do the work. Can you just unpack that relationship between the I'm the app builder. What's my relationship to Kubernetes? >> (laughs) A love hate relationship. Because Kubernetes is going to help you a lot, but Kubernetes also demands a lot, alright. So-- >> Explain that. Demands a lot. What did you mean by that? >> The architectures that we are used to. Sorry. >> It demands a lot. >> It demands a lot. The architectures that we are used to need to change, and if you come from, let's say 10 years ago, 15 years ago, right, and we are building a reactive application which at that point would just be called a web application, you have a request coming in, and a web server taking that request and basically spawning the request context. In that request context, your application is still sequential, alright. And if everything fails, the database is here to save the day, the transactions. It's here to save the day and will prevent you from running into any inconsistencies. Now, if you're in a microservice architecture world right, multiple different microservices, no transactions there to save the day. You have to architect with that reality in mind. Kubernetes cannot provide an abstraction that make the reality of distributed applications disappear and look like one local application. It cannot. However, it can support you if you've got the application architecture right. It can support you to actually bring the application to life. And in that case, I do like to differentiate between system, application, and platform. The application is all the bits that you build, right. The platform is all the bits that run your application. And it is the system, basically the combination once the application and the platform are composed, right, that is now scalable and reliable by construction. And you can rely on a lot of pieces when it comes to Kubernetes to actually make this a reality. >> So as people are out there thinking about cloud-native, this modern era's upon us. We've seen observability become a very important topic. And that, you know, that's basically network management in my mind. But we've seen observability have its own category and its big successes out there, PagerDuty, SignalFx, they all got li-- Well all these ventures got successes. Automation's another area. How do you see the interplay between automation and observability? Because Kubernetes has a lot of things going on. Application's going to have a lot more services happening and with microservices and other things. Observability and automation are two important concepts besides orchestration Kubernetes, though observability and automation. How do you see those fitting into that cloud-native architecture? >> So, observability. When we hear observability, right, we should ask ourself the question where "Who is the observed, and who is the observer? And classically, if you think of the observer, we think about ourselves, right? We have either the developers and we have an or we have an operation's team, and it is the operations team that is fed the data from the observability tool set, alright. However, now if we bring operations into the mixture, and especially operation automation, we can close the loop between observability, automation operation, and again, observability. That is the observability tool set, alright, monitoring the application, feeds into the operation of the application in order to actually, again, orchestrate parts of the application. And here with Kubernetes is actually the perfect example and a very simple example is autoscaling. So, autoscaling on Kubernetes, we are basically just monitoring either metrics like for example, CPU load or memory pressure, or CPU load and memory load, or we are looking into application metrics like the messages queued up in a message queue. And this is now the indicator for Kubernetes to actually scale up more pods on demand or scale down more pods on demand. And yes, this is not rocket science. We had this for a while, yet with Kubernetes and it's extensibility, right, we can take that further and further down up from a very generic level where we have autoscaling on a very generic level to an absolutely application specific or use case specific level. If you dig into Knative, for example, you will actually quickly discover that Knative is or, especially Knative Serving, one of the subsets on K Native, is a operations automation platform for microservice applications on Kubernetes. And again, it feeds the observability into the operations and the operations into the observability. >> They work hand in hand? >> They work hand in hand. >> Dominik, I want to ask you, put you on the spot here with a question, so take your time to think about this. What is the most important story or thread or topic or interest that people should pay attention to in this cloud-native wave? And the second part is what's the most important thing that people need to be paying attention to that they might not be paying attention to? >> Well, unfortunately, I think I have to disappoint you. The one most important one is actually very hard to find. It will influence everything. It will influence your organization. It will influence the architecture of your applications. It will influence how you operate these applications and how you move forward with new versions. So, which one is the most important one or the most significant one very much depends on your role. But there is absolutely no question that the cloud-native journey effects all of these roles. >> So, then, you could argue that the top story is that cloud-native is a completely new operating model different from the old way of doing it? >> Yes. >> Would you agree with that? >> I very much agree with that. >> Because some people think like "Cloud-native, I don't even know what that is. "I'm in the 1990s with my IT department, "and my application developer's still running "single threaded mainframes." >> You know, based on the definition-- Doesn't the definition actually sound pretty innocent? Alright. Scalable and reliable by construction. That actually doesn't sound like it's magic dust and that also doesn't sound too hard. But once you actually start uncovering and dive into what that actually means, right, then you see that the implications of that, right, are far reaching. It starts from UX engineering to software engineering to the operations, and it will effect the entire organization and organizational setup. >> Let's just say you and I are having a beer. It's Oktoberfest, you know, we're having a beer, and I say, "Hey, I have, you know, "I've got to get modern with my IT. "My boss is, you know, banging down my doors saying "We need to go cloud-native. "we've got to get modern applications." But we're running old school IT. Dominik, what do I do? Give me some advice. What's the playbook? What's your--what would you tell me? >> A playbook is again actually fairly hard because on the one side, we are actually not very far into this journey. So, it is not necessarily that there is a lot of chapters in this playbook to choose from. And the other one is, you have to give your IT department the possibility to actually re-architect the entire system. Of course, this is a step by step journey, and you cannot do this overnight. But if you wanted to arrive at a truly cloud-native destination, you actually have to walk the entire cloud-native journey. >> Talk about the intersection between design and development. Cause this, again if everything is flipped upside down where applications are in charge, UX and UI are important. UX, meaning thinking about the user experience engineering is super critical to get that done upfront, just like security. If security is being done on the front end baked into everything, doesn't UX have to be baked into everything? If that's the case, that's again a dynamic. So what's your take on that development and design intersection. >> Remember 15 years ago? It was like when do we bring in a UX designer? >> At the end of the project. (laughs) >> At the absolute end of the project, exactly. So we have it ready, and then we have only one demand, make it pretty, alright. So, obviously, that didn't work great. >> Well, I mean that made sense in with in the web, the web was very limited at the time, HTML and you had some interactive base interactive features, so it was a limited tool set then. >> At that time, it did work, but it was still not ideal. >> Yes, and I agree. >> Right? But now we actually--we need to flip. We need to flip the playbook there on its head. And I would argue that as an application developer my boss, so to say, the one who is giving me the requirements, are the UX engineers right now. So, the UX engineers are the ones, alright, that determine the functional requirements of my application. Now, as a application engineer, I still determine A, security and B, also the non-functional requirements of my application. And once again, we come to reliability or we come to scalability and reliability by construction. So, we also need to start working hand in hand together. So, UX and UX design, or design and development, looking at design and development, you see there is somewhat of a misalignment to begin with. UX design is responsible for building the right thing, and development is responsible for building the thing right. Okay. So in that case we are almost orthogonal on our way, right. And in the cloud-native world, actually forces us together. And as a simple example, if you look at one web page now, that may actually be served by multiple microservices. So, given the possibility of partial failure, alright, will the page come up, or will the page not come up? It's actually not a binary condition or a binary decision anymore, right. Parts of the page may be up. Parts of the page may be down. Is that critical? Is the page still viable, or is it not? That is for the UX designer to decide, and I am here to help them. >> So how's the balance get aligned? How do you realign that you're saying bring in UX to lead the application development then to the application developer then to the development team? >> It actually has to be very short feedback cycle. So, I personally argue for designers and developers going along that journey together so there shall not be a hand off. Once there is an actual hand off, you already lost. >> So cloud-native. We're bringing everything together. UX, the front end. Applications taking control. Infrastructure is code. This paradigm's significant. This is here to stay for the next generation or two at least. >> Yes, this paradigm actually does change how we approach software engineering at large. >> Alright, we're going to dig into more of it. There's plenty more to talk about. We've got CUBEcon coming up in San Diego, STO, service meshes, state flow applications, a lot more stuff to talk about. Dominik, thanks for having this conversation demystifying cloud-native, here with Dominik Tornow, Principal Engineer at Cisco, Office of the CTO. I'm John Furrier, theCUBE. Thanks for watching. (energetic music)

