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Show Wrap | KubeCon + CloudNativeCon NA 2022


 

(bright upbeat music) >> Greetings, brilliant community and thank you so much for tuning in to theCUBE here for the last three days where we've been live from Detroit, Michigan. I've had the pleasure of spending this week with Lisa Martin and John Furrier. Thank you both so much for hanging out, for inviting me into the CUBE family. It's our first show together, it's been wonderful. >> Thank you. >> You nailed it. >> Oh thanks, sweetheart. >> Great job. Great job team, well done. Free wall to wall coverage, it's what we do. We stay till everyone else-- >> Savannah: 100 percent. >> Everyone else leaves, till they pull the plug. >> Lisa: Till they turn the lights out. We're still there. >> Literally. >> Literally last night. >> Still broadcasting. >> Whatever takes to get the stories and get 'em out there at scale. >> Yeah. >> Great time. >> 33. 33 different segments too. Very impressive. John, I'm curious, you're a trend watcher and you've been at every single KubeCon. >> Yep. >> What are the trends this year? Give us the breakdown. >> I think CNCF does this, it's a hard job to balance all the stakeholders. So one, congratulations to the CNCF for another great KubeCon and CloudNativeCon. It is really hard to balance bringing in the experts who, as time goes by, seven years we've been all of, as you said, you get experts, you get seniority, and people who can be mentors, 60% new people. You have vendors who are sponsoring and there's always people complaining and bitching and moaning. They want this, they want that. It's always hard and they always do a good job of balancing it. We're lucky that we get to scale the stories with CUBE and that's been great. We had some great stories here, but it's a great community and again, they're inclusive. As I've said before, we've talked about it. This year though is an inflection point in my opinion, because you're seeing the developer ecosystem growing so fast. It's global. You're seeing events pop up, you're seeing derivative events. CNCF is at the center point and they have to maintain the culture of developer experts, maintainers, while balancing the newbies. And that's going to be >> Savannah: Mm-hmm. really hard. And they've done a great job. We had a great conversation with them. So great job. And I think it's going to continue. I think the attendance metric is a little bit of a false positive. There's a lot of online people who didn't come to Detroit this year. And I think maybe the combination of the venue, the city, or just Covid preferences may not look good on paper, on the numbers 'cause it's not a major step up in attendance. It's still bigger, but the community, I think, is going to continue to grow. I'm bullish on it. >> Yeah, I mean at least we did see double the number of people that we had in Los Angeles. Very curious. I think Amsterdam, where we'll be next with CNCF in the spring, in April. I think that's actually going to be a better pulse check. We'll be in Europe, we'll see what's going on. >> John: Totally. >> I mean, who doesn't like Amsterdam in the springtime? Lisa, what have been some of your observations? >> Oh, so many observations. The evolution of the conference, the hallway track conversations really shifting towards adjusting to the enterprise. The enterprise momentum that we saw here as well. We had on the show, Ford. >> Savannah: Yes. We had MassMutual, we had ING, that was today. Home Depot is here. We are seeing all these big companies that we know and love, become software companies right before our eyes. >> Yeah. Well, and I think we forget that software powers our entire world. And so of course they're going to have to be here. So much running on Kubernetes. It's on-prem, it's at the edge, it's everywhere. It's exciting. Woo, I'm excited. John, what do you think is the number one story? This is your question. I love asking you this question. What is the number one story out KubeCon? >> Well, I think the top story is a combination of two things. One is the evolution of Cloud Native. We're starting to see web assembly. That's a big hyped up area. It got a lot of attention. >> Savannah: Yeah. That's kind of teething out the future. >> Savannah: Rightfully so. The future of this kind of lightweight. You got the heavy duty VMs, you got Kubernetes and containers, and now this web assembly, shows a trajectory of apps, server-like environment. And then the big story is security. Software supply chain is, to me, was the number one consistent theme. At almost all the interviews, in the containers, and the workflows, >> Savannah: Very hot. software supply chain is real. The CD Foundation mentioned >> Savannah: Mm-hmm. >> they had 16,000 vulnerabilities identified in their code base. They were going to automate that. So again, >> Savannah: That was wild. >> That's the top story. The growth of open source exposes potential vulnerabilities with security. So software supply chain gets my vote. >> Did you hear anything that surprised you? You guys did this great preview of what you thought we were going to hear and see and feel and touch at KubeCon, CloudNativeCon 2022. You talked about, for example, the, you know, healthcare financial services being early adopters of this. Anything surprise either one of you in terms of what you predicted versus what we saw? Savannah, let's start with you. >> You know what really surprised me, and this is ironic, so I'm a community gal by trade. But I was really just impressed by the energy that everyone brought here and the desire to help. The thing about the open source community that always strikes me is, I mean 187 different countries participating. You've got, I believe it's something like 175,000 people contributing to the 140 projects plus that CNCF is working on. But that culture of collaboration extends far beyond just the CNCF projects. Everyone here is keen to help each other. We had the conversation just before about the teaching and the learnings that are going on here. They brought in Detroit's students to come and learn, which is just the most heartwarming story out of this entire thing. And I think it's just the authenticity of everyone in this community and their passion. Even though I know it's here, it still surprises me to see it in the flesh. Especially in a place like Detroit. >> It's nice. >> Yeah. >> It's so nice to see it. And you bring up a good point. It's very authentic. >> Savannah: It's super authentic. >> I mean, what surprised me is one, the Wasm, or web assembly. I didn't see that coming at the scale of the conversation. It sucked a lot of options out of the room in my opinion, still hyped up. But this looks like it's got a good trajectory. I like that. The other thing that surprised me that was a learning was my interview with Solo.io, Idit, and Brian Gracely, because he's a CUBE alumni and former host of theCUBE, and analyst at Wikibon, was how their go-to-market was an example of a modern company in Covid with a clean sheet of paper and smart people, they're just doing things different. They're in Slack with their customers. And I walked away with, "Wow that's like a playbook that's not, was never, in the go-to-market VC-backed company playbook." I thought that was, for me, a personal walk away saying that's important. I like how they did that. And there's a lot of companies I think could learn from that. Especially as the recession comes where partnering with customers has always been a top priority. And how they did that was very clever, very effective, very efficient. So I walked away with that saying, "I think that's going to be a standard." So that was a pleasant surprise. >> That was a great surprise. Also, that's a female-founded company, which is obviously not super common. And the growth that they've experienced, to your point, really being catalyzed by Covid, is incredibly impressive. I mean they have some massive brand name customers, Amex, BMW for example. >> Savannah: Yeah. >> Great point. >> And I interviewed her years ago and I remember saying to myself, "Wow, she's impressive." I liked her. She's a player. A player for sure. And she's got confidence. Even on the interview she said, "We're just better, we have better product." And I just like the point of view. Very customer-focused but confident. And I just took, that's again, a great company. And again, I'm not surprised that Brian Gracely left Red Hat to go work there. So yeah, great, great call there. And of course other things that weren't surprising that I predicted, Red Hat continued to invest. They continue to bring people on theCUBE, they support theCUBE but more importantly they have a good strategy. They're in that multicloud positioning. They're going to have an opportunity to get a bite at the apple. And I what I call the supercloud. As enterprises try to go and be mainstream, Cloud Native, they're going to need some help. And Red Hat is always has the large enterprise customers. >> Savannah: What surprised you, Lisa? >> Oh my gosh, so many things. I think some of the memorable conversations that we had. I love talking with some of the enterprises that we mentioned, ING Bank for example. You know, or institutions that have been around for 100 plus years. >> Savannah: Oh, yeah. To see not only how much they've innovated and stayed relevant to meet the demands of the consumer, which are only increasing, but they're doing so while fostering a culture of innovation and a culture that allows these technology leaders to really grow within the organization. That was a really refreshing conversation that I think we had. 'Cause you can kind of >> Savannah: Absolutely. think about these old stodgy companies. Nah, of course they're going to digitize. >> Thinking about working for the bank, I think it's boring. >> Right? >> Yeah. And they were talking about, in fact, those great t-shirts that they had on, >> Yeah, yeah, yeah, yeah. were all about getting more people to understand how fun it is to work in tech for ING Bank in different industries. You don't just have to work for the big tech companies to be doing really cool stuff in technology. >> What I really liked about this show is we had two female hosts. >> Savannah: Yeah. >> How about that? Come on. >> Hey, well done, well done on your recruitment there, champ. >> Yes, thank you boss. (John laughs) >> And not to mention we have a really all-star production team. I do just want to give them a little shout out. To all the wonderful folks behind the lines here. (people clapping) >> John: Brendan. Good job. >> Yeah. Without Brendan, Anderson, Noah, and Andrew, we would be-- >> Of course Frank Faye holding it back there too. >> Yeah, >> Of course, Frank. >> I mean, without the business development wheels on the ship we'd really be in an unfortunate spot. I almost just swore on television. We're not going to do that. >> It's okay. No one's regulating. >> Yeah. (all laugh) >> Elon Musk just took over Twitter. >> It was a close call. >> That's right! >> It's going to be a hellscape. >> Yeah, I mean it's, shit's on fire. So we'll just see what happens next. I do, I really want to talk about this because I think it's really special. It's an ethos and some magic has happened here. Let's talk about Detroit. Let's talk about what it means to be here. We saw so many, and I can't stress this enough, but I think it really matters. There was a commitment to celebrating place here. Lisa, did you notice this too? >> Absolutely. And it surprised me because we just don't see that at conferences. >> Yeah. We're so used to going to the same places. >> Right. >> Vegas. Vegas, Vegas. More Vegas. >> Your tone-- >> San Francisco >> (both laugh) sums up my feelings. Yes. >> Right? >> Yeah. And, well, it's almost robotic but, and the fact that we're like, oh Detroit, really? But there was so much love for this city and recognizing and supporting