>> From San Francisco, it's theCUBE covering Conga Connect West 2018. Brought to you by Conga. >> Hey, welcome back everybody, Jeff Rick here with theCube. The Mark Benny office finished this portion of the keynote, so we can get back to business here. Special event outside of sales force, the 171,000 people over watching Mark and the keynote. We're here at a special Conga event, it's called Conga Connect West. It's about 3,000 people they said they had last year, 3 days of taking over the thirsty bear, they've got free food, free drink, free entertainment, lot of demos, come on over. The invitation is open. Just make sure you come early because the line is really long, but we're excited to get into it with a practitioner, we love to talk to customers. So, really excited to have our next guest, Susan O'Leary, she's a continuous improvement leader 6and program manager for Abiomed. Great to see you. >> Hey Jeff, thank you so much for that introduction. I'm so excited to be here. >> Excellent, and with her is Will Spindla, the VP of marketing from Conga. Will, great to see you. Warming up before your panel tomorrow. >> Exactly. (laughs) >> So, first off, impressions of this show, it never fails to amaze me when we come to Dreamforce, what happens to downtown San Francisco. >> It's insane, isn't it? >> It is crazy. It never disappoints, there is so much going on at every moment, and especially right here at Connect West. >> Right. So, what is Abiomed, for folks that aren't familiar with the company? >> So, Abiomed, we're a class-3 medical device company. We make the world's smallest heart pump and our corporate mission is to recover hearts and save lives. And more recently, we have some commercials for our flagship product, the Impella product, on T.V. So I feel like we've really arrived at some point in the company's maturity that we have television commercials. >> Right, so what does class-3 mean? >> So, it's a certain level of classification within the FDA, and class-3 means essentially, in the simplest way, that it goes inside the body. >> Okay. >> So, the rigor at which it's controlled, and how products are introduced into market, have a very rigorous path for patient quality and compliance and safety, it's a pretty exciting space to be, but it's not easy to bring a product to market. >> And you've got hardware, I imagine you've got all kinds of crazy software, you probably have all types of continuous monitoring, not a simple device. >> No. >> And a very important one. >> A very important one. That's right. >> So we're here at Conga, Connect West, what do you guys do with Conga, where does Conga play in your world? >> So Conga has enabled Abiomed to do amazing things. We're here at Dreamforce, obviously as Salesforce customers, and we began our journey with Salesforce back in 2009, and we discovered that we had some business processes that still resided outside of Salesforce, that people were struggling with these PowerPoint presentations and putting together their sales forecast, and all the data that would really drive that lives in the Salesforce orb. A tour on the app exchange back probably 2010 I would say, Will, and Jeff, I found the composer product, and it was a pretty easy sell to our VP of sales, a quick proof of concept, taking certain data that people were manually manipulating and with the click of a button, here is your forecast blown up in all kinds of colors and charts and graphs, it was a game changer. >> All right, so that's early intro, right, 'cause the biggest knock on Salesforce, always, is getting sales people to use it, right, and changing behavior is much harder than writing software or developing software. So, did you find that that app was the killer app to get the sales team to actually use the tool? >> Well, so they were using- >> 'Cause everybody's got the same story, right, everyone's got PowerPoint, and a lot of times people use Salesforce for reporting, not actually working, and now it's double data entry, I can't stand it, but it sounds like this composer was really a game-changer for you. >> Well, it brought the best of both worlds together because our field organization was using Salesforce, they're doing their work in that application, and yet the model that leadership wanted for delivering their weekly forecast in their update was very, very specific, and you couldn't do that in any Salesforce report. You can do it in Excel. >> So the forecast model was outside of Salesforce driven by the executive leadership, even though the day-to-day work was happening inside of Salesforce? >> You're right, you're right. >> And this was like, "Oh, it happens over and over again?" >> (laughs) It was the visualization that was impossible in standard Salesforce reports, but you could build it in Excel, and then merge the data with the composer product, so that was our first use case, and we have invented so many more, but that got us in the door, so to speak. >> So, Will, have you ever heard that story before? >> Well, what I was going to say, I think it's interesting because I worked at Salesforce for about six years before I came to Conga, and one of the things that we often saw was that sales people sometimes put their data in Salesforce, unless they're coaxed very greatly, but what they actually don't do a lot of the time is leverage the data that's inside there once it's there. And so the nice part about having a tool like Conga is that you can make it so the sales people don't have to do anything with the data, right? You can automate- >> Exactly. >> Creation of reports and charts and PowerPoint presentations, so that the sales reps, they don't have to do anything. >> They just click a button. >> Click a button. >> They click a button, they have the relationships with their customers, they know how to win the deals, they know how to take all those conversations to the next level, and why do we want them crunching numbers and doing that? We don't want them doing that. There's no value in that. So, you find great tools that take the data and put it in a button, and game changed. >> Yeah, and then you can ensure that whatever process or policy your company, like Abiomed has, every single sales rep is within that guideline, so they're not making their own decisions, they're doing what the organization wants them to. >> That's right, they're following a tested and validated model that delivers what leadership wants. And I'm probably not joking if I say half a day on Friday, if you were a cardiology account manager, you would be trying to cobble this together in a PowerPoint and then turn it in to the office. Half a day. >> So the office is asking for a PowerPoint presentation on the updated status of your pipeline, basically? >> This very specific visualization model. And, with Composer, with how people are with data, they think that this is all they really need, but once they saw what we could put in that output document from Composer, it has grown to be an enormous analytic tool set for the field team that drives their forecast. >> I'm just curious in terms of the scale and the size of team, don't tell me anything out of school but, are you talking tens of reps, hundreds of reps? >> Hundreds of reps. >> Hundreds of reps. >> Globally, we have over 100 sales territories, and so we have easily 450 feet on the street. And certain people have different roles, right, so the cardiology account manager role is that forecasting leader in the company, that person is really clicking that button to generate that document, and there's well over 100 in our organization. >> So, Will, you hear these stories all the time, I'm sure, is Composer the killer app to get people to start to embrace this tool? Do you see that time and time again? >> Yeah, I think one of the nice parts about Composer is that you can, in some respects, direct your entire sales or organization on the way the company wants to showcase themselves, whether it's in reporting, whether it's highly branded and pixel-perfect documents, what we've seen a lot of people do is you may have a monthly or a quarterly business review. >> Oh, we do that! We have Composer for that. We have this beautifully crafted merge template that delivers a business review to our customers. Yeah, that was the second thing we did with Composer. >> That's right. >> Where we first did the forecast then we did the business review. >> Business review. >> Wow! >> And you can do that in Excel, or in PowerPoint, or in Word, or even in HTML, it just gives you the ability to take data, that sits inside Salesforce, and push it out in any format you want. And the nice part, too, is you can pull data from other systems. >> Right. >> So it can be in your ERP or your accounting system and brings it all into one spot. >> I just can't help but think of the poor guy on the receiving end of the 450 PowerPoint decks on Friday afternoon, I mean how did that get rolled up? >> Yeah, we had another process for that. >> I don't want to hear that one, that one sounds scary. >> There's the regional, there's a country base- >> Too much. >> And it's all Composer. It's all Composer. >> Last question for you, Susan. So, have you been able to leverage the success of Composer to basically expand into more applications in the Salesforce suite with Conga or other, to actually get your adoption up, and now start to add more and more applications? >> Yeah, that's a great question, Jeff, and certainly Composer was that early-adoption product that was such an easy sell, it had win-win written over it in capital letters, everybody really got it right away. "We're buying this, we're doing this." And then over the years, Conga in its development life cycle put out a couple other game-changing products that we also have, we have their Action Grid product, and their contract solution. >> Was that as easy of a sell? >> Yes. >> Okay. (laughs) >> Well, it wasn't IT organizations selling solution on business, business is saying, "We want a quoting platform, and we need something better than standard Salesforce." So, we started looking at what is now CPQ, but it was called Steelwork at the time, and then we needed to solve for the contract life cycle management part of that, and a contract product didn't even exist at the time. And we were looking at other solutions, and we were trying to make something work, and we learned about the contract product through a Connect event that a colleague of mine attended, and came back from that event, and just said "Sue, you've got to stop everything you're doing, you've got to go talk to Pete Castro at Conga, and you have to see this contract tool. Because I know we're almost at the end of this project, but literally you're going to rip out everything that we did before and you're going to want to do this." So guess what we did? We did it! >> Will, you can't let this one off your hip, I'm telling you. She's awesome. >> It was a tough timeline and that was part of the promise that we needed to hear back when we went to the table, was we can't miss our launch. >> Yeah, yeah. >> To do this pivot and switch and can we do it? >> But that's easy compared to getting sales people to change behavior, timelines are one thing, but if you got people to actually use the tool the way the tool is supposed to be used, then the ancillary benefits are tremendous. Thank you for sharing that story with us, Sue. >> You're very welcome, Jeff. We do have the Action Grid product, but I'm not the expert in that space, but I've seen some amazing things. >> You've got the sales people using Salesforce on a weekly basis, plant the flag and call it enough. Come on now! All right, so thanks again. He's Will, she's Sue, I'm Jeff, you're watching theCube for Conga Connect West at Salesforce Dreamforce in San Francisco, thanks for watching. (electronic music)