its residents that we just don't see at conferences. You uncovered a lot of that with your swag-savvy segments, >> Savannah: Yeah. >> And you got more of that to talk about today. >> Don't worry, it's coming. Yeah. (laughs) >> What about you? Have you enjoyed Detroit? I know you hadn't been here in a long time, when we did our intro session. >> I think it's a bold move for the CNCF to come here and celebrate. What they did, from teaching the kids in the city some tech, they had a session. I thought that was good. >> Savannah: Loved that. I think it was a risky move because a lot of people, like, weren't sure if they were going to fly to Detroit. So some say it might impact the attendance. I thought they did a good job. Their theme, Road Ahead. Nice tie in. >> Savannah: Yeah. And so I think I enjoyed Detroit. The weather was great. It didn't rain. Nice breeze outside. >> Yeah. >> The weather was great, the restaurants are phenomenal. So Detroit's a good city. I missed some hockey games. I'd love to see the Red Wings play. Missed that game. But we always come back. >> I think it's really special. I mean, every time I talked to a company about their swag, that had sourced it locally, there was a real reason for this story. I mean even with Kasten in that last segment when I noticed that they had done Carhartt beanies, Carhartt being a Michigan company. They said, "I'm so glad you noticed. That's why we did it." And I think that type of, the community commitment to place, it all comes back to community. One of the bigger themes of the show. But that passion and that support, we need more of that. >> Lisa: Yeah. >> And the thing about the guests we've had this past three days have been phenomenal. We had a diverse set of companies, individuals come on theCUBE, you know, from Scott Johnston at Docker. A really one on one. We had a great intense conversation. >> Savannah: Great way to kick it off. >> We shared a lot of inside baseball, about Docker, super important company. You know, impressed with companies like Platform9 it's been around since the OpenStack days who are now in a relevant position. Rafi Systems, hot startup, they don't have a lot of resources, a lot of guerilla marketing going on. So I love to see the mix of startups really contributing. The big players are here. So it's a real great mix of companies. And I thought the interviews were phenomenal, like you said, Ford. We had, Kubia launched on theCUBE. >> Savannah: Yes. >> That's-- >> We snooped the location for KubeCon North America. >> You did? >> Chicago, everyone. In case you missed it, Bianca was nice enough to share that with us. >> We had Sarbjeet Johal, CUBE analyst came on, Keith Townsend, yesterday with you guys. >> We had like analyst speed dating last night. (all laugh) >> How'd that go? (laughs) >> It was actually great. One of the things that they-- >> Did they hug and kiss at the end? >> Here's the funny thing is that they were debating the size of the CNC app. One thinks it's too big, one thinks it's too small. And I thought, is John Goldilocks? (John laughs) >> Savannah: Yeah. >> What is John going to think about that? >> Well I loved that segment. I thought, 'cause Keith and Sarbjeet argue with each other on Twitter all the time. And I heard Keith say before, he went, "Yeah let's have it out on theCUBE." So that was fun to watch. >> Thank you for creating this forum for us to have that kind of discourse. >> Lisa: Yes, thank you. >> Well, it wouldn't be possible without the sponsors. Want to thank the CNCF. >> Absolutely. >> And all the ecosystem partners and sponsors that make theCUBE possible. We love doing this. We love getting the stories. No story's too small for theCUBE. We'll go with it. Do whatever it takes. And if it wasn't for the sponsors, the community wouldn't get all the great knowledge. So, and thank you guys. >> Hey. Yeah, we're, we're happy to be here. Speaking of sponsors and vendors, should we talk a little swag? >> Yeah. >> What do you guys think? All right. Okay. So now this is becoming a tradition on theCUBE so I'm very delighted, the savvy swag segment. I do think it's interesting though. I mean, it's not, this isn't just me shouting out folks and showing off t-shirts and socks. It's about standing out from the noise. There's a lot of players in this space. We got a lot of CNCF projects and one of the ways to catch the attention of people walking the show floor is to have interesting swag. So we looked for the most unique swag on Wednesday and I hadn't found this yet, but I do just want to bring it up. Oops, I think I might have just dropped it. This is cute. Is, most random swag of the entire show goes to this toothbrush. I don't really have more in terms of the pitch there because this is just random. (Lisa laughs) >> But so, everyone needs that. >> John: So what's their tagline? >> And you forget these. >> Yeah, so the idea was to brush your cloud bills. So I think they're reducing the cost of-- >> Kind of a hygiene angle. >> Yeah, yeah. Very much a hygiene angle, which I found a little ironic in this crowd to be completely honest with you. >> John: Don't leave the lights on theCUBE. That's what they say. >> Yeah. >> I mean we are theCUBE so it would be unjust of me not to show you a Rubik's cube. This is actually one of those speed cubes. I'm not going to be able to solve this for you with one hand on camera, but apparently someone did it in 17 seconds at the booth. Knowing this audience, not surprising to me at all. Today we are, and yesterday, was the t-shirt contest. Best t-shirt contest. Today we really dove into the socks. So this is, I noticed this trend at KubeCon in Los Angeles last year. Lots of different socks, clouds obviously a theme for the cloud. I'm just going to lay these out. Lots of gamers in the house. Not surprising. Here on this one. >> John: Level up. >> Got to level up. I love these 'cause they say, "It's not a bug." And anyone who's coded has obviously had to deal with that. We've got, so Star Wars is a huge theme here. There's Lego sets. >> John: I think it's Star Trek. But. >> That's Star Trek? >> John: That's okay. >> Could be both. (Lisa laughs) >> John: Nevermind, I don't want to. >> You can flex your nerd and geek with us anytime you want, John. I don't mind getting corrected. I'm all about, I'm all about the truth. >> Star Trek. Star Wars. Okay, we're all the same. Okay, go ahead. >> Yeah, no, no, this is great. Slim.ai was nice enough to host us for dinner on Tuesday night. These are their lovely cloud socks. You can see Cloud Native, obviously Cloud Native Foundation, cloud socks, whole theme here. But if we're going to narrow it down to some champions, I love these little bee elephants from Raft. And when I went up to these guys, I actually probably would've called these my personal winner. They said, again, so community focused and humble here at CNCF, they said that Wiz was actually the champion according to the community. These unicorn socks are pretty excellent. And I have to say the branding is flawless. So we'll go ahead and give Wiz the win on the best sock contest. >> John: For the win. >> Yeah, Wiz for the win. However, the thing that I am probably going to use the most is this really dope Detroit snapback from Kasten. So I'm going to be rocking this from now on for the rest of the segment as well. And I feel great about this snapback. >> Looks great. Looks good on you. >> Yeah. >> Thanks John. (John laughs) >> So what are we expecting between now and KubeCon in Amsterdam? >> Well, I think it's going to be great to see how they, the European side, it's a chill show. It's great. Brings in the European audience from the global perspective. I always love the EU shows because one, it's a great destination. Amsterdam's going to be a great location. >> Savannah: I'm pumped. >> The American crowd loves going over there. All the event cities that they choose are always awesome. I missed Valencia cause I got Covid. I'm really bummed about that. But I love the European shows. It's just a little bit, it's high intensity, but it's the European chill. They got a little bit more of that siesta vibe going on. >> Yeah. >> And it's just awesome. >> Yeah, >> And I think that the mojo that carried throughout this week, it's really challenging to not only have a show that's five days, >> but to go through all week, >> Savannah: Seriously. >> to a Friday at 4:00 PM Eastern Time, and still have the people here, the energy and all the collaboration. >> Savannah: Yeah. >> The conversations that are still happening. I think we're going to see a lot more innovation come spring 2023. >> Savannah: Mm-hmm. >> Yeah. >> So should we do a bet, somebody's got to buy dinner? Who, well, I guess the folks who lose this will buy dinner for the other one. How many attendees do you think we'll see in Amsterdam? So we had 4,000, >> Oh, I'm going to lose this one. >> roughly in Los Angeles. Priyanka was nice enough to share with us, there was 8,000 here in Detroit. And I'm talking in person, we're not going to meddle this with the online. >> 6500. >> Lisa: I was going to say six, six K. >> I'm going 12,000. >> Ooh! >> I'm going to go ahead and go big I'm going to go opposite Price Is Right. >> One dollar. >> Yeah. (all laugh) That's exactly where I was driving with it. I'm going, I'm going absolutely all in. I think the momentum here is building. I think if we look at the numbers from-- >> John: You could go Family Feud >> Yeah, yeah, exactly. And they mentioned that they had 11,000 people who have taken their Kubernetes course in that first year. If that's a benchmark and an indicator, we've got the veteran players here. But I do think that, I personally think that the hype of Kubernetes has actually preceded adoption. If you look at the data and now we're finally tipping over. I think the last two years we were on the fringe and right now we're there. It's great. (voice blares loudly on loudspeaker) >> Well, on that note (all laugh) On that note, actually, on that note, as we are talking, so I got to give cred to my cohosts. We deal with a lot of background noise here on theCUBE. It is a live show floor. There's literally someone on an e-scooter behind me. There's been Pong going on in the background. The sound will haunt the three of us for the rest of our lives, as well as the production crew. (Lisa laughs) And, and just as we're sitting here doing this segment last night, they turned the lights off on us, today they're letting everyone know that the event is over. So on that note, I just want to say, Lisa, thank you so much. Such a warm welcome to the team. >> Thank you. >> John, what would we do without you? >> You did an amazing job. First CUBE, three days. It's a big show. You got staying power, I got to say. >> Lisa: Absolutely. >> Look at that. Not bad. >> You said it on camera now. >> Not bad. >> So you all are stuck with me. (all laugh) >> A plus. Great job to the team. Again, we do so much flow here. Brandon, Team, Andrew, Noah, Anderson, Frank. >> They're doing our hair, they're touching up makeup. They're helping me clean my teeth, staying hydrated. >> We look good because of you. >> And the guests. Thanks for coming on and spending time with us. And of course the sponsors, again, we can't do it without the sponsors. If you're watching this and you're a sponsor, support theCUBE, it helps people get what they need. And also we're do a lot more segments around community and a lot more educational stuff. >> Savannah: Yeah. So we're going to do a lot more in the EU and beyond. So thank you. >> Yeah, thank you. And thank you to everyone. Thank you to the community, thank you to theCUBE community and thank you for tuning in, making it possible for us to have somebody to talk to on the other side of the camera. My name is Savannah Peterson for the last time in Detroit, Michigan. Thanks for tuning into theCUBE. >> Okay, we're done. (bright upbeat music)