>> From the SiliconANGLE Media office in Boston, Massachusetts. It's theCUBE. Now, here's your host, Dave Vellante. >> Thanks Peter. We're back for the deep dive. Beth Phalen is joining us again and Ruya Barret who's the vice president of marketing for Dell EMC's data protection division. Thanks guys for coming on. Ruya let me start with you. Why are customers, what are they telling you in terms of why they're acquiring your data protection solutions? >> Well Beth talked a little bit about the engineering effort and collaboration we've been putting in place and so did Yang Ming with Vmware. So whether that's integration into vCenter or vSphere, or vRealize operations manager, vRealize automation or vCloud director. All of this work, all of this engineering effort and engineering hours is really to do two things deliver simply powerful data protection for VMware customers. >> What do you mean by simple? >> Simple. Well simple comes in two types of approaches, right? Simple is through automation. One of the things that we've done is really automate across the data protection stack for VMware, whereas 99% of the market solutions really leave it off at policy management, so they automate the policy layer. We automate not only the policy layer but the vProxy deployment, as well as the data movement. We have five types of data movement capabilities that have been automated, whether you're going directly from storage, to protection storage, whether you're doing client to protection storage, whether you're doing application to protection storage, or whether you're doing hypervisor direct to application storage. So it really is to automate and to maximize the performance of to meet the customer's service levels. So automation is critical when you're doing that. The other part of automation could be in how easy Cloud is for the admins and users. It really has to do with being able to orchestrate all of the activities, you know, very simply and easily. Simplicity is also management. We are hearing more and more that the admins are taking on the role of doing the backups and restores so our efforts with VMware have been to really simplify the management so that they can use their native tools. We've integrated with VMware for the V admins to be able to take backup and restore just a part of their daily operational tasks. >> So when you talk about power, is that performance? You've referenced performance but is it just performance or is it more than that? >> That's also a great question Dave, thank you. Power really, in terms of data protection, is three-fold. It's power in making sure that you have a single powerful solution that really covers a comprehensive set of applications and requirements, not only for today, but also tomorrow as needs. So that comprehensive coverage, whether you're on premise or in the Cloud is really critical. Power means performance, of course it means performance. Being able to deliver the highest performing protection and more importantly restores, is critical to our customers. Power also means not sacrificing efficiency to get that performance. So efficiency we have the best source side deduplication technology in the market. That, coupled with the performance is really critical to our customers. So all of these, the simplicity, the comprehensive coverage, the performance, the efficiency, also drives the lowest cost to protect for our customers. >> All right. I want to bring Beth Phalen into the conversation. Beth, let's talk about Cloud a little bit. A lot of people feel as though I can take data, I can dump it into an object store in the Cloud, and I'm protected. Your thoughts. >> Yeah, we hear that same misconception, and in fact the exact opposite is true. It's even more important that people have world class data protection when they're bringing Cloud into their IT environment. They have to know where their data is and how is it protected and how to restore it. So we have a few innovations that are going on here. For a long time we've had our hyper Cloud extensions. You can do Cloud tearing directly from data domain, and now we've also extended what you can do if you're a VMware Cloud AWS customer so that you can use that for your Cloud DR configuration, fail over to AWS with VMware Cloud, and then fail back with Vmotion if you choose to, and that's great for customers who don't want to have a second site, but do want to have confidence that they can recover if there's a disaster. On top of that we've also been doing some really great work with VMware with VCloud director integration. Data protection as a service is growing like crazy. It's highly popular around the globe as a way to consume data protection, and so now you can integrate both your VMware tasks and your data protection tasks from one UI in the cloud director. These are just a few of the things that we're doing. Comprehensively bringing data protection to the cloud is essential. >> Great, okay. Dell EMC just recently made an announcement. The IDPA DP4400. Ruya, what's it all about? Explain it. >> Absolutely. So what we announced is really an integrated data protection appliance turn key, purpose built, to meet the specific requirements of mid-size customers. It's really to bring that enterprise sensibility and protection to our mid-size customers. It's all-inclusive in terms of capabilities so if you're talking about backup, restore, replication, disaster recovery, Cloud disaster recovery and Cloud long-term retention. All at your fingertips, all included, as well as all of the capabilities we talked about in terms of enabling VM admins to be able to do all of their daily tasks and operations through their own native tools and UIs. So it's really all about bringing simply powerful data protection to mid-size customers at the lowest cost to protect, and we now also have a guarantee under our future proof loyalty program, we are introducing a 55 to one deduplication guarantee for those exact customers. >> Okay. Beth, I wonder if you could talk about the motivation for this product. Why did you build it and why is it relevant for mid-size customers? >> So we're known as number one in enterprise data protection. We're known for our world class, best in the class, best in the world dedu capabilities, and what we've done is we've taken the learnings and the IP that we have that served enterprise customers for all of these years and then we're making that accessible to mid-size customers, and there are so many companies out there that can take advantage of our technology that maybe couldn't before these announcements. So by building this we've created a product that a mid-size company may have a small IT staff. Like I said at the beginning, may have VM admins who are also responsible for data protection. Now they can have what we bring to the market with best in class data protection. >> I want to follow up with you on simple and powerful. What is your perspective on simple? What does it mean for customers? >> I mean if you break it down, simple means simple to deploy two times faster than traditional data protection. Simple means easier to manage with modern HTML five interfaces that include the data protection, day to day tasks, also include reporting. Simple means easier to grow, growing in place from 24 terabytes up to 96 terabytes with just a simple software license to add at 12 terabyte increments. So all of those things come together to reduce the amount of time that an IT admin has to spend on data protection. >> So when I hear powerful and I hear mid-size customers I'm thinking, okay I want to bring enterprise class data protection down to the mid-size organization. Is that what it means? Can you actually succeed in doing that? >> If I'm an IT admin, I want to make sure that I can protect all of my data as quickly and efficiently as possible, and so we have the broadest support matrix in the industry. I don't have to bring in multiple products to support protection of my different applications, that's key. That's one thing. The other thing is I want to be able to scale. I don't want to have to be forced to bring in new products. With this, you have a logical five terabytes on prim. You can grow to protecting additional 10 terabytes in the Cloud, so that's another key piece of it, scalabililty. >> Petabytes, sorry, Petabytes. >> Petabytes. >> You said terabytes. (laughs) >> Of course, yes. What am I thinking? And then, last but not least, it's just performance. It runs on a 14G powered server. You're going to get the efficiency. You can protect five times as many VMs as you could without this kind of product. So all of those things come together for power, scalability, support matrix, and performance. >> Great, thank you. Okay, Ruya, let's talk about the business impact. Start with this sort of IT operations person. What does it mean for that individual? >> Yeah absolutely. So first, you're going to get your weekends back, right? So the product is just faster. We talked about it's simpler. You're not going to have to get a PhD on how to do data protection to be able to do your business. You're going to enable your V admins to be able to take on some of the tasks. So it's really about freeing up your weekends, having that sound mind that data protection is just happening, it works. We've already tried and tested this with some of the most crucial businesses with the most stringent service level requirements. It's just going to work, and by the way, you're going to look like a hero because with this 2U appliance, you're going to be able to support 15 petabytes across the most comprehensive coverage in the data center. So your boss is going to think you're just a super hero. >> Petabytes. >> Exactly. Petabytes, exactly. So it's tremendous for the IT user and also the business user. >> Wait, wait, what about the boss? What about the line of business? What does it mean to that individual? >> So if I'm the CEO or the CIO I really want to think about where am I putting my most skilled personnel, and my most skilled personnel, especially as IT is becoming so core to the business, is probably not best served doing data protection. So just being able to free up those resources to really drive applications or initiatives that are driving revenue for the business is critical. Number two, if I'm the boss, I don't want to overpay for data protection. Data protection is insurance for the business. You need it, but you don't want to overpay for it. So I think that lowest cost is a really critical requirement. The third one is really minimizing risk and compliance issues for the business. If I have the sound mind and the trust that this is just going to work, then I'm going to be able to recover my business no matter what the scenario, and that it's been tried and true in the biggest accounts across the world. I'm going to rest assured that I have less exposure to my business. >> Great. Ruya, Beth, thank you very much. Don't forget, we have an ask me anything crowd chat at the end of this session. So you can go in, login with Twitter, LinkedIn or Facebook and ask any question. All right, let's take a look at the product and then we're going to come back and get the analysts' perspective. Keep it right there. (electronic music)

>> Live from San Francisco, it's theCUBE covering DockerCon 18, brought to you by Docker and its ecosystem partners. >> Welcome back to theCUBE's coverage of DockerCon 2018. We are in San Francisco at Moscone, US. It's a spectacular day in San Francisco. It's a day to play hooky frankly, or play hooky and watch theCUBE. I'm Lisa Martin with John Troyer, and we're excited to welcome to theCUBE Abby Fuller, Developer Relations from AWS. Abby, great to have you here. >> Happy to be here. >> So you were a speaker at DockerCon 2018. Tell us a little bit about that and your role in Developer Relations. >> So I work in Developer Relations for AWS. So I used to be a devops engineer, and now I go around talking to customers and developers and other software engineers, and teaching them how to use things with AWS, or this morning it was teaching everyone how to build effective Docker images. >> So I read in your bio on the DockerCon website of the speakers that you're a container fan. We know you're a music fan, but you're also a container fan. What is it about that technology that you just go, "Oh, this is awesome, "and I can't wait to teach people "about the benefits of this"? >> So I switched over to container as a customer before I started working at AWS, and the biggest reasons for me, the first one was portability, so that I could do everything that I needed to run my application all in one place. So I think a big problem for a lot of developers is the whole what works on my machine? So being able to package everything together so that it worked on my machine, but also on a staging environment, a QA environment, and on your machine, that was the biggest thing for me. And that it removed some of the spaghetti code that came before, and it just made everything, it was all packaged nicely, I could deploy it a little bit more easily, a little bit faster, and I eliminated a lot of the why doesn't it work now when it worked before? >> Abby, one of the paradoxes of where we are in 2018 is AWS has been around for a decade, but yet here at the show, about half the folks raised their hand to the question, this is your first DockerCon? Are you just getting started with Docker and containers? So as an evangelist, Evangelist Developer Relations, you're the front line of talking with people at the grassroots. So can you talk a little bit about some of the different personas you encounter? Are you meeting people who are just getting started with their container journey? Or are you spending a lot of time kind of finessing the details about that API, APIs and changes and things like that at AWS? >> I think my favorite part about talking to AWS customers is that you get the whole range, right? So you get people that are just starting and they wanna know how do I build a container? How do I run it? How do I start from zero? And then you get the people that have been doing it for maybe a year or maybe two years, and they're looking for like advanced black belt tips, and then you get the other group which is not everyone is building a greenfield application, so then you get a really interesting subset where they're trying to move over from the whole monolith to micro services story. So they're trying to containerize and kind of adopt agile containerize approaches as they're moving over, and I think the best part is being able to talk to the whole range 'cause then it's never boring. >> What are some of the big barriers that you see for organizations that are maybe on the very very beginning of the journey or maybe before it, when you're talking with customers or developers, what are some of the things that you're hearing them say, "Ah, but what about these? "How can you help me eliminate these challenges?" >> Two big ones for me. The first one is the organizational changes that go around the infrastructure change. So it doesn't always work to just containerize what you already had, and then call it a day. So a lot of people are decomposing, they're going with micro services at the same time as they're going with containers. And I think wrapping your head around that kind of decomposition is the first kind of big challenge. And I think that we really just had to educate better. So show people, so here are some ways that you can break your service up, here are some things to think about when you're figuring out service boundaries. And I think the other one is that they often want a little bit of help when they're getting started. So either educational resources or how can AWS manage part of their infrastructure? Will they focus on the container part? So it's really interesting and it runs a whole gamut. >> Abby, you in Developer Relations, I love the trend, the community orient and trend, they're great, of peers helping peers, you're out there, you're wearing a Bruce Springsteen shirt right now, you made a Wu Tang joke in your talk today which is something that one did not do a few years back, right? You had to kinda dress up, and you were usually a man, and you wore a tie. >> Got my blazer on today. >> You look very sharp. Don't get me wrong. But as you talk to people, one, what's your day like or week like? How many miles do you have this year? That's private. But also as people come up to you, what do they ask you? Are you a role model for folks? Do people come up and say, "How can I do this too?" >> Yeah, so miles for this year. I think like 175,000. >> Already just in June? >> Already this year. So, this is a lot of what I do. I talk to all kinds of customers. I do bigger events like this, I do meet-ups, I do user groups, I go to AWS summits, and dev days and builders days, and things like that. I meet with customers. So day-to-day changes everyday. I'm obviously big on Twitter, spend a lot of time tweeting on planes. It really depends. This is a lot of what I do and I think people, I don't think you can ever really call yourself a role model, right? I love showing people that there's pass into tech that didn't start off with a computer science degree, that there's tons of ways to participate and be part of the tech community, 'cause it's a great community. >> You're not just a talker, you're a coder too. >> Yeah, yeah, so every job before this one with the exception of my very first job which was in sales. I was a dev ops engineer right up until I took the job at AWS, and I like to think that I never left, I'm just no longer on call. But I build my own demos, I write my own blog posts, I do all my own slides and workshops, so still super active, just not on call, so it's the best of all the worlds. >> So you went to Tufts, you didn't major in computer science. >> No. >> You are, I would say, a role model. You might not consider yourself one-- >> Well you can say it, yeah. >> I can say it exactly. It's PC if I say it. But, one of the things that's exciting to have females on the show, and I geek out on this is, we don't have a lot of females in tech. I mean, I think the last stat that I saw recently was less than 25% of technical roles are held by women. What was your career path if we can kinda pivot on that for a second, 'cause I think that's quite interesting. And what are some of the things that you've said, "You know what, I don't care. "I enjoy this, I wanna do this,"? 'Cause in all circumstances you are a role model, but I'd love to understand some of the things you encountered, and maybe some of your advice to those that'll be following in your footsteps. >> Yeah, so I went to school for politics. Programming was a little bit of a side hobby before that, mostly of the how can I do this thing, do this thing that it's not supposed to be doing? So I did that, I went to school. I took a computer science class my very last semester in school. I did not know that it was a thing before then, so I'm I guess a little slow in the comp sci uptake. And I was like, oh wow cool, this is an awesome, this could be an awesome career, but I don't know how to get into it. So I was like okay, I'm gonna go to a startup, and I'm gonna do whatever. So I take a sales job. I did that for maybe nine or 10 months. And I started taking on side projects. So how to write email templates in HTML that I could use that directly showed an impact to my sales job. Then the startup, as startups do, got acquired. And as part of the acquisition I moved my little CRM engineering job to the product team. And then, I'm gonna be honest, I bothered the CTO a lot. And I learned side projects. I was like I've learned Python now, what can you have for me? So I basically bothered him a lot until he helped me do some projects, and totally old enough now to admit that he was very kind to take a chance on me. And then I worked hard. I did a lot of online classes. I read a lot of books. I read a lot of blogs. I'm a big proponent in learning by doing. So I still learn things the same way. I read about it, I decide that I wanna use it, I try it out, and then at the point where I get where I don't quite know what's happening, I go back to documentation. And that got me through a couple of devops jobs until I got to evangelism. And I think the biggest advice I have for people is it's okay to not know what you want right away which is how I have a politics degree. But you can work at it. And don't be afraid to have mentors and communities and peers that can help you 'cause it's the best way to participate, and it's actually whether you have a comp sci job or not, it's still the best way to participate, and that you can have, there are so many nontraditional paths to tech, and I think everyone is equally valuable, because I think I write better coming from a liberal arts degree than I would have otherwise. So I think every skill that you bring in is valuable. So once you figure out what you want, don't be afraid to ask for it. >> The thing I'm hearing here is persistence. And it just reminded me, a quick pivot, of I hosted theCUBE at Women Transforming Technology just a couple weeks ago at VMWare, and they just made a massive investment, 15 million into a lab, a research lab at Stanford, to look at the barriers that women in tech are facing. And one of our guests, Pratima Rao Gluckman, just wrote a book called Nevertheless, She Persisted. It reminded me of you because that's one of the things that I'm hearing from you is that persistence that I think is a really unique thing there. Sorry, I just had to take a little side. >> I saw you looked that up. And actually I saw the title and I have not read it yet, but I have a flight back to New York after this so I'll have to find that. >> You've got time. >> Yeah. >> Over and over again as I talk with folks about IT and tech careers, right? It's that thinking expansively about your job, trying things, being a continuous learner, that is the thing that actually works. Maybe pivoting back to the tech for a sec then, obviously here container central, DockerCon 2018, Kubernetes actually was a big news this morning at the keynote, a big announcement, how Docker EE is gonna connect to Amazon EKS among others, kind of being able to manage the Kubernetes clusters up there in the cloud. And EKS actually just had, it just