Published Date : Oct 28 2022

SUMMARY :

for inviting me into the CUBE family. coverage, it's what we do. Everyone else leaves, Lisa: Till they turn the lights out. Whatever takes to get the stories you're a trend watcher and What are the trends this and they have to maintain the And I think it's going to continue. double the number of people We had on the show, Ford. had ING, that was today. What is the number one story out KubeCon? One is the evolution of Cloud Native. teething out the future. and the workflows, Savannah: Very hot. So again, That's the top story. preview of what you thought and the desire to help. It's so nice to see it. "I think that's going to be a standard." And the growth that they've And I just like the point of view. I think some of the memorable and stayed relevant to meet Nah, of course they're going to digitize. I think it's boring. And they were talking about, You don't just have to work is we had two female hosts. How about that? your recruitment there, champ. Yes, thank you boss. And not to mention we have John: Brendan. Anderson, Noah, and Andrew, holding it back there too. on the ship we'd really It's okay. I do, I really want to talk about this And it surprised going to the same places. (both laugh) sums up my feelings. and the fact that we're that to talk about today. Yeah. I know you hadn't been in the city some tech, they had a session. I think it was a risky move And so I think I enjoyed I'd love to see the Red Wings play. the community commitment to place, And the thing about So I love to see the mix of We snooped the location for to share that with us. Keith Townsend, yesterday with you guys. We had like analyst One of the things that they-- And I thought, is John Goldilocks? on Twitter all the time. to have that kind of discourse. Want to thank the CNCF. And all the ecosystem Speaking of sponsors and vendors, in terms of the pitch there Yeah, so the idea was to be completely honest with you. the lights on theCUBE. Lots of gamers in the obviously had to deal with that. John: I think it's Star Trek. (Lisa laughs) I'm all about, I'm all about the truth. Okay, we're all the same. And I have to say the And I feel great about this snapback. Looks good on you. (John laughs) I always love the EU shows because one, But I love the European shows. and still have the people here, I think we're going to somebody's got to buy dinner? Priyanka was nice enough to share with us, I'm going to go ahead and go big I think if we look at the numbers from-- But I do think that, I know that the event is over. You got staying power, I got to say. Look at that. So you all are stuck with me. Great job to the team. they're touching up makeup. And of course the sponsors, again, more in the EU and beyond. on the other side of the camera. Okay, we're done.