had its general availability I believe, right? In the last week or so? >> Yeah, so, excited to see EKS in the keynote this morning. We're always happy to deepen our partnerships. Yeah, and we've been in preview since re:Invent, and then we announced the general though of EKS, so Amazon Elastic Container Service for Kubernetes, long acronym. So EKS, we announced the GA last Tuesday. >> The interesting thing about AWS is somebody just compared it, I saw a tweet today to an industrial supply store and it's a huge warehouse full of tools that you can use, and that includes containers. But for containers, the three pieces that are the largest are EKS, ECS, and Fargate. Can you kinda tease those out for us really briefly? >> Yeah so envision if you would a flow chart. So if you wanna run a managed container on AWS, first you pick your orchestration tool, so EKS or ECS. ECS is the one that we've been working on for quite a few years now, so Elastic Container Service. Once you've chosen your orchestration tool, for ECS you have another set of choices which is either to run your containers in the EC2 mode which is manager, cluster, infrastructure as well, so the underlying EC2 hosts. And Fargate mode, where you only manage everything at the container level and task definition level, so no cluster management. >> And that's all taken care of for you. >> That's all taken care of for you. So Fargate I think is not actually a service in the traditional way that we would say that ECS is a service, and more of like an underlying technology, so that's what enables you to manage everything at just the container level and not at the cluster level. But I think the best way of describing it is actually is, there's a really nice quote floating around that said, "When I ask someone for a sandwich, "they don't wanna know the whole sandwich logistics chain, "so how do I get turkey, how do I get cheese, "how do I get mayo on the bread, "they just want the sandwich." So Fargate for, I think, a lot of people, is the sandwich. So I just want the sandwich, just give me your container, don't worry about the rest. >> So we've already established Abby has a lot of miles already in half a year, so I'm thinking two things. One, we should travel with her 'cause we're probably gonna get free upgrades. And two, you speak with a lot of customers. So tell us about that customer feedback loop. >> Something that I really love about working at Amazon is that so much of our roadmap is driven by customer feedback. So actually something that was really cool is that this morning, so ECS announced a daemon-scheduler, so run tasks one per host on every host in the cluster, so for things like metrics, containers, and log containers. And something that is so cool for me is that I asked for that as a customer, and I just watched us announced it this morning. It's incredible to see every single time that the feedback loop is closed, that people ask for it and then we build it. The same thing with EKS, right? We want you to have a great experience running your infrastructure on AWS, full stop. >> Can you give us an example of a customer that's really been impactful in terms of that feedback loop? One that really sticks out to you as a great hallmark of what you guys are enabling. >> I think that all of our customers are impactful in the feedback loop, right? Anyone from a really small startup to a really large enterprise. I think one that was really exciting to me was a very small Israeli startup. They went all in on managing no EC2 instances very quickly. They're called The Tree. So they were my customer speaker at the Tel Aviv summit, and they managed zero EC2 instances. So they have Fargate, they have Lambda, they managed no infrastructure themselves. And I just think it's so cool to watch people want things, and then adopt them so quickly. And the response on Twitter after the daemon-scheduler this morning is like, my favorite tweet was, "This is customer feedback done right." And I love seeing how happy people are when they ask for something or are saying, "Now that you've added that, "I can delete three Lambda functions "because you made it easy." And I love seeing feedback like that. So I think everyone is impactful, but that one stuck out to me as someone that adopted something incredibly quickly and have been so, they're just so happy to have a need solved for them. >> Well that's the best validation that you can get is through the voice of the customer. So to hear that must feel good that not only are we listening, but we're doing things right in a way that our customers are feeling how valuable they are to us. >> Happy customers are the best customers. >> They definitely are. >> Yeah. >> We learn a lot from the ones that aren't happy, and there's a lot of learnings there, but hearing that validation is icing on the cake. >> Always. >> Last question for you. With some of the announcements that came out today, and as this conference and its figure has grown tremendously, when I was walking out of the general session this morning, I took a photo because I don't think I've seen a general session room that big in a long time, and that was just at the Sapphire last week which has 20,000 attendees. I was impressed with how captivated the audience was. So last question, what excites you about some of the things that Docker announced today? >> So I think that's interesting. Something that's excited me in general is watching the community itself flourished. So there's many, there's Kubernetes CGroups, and there's user groups, the discussion online is always incredibly rich and vibrant, and there are so many people that are just so excited for anything. It's all companies building what they're looking for. And I love seeing things like the Docker Enterprise Edition announcement this morning where the demo is EKS, but I just love seeing customers get the choice to do whatever they want. They have all the options out there, and that you can see how much more rich and vibrant everything is. From even a couple years ago, there's more people every year, there's more sessions every year, the sessions are bigger every year. And I just love that. And I love seeing when people get so excited, and then seeing people that came to your talk two years ago, come back and give their own talk I think is amazing. >> Oh, talk about feedback. That must have felt really good. >> I think it's not a reflection on me, it's a reflection on the community. And it's a very supportive community, and it's a very excited and curious audience. So if you see their reception to other people that talk a lot being like, oh we're really happy to have you, then the next year you're like, well I have a story and I wanna tell it, so I'm gonna sit in my own session, and I think that's the best. >> Well Abby, it's been such a pleasure to have you on theCUBE, thank you. >> Thank you for having me. >> Thank you for stopping by. And your energy is infectious so you'll have to come back. >> Anytime. >> We wanna thank you for watching theCUBE. I'm Lisa Martin with John Troyer, live from San Francisco at DockerCon 2018. Stick around, we'll be right back after a short break. (upbeat music)

>> Live from San Francisco, it's theCUBE. Covering DockerCon '18. Brought to you by Docker and its ecosystem partners. >> Welcome back to theCUBE. We are live in San Francisco at DockerCon 2018. I'm Lisa Martin with John Troyer on a stunning day here in San Francisco. This event draws between 5,000 and 6,000 people in only its fifth year. They did a very good job during the general session this morning, John, of having some great female leaders on stage and we're very pleased to welcome another female leader to theCUBE for the first time. Alex Qin, you are the Director of Technology at Gakko. Welcome to theCUBE. >> Thank you, thank you. It's great to be here. >> So, you're speaking here at DockerCon 2018, I want to get to that in a second, but tell us a little bit about Gakko. What do you guys do? >> Um, yeah. So we're a global education design studio based in Tokyo and New York and what we do is we put on experimental education programs and build experimental education technology that aim to reclaim the magic of learning. So, we put on summer camps, we have coding classes, music classes and we build software for early learners. >> And by early learners what age group are you talking about? >> So ages three to five. What we build is beautiful story and art driven apps for kids ages three to five to be able to spend time more thoughtfully on tablets 'cause nowadays kids are always on tablets no matter what we do and so what we want to do is create a world that they can be in, in which parents feel like, this is a good place for my child to spend time. They're learning, it's artful, it's thoughtfully built. >> Great, well Alex you are also the founder of The Code Collective. >> The Code Cooperative, yes. >> The Code Cooperative, I'm sorry. How did you get started with that and can you tell us a little bit about that as well? >> Yes, so The Code Cooperative is my passion project and I started it in 2016, the day after the presidential elections actually, and it's an organization that teaches formerly incarcerated individuals computer literacy and coding, so that they can build websites and technical solutions to the problems they've identified in the criminal justice system. >> Some examples of that might be? >> A story I love to tell is from the pilot class. I had one student who was a 65 year old man and he'd been in prison for over 20 years and so at 65, he took our class and he learned HTML, CSS and JavaScript and built a website that aims to educate visitors about the legacy of slavery and Jim Crow in the criminal justice system today. Just like an interactive quiz. Yeah, that was really cool. It was called The Criminal Injustice System. >> Nice, nice. >> What were some of the drivers that really led you to go, you know what? We've got a huge opportunity here to take some of these people who have had made some different choices and really, sort of, rehabilitate them in a way that's gonna enable tech for good. What were some of those things that you just went, we've got to do this? >> That's a good question. Well, I read the book, The New Jim Crow, which you may have heard of. It's an incredible book that really details a lot of the problems that exist today within the U.S. criminal justice system and I thought to myself, I want to learn more about the justice system and contribute positively to justice system reform, but I don't know anything about it. So what I should do is work with people who have been through the system, learn from them and empower them to highlight the issues that they see within the justice system and that's something that I think is really important. When it comes to building technology, right now the gatekeepers of tech are kind of a homogenous group and we tend to build tech solutions for the entire world, but actually the people who are best equipped to solve problems are those who have experienced them and so that's why I decided to start The Code Cooperative. >> Nice. Alex, you're talking here, you've got an interesting titled session, I'll make sure I get it right, Shaving My Head Made Me a Better Programmer. If I can connect that to the rest of the