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Karthik Narain & Chris Wegmann, Accenture | AWS re:Invent 2021


 

(upbeat music) >> Hello, everyone. Welcome back to theCUBE's coverage of AWS re:Invent! 2021. I'm John Furrier, your host for the theCUBE, a lot of great action here. A lot of great solutions. Great keynote. The future of cloud's going to be all about purpose-built software platforms, enabling more and more SaaS, faster performance with custom chips, all enabling great stuff. I have two great guests here. Who are going to talk about it from Accenture. We've got Karthik Narain, global lead of Accenture's Cloud First. Welcome to the program. Good to see you and Chris Wegmann, AABG Accenture Amazon Business Group. Technology leads senior manager. Thanks for coming on. >> Great to be here. >> I was commenting before we came on about Accenture's work you guys been doing with the clouds in my article, I posted before re:Invent!. Dave Vellante coined the term superclouds, which we kind of just put out there, but the idea that people can build really strong platforms that enable a new kind of Saas has been the big wave. Connect has been a great example. We heard on stage from Adam, the CEO. Chris, this has been something that's been a real change where it's not just lift and shift and refactor, it's build value in a platform and new SaaS capabilities. What's your reaction to that? >> Yeah, I would absolutely agree. We've seen this change over time. We've seen the lift and shift and modernize and it's definitely moved into the Superclouds. I like the term, but you know, we call them cloud continuums, which we'll talk a little bit about, it's about building these purpose-built solutions. I think if you look at the keynote today, you look at, everybody that was on stage. United and everyone talking about what they're building, their technology companies now, they're not just the business. >> You guys did some new research, coining new terms and Cloud First. What is this all about? What is this new wave you guys are talking about? >> Yeah, so John, you know, few years ago, when people talked about cloud, they generally meant public cloud. I think the definition of cloud is changing and expanding. And from now on, whenever people talk about cloud, it's actually a cloud continuum. It's a continuum of capability from public to Edge and everything in between all seamlessly connected by Cloud First networks, which means all the capabilities that customers used to get from one public cloud destination. They can actually access that across the continuum, whether that be in their own private data center, using the capability of cloud with AWS's Outpost and other capabilities. Or they could use the capability in their Edge location, whether it's their retail centers, their warehouse locations, manufacturing and so on and so forth. So organizations are using the power of cloud beyond one purpose and one destination, but more as an operating system going forward. >> Chris, what's your take on this redefinition of cloud what's your take on it? >> I think it's much needed. I think Andy kicked it off last year when he recognized the term hybrid. We all, who've has been around a while kind of chuckled because they finally said the word. But if you look at the keynote today, they just continued it. Adam picked it up and ran with it. If you look at all the services, Wavelength and all the different services, there's not a single customer that I have, that's just using EC2 or S3 right. They're using all these different services you saw today. You saw all the different services that United put up on the screen. That DISH put up on the screen. So yeah, it's how people and companies, if they're truly going to transform and truly use cloud to transform, you have to use the whole continuum. >> Yeah. And I think the continuum message is a good one because if you look at what the evolution is, that was interesting to. Adam went on and did kind of a history lesson in the beginning, it felt like I was in the Star Wars movie, like back in the old days. And then you kind of progressed. You had to be really elite to roll your own cloud. And the hyperscalers did that, you saw that. Now you still have elite technical people, but now it's general purpose, or purpose built. It's like having prefabricated platforms and open source. We've learned that why do you want to reinvent the wheel if you don't have to? So if I want a call center I get Connect, if I want to have a big plugin platform, I can still build on top of and have that SaaS unique application. This seems logical. This is new. (laughter) This is the continuum. I mean, it seems obvious now looking at it, but how far along in are people getting this. Karthik, what's your take on this? >> I think customers are getting it. They are looking at cloud more as an operating system for their future innovation. They liked the concept that they got from the public cloud, which is easy configurability, consumability and automatability of their infrastructure assets. And when you can get that capability as an operating system for your entire enterprise, and you could innovate across the spectrum, that's extremely powerful. We see companies accelerating their adoption to cloud, but we are also seeing over the last three years, a lot of that adoption was using cloud as a migration destination. But now with the power of the cloud continuum, where innovation is available, that so many new services that Adam launched today, you could use truly cloud as an innovation engine. And we're actually seeing that the clients who are using the cloud continuum for innovation are doing much better than the ones that are using cloud as a migration destination. In fact, they're doing two X to three X use of cloud for innovation and uplifting knowlEdge where they are actually using three X more cloud for sustainability purposes. So huge, huge value. >> Yeah, I mean, this is a great point. Great insight, because what you're saying is essentially you can't hide anymore. The projects are either going to be successful or not. You can see whether it's useful or not, and now you're tying cloud adoption and outcomes together. Where you can look it and saying, we need to make this outcome work. Not for building, for building sake. Those projects were discovered during the pandemic. Why are we doing that? So you can't hide that ball anymore. >> Right and everybody's got to do it now, right? I mean, you don't have a choice. The pandemic is now forcing companies to change. They've changed. And that the research shows that the companies that have truly adopted the whole continuum are doing much better than the companies that didn't. >> What's pattern in this continuum research you guys, what's the big takeaway that you guys have found in that study, in that customer experience that you're having. What's the big, Aha moment. >> I think there are a few things. Number one surprising aspect is that the companies that use cloud for a broader innovation objective, actually, were saving more than the ones that use cloud just as a cost saving initiative. That was a big, Aha moment. Number two, when you talk about all of this innovation that AWS provides, sometimes it's easy for organizations to shrug it off saying, this looks like this is only for the elite companies, or this is only for the digitally native companies to follow. But our research showed that the companies that were successful adopting cloud continuum, the ones that we call less continuum competitors, 60% of them are pre-digitally born organizations. And they were reaping the benefits and they were growing faster, saving more, being more innovative than all others. So this is truly usable across the spectrum of the G 2000 enterprise. >> Yeah, and I think it's a no brainer, but now that you have, customers are transforming, they have multiple clouds. You have AWS, Azure, Google cloud, people were trying to find their swim lane. We heard about skill gap shortage. We did some reporting on that, that this idea of multi-cloud maybe not, I can't hire enough people. I'm going to bet on this cloud, maybe use that cloud. How are people looking at that? How do you guys see that the cloud competitive continuum, or how is the cloud competition affecting the cloud continuum from a customer standpoint? >> Yeah. I mean, you got to look at it, do you use the whole continuum? You've got a lot of cases, you got to be on the same cloud, right. You can use the whole, you got to use all the different components, all the different services. So I think we are seeing customers that are picking one and starting with one and then adding others. I see a lot of my customers who are using multiple clouds, but they're using them in different business units, right? So they may pick one business unit to go deep with AWS on, they may go use another business unit to go deep on another cloud, right? So yeah, I mean, everyone is getting multiple, but a lot of they're starting with one and then adding a second one or a third along the way. >> Karthik, this is what I was trying to get out of my story. It's a hard, very nuanced point. But if you look at the success of say Snowflake and Databricks, all bet on Amazon and their superclouds, they are on Amazon, but they're now working with Azure as well, because why wouldn't you want to open up your market? >> Exactly. And even the industry companies that want to monetize their capabilities using the digital ecosystems are doing that. For example, Siemens wanted to bring all their capabilities in manufacturing and machine operating system into a platform called MindSphere. And they knew that their end goal was going to be multi-cloud, but they want to practice, leveraging the power of cloud with one platform. And when they created MindSphere, they started with AWS and they created that solution in the public cloud and private cloud also at the Edge by leveraging the power of cloud from public to Edge and proved it out. And once it started working and they were able to roll it out for customers. Now they are giving customers the choice to be able to use it in other clouds as well. >> Yeah Karthik, you mentioned earlier at the top of our interview about the platform of the cloud and Dave and I were talking on our keynote review. We did a little history lesson of when Microsoft owned the monopoly of windows, the system software, and they had the application suite with office, but they still wanted developers to build on top of windows. Okay. But now with cloud that's one big windows platform like thing. So the developers ecosystem is evolving. And so one of the things we're watching, I want to get your reaction to this. Is in every major inflection point in the computer industry, when new ways to build and write code rolled out, the application owners always wanted their software to run on the fastest platform. Speeds and feeds matter in these shifts, because why would I want to have my software run slower? >> Yeah. >> What is your reaction to that? >> Yeah, absolutely. And again, there's a lot of things that the industry is going through and we are pushing the envelope on digitization. And today's keynote. When you saw the CEO of NASDAQ talking about the technology bottlenecks that were preventing the matching algorithm to be finally taken to cloud. Now that capability that's available at with AWS is what is enabling that matching algorithm to be taken to cloud through the power of Edge. So there's so much technology innovation, that's happening. That's constantly expanding the boundaries of posibilities. >> I mean, that's exactly the point. And I wrote this in my story and it came out on the keynote today, which was Adam saying, the clouds expanding that's the continuum. If it's running cloud operations, does it matter what it is? I mean, it's, if you're at the Edge and you're running cloud, maybe cause you want latency, of course you want to have low latency. Why wouldn't you want outposts. Again, this is all cloud operations. DevSecOps data is now kind of cloud operationalized. That seems to be what's happening. >> Yeah, I think the developers love the fact that they can write for one and put it anywhere, right? And whether it's a EKS on Inside, I don't even know what you call anymore, the public cloud, right? Or all the way out at the Edge, right? You write it once, you can deploy it there and it makes their lives a lot easier. And you know, as you said, it's all about performance. So they get the best option. >> Well, We love having you guys on the theCUBE, Accenture. You guys have really smart, talented people, always great commentary. Dave and I were looking at reviewing the tape so to speak. It's not really tape anymore. It's it's digitally stored on a S3, but we were looking back at 2016 when we first started talking about horizontally scalable cloud and vertically specialized applications. If you look at the keynote today and squint through the announcements, Amazon's going to offer full horizontal scalability and vertical specialization at the app level with machine learning capabilities. This means that you need data to be horizontally addressable, which is kind of counterintuitive, but you're seeing all the success on data lakes and lakes. This is the new architecture. It's kind of proven now, what do you guys think? >> Yeah, again, the aspect of cloud is about democratised innovation. The first element is, even though there's so much infrastructure build-out and infrastructural elements where there's continuous innovation going on, the enterprises and developers are moving from Bivives built decisions to assembling and consuming options. And when they assemble and consume, they want newer and newer services to be available. That is very specific to their industry and specific to functions, whether it is supply chain function or manufacturing function or so on and so forth. For this, there are going to be specific data that is going to be required, or operational for that particular use-case. But the whole idea of predictive analytics and AI and machine learning and data science is about how do you find correlations between operational data for a particular capability, with things that in the previous world was unrelated. For that you need to bring all of this data together. Time will tell whether all the data is going to move to one location or is there going to be distributed computing of that data with more technology, but that's the role that data is going to play in these verticalized solutions. >> Yeah, I mean, that's awesome. I want to get you guys while I got one, a couple of minutes left. Advice to people that look into go this next level. They know the continuum is coming, you guys been providing great solutions and advice to your customers. For the folks watching, what advice can you give where they're just putting their toe in the water or want to go full in? >> Yeah, so, we found in that research that there were some common patterns that were followed by these continuum competitors, the ones that were succeeding or winning in the cloud. And there was namely four of them, the first one, and these four can be adopted by others for them to also win in the continuum. The first one was looking at the power of the continuum, how the technology is evolving and creating a strategy to take advantage of the evolution of the continuum. That's number one. Number two, this is about organizational change. So don't go about this change in a soft manner. There are elements that you need to change within your organization to imbibe this wholeheartedly. That's the second thing. Third thing is one common aspect that all the continuum competitors followed was they put experience at the forefront for everything. For their end customers. Last but not the least. This is a holistic journey and an enterprise wide journey. And this would require CSO level, CEO level commitment on a longer term to achieve this. So with these four things, most companies can achieve the successes that the continuum competitors are seeing. >> Awesome insight, Chris, real quick, 30 seconds. What's your advice. >> Chris: Don't be afraid. (laughter) It's pretty simple. >> The water's warm, come on in >> Yeah, come on in. A lot of gone before you, right? It can be scary. It can be daunting, right? A lot of services. Don't be scared to get in and go at it. >> Yeah, one of the jobs I love about being theCUBE host is, you talk to people many years earlier, you guys got it right at Accenture. Congratulations. You were deploying, you saw this wave of purpose-built before anyone else and congratulations. Great success. >> Thanks, thanks for having us on theCUBE. >> Okay, I'm John Furrier. You're watching us here live in Las Vegas, for AWS re:Invent 2021 coverage. TheCUBE, the leader in tech coverage. (upbeat music)

Published Date : Dec 1 2021

SUMMARY :

Good to see you and Chris Wegmann, but the idea that people can I like the term, but you know, What is this new wave you that across the continuum, Wavelength and all the different services, This is the continuum. of the cloud continuum, during the pandemic. And that the research that you guys have found is that the companies that use cloud but now that you have, all the different services. But if you look at the And even the industry companies And so one of the things we're watching, that the industry is going through and it came out on the keynote today, I don't even know what you call anymore, reviewing the tape so to speak. but that's the role that I want to get you guys while I got one, that all the continuum What's your advice. (laughter) It's pretty simple. Don't be scared to get in and go at it. Yeah, one of the jobs I love TheCUBE, the leader in tech coverage.

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Drew Schulke, Dell Technologies | CUBE Conversation


 

>>Hi there. Welcome to this cube conversation. I'm John Farah, your host of the queue here in Palo Alto, California in our studios for cube conversation and remotely drew showcase VP of product management at Dell technologies. This segment is about autonomous operations and moving beyond the hype into practice reality of what's going on in automation. Drew, thank you for coming on this cube conversation >>And great job. Thanks John. >>So, uh, uh, automation, autonomous operation, everyone sees the Tesla's a self-driving cars. We even heard words like self-driving store self-driving data center, self-driving cloud. It's kind of a buzz word. It's been hyped up a lot, but it's becoming much more of a reality as people start to think about how to automate a way the, the manual undifferentiated tasks and move the value into either writing better software or into operations. This is kind of a hot topic. Uh, why, why is it so hot right now? What's your take? >>Yeah, I think the answer to this lies really in the digital transformation that every company is having to embrace right now. And I use the word company, but everything I described here would apply to public entities as well. I have plenty of conversations with governments and universities and so forth. And the leverage that cost share that I've heard used before. If you're not a technology company and you don't think you need to become one, you're not going to be around for very long because every business to business, business to consumer, even consumer to consumer interaction is becoming digitized. And so, you know, making all those connections, digital based takes human talent. And that's really at the core of why this is a hot topic. You know, anybody who's going to try and hire that talent right now, or who's actively trying is going to tell you the competition is fierce. >>It's a sellers market, so to speak in terms of getting capable it talent. And so this topic of automation and autonomous operations has an incredibly pragmatic component to it because you can't hire your way through digital transformation. Uh, if you're an element of your strategy is going to have to involve making that talent more efficient. And so along with good business processes, automation is going to be a prerequisite to make any progress on your digital transformation within a finite set up of it talent. So, you know, to your question, why is it a hot topic? I, you know, look at every entities, digital transformation is going to dependent on, >>You know, you've been around, uh, seeing a lot of ways of innovation come and go. You know, every one has its own kind of like unique characteristics. Now we're seeing with this transformation, this digital transformation, a lot of things kind of coming together. So it's always been the classic people, process technologies, you know, the three kind of areas people talk about, but if you look at what cloud and now edge and distributed computing is bringing into the equation, companies are identifying competitive advantages to processes that can be software enabled or defined or automated and where their workflows are, the IP of company. So this is kind of like a new revelations. Like, I mean, Ross has always been great with your manufacturing, whatever that was in place, but now the scale of that in digital with the apps out there, this has been a big focus of the modernization of applications. What's your, what's your reaction to that? >>Yeah, no, no, very much so it's, um, you bring up an excellent point kind of all the focus and attention that corporations have given to these other processes for time now that you know, this, this whole, um, you know, online, digital digitize, modern operations model, if it's flowing into that as well. And you know, it's, you know, at the end of the day to, to the, some of the points that you made here, you know, are, are you and your whatever business or entity that you're supporting, you know, are you pushing out the lovers levels of features and capabilities that your internal customers or your external customers need at the pace and velocity that you need to that's, that's where competition is going to take place. That's where business is going to be won or lost. And so I think seeing an indexing of the processes around that and our customers starting to think more about that is critical. Just as much to your point, as you know, uh, you know, the, this technology strategy. Um, and, and how are you going to engage, you know, your customers through a, uh, uh, a modern, you know, digitize processes is important for the factory as the factory line for Ford motor company is in terms of how they're going to be interfacing with their customers. So, um, yeah, very, very timely. And certainly top of mind. >>Yeah. And a lot of CEO's and customers that you work with. I know you guys are having a lot of conversations. We've talked with you guys in the past, across all of Dale, actually Dell technologies, and it's the same conversation. It's distributed computing and automation, AI machine linear, all factoring in workflows becoming competitive advantage. Now we're into this autonomous phase, which is like self running or healing or all these new, new stuff. When customers think about this, and we've heard CEOs talk about strategies, don't touch the white hot core until you get to the edges first, put your toe in the water, different approaches to tackling autonomous operators. What sort of, um, strategies and results should customers expect as they go in and start jumping into the, into the, into the pool, if you will, you know, as they start, >>I'm glad you asked this question because the subject of automation gets lumped in with a lot of topics with similar, you know, buzzwords of AI and machine learning and self-healing, and self-driving while these technologies like that make autonomous operations. In reality, we run the risk of having the underlying technology, dominate the discussion, and that's not where it needs to go in, in, in my discussions with customers, they don't care if the underlying technology is machine learning or deep learning, you know, it doesn't really matter. They want to see tangible out. So, and so when we talk about the kind of results to expect, there's some pretty simple questions to ask is, you know, that I, you know, I engage with any CIO or any company, a person in an it operations capacity is, is my, is my team spending, you know, how much time is my team spending on updates or the updates taking place within tighten up windows? >>Is my team getting the root cause of issues faster? Is my team closing out tickets faster is my business deploying more applications per week, per month, per year. These are the kinds of things that really matter. I mean, this is where the rubber meets the road on this, and, you know, the way we approach this is as we deliver more capabilities and features in this space of autonomy, we're constantly engaging our customers in a before and after state to understand if we really moved the needle. And so we, we, we do collect data on this front to see if we are delivering tangible results. And you know, what we've seen just in the past year is when we do this and do it right, we're seeing issue resolution times dropping like 50 to 90%. We're seeing time spent on admin tasks reduced by like 85%. We're seeing operations cost dropped by a third, you know, applications being pushed out, almost doubling. So these are, these are the real benefits, right? If you, if you can free up and pull the human component out of some of these, you know, necessary, but not necessarily, um, you know, value added tasks, uh, in your day to day operations, this is the kind of results customers can see. >>I want to ask you about your recent event hosted by mark Hamill, but about the framework you guys announced. But before that, I want to ask you, I got your here about supply chain. I mean, honestly, Dell made, made its bones in supply chain and innovation going back to the early days, Michael's book is awesome and he talks about being successful. Um, but you started to hear words like software supply chain is starting to hear words like the word supply chain is now becoming lingua franca in business, not just on moving goods here and there. Digital supply chains are emerging and it's impacting developers because they have to secure them. And there's also mindset of an operational mindset, our systems thinking, uh, with as well as design thinking, but mainly systems thinking. So this is not for the, you know, supply chain geeks out there. This is like hitting me. And she, this notion of supply chain doesn't promise operations hit to the core of this. >>Yeah. It, um, yes, it should, because ideally what you're doing is your autonomous operations strategy is contemplating the fact that that supply chain is going to be fluid. Like, you know, and, and so, you know, just think about the, the, the, you know, the, the, the underlying infrastructure and the choices that you have being, um, on, um, on bare metal on VM, based on container-based, there's different distributions within that. We then start to think about, you know, how I might orchestrate that then the different platforms that we have there around configuration management or application orchestration, um, you're right. That supply chain does become pretty complex. And so, um, us as a, as a provider to customers that are having to do with that software supply chain, um, you, what we need to be cognizant of is the fact that, you know, we can't dictate that always, we have to assume there's going to be changes in there. And so that certainly does influence our approach and trying to make that as, um, you know, friendly to a heterogeneous environment that we know is going to change going forward. Awesome. >>And we're going to see more of that kind of thinking and apply into the people skill, skill development, and also software automation to offload that. But okay. Back to the event you guys had mark Hamill, who's, I'm a huge fan of star wars. Uh, the kid I master, um, represents the old guard, you know, let's do it now, looking at the cloud. Um, you guys announced that that event, this autonomous operations framework, could you talk about what that is and why is it important? >>Yeah, so to begin with, you know, if you had told me when I was watching mark Hamill as a child in a movie theater, that he would one day help me do my job, I would have gone insane. But anyways, um, that, that aside that, that autonomous operations framework, it's built around six levels of automation. And we can talk, take the cue from the society of automotive engineers and work that they had done around autonomous cars, but we believed that we needed something distinct for, for it. And, you know, it starts off with level zero, which is no automation, look at your there's a human doing absolutely everything. And you progress up through five subsequent levels of operator assisted, partial automation, conditional automation, level five, being full autonomy. There's a set of expectations with each of these. And look as you progress up the level of involvement of humans in the decision, and the reaction is decreased each and every step, and some might say, well, so what all you did is document a framework. >>Well, it's important to both our customers and then our internal teams that have to deliver this. And let me just elaborate on that a little bit. Why it's important to customers is that automation implies trust. As, as, as you know, you as my infrastructure provider Dell, do I trust you to automate something that is typically involved my own team, assessing what it is the problem to be and determining the remediation action. Am I willing to hand over the keys to that to you? Uh, you have to earn that and you earn that by progressing up through these different levels. And, you know, if I can't trust you with, you know, conditional automation, I'm not going to trust you with full autonomy. So the customer is, you know, there's a, there's a psychology that's involved here that they have to progress through these levels. And so you have to be deliberate, I'd say as well, you need to recognize that not all customers are going to progress through that at the same pace. >>So it's important that when we think about how we're going to provide this, yeah, we want to have an option for the highest level of autonomy as possible, but that doesn't mean all customers are going to be ready. So we need to think about, you know, how do you provide the N minus one and minus two levels of capabilities. So we're meeting customers where they are in terms of their comfort and, and embracing this idea of autonomous. And then, you know, for us internally, that's the customer's perspective for us. Then this is a, a great set of guideposts for our teams to think about how we advance. And so when we have a feature, um, that, that we're deploying and making available, let's say it's sort of a workload contention feature, right? We then think about that about, okay, how do we start to advance up through the different levels here? We know workload contention is an important problem, but how do we start to take the human out of that equation in a methodical way to advance them through these levels? So we give a suite of options to our customers to do without that. >>True. Talk to me about your reaction with customers. Cause I know there's a spectrum of customers that are leaning in, some are putting the toe in the water, so to speak somewhat more information, some are just looking at the architecture of how they're going to scale post COVID and then have a growth strategy for their business, what feedback you're getting, where are, how would you put the customer's mindset? Um, and, and can you describe the makeup of the customer profile for >>Yeah. You know, I would say, um, you know, there, you know, when we were talking about these six levels, there, there were about halfway up in general. If you, if you ask me to kind of do the bell curve, right. And in terms of comfort level, and we'll, we'll call it like partial or conditional automation there where it's like, you know, in general, it's like, okay, we, we, we know we need to take some of the humans out of this, but why don't we start by, you know, you recommending what the remediation is. I'll take a look at it and decide if I want to implement it or recommend the remediation and give me a button I can click to, to, to act upon it. So there's still some level of human checks and balances in there, but we've taken a lot of the grunt work out of it, so to speak, um, to do it. >>But that's where they are. They, they certainly aspire to move up again, back to this resource crunch, competing for talent than I can't keep hiring people to keep up with the work here and what they want to do is work with us to, okay, so how do I evolve this to start to prove it then? And this is where we can kind of go back to some of these things of the machine learning and so forth, where it's up to us as we think about how we design the systems around this is how can we start to observe how customers are responding to our recommendations? Are they always taking on, are they modifying them so we can get smarter in terms of what it is we're going to suggest and what we're just we're going to automate so that we're doing it around their values, not necessarily ours, that's a really important component here. This value based approach that we need to embrace, because, you know, you know, what, what might be considered an acceptable set of circumstances for a financial services company? You know, it might not be for a manufacturing company. And so that's something that we need to take into account in the overall design. >>Yeah. And also to your point earlier about meeting them where they are, is super important. And I think what's interesting, I've been watching over the past five Dell technology worlds, um, the tradition transition of Dell becoming much stronger and, and, and cohesive in each element of the end to end mix if you will, of hybrid. Um, and that's been a big boost. Um, and so as customers go, okay, I still got to get better. So they get, they're taking this way. And some, some customers, you know what I need to do more, but you guys are running these companies with your technology. So it's not like as easy, it's not a clean sheet of paper. In some cases, it is when you have new projects, they go cloud native and they just ended, they deploy, uh, and they have an edge and all that good stuff. But in terms of making autonomous operations real in terms of your roadmap, as you guys evolve, um, how close are you to having that secret formula? Or do you have the secret formula now? What is it? >>Yeah, so the short answer is, you know, do we have the, the, the secret sauce that we do? And, but that doesn't mean we're done like, so, so back to the framework, like nobody in the industry is at full autonomy. So let's just be really honest. There it's a, it's an aspirational north star that we, we all have to make progress to, but you know, what that means is you can take something that has a level of autonomy today. And let's take something like workload contention analysis that I brought up earlier, where, you know, we can identify where we've got workloads competing for shared resources that need to be redistributed. You know, today we flagged that contention and let the customer determine remediation. So, Hey, we're, we're letting you know you've got a problem. Um, you know, they're going to determine that remediation based upon their first hand knowledge of the environment and applying the values that they have to determine the best path, but, you know, our task is then to gain insight on that and how our customers are choosing to remediate, translate those into rule-based decisions for an explicit outcome that kind of advances you up one step, moving beyond rules. >>You start to understand more generalized outcome sot. That's a conditional automation. And then you move beyond that to get to a service level based objective, which would be high autonomy. So you're there, but this, this framework clearly calls out like this is a journey like there's no, you never really get to the end, so to speak. And that's fine, right? That, that Nirvana of full autonomy, we all should aspire to it, but we are going to be very, very deliberate in terms of how we take things like this and advance them up through the framework to make it more real. And again, give customers choice as they're willing to progress up through that trust will be there with an option for them when they, when they want to stay back with where they are, because that's where their comfort is. We'll be able to meet them there. >>Yeah. And I think also that be fair to anyone who may look at this as, you know, kind of like maybe future every, every customer you have is different operationally. I mean, you have, again, you mentioned financial FinTech, they're huge. If financial services area versus say, you know, classic enterprise, I mean, it could be insurance or whatever, a lot of legacy, and now new technologies coming in, this is all part of the, the opportunity is to kind of bring that together. Um, and it's not going to switch. >>Yeah, it is. And I'll just, you know, the one last plug for why I feel great about doing this as Dell technologies is I think about the, the breadth of what we cover in that environment, you know, with the, the breadth of our portfolio and the level of insights that we can have by kind of contemplating all the impacts across that typology that we span. Um, it's super exciting in terms of kind of what we can really unlock here in terms of value from an end date >>Drew. It's great to chat with you. I have one quick, more important question. Most important question is, did you get a selfie with mark Hamill Come on in every star wars? I mean, I'm a huge star wars fan, of course, star wars, star Trek are all on the same tier. Yeah. >>Uh, no, sorry. I missed out. I was, I was virtual for that one. So, um, although I probably could have done a screenshot on zoom or something like that and claimed it. So, but the >>Well great to have you on the queue. Thanks for your insight. I think this is a great area. Autonomous operations are moving beyond the hide, was seeing evidence in it. You seeing us the on clean sheet of paper, Greenfield opportunities, and then as it comes into the white hot core enterprise, um, even more trust is needed. Even more reliability track record you guys doing great work. Thank you so much for sharing on the cube. Great. Thank you, John. Okay. This is the cube. I'm Sean for your host for this cube conversation. Thanks for watching.