DockerCon, maybe, I mean, Docker has been very good at their whole history about developer experience, making things easier for people and I think sometimes people don't realize not only when you make things easier, you actually can bring in new audiences. Kids, prisoners, right, are able to use today's technology where 30, 40 years ago they wouldn't have had access to it because it's easier, it's more powerful, it's more ubiquitous. But sometimes we get stuck in old tropes and so I'd love for you to kind of talk a little about your talk and kind of, what you're going to be talking about here at the show. >> Sure, yes. So, my talk is called Shaving My Head Made Me a Better Programmer and it's a little bit of a misleading title, but basically it's the story of my journey though the tech industry as a minority woman. So I studied computer science and I've been a software engineer for my entire career and yet, I've encountered a lot of challenges because of my gender, because of how I present to the world and when I shaved my head, a lot of those challenges kind of disappeared because I wasn't perceived as feminine anymore and so when I realized that tech isn't the meritocracy that I thought it was, I kind of started on this new quest to make tech as diverse and inclusive as possible so that people from all backgrounds, all genders can learn to code and write code happily and safely and it's just the story of how that happened and the lessons I've learned and some tips on how to make organizations more inclusive because that's the bulk of my work now. >> So you were a C.S. major in New York? >> Yes. >> So were you always interested in STEM as a kid or was it something that you got into when you were in college? What was that sort of age that you found it really exciting and said, no matter what, even if there's very few women here, I love this, I want to do this? >> That's a great question. So I am originally from France, actually. And when I was growing up there was really little computer science education in schools, but I really wanted to be an astronaut when I got to college so I joined the engineering program at my school and I'd never coded at that point, but one of the requirements was an intro to programming class in Python. So I took it and I fell in love with it immediately and I was like, I'm majoring in computer science, this is so cool, this is the coolest thing I've ever done and as I entered the computer science world I realized, oh, there's not that many women here and actually, I'm treated very differently. So, I fell in love with it and then because I love it so much I just kind of powered through. >> Your passion is very palpable, so at any point did you feel, sort of, out of place? Going, I'm one of the only females here, or did you say, I don't care, I like this. >> Yeah, it's both. I mean, you feel out of place when there's very few people who look like you in the room. Even if you don't want to feel out of place, even if you try to pretend that's not the case, you can't help but feel that and when I was starting out and throughout my career, people didn't necessarily want to work with me, didn't believe I was a good programmer, even though I was at the top of all my classes and so even though I tried to make the most out of my experience, I couldn't really escape the stigma attached to my gender in this field. >> Alex, we're at an interesting part of our culture now, I suppose, especially online. On one hand, social media has elevated a lot of folks' voices that would not have been heard otherwise because of gatekeepers. On the other hand, we have our current online discourse, which is kind of, not very pleasant sometimes. So I am interested both kind of how you're navigating that online and then maybe as a followup, then as you work with companies, how you're working with them and what you're telling them, but in terms of online, I love Twitter and yet it frustrates me. Facebook as well, et cetera. How do you navigate that online yourself? >> That's a great question. Honestly, I have been kind of retreating from social media. I haven't really experienced too many negative interactions on social media because I'm not really a big presence there. I did kind of have a really bad experience once during a Grace Hopper conference. I tweeted something during the Male Allied panel of like, 2015, or something and that got picked up by some GamerGate writers and then a lot of people started tweeting negative things at me, but that's kind of the extent of my negative experiences online. I do think that, as you say, social media has allowed for uplifting of voices that were previously unheard, has allowed for activism to organize. There's so many positive things that come from social media and also it has a really nefarious affect on people and I think that something needs to change in terms of how these companies build their software. It needs to be safer for all people and also needs to be built more ethically. Less trying to manipulate our psyches. >> That's, I think, super important. Luckily at least that's a conversation now, right Lisa? That at least Facebook, I think eventually as a society we'll, I hope, we'll get through this and figure this out, but I don't feel like we're particularly literate with social at this point. But I did want to ask about your work with companies. You said you do talk with some companies about diversity and things like that, is there any either signs that folks are getting it right or things that you start off with as you're working, if someone asks, how do we become a more diverse workforce? >> Yeah, that's a good question. I can't really point to any companies that, I say, are doing amazing. There are some companies where I know folks are very happy. Slack is one of them, thoughtbot is another one of them. I'll say Gakko, but a few tips I generally give organizations is that you need to work to understand the problem. Why is there a lack of diversity in tech? Why is your team not diverse? Then you need to measure your data. You can't make a positive change if you don't know how much you're changing, right? So gather diversity data on your team, not just in terms of who's there, but who's in a leadership role. Who gets promoted? Who gets fired? Who's a manager? And then you need to commit. That's, I think, the place where a lot of people struggle is there's a lot of candidates who fit this, kind of, homogenous image of what a programmer is and so it can be easy sometimes to be like, well we need to hire someone right now so let's just hire this person. But in order to actually make a change you need to commit and you need to say I'm not going to compromise on the goals that we've set. >> You're absolutely right, that commitment word is exactly what's needed to drive that accountability to hold organizations up to that. I was just at VMware a couple of weeks ago in Palo Alto at the Women Transforming Technology event and we had a whole day of all talking with females in tech, which I always loved to do and theCUBE is very passionate about supporting that. The cultural change is imperative. We talk about digital transformation at every event and there's the CIO that says, hey we have to change the culture here to transform digitally, but also to start moving those numbers from, what, less than 25% of tech roles are held by women. The culture has to change. It seems like you're in a position, potentially, to actually influence the culture at these companies that you talk to about opening their eyes to commit. Does that excite you from within? >> Yes, I do talk to a lot of organizations about this, but I think the work that I do that might actually tip the scale is, basically, the education programs that I run in New York. All of my classrooms reflect the diversity of New York, both in terms of student and teacher bodies. So all of my students learn in an environment that is extremely diverse. They learn from teachers who look like them and I wish I learned to code in that way. Another important thing we teach our students is how to code as an ethical endeavor. So we teach our students to measure the ethical ramifications of their decisions when they build software so that hopefully the technologists of tomorrow, the CTO's of tomorrow they build code in a way that is best for humanity. They build code with empathy. >> Goin' back to your day job. You're working with kids. We talked about getting through social media, cultural change. Its going to depend on the next generation. So Alex, are the kids alright? Are they gonna save us? >> The kids are pretty alright. I mean, so my classroom is basically coding meets social entrepreneurship so all of our kids build an app that solves a problem they've identified in their communities and these kids are just coming up with the most beautiful solutions, like, more brilliant than any adult that I've met. I feel good about the future. >> Well, it's key to get those different perspectives and when you were saying, they're having the opportunity to code and create apps that are relevant to them that's where you can really ignite that passion. >> Exactly, that's so important >> It is important because when you're passionate about something, and we saw that on stage today with a lot of the Docker folks and Microsoft and McKesson, when you're passionate about something and really making a change, you can feel it. So it's good to hear that we're going in the right direction. Also, we're in this age, you talked about ethics, where it's essential. Because technology, we see a lot of examples where tech is not used for good and there's world leaders getting some of the leaders of tech companies together saying, I'm challenging you, make tech for good because we're seeing too much of the negative right now. How does that influence, whether it's the breaches at Equifax, or, there was a breach recently at MyHeritage, the DNA testing companies, to Cambridge Analytica. How do you see the kids, the young kids respond to that, going, that's a really poor use of tech. Are they aware of that? >> I think some kids are and in our classroom we spend some time talking about, we have discussions about, ethics of software. So that's something that's very important to us. But largely, most classrooms in the United States, no, I mean computer science education is not a standard in most classrooms in the US. In New York state, only 1% of high schoolers actually have access to any kind of computer science education and so most kids, they might hear tid bits from the T.V. or social media or something, but they're not necessarily informed enough to make one, good decisions as consumers and two, good decisions as potential technologists. So that's something that we are trying to spread and I hope other folks are also trying to work on. >> Another thing that I think is shocking is when we were at the Women Transforming Technology event just a few weeks ago at VMware in Palo Alto, they just announced with Stanford, Stanford is investing 15 million dollars into their gender research. VMware and Stanford wanting to look at what are the barriers for women in tech and minorities in tech and starting to dissolve some of those barriers. One of the things they actually had in their press release announcing this big 15 million dollar investment from VMware and Stanford is a Mckinsey report that said 20%, sorry, enterprise organizations that have females in management positions, probably executive management positions, didn't specify positions, are 20% more profitable. You just think, the numbers are saying when you have more thought diversity, you're actually going to be a more profitable organization, but I think to your point earlier, Alex, there has to be a commitment and there has to be a group within an organization that stands accountable. >> Absolutely. >> So we are thankful for you. (Alex laughs) for donating some of your time today to tell us what you're doing, it's good to hear the next generation, John, I think they got our backs. >> Alright, that's good. >> And Alex, have a great time with your very provocative session this afternoon. >> Thank you. >> We thank you so much for your time and it's really cool to hear how you're using your passion for tech for good. >> Thank you so much, it was great to be here. >> We want to thank you for watching theCUBE. I'm Lisa Martin with John Troyer. From San Francisco at DockerCon 2018. Stick around, John and I will be right back with out next guest. (upbeat music)

(energetic music) >> [Narrator] From San Francisco, it's theCUBE, covering Radio 2018. Brought to you by VMware. >> Hello everyone. Welcome to the special CUBE coverage here in San Francisco, California for VMware's Radio 2018 event. This is their R&D big event kickoff. It's like a sales kickoff for engineers, as Steve Herrod said on stage. Out next guest is Mornay Van Der Walt, VP of the Explore Group, Office of the CTO. Also, program chair of the Event Today Conference, working for the collective of people within VMware on a rigorous selection committee for a high bar here at your event. Welcome to theCUBE. Thanks for joining me. >> Thank you. >> Talk about the event, because I know a lot of work went into it. Congratulations, the talks were amazing. I see the schedule. We have Pat Gelsinger coming on later today. We just had Ray O'Farrell on. This is like the, I don't want to say, Burning Man of Vmware, but this is really a recognition, but also really important innovation. Take a minute to talk about the process that you go through to put this together. It's a fantastic event. The smartest minds, the cream rises to the top. It's hard, it's challenging, it's a team effort, but yet you gotta ride the right waves. >> Right. So, RADIO: R&D Innovation Offsite. And as you said, it is tough because we've got this huge R&D community and they've all got amazing ideas. So they get the opportunity to submit ideas. I think this this year we have over 1,700 ideas submitted, and at the end of the day we're only going to showcase 226 of those ideas across research programs, posters, breakout sessions, Just-In-Time BOFs, Birds Of a Feather. You know, so, the bar is high. we've got a finite amount of time, but what's amazing is we take these ideas, and we don't just showcase them at RADIO. We have four other programs that give us the ability to take those ideas to the next level. So when we think about the innovation programs that come out of OCTO, this is really to drive what we call "Off-Road Map Innovation." So Raghu and Rajiv, with our Product Cloud Services Division, are driving road map, zero to three years out the stuff that you can buy from sales, >> [Furrier] Customer centric? >> Customer centric, yeah. OCTO is providing an innovation program structure, these five programs: Tech Talks, Flings, Borathons, RADIO, and xLabs, and as a collective, they are focused on off-road map innovation. Maybe something that's-- >> Give me an example of what that means, Off-Road Map. >> Sure. So last year at RADIO we did a paper that was showcased on functions as a service. So you think of AWS Lambda, right. [Furrier] Yep, yep >> VM was uniquely positioned, with the substrate, to manage and orchestrate VM's containers and whynot functions. So this radio paper was submitted, I then, as the xLabs group, said we're going to fund this, but given where we are in this market, we said, "Alright, we'll fund this for 12 months." So, we're incubating functions as a service. In July/August time frame, that'll actually exit xLabs into the Cloud Native business. >> It's a real rapid innovation. >> Very rapid. >> Within a 12 month period, we're gonna get something into a BU that they can take it to market. >> Yeah, and also I would say that this also I've seen from the talks here, there's also off-road map hard problems that need to kind of get the concepts, building blocks, or architecture... >> [Van Der Walt] Correct. >> With the confluence of hitting, whatever, its IOT or whatever, blockchains, seeing things like that. >> [Van Der Walt] Yeah. Correct. >> Is that also accurate too? >> Very true. And, you know, Ray had a great slide in his keynote this morning, you know, we spoke about how we started in 2003, when he joined the company, it was all about computer virtualization. Fast-forward 15 years, and you look at our strategy today, it's any Cloud, any device, any app, right? Then, you gotta look to the future, beyond there, what we're doing today, what are the next twenty years going to look like? Obviously, there's things like, you know, blockchain, VR, edge computing, you know, AIML... >> [Furrier] Service meshes? >> Services meshes, adaptive security. And, you know, people say, "Oh, AIML, that's a hot topic right now, but if you look back at VM ware, we've been doing that since 2006. Distributed resource scheduler: a great example of something that, at the core of the product, was already using ML techniques, you know, to load-balance a data center. And now, you can load-balance across Clouds. >> It's interesting how buzzwords can become industry verticals. We saw that with Hadoop; it didn't really happen, although it became important in big data as it integrates in. I mean, I find that you guys, really from the ecosystem we look at, you guys have a really interesting challenge. You started out as "inside the box," if you will. I saw your old t-shirt there from the 14 year history you guys have been doing this event. Great collection of t-shirts behind me if you can't see it. It's really cool. But infrastructures, on premise, you buy, it's data center, growth, all that stuff happened. Cloud comes in. Big data comes in. Now you got blockchain. These are big markers now, but the intersection of all these are all kind of touching each other. >> [Van Der Walt] Correct. >> IOT...so it's really that integration. I also find that you guys do a great job of fostering innovation, and always amazed at the VM world with some great either bechmarks or labs that show the good stuff. How do you do it? Walk me through the steps because you have this Explorer program, which is working. >> [Van Der Walt] Yeah >> It's almost a ladder, or a reverse ladder. Start with tech talks, get it out to the marketplace... >> [Van Der Walt] Do a hackathon. >> Hackathon. Take us through the process. So there's four things: tech talks, borathons, which is the meaning behind the name, flings, and xLabs. >> Correct >> Take us through that progression. >> ... and RADIO, of course. >> And RADIO, of course, the big tent event. Bring it all together. >> So, I'm an engineer. I have a great idea. I wanna socialize it; I wanna get some feedback. So, at VMWare, we offer a tech talk platform. You come, you present your idea. It's live. There'll be engineers in the audience. We also record those, and then those get replayed, and engineers will say, "You know, have you thought about this?" or "Have you met up with Johnny and Mary?" They're actually working on something very similar. Why don't you go and, you know, compare ideas? I can actually make that very real. I was in India in November, and we were doing a shark tank for our xLabs incubator, and this one team presented an idea on an augmented reality desktop. We went over to another office, actually the air watch office, and we did another shark tank there. Another team pitched the exact same idea, so I looked at my host, and I said, "Do these two teams know each other?" and the guy goes, "Absolutely not," so what did we do? We made the connection point. Their ideas were virtually identical. They were 25 kilometers apart. Never met. >> [Furrier] Wow. >> You know, so when, that's one of the challenges when your company becomes so big, you've got this vast R&D organization that's truly global, in one country 25 kilometers apart, you had two teams with the same idea that had never met. So part of the challenge is also bringing these ideas together because, you know, the sum of the parts makes for a greater whole. >> And they can then collectively come together then present to RADIO one single paper or idea. >> [Van Der Walt] Absolutely, or go ahead and say, you know what, let's take this to the next step, which would be a borathon, so borathons are heckathons. >> Explain the name because borathon sounds like heckathon, so it is, but there's a meaning behind the name borathon. What is the meaning? >> Sure. So, our very first build repository was named after Bora Bora, and so we paid homage to that, and so, instead of saying a heckathon, we called it a borathon. And one of our senior engineers apparently came up with that name, and it stuck, and it's great. >> So it's got history, okay. So, borathons is like ... okay, so you do tech talks, you collaborate, you socialize the idea via verbal or presentation that gets the seeds of innovation kinda planted. Borathon is okay, lets attack it. >> Turn it into a prototype. >> Prototype. >> And it gets judged, so then you get even more feedback from your most senior engineers. In fact ... >> And there's a process for all this that you guys run? >> Yeah, so the Explorer groups run these five innovation programs. We just recently, in Palo Alto, did a theme borathon. Our fellows and PE's came together. Decided the theme should be sustainability, and we mixed it up a little bit. So, normally, at a borathon, teams come with ideas that they've already been developing. For this one, the teams had no idea what the theme was going to be, so we announced the theme. Then, they showed up on the day to learn what the five challenges were going to be, and some of those challenges, one of them was quite interesting. It was using distributed ledger to manage microgrids, and that's a ... >> A blockchain limitation >> Well, it's a project that's, you know, is near and dear to us at VMWare. We're actually going to be setting up a microgrid on campus, and if you think about microgrids, and Nicola Acutt can talk more to this, we're gonna be looking at, you know, how can we give power back to the city of Palo Alto? Well, imagine that becoming a mesh network. >> [Furrier] With token economics. >> How do you start tracking this, right? A blockchain would be a perfect way to do this, right? So, then, you take your ideas at a borathon, get them into a prototype, get some more feedback, and now you might have enough critical mass to say, "Alright, I'm going to present a RADIO paper next year." So, then, you work as a team; get that into the system. >> [Furrier] And, certainly, in India and these third-world countries now becoming large, growing middle-class, these are important