Published Date : Nov 4 2021

SUMMARY :

Drew, thank you for coming on this cube conversation And great job. people start to think about how to automate a way the, the manual undifferentiated And so, you know, making all those connections, digital based takes human talent. So, you know, to your question, why is it a hot topic? process technologies, you know, the three kind of areas people talk about, but if you look at what cloud and now that you know, this, this whole, um, you know, online, digital digitize, if you will, you know, as they start, to ask is, you know, that I, you know, I engage with any CIO or any company, I mean, this is where the rubber meets the road on this, and, you know, the way we approach this is as So this is not for the, you know, supply chain geeks out there. We then start to think about, you know, how I might orchestrate that then the different platforms that we have there around configuration Back to the event you guys had mark Hamill, Yeah, so to begin with, you know, if you had told me when I was watching mark Hamill as a child And so you have to be deliberate, I'd say as well, you need to recognize that not all customers are going So we need to think about, you know, how do you provide the N minus one and minus two levels of capabilities. and can you describe the makeup of the customer profile for we, we know we need to take some of the humans out of this, but why don't we start by, you know, you recommending what the you know, you know, what, what might be considered an acceptable set of circumstances for a And some, some customers, you know what I need to do more, but you guys are running these companies Yeah, so the short answer is, you know, do we have the, And then you move beyond that to get to a service level based objective, which would be high autonomy. you know, classic enterprise, I mean, it could be insurance or whatever, a lot of legacy, And I'll just, you know, the one last plug for why I feel great about doing this Most important question is, did you get a selfie with mark Hamill So, but the Well great to have you on the queue.

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Claire Hockin, Splunk | Splunk .conf21


 

(soft music) >> Hi, everyone. Welcome back to the Cube's covers of Splunk's dot com virtual event, their annual summit. I'm John Ferry, host of the cube. We've been covering dot conf since twenty twelve. Usually a physical event in person. This year it's virtual. I'm here with Claire Hockin, the CMO of Splunk. She's been here three and a half years. Your first year as CMO, and you got to go virtual from physical. Welcome to the cube. Good to see you. >> Thank you very much, John. Great. >> I got to ask you, I mean, this has been the most impressive virtual venue, you've taken over the hotel here in Silicon valley. You're entire teams here. It feels like there's a dynamic of like the teamwork. You can kind of feel the vibe. It's almost like a little VIP Splunk event, but you're broadcasting it to the world. Tell us what's happening. >> Yeah, it's been, I think for everyone a year where we really hope to be back to having a hybrid event, so having a big virtual component, but running dot conf as we had before from Las Vegas, which wasn't possible. So what we thought in the last six weeks is that we would actually bring the Splunk studio to a physical location. So we've been live all of this week from California, where we're sitting today and really thought through bringing the best of that programming to our, you know, our amazing audience of twenty six thousand people. So we were sitting here in a studio, we have a whole live stage and we've activated the best of dot conf to bring as many Splunkers as we can. And as many external guests to make it feel as real and as vibrant as possible. So. >> I have to say I'm very impressed. Since twenty twelve we've been watching the culture evolve. Splunk has always been that next big thing. And then the next big thing again, it seems to be the theme as data becomes so bigger and more important even than ever. There's a new Splunk emerging, another kind of next big thing. And this kind of says the patterns like do something big, that's new, operationalize it and do something new again. This is a theme, big part of this culture here. Can you share more about how you see this evolving? >> Sure. And I think that's what makes Splunk such a great place to be. And I think it attracts people who like to continually challenge reinvent. And I think we've spent a lot of time this year building out our portfolio, going through this cloud transformation. It just gives you a whole new landscape of how you unlock that power of data and how customers use it. So we've had a lot of fun, always building on top of that building, you know, our partnerships, what customers do and really having fun with it. I think one of the best things about Splunk is we do have this incredibly fun and playful brand and as data just becomes something that is more and more powerful, it's really relatable. And we have fun with activating that and storytelling. So, yeah. >> And you have a new manager, Teresa Carlson came in from Amazon web services. You have a lot more messaging kind of building on previous messaging. How are you handling and looking at the aperture of, that's growing from a messaging standpoint, you have a partner verse, which has rebranded of your solution of your ecosystem, kind of a lot of action going on in your world. What's the update? >> Yeah. It keeps us busy. And I think at one end, you know, the number of people that are using Splunk inside any customer base is just growing. So you have different kinds of users. And this year we're really working hard on how to partner and position Splunk with developers, but at the top end of that, the value of data and the idea of having a data foundation is something that's incredibly compelling for CTOs. So working really hard about looking at Splunk and data from that perspective, as well as the individual uses across areas like security and observability. So. >> You know, one of the things I wanted to ask you is, I was thinking about this when I was driving in this morning, Splunk has a lot of customers and you keep your customers and you've have a lot of customers that organically came into the Splunk through the product leadership and just great product. And then as security became more important, Splunk kind of takes that territory now. Now mainstream enterprise with the platform are leaning into Splunk solutions, and now you've got an ecosystem. So it's just becoming bigger and bigger just seems that the scale of the Splunk is growing radically bigger than it was, Is that happening? And what's your take on that? >> I think that's definitely a thing, John. So I think that the power of the ecosystem is amazing. We have customers, partners, as you've seen and everything just joins up. So we're seeing more and more dot joining through data. And we're just seeing this incredible velocity in terms of what's possible and how we can co-build with our partners and do more and more with our customers. So Splunk moves incredibly quickly. And I think if anything, we're just, gaining velocity, which is fun and also really challenging. >> Cloud-scale. And certainly during the pandemic, you guys had a tailwind on the business side, talk about the journey that you've had with Splunk as in your career and also for the customers. How are they reacting and what can they expect as Splunk continues to evolve? >> I think we're working really hard to make sure that Splunk is easier to use. Everything gets every more integrated. And I think our goal and our vision is you just capture your data and you can apply it to any use case using Splunk. And to make it sort of easier see that data in action. And one of the things I love from today was the dashboard studio. They're just these beautiful visualizations that really are inspiring around how data is working in your organization. And for me, I've been a Splunker for three and a half years. And I just think there is just so much to do, and there's so much of our story ahead of us and so much potential. So just really enjoying working with customers on the next data frontier, really. >> You have the Jedi Knight from Star Wars speaking, you had the F1 car racing. Lando was here, kind of the young Jedi, the old Jedi. The generations are coming together. You're seeing that old IT world, which relied on Splunk. And now you have this new developer real-time shifting left with security DevOps now going mainstream, you kind of have the confluences of these cultures coming together. It's not really clashing. It's kind of jelling. How are you handling that? How do you see that? What's Splunk kind of doing? Because I can see the themes, am I right? >> No, no. One of the stories from this morning that really struck me is we have Cal Poly and we worked with Cal Poly on their security and they actually have their students using Splunk and they run their whole security environment. And at the very top end, you have Walmart, the Fortune one, just using Splunk at a massive, incredible scale. And I think that's the power of data. I mean, data is something that everyone should and can be able to use. And that's what we're really seeing is unlocking the ability to bring, you know, bring all of your data in service of what you're trying to do, which is fun. And it just keeps growing. >> We had Zach Brown, the CEO of F1 McLaren Racing Team, here on the queue earlier. And it was interesting cause I was like driving the advantage with data, you know, kind of cliche, but they're using data very specifically, highly competitive. It almost kind of feels like a cloud kind of scale model because we've got thousands of people working on the team. They're on the track, they're competing, they're using data, they got to be agile and they got to be fast real time. Kind of sounds like the current enterprise's these days. >> Absolutely. And I think what's interesting about McLaren that the thing I love is either they have hundreds of terabytes of data moving at just at incredible speed through Splunk Enterprise, but it all goes back to their mission control in the UK. And there are 32 people that look at all that data. And I think it's got a half second delay and they make all the decisions for the car on the track. And that I think is a great lesson to any enterprises you have to, you know, you have to bring all that data together and you have to look at it and take decisions centrally for the benefit of your whole team. And I think McLaren is a really good example of when you do that it pays dividends and the team has had a really, really great season. >> Well, I want to say congratulations for pulling off a great virtual event. I know you had your physical event was on track and literally canceled the last minute because of the pandemic with the Delta virus. But it was amazing, made for digital TV kind of event. >> Absolutely, >> This is the future of media. >> Absolutely. And it is a lot of fun. And I think I'm really proud. We have done all of this with our in-house team, the brand, the experiences that you see, which is really fantastic. And it's given us a lot of ideas for sort of, you know, digital media and how we story tell, and really connect to our twenty thousand customers or two hundred and thirty thousand community members and keep everyone connected through digital. So this has been a lot of fun and a really nice moment for us this week. >> You know it's interesting, I was saying to the team here on one of our breaks, is that when you have this kind of agility with media to tell your own story directly, you're almost telling more stories there before. And there's a lot to tell you have a lot of successful customers, the new partners. What's the coolest story that you've seen. What would you share that you think is your favorite? If you could pick one or a few of them, what are your top stories that you see happening? >> So I've talked about Cal Poly, which I love because it's students and you know, the scale of Walmart, but there are so many stories. And I think the ones that I love most are the data heroes. We talk about the data here is a lot of Splunk and the people that are able to harness that data and to take action on that data and make something amazing happen. And we just see that time and time again, across all kinds of organizations where data heroes are surfacing, those insights. Those red flags, if you like and helping organizations stay on step ahead. And Conf is really a celebration of that. I think that's why we do this every year. And we really celebrate those data heroes. So across the program, probably too many to mention, but in every industry and at every scale, people are, you know, making things happen with data and that's an incredibly exciting place to be. >> Well you have a lot of great customers to, to use as references. But I got to ask you that as you go forward this year in marketing, what are your plans to take on this new dynamic? You've got hybrid events, you've got the community is always popular and thriving with Splunk at large-scale enterprises, global system integrators, doing business deals with you guys, as you guys are continuing to grow and grow and grow, what's the strategy? How do you keep the Splunk coolness going? Cause that's, you know, you guys are growing so fast. That's your job, is to keep things on track. What's your strategy? >> I think I look at that and just, we put the customer at the heart of that. And we think, you know, who are the personas, who are the people that use Splunk? What's their experience? What are they trying to do? What are those challenges? And we design those moments to help them move forward faster. And so that I think is just a really good north star. It is really unifying and our partners and customers, and every Splunker gets really behind that. So stay focused on that. >> Thanks for coming on the Cube, really appreciate it. Congratulations for great event. And thanks for having the Cube. We love coming in and sharing our media partnership with you. Thank you for coming. >> Thank you so much. And next year is your tenth year John. So we look forward to celebrating that as well. Thank you very much. >> Thank you. Thanks for coming on. Okay it's the Cube coverage here live in the Splunk studios. We are a virtual event, but it's turning out to be a hybrid event. It's like a VIP event, a lot of great stories. Check them out online. They'll be recycling through so much digital content. This is truly a great digital event. Jeffery, hot of the Cube. Thanks for watching. (soft music)

Published Date : Oct 20 2021

SUMMARY :

I'm John Ferry, host of the cube. Thank you very much, John. You can kind of feel the vibe. programming to our, you know, how you see this evolving? And I think that's what makes Splunk And you have a new manager, And I think at one end, you know, and you keep your customers And I think if anything, we're just, on the business side, And one of the things I love from today And now you have this new developer And at the very top end, you have Walmart, Kind of sounds like the current And I think what's interesting I know you had your the brand, the experiences that you see, is that when you have this kind of agility is a lot of Splunk and the But I got to ask you that as you And we think, you know, And thanks for having the Cube. And next year is your tenth year John. Jeffery, hot of the Cube.

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Matt Garman, AWS | AWS Summit Online 2020


 

>>from the Cube Studios in Palo Alto and Boston connecting with thought leaders all around the world. This is a cube conversation. >>Everyone. Welcome back to the Cube's virtual coverage of AWS Summit Online. Their virtual conference. I'm John Furrier here in the Cube studio for a conversation with Matt Garman, Vice president. Sales amount of AWS. We're here with our quarantine crew. Matt. Thanks for joining me. I know your remote as well. We're living in a virtualized world. Thanks for coming on. AWS Summit is now online. You're running sales and market for the company. This is really caught a lot of companies by surprise this this situation sheltering in place. It's highlighted a lot of scale problems. One of them is events. So we're here at the AWS Summit online, and you guys are still pulling it off A lot of content. Great to see you. >>Great. Thanks. Thanks for having me. >>So before we get into some of the announcements in the customer focus things that you guys are doing, you and I both met. We did an interview when you were running the EEC to you've been with Amazon for a long time, Got a storied history. You were there from one E. C two launched saw Amazon grow. This really kind of ties into some reporting that we've been doing where cloud native a scale of what advice became it really was a game changer and that showed the at scale opportunity for startups. And now the enterprise. This covert 19 is really showing companies and individuals their living it, of being disrupted, where the Internet and large scale tools and technologies can help them, but also exposes gaps in their lives or in companies, cases, things like provisioning VP ends. Maybe they didn't figure out 100% would be at home, but then going forward, the applications are now thinking about this new virtualized world. Even when it comes back to normal, be somewhat of a hybrid, you know, integrated world. This will put pressure on you guys as Amazon to build more capacity like you did with the see too, but at a whole nother level. So I want to get into that and more. But this covert 19 really has changed the game for the world. What do you guys see in your customer base? This is a big part of the conversation. What's going on? >>Thanks, John, And you're right. This is an unprecedented time for us, and on day eight of us as well as our customers are all trying to figure it out. I think you know, part of part of what we've seen from our customers as we talk out there, whether they're public service or private customers is is really that that demands that they're seeing from their customer bases are rapidly changing. Some customers have their businesses have seen much fewer lower demands and others before. But others they're seeing 10 21 100 x more business than they were before. And what we're seeing is that those customers that have their business running in the cloud are able to handle that on quickly. Our ableto adapt and change and grow with their changing customer base, and sometimes that's internal. Sometimes you're like you said. That's because, um, they need to scale up their VPN or they need to scale up their virtual workstations. Other times, it's customers who maybe they run a large call center business. But their call center folks are no longer able to come into the office, and they quickly spin up a virtual call center. We've seen our Amazon connect business really, really take off as customers quickly united to figure out how they can manage the actually increased call Williams they're seeing, but in a virtual location. And finally, we're just seeing some customers, whether they're from entertainment from communication or online education. Many of these businesses they're scaling rapidly wouldn't have been able to do it if they're running in their own data center. But because they're in the cloud, they're able to quickly spin up more instances, spin up more storage and meet the demands of their customers. So I think it's been nice to see. Fortunately for us, we've had many years, as you mentioned, I used to run the C two team on, and we've been thinking for over a decade about how we really manage that supply chain. How do we ensure that we're able to handle rapidly scaling? So we've really optimized our supply chain Unfortunately, in a good position where we can continue to operate, continue to scale and continue to handle the demands are growing customer base even unprecedented times like this. >>You know, you mentioned that I want to get into that concept. You wrote a block post the other day on the Amazon Day one blawg keeping organizations running during Covad 19 and you kind of teased out this point about average connected time. And if you think about this crisis, this really is that the true test for scale and elasticity of having that cloud model and some of the clouds have not done as well as Amazon. There's been some stories out there. Google and Microsoft has had the up time you guys had, but this really has been the future pulled forward. So you guys have a lot of customers like Netflix like slack, that are really taken advantage of this. This is the true test of cloud and only the beginning again. Like I said, this is going to show a lot of gaps in most other traditional enterprises. But this highlights the tests that you guys were waiting for. I won't say that you're waiting for a crisis, but cloud, this is ultimately the test. Your thoughts on Netflix, who Lou Slack, A bunch of other names land and he throws the slide. But we have re invent. But the >>big I think if you look at, obviously we have a lot more time at home, right? I'm at home here in Seattle. A lot of us are spending more time at home. And so a lot of the streaming services like you said, the Netflix is the who lose that Disney Pluses of the world. Also games. Think about how many kids were playing fortnight or playing a or the video games. A lot of those businesses have really seen an increase in their demand on they have been able to just seamlessly scale along with eight of us on the work side. Think about everybody from slack that runs entirely on AWS Zoom, who runs the vast majority of their infrastructure and aws all of these communication on work from home capabilities. These are all running on AWS enabled many of the scale, and we think all of our kids, our kids are all trying to figure out what a school look like. You don't actually go to school. I was talking from the team at Blackboard. They've seen a 10 sometimes even 100 X increase in their business. America will just seamlessly scale up on demand. I mean, really overnight just exploded. >>I was on Twitter just the other day, talking with some folks because the whole jet, I think, is going down. I was gonna wing of my normal commentary. Um and this is the public sector challenge as well. You mentioned schools. These air traditionally? No, I t or enterprise like chops. They need scale now. They need it fast. They have to stand up. I imagine this is the kind of scenario that this is also gonna hit the small, medium sized enterprises as well as some of the big ones. So the big guys have legacy problems, data silos, whatever we've had, great. Comes with some of your team members there. But that's just one sector. You got small, medium size enterprises that don't have any I t public sector and education. They're gonna be in market in months, if not >>tomorrow. Public sector is a super interesting one. And, frankly, our public sector team I don't know that they have slept in the past three months working to try to help governments, both the United States and internationally, everything from me. If you think about it, our our unemployment systems in states across the United States have gone from something like 3% unemployment claims to 15% unemployment claims within a two month period. Those systems are not meant to scale like that, and they reached out to us pretty quickly to see how we could help them start to scale. You think about some of the the systems that are trying to send out checks to people, systems that are trying to send out small making loans to folks. We've been really working deeply with many of those government agencies to try to figure out how we can get the money in the hands of the individuals that need it as quickly as possible and really help those legacy systems. Sometimes they're built on, you know, legacy databases or Oracle's or Microsoft sequel systems. And those things just aren't scaling. And they're trying to figure out How can they get to a more modern architecture that can really keep scaling with the needs of the new demand that they're reaching? It's just something that didn't anticipate before. >>Yeah, and I think your customers, as you're now going to be overseeing the larger global organization, sales and marketing, um, it's not like you guys are preaching to the customers because you're living through the same crisis in an environment that they are. You certainly can align with their empathy and certainly help them solve problems. But now we're in a business climate where we're seeing unemployment numbers of massive numbers. Usually companies come out of these challenges, and we think it could be highly accelerated on an upward trajectory, flat or negative. In 2008. That crisis we saw the winners come out of that one. You guys rode that wave with AWS. Easy to can. You know that world now coming out of this next pandemic, it's going to be hybrid or virtualization of meat of life. >>How are >>you leading your team? How are you talking to customers? I'm out of this empathy, but you got to run an organization. You have to still sell services and market your products You got reinvent was a physical event. I mean, >>these air, >>huge challenges you're living them to. What's your >>take on >>all this? >>Yeah, part of I think you know, in my new role. And as you mentioned, I used to run the computing with AWS, including easy to many compute services for about 13 years before coming and running. Now the sales and marketing, or AWS >>and And in >>that role, you know, a lot of what I would think about is how we really help our customers understand how critical it >>is to the >>her hair. The cloud gives you just so much more flexibility, so much more agility. And we would you know, there's a bunch of the early adopters would lead into that and really got it. And once they got onto the cloud, they saw their innovation level went up, their agility goes up all those things. But, you know, there was still a lot of folks that were they're interested. I mean, we obviously have, ah, decent sized business today and many, many millions of customers that are using the cloud today. But some of them are have been slower to kind of fully adopt and really move all of their business critical workloads to the cloud. I firmly believe that coming out of this crisis, you're gonna have two types of of businesses. You're gonna have some that just go into their shell, right? They're just going to say I'm just gonna try to survive. I'm just gonna try that to get by, going to try to conserve every little bit of something. I can just protect what I have. You know, I don't think those are long term. I'm not optimistic of. Those are going to be the businesses that right. I think every time you see a crisis, you have businesses that lean into it. They're smart about it. They think about long term. What are the things that are going to help me compete in this new world? And I think Cloud is gonna be one of those things. We've talked to everybody from airlines to traditional Fortune 500 enterprises, and they see that like they're still leaning into the cloud, even even airlines. No one's been hit harder than the airlines. And even I've talked to several executives and airlines their saying Look, my cloud initiative, that's the thing I'm not cutting. I'm gonna cut everything else. But this is the thing that's gonna let me succeed when I really get into that new world. And so I really think you're going to see some of those folks that maybe you were hesitant before so again in the next 34 years. Maybe I'll get to the cloud. I really think that they're going to start to lead in because they're going to realize if my competitors or in the cloud and I'm not that is gonna be a significant disadvantage and, you know, knock on wood. Hopefully, there's no other global pandemic, but they have to deal with. But I think it just really highlights any uncertainty in the world. There's going to be differences and they just are unable to deal with to the flexibility and the scale that they want to go up and down, by the way that they're unable to really handle whatever the world throws up. But I think we're going to be living in a continually uncertain environment. >>Yeah, I definitely would agree with you, and I think it's going to get back to normal at some point, but even is gonna have an impact into 2021 as many people are kind of figuring out the window, people saying no spring 2021 Maybe, you know, there we started get some semblance of normality the way it was, but still that environment and this brings up the whole summit online that you guys are doing. Your summits have been a great set of events. We've covered many of them with the real key physical cube. Now we're doing the Virtual Cube. They've been a practitioner and user, the developer builder event. It's a free event. Nutrition had. Now you have them all over the world. They're going on virtual. People still need to build out these projects. There's still a demand, and some projects are being cut. Some are, as you guys look over the horizon with your customer base conversations around what to fund whatnot the fund. As you mentioned. What are some of the things that you're seeing and recommending to customers that they should continue to double down on? Because smart manager is going to step back and say, Hey, I can see some gaps. We're going to double down on that and we're gonna kill that. We're gonna move this over here. There's going to be a reinvention and growth strategy that they have to figure out quickly. There's no yet playbooks emerging, but it's clear out the video virtual interactions. But those projects get double down your thoughts on the customer builders out there. >>I think that's absolutely right in it and expands every industry you can think about. Think about, you know, I was talking Teoh several customers in the healthcare space. And how long has it been five years that people have been touting that telemedicine is really gonna be that thing that eventually comes and eventually becomes a big thing? This has really accelerated that, such that. Now I've talked to probably dozens and dozens of people who, for the very first time of talk to their doctors over being their cell phone because they don't want to go into the hospital for you're getting, you know, six or something like that. Then they just have a minor medical things you need to do. Telemedicine is one of those things that is really taking off, and there's been really enabling, frankly, that customers have been able to do telemedicine. That's really helps, knows that that wanted to stay safe but also get good medical advice. I think that's just one example where we're gonna continue to see this go. I think coming out of this the other thing, our custom, lot of our customers were thinking about, and anytime you really go into an uncertain economic world. You want to think about capital preservation. Now is not the time you want to go spend money to build your own data center or to buy your own servers. If ever there was a time where the cloud makes the most sense, capital preservation >>is E >>particularly we don't know if there's gonna be an economic recession. We don't know how long this is going to take. All businesses, whether they're severely impacted, should be really thinking about that capital preservation. But they've also got to be thinking about how they innovate. You know, I've talked to ah, popular ride sharing customer the other day, and they were talking about how ride sharing his way down. But they're still using this as a time to lean forward into innovation because they know coming out of this, they want to be ahead of where their competitors are going to be. And they really want to use this as an opportunity to take their own internal teams, focus them on where they think the biggest potential is gonna be. And then once the economy turns around people out and about again, they can hit the accelerator and really take off. So I think that's really how a lot of our customers were thinking about situation where they're right now. >>You know, you guys haven't had a steep learning curve over the years with cloud and cloud scale. I think as the world comes in, the human capital piece becomes interesting, too, not just on of spending with money, monetary, the human capital to work, how people are contributing. So this brings up the whole reinvention. It's funny to watch as people are forced with these first generation problems of how to make things digital, how to get scale going. You have people who have learned it, have a learning curve, and again there's no compression algorithm for experience, as you guys like to point out. So >>this is >>creating this kind of like, How do I change the roles of my company? And so I want to get your thoughts because we're looking for proof points because a lot of the answers are not yet evolved and usually things they're not understood before they become mainstream. But people have to react really fast. What are some examples? Can you give around how Cove in applications are rolling out because that's truly a indicator in my mind of what people are doing with the cloud. Because Covert was an instant response. We've already interviewed a few folks that are on Amazon around Covitz Solutions, where the standing of either analytics or doing some things Could you use the covert of example of how rapid deployment or reinvention of data or business models our rendering themselves? >>Yeah, absolutely. I think there's a couple of different what one is. But for the very first thing that most people look at is how do we get data like we just need to find data around this space. And so we've worked with a number of partners and customers on How do we really go, help build Data Lakes in the cloud and coming getting all that data in one place so that both governments as well as private enterprises, can really start to think of that Data slices in different ways on get to look at what is the actual data, whether it's one of the number of hospital that's available one of the number of tests that are happening, you know, one of the number of oh infections that we're seeing, where the rate of change, etcetera. We also work with a number of our analytics partners, and we have a wide range of analytics partners that are really taking this as an opportunity where they can rapidly then take that data and slice it a number of different ways to try to help understand how they respond. I think you know, the first part of that was on the healthcare side where folks were saying, Where do we need enough ventilators? Where we where do we need to go? Build hospitals? Are we start to identify hot spots right where I see if you can really look at kind of second order derivatives of kind of changes, and you can look at it close enough, you could say, Oh, there's a hot spot popping up in this particular area and eventually you know, if we can get some better data, contract tracing and things like that where you can open up the economy and still have, you know very quickly identify where a hot spot might be a merging. Those are the types of data pieces that you know what the right levels of of security and data privacy, but with but with access to that data, we can get a handle on how some of these things are happening. Then I think you go and you look at s So that's that's kind of some of the data analytics pieces. Right? Then you also go look at what are folks doing on the testing side? And I think, you know, there's a lot of discussion about how well testing is done. I think we all >>know that there >>are ways that we always thought maybe it was a little bit further along with it is, but there's a number of private places that are actually really speeding up. I think this is one of the big areas that Amazon best, right? And I don't I don't know. We'll see if we are able to get there faster than some of the other places, but we we see a real need for testing. Testing is one of those such a critical component if we could do rapid testing, frequent testing, both for our own employees. But frankly, for for all the industries that we all rely on, I have come to rely on, particularly in this virtual world. We know that the faster we can get testing and more reliable, we can get testing. The better we are able to then isolate, get people to self quarantine and really kind of control that mass spread >>of the >>disease. >>I know >>you know >>healthcare is interesting. One of the emerging things we're seeing coming out of the summit here and some of the conversations we had is how the enterprise has always been kind of a hard environment to find stuff. As people live at home and working at home, working remotely, working in remote teams, the idea of searching for stuff becomes interesting. So you guys announced the general availability, Kendra. The timing couldn't have been better for that, because that's really giving you a Google like vibe feel for funding information. But it's really an integration play under the covers, so I think that's the kind of trend that we're seeing. We're seeing also startups putting up APS out there so you see a lot of activity. That's kind of in line with this. That you guys are announcing anything >>at any >>update on the Kendra or >>Canada is fantastic, and it's it's really I think struck a nerve with folks where the traditional way of thinking about search, particularly internal for internal Internets just doesn't work. You know how many hits you get and how many millions of people across billions and billions of people on the Internet that that model works on the Internet. You might be looking for very specific things. Um, and with machine learning, we're able to tell what is the intent of the requests that people are looking for and take you to the right place so that if you say you know one of the hours of my help desk, there's a very specific page that you're looking for, which is this number. In fact, you're not looking for a job to go to. You're not looking for information about help desks. You're looking for the actual hours of my internal help desks, particularly probably from my building. And as we do build these ML models that can start to learn on how your Internet works and how people are thinking about it and what's helpful or not, we've been able to improve an Internet search orders of magnitude. I've used it internally for our own. I'm instrumented it. It's night and day compared to what we used before was kind of your keyword search type of thing. So I think applying ML, particularly when people remote and really relying on resource, is like that where they can't just, you know, lean over to a cube next to them and say, Hey, we're still you know what time is the help desk open? >>I think getting breaking down the silos to just we build that abstraction layer a data leak really kind of makes a big difference. >>That's right. >>So final question for you as companies settle into the new realities that are upon them, what's the outlook for the rest of 2020 for you guys? And what do you say? That customers that are here on the online trying to consume the virtual content that they should be building out because you've got not just customers. You've got commercial customers, you got public sector and you got an ecosystem. You got partners out there who are building on top of AWS. Um, rolling this together. What's your message to them? What's on the outlook? >>2020 Number one. I encourage everyone to take advantage. I think In many ways, some of these virtual summits are great opportunity, maybe, for those were unable to travel to the summit or to be able to actually physically get there. It's a great opportunity to learn, really dive in trying to do some virtual labs really get in and understand some of the new features and functionality that are out there from a partner perspective. Many of the things that we're building, whether it's our outflow service that we just launched a couple of weeks ago, that helps us to really connects to our various partners into a data lake. As John was mentioning those air, these were really some of the things that you know, if you think about our broad swath of our partner ecosystem, encourage our customers to really look at all of the partners that are running on AWS who have great solutions. Like the Cube. You're looking for virtual events. They have. They have an awesome product you should check out, but we have a wide set of partners that will help you. Yeah, put together the virtual world that you all are trying to work through right now and encourage you just to learn >>I really appreciate the plug, actually, one for the cube. A new event Cloud. What? We're trying to figure it out. I think this kind of reminds me of a famous quote I heard on the queue, which is a notable one, is that everything in the future that is going to be invented was on Star Trek or Star Wars. So I assume we're gonna have video cameras and everyone's office, and we'll be able to go and talk to folks. So looking forward to again, standing up content, getting the content and connecting people. Thanks for spending >>the >>time out of your day to come in and talk with me and share your insights. And, ah, Amazon Summit Web services Summit online Virtual cube Virtual. Thanks for your time. Appreciate your insights. >>Great. Thank you. >>OK, Cube here. Virtual in our studio covering remotely all the top content out there covering AWS summit online. There's a whole new reality rolling it together. I'm John Furrier. Thanks for watching. Yeah, yeah, yeah, yeah