technologies to build on top of, say, mobile... >> [Van Der Walt] Absolutely. >> And with solar and power coming in, it's a natural evolution, so that's good use case. Okay, so, now I do the borathon. I've got a product. Flings? >> It's a prototype, right, so now ... >> You can socialize it, you have a fling, you throw it out there, you fling it out there What happens? >> Yeah, so, I've done something at a borathon. It's like, I want to get some actual feedback from the ecosystem: our customers and partners. That example I used with vSAN. You know, vSAN launched. We wanted to get some health analytics. The release managers were doing their job. The products got a ship on the state. Senior engineers on the team got a health analytics tool out as a fling. It got incredible feedback from the community. Made it into the next release. We did the same with the HTML clients, right? And that's been in the press lately because, you know, we've got Rotoflex. Now, there's HTML, but that actually started - two teams started working on that. One team just did HTML >> a very small portion of the HTML client, presented a RADIO paper. Two years later, another team, started the work, and now we have a full-fledged HTML client that's embedded into the VIS via product. >> [Furrier] So, the fling brings in a community dynamic, it brings in new ideas, or diversity, if you will. All kinds of diverse ideas melting together. Now, xLabs, I'm assuming that's an incubator. That brings it together. What is xLabs? Is that an incubator? You fund it? What happens there? >> So with an xLabs, the real way to think about it, it's truly an incubator. I don't want to use the word "start-up" there because you've clearly got the protection of the larger VMware organization, so you're not being a scrappy start-up, but you've got a great idea, we see there's merit ... >> [Furrier] Go build a real product. >> We see it more being on the disruptive side, and so we offer two tracks in the xLabs. There's a light track, which typically runs three to six months, and you're still doing your day job. You know, so you're basically doing two jobs. You know, we fund you with a level of funding that allows you to bring on extra contracting, resources, developers, etc., and you're typically delivering one objective. The larger xLab is the full-track, so functions as a service. Full-track, we showcased it as a RADIO paper last year. We said, "Alright, we're going to fund this. We're going to give it 12 months worth of funding, and then it needs to exit into a business unit," and we got lucky with that one because we were already doing a lot of work with containers, the PKS, the pivotal. >> [Furrier] Do the people have to quit their day job, not quit their day job, but move their resource over? >> [Van Der Walt] Absolutely. >> The full-track is go for it, green light >> Yep >> Run as fast as you can, take it to this business unit. Is the business unit known as the end point in time? Is it kind of tracked there, or is it more flexible still. >> Not all the time. You know so sometimes, with functions it was easier, right? So, we know we've got pull for zone heading up Cloud native apps. The Cloud native business unit is doing all the partnerships with PKS. That one makes sense. >> [Furrier] Yeah. >> We're actually doing one right now, another xLabs full, called network slicing, and it's going to play into the Telco space. We've obviously got NFV being led by Shekar and team, but we don't know if network slicing, when it exits, and this one is probably going to have a longer time arise and probably 24-36 months. Does it go into the NFV business unit, or does it become its own business unit. >> [Furrier] That's awesome. So, you got great tracks, end to end, so you have a good process. I gotta ask you the question that's on my mind. I think everyone would look at this, and some people might look at Vmware as, and most people do, at least I do, as kind of a cutting-edge tier one company. You guys always are a great place to work. Voted as, get awards for that, but you take seriously innovation and organic growth in community and engineering. Engineering and community are two really important things. How do you bring the foster culture because engineers can be really pissed off. "Oh my god! They're idiots that make the selection!" because you don't want engineers to be pissed cuz they're proud, and they're inventing. >> Yep, yep. >> So, how to manage the team approach? What's the cultural secret in the DNA that makes this so successful over 14 years? >> So, before I answer that question, I think it's important to take a step back. So, when we think about innovation, we call this thing the Vmware "innovation engine." It's really three parts to it, right? If you think about innovation at its core: sustaining, disruptive, internal, external, And, so, we've got product Cloud Services group, Raghu and Rajiv, we've got OCTO, headed up by Ray, we've got corp dev headed up by Shekar. Think of it as it's a three-legged stool. You take one of those legs away, the stool falls over. So, it's a balancing act, right? And we need to be collaborating. >> [Furrier] And they're talking to each other all the time. >> We're talking to each other all the time, right? Build or buy? Are we gonna do something internal, or we gonna go external, right? You think something about acquisitions like Nicira, right? We didn't build that; we bought it. You think about Airwatch, right? Airwatch put us into the top right quadrant from Gartner, right? So, these are very strategic decision that get made. Petchist presented at Dell emc world, Dell Technologies world. He had a slide on there that showed, it was the Nicira acquisition, and then it sort of was this arc leading all the way up to VeloCloud, and when you saw it on one slide, it made perfect sense. As an outsider looking in, you might have thought, "Why were they doing all these things? Why was that acquisition made? But there's always a plan, and that plan involves us all talking across. >> [Furrier] Strategic plan around what to move faster on. >> Correct >> Because there's always the challenge on M&A, if they're not talking to each other, is the buy/build is, you kinda, may miss a core competency. They always ... what's the core competency of the company? And should you outsource a core competency, or should you build it internally? Sometimes, you might even accelerate that, so I think Airwatch and Nicira, I would say, was kinda on the edges of core competency, but together with the synergies ... >> [Van Der Walt] Helped us accelerate. >> And I think that's your message. >> [Van Der Walt] Yep. >> Okay, so that's the culture. How do you make, what's the secret sauce of making all this work? I mean, cuz you have to kinda create an open, collaborative, but it's competitive. >> [Van Der Walt] Absolutely. >> So how do you balance that? >> You know, so clearly, there's a ton of innovation going on within the prior Cloud services division. The stuff that's on the truck that our customers can buy today, alright? We also know we gotta look ahead, and we gotta start looking at solving problems that aren't on the truck today, alright? And, so, having these five programs and the collective is really what allows us to do that. But at the same time, we need to have open channels of communication back into corp dev as well. I can give you examples of, you know, Shekar and his team might be looking at Company X. We're doing some exploratory work, IOT, I did an ordered foray. IOT is gonna be massive; everybody knows that, but you know what's going to be even more massive is all the data at the edge, and what do you do with that data? How do you turn that data into something actionable, right? So, if you think about a jet engine on a big plane, right? When it's operating correctly, you know what all the good levels are, the metrics, the telemetry coming off it. Why do I need to collect that and throw it away? You're interested in the anomalies, right? As we start thinking about IOT, and we start thinking all this data at the edge, we're going to need a different type of analytics engine that can do real-time analytics but not looking at the norm, looking at the deviations, and report back on that, so you can take action on that, you know? So, we started identifying some companies like PubNub, Mulesoft, too, just got acquired, right? Shekar and his team were looking at the same companies, and was like, "These companies are interesting because they're starting to attack the problem in a different way. We do that at Vmware all the time. You think about Appdefense. We've taken a completely different approach to security. You know what the good state is, but if you have a deviation, attack that, you know? And then you can use things like ... >> It's re-imagining, almost flipping everything upside-down. >> Yeah, challenging the status quo. >> Yeah, great stuff, great program. I gotta ask you a final question since it's your show here. Great content program, by the way. Got the competition, got the papers, which is deep, technical coolness, but the show is great content, great event. Thanks for inviting us. What's trending? What's rising up? Have you heard or kind of point at something you see getting some buzz, that you thought might get buzz, or it didn't get buzz? What's rising of the topics of interest here? What's kind of popping out for you; what's trending if I had to a Twitter feed, not Twitter feed, but like top three trending items here. >> Well, I'll take it back to that last borathon that we did on sustainability. We set out the five challenges. The challenge that got the most attention was the blockchain microgrid. So, blockchain is definitely trending, and, you know, the challenge we have with blockchain today is it's not ready for the enterprise. So, David Tennenhouse and his research group is actually looking at how do you make blockchain enterprise ready? And that is a difficult problem to solve. So, there's a ton of interest in watching ... >> [Furrier] Well, we have an opinion. Don't use the public block chain. (both laugh) >> So, you know, that's one that's definitely trending. We have a great program called Propel, where we basically attract the brightest of the brightest, you know, new college grads coming into the company, and they actually come through OCTO first and do a sort of onboarding process. What are they interested in? They're not really interested in working for a particular BU, but, you know, when we share with them, "You're gonna have the ability to work on blockchain, AI, VR, augmented reality, distributed systems, new ways of doing analytics >> that's what attracts them. >> [Furrier] And they have the options to go test and put the toe in the water or jump in deep with xLabs. >> Absolutely >> So, I mean, this is like catnip for engineers. It draws a lot of people in. >> Absolutely, and, you know, we need to do that to be competitive in the valley. I mean, it's a very hard marketplace. >> Great place to work. >> You guys have a great engineering team. >> Congratulations for a great event, Mornay, and thanks for coming on theCUBE. We're here in San Francisco for theCUBE coverage of RADIO 2018. I'm John Furrier. Be back with more coverage after this break. Thanks for watching. (upbeat techno music)