Published Date : May 13 2020

SUMMARY :

from the Cube Studios in Palo Alto and Boston connecting with thought leaders all around the world. So we're here at the AWS Summit online, and you guys are still pulling it off Thanks for having me. So before we get into some of the announcements in the customer focus things that you guys are doing, I think you know, part of part of what we've seen from our customers as we talk out there, Google and Microsoft has had the up time you guys had, but this really has been the future pulled forward. of the streaming services like you said, the Netflix is the who lose that Disney Pluses of the world. that this is also gonna hit the small, medium sized enterprises as well as some of the big ones. many of those government agencies to try to figure out how we can get the money in the hands of the sales and marketing, um, it's not like you guys are preaching to the customers because you're living through the same You have to still sell services and market your products What's your Yeah, part of I think you know, in my new role. And we would you know, there's a bunch of the early adopters would lead into that and really got it. and growth strategy that they have to figure out quickly. Now is not the time you want to go spend money to build your own data center or to buy your own servers. We don't know how long this is going to take. You know, you guys haven't had a steep learning curve over the years with cloud and cloud scale. But people have to react really fast. I think you know, the first part of that was on the healthcare side where folks were saying, We know that the faster we can get testing and more reliable, we can get testing. So you guys announced the general availability, Kendra. You know how many hits you get and how many millions of people across I think getting breaking down the silos to just we build that abstraction layer That customers that are here on the online trying to consume the virtual content that to work through right now and encourage you just to learn I really appreciate the plug, actually, one for the cube. Thanks for your time. Thank you. Virtual in our studio covering remotely all the top content out there

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Tim Cramer, Red Hat | Red Hat Summit 2020


 

>> From around the globe, it's theCube with digital coverage of Red Hat Summit 2020, brought to you by Red Hat. >> Welcome back. I'm Stu Miniman, and this is the cubes coverage of Red Hat Summit 2020. Of course, this year's event happening digitally, we're talking to Red Hat executives, partners, customers, where they are around the globe, bringing them remotely into this digital event. And really important topic, of course, has been Automation for a long time, I think back to my career automation is something we've been talking about for decades, but even more important in today's age. Happy to welcome back to the program, Tim Kramer with Red Hat, Vice President of Engineering is that I don't have listed view here. But since we last talked to him at Ansible Fest, has been a little expansion in the scope of what you're working on. First of all, welcome back, and tell us what's new in your world? >> All right, thanks a lot. Yeah, there's been rather substantial change in roles. I'm now in charge actually, of all of the engineering within Red Hat. All the development engineering site includes: the middleware teams, Red Hat Enterprise Linux, of course management and automation, the new team that we just brought over from IBM doing Advanced Container Management. I'm basically running the whole thing and OpenShift of course. >> Excellent. Just a few things to keep you busy. Congratulations on that and love your support in the the Boston "Hello World" rella eight shirt that of course we saw last year at summit. I know one of the things being digital is people do miss some of the t-shirts. I know my family was quite fond of the "May The Fourth Be With You" shirts, that Red Hat did one year at summit. Of course, celebrating Star Wars Day, highly celebrated in in the Miniman household. But Tim, let's talk about Ansible. This brings our audience up to speed, what's happening that some of the latest pieces, and of course, it's been one of the great success stories. Ansible was a lot of adoption before the acquisition, but really accelerated over the last few years? >> At Ansible Fest, we talked a lot about technology to come and showed a few demos of the possibilities. What we have done since then is actually bring all of that technology to life and to expand it. One thing that Red Hat has really done is continue to invest heavily in Ansible, to make sure that we can bring new capabilities and new value to the subscription for everyone. Some of the things that have been happening since summit, which of course we are in, and since Ansible Fest, since we last talked was it, the community continues to scale at a really rapid rate. It's almost hard to keep up. And the number of modules that we have had is grown just tremendously. We have well over 3000 modules now that are available, and as customers and partners and also just casual users are looking through that, it's difficult to figure out: what's really supported? What's really rock solid? What can I count on? And what is, maybe sort of that Wild West community, I'm just trying out some stuff with Ansible and see how it goes. We've been focusing on a lot, is a place that you can come to the Ansible automation platform and the hub where you can now get this content and you can rely on the fact that it's going to be certified by partners, tested by partners, they're always keeping up with the latest updates. A great example of this is, let's just take NetApp or F5, or Cisco as good examples, across the various spaces, we absolutely in the Ansible engineering team are not experts on all of the latest changes, the new hardware coming out, the new software upgrades that they're making. And our ability to keep up with that is pretty difficult. We just can't do it, but they sure can. And their customers, and our customers are both demanding that we give them more content, better content, and we need to be able to do it at the rate that our partners want to be able to provide that kind. As an example, normally we were kind of slowing Ansible down and trying to do one release every six months. But if a new piece of software, a new switch or a new disk array or anything comes out in the meantime, all of our customers had to wait for that next six months release, that was not very convenient. And having an expectation that our partners are going to line up on our schedule is, well, That didn't work out so well for them. We've created the certified content. And we now have the goals to have 50 certified partners. Back at first, I think we had three or four. We're now up to 30, our goal is to hit 50. We had about 100 modules that we showed at fest that were certified, we now have over 1200 modules that are certified content. And these are our partners, creating this content and making it stable and secure for everyone to use. >>So that, I think, by far   >> That was the coolest thing that we've done. >> Yeah, it's great to see that progress. Congratulations on the momentum since Ansible Fest. One of the other things talked about that back at that show, we talked about how analytics and automation, how those are going together, how's adoption been? Is this impossibly met? >> Adoption on the analytic side has been... It's been taking off. It was pretty nascent. I can tell you that, that we've grown by about five X there, but we started a little bit small. We had a few customers that signed up early on to do it. I think probably the more impressive thing is that, we have a couple of customers in markets that you would traditionally think, we're not going to get their data, they're more concerned about what we're sharing, but we have a major bank, we have a major manufacturer that have well over 10,000 systems providing data back into Red Hat that allows us then to analyze and provide a bunch of analytics back on their running estate. And I think that's amazing, seeing the big customers that are coming in from Marcus that you might think, we're probably not going to get a lot of uptake has been really exciting to me. >> All right, you talked a bit about how Ansible fits into the ecosystem, of course being at summit, want to understand a bit more how Ansible the latest of how it's fitting into the rest of the Red Hat portfolio. I've got interviews with Stephanie Shiraz, talking about you, Raul and Joe Fitzgerald, talking about ACM, your group I know is heavily involved working on a lot of those pieces. Help us understand how this is kind of a seamless portfolio. >> I think that's one of the most important things that we do within Red Hat team, is that we have to share the sufficiency across all the product groups and make them better and provide an additional enhanced value there. We've done a lot on the RHEL side, probably one of the maybe lesser known thing is that, we've been working really closely on OpenShift. And actually, we have a lot of customers now that really want the Ansible automation hub available on OpenShift as a first-class application. We're doing things, we're writing operators for those so that we can automate the updates and upgrades and back up and all of that important functionality, so that it's really easy, than to manage your Ansible automation hub, running on OpenShift, that's one big thing. And then we're going to integrate that really well into the advanced container management, that the team from IBM that came over is working towards. I have a really close partnership with ACM team to make sure that we can start to not only gather lists of affected systems, but then take that list and do a bunch of automations against it. >> That's one. On the RHEL side, we've done a lot. We introduced at last summit rally, and we talked about having insights as part of that. Since then, we've been adding more and more capabilities into insights, and to enhance that value of the subscription route. We looked at adding in, well, advisor is now what we used to call insights. It's just something that advises you about problems or issues that may be occurring in your URL instances that are running on prem. We've also added in a drift service, so you can tell if your configurations are sort of drifting apart. We've added in a compliance checker, so you can define some kind of a policy or compliance that you want to enforce on all of your running instances, and we make sure that you're still compliant. We also have a vulnerability detector, which you'd kind of expect, so any nasty security issues that come along, we can pop those up and show you right away. And probably some of the... One of the newer things is, we allow you to do patching. And you can do that patching, right from cloud@redhat.com. We also have another new very exciting feature, which is Subscription Watch, also on cloud@redhat.com. And what this allows you to do is to see and manage all of your subscriptions across your entire hybrid estate. From what you're running on prem, to what you're running in any of the public clouds, we can actually track that for you. You can see what kind of usage you have. And then, make better economic decisions for yourself, and then be able to easily expand that usage if you want to, it used to be a little bit more difficult to do that. We're trying to make subscriptions just like as much in the background as possible to make it easier for our customers. >> Tim, one of one of the big changes customers have to go through is moving from, their environment in their data centers, to the leverage of SaaS and managing things that are outside of their control and the public cloud. You've got an engineering development team, and you've got software that went from, mostly going in customers data centers too, you've got SaaS offerings, you're living in the public cloud. Want to understand, what's changing in your world? What advice would you give to other people as to kind of the learnings that Red Hat has had going through those pieces? >> It's actually a kind of a neat story, because after we change to start making a lot of our services that we had just only shipping products on prem into cloud based services, we had to develop this platform to be able to host all of these services. We started with the insights platform, because we already had that running out in the public cloud. So that was the obvious first thing to base everything on. But we had to build out that platform so that it could support all these services, the ones I just talked about, that are with REL are really good examples. Between a policy, compliance drift, all of these different kinds of services that we're offering, we had to build out that set of capabilities and services in what we're calling sort of the cloud@redhat.com platform. What I'm seeing is that a lot of customers are going through some of these same kinds of thoughts. Like they have a myriad, let's say of applications that are running that they're trying to provide back into their their own company. Different divisions of a company, they have things that are running in the cloud, some things that are running on prem, and they want to start to be able to offer a more cohesive set of services, consolidate some of these, share some of the engineering effort that they have across their various teams. This is exactly the journey that we went through to get to cloud@redhat.com. Finding a surprising number of customers that are actually really interested just in that story, about how we did that. One of the things that we've found is, we've been working with the folks at the open innovation labs within Red Hat. And this is one of the transformation stories that they see constantly as well. We've worked with them and shared this, they're a great resource to help customers kind of think through that problem and get them into a new kind of a platform. But it's quite a journey. We've been really focused on the infrastructure and on prem. Moving to the cloud was a big. But I'll tell you it engineering can move so much faster in a SaaS service than it can with on prem software delivery. It's been remarkable how quickly we could get there. >> Tim, one other thing, if I look at Red Hat, you're a global company, most development organizations are highly distributed to begin with. So many companies today are now having to rapidly figure out how do I manage people that are working from home? How do I live in these environments? From an automation tooling, we'd love to hear any advice you have there, as well as just anything else from your engineering experience in your teams that other people might be able to learn from, as they're dealing with today's landscape. >> To be honest, this is a... We have never seen anything like this in our history, with this kind of pandemic that's happening worldwide. It's shifting everything about business. And it has been challenging just within Red Hat engineering for how we can manage the engineers and their expectations and how difficult it can be to work from home. I have amazing stories from my own engineers. I had an engineer who's in Spain and his wife is a nurse. She's on like 18-hour shifts, the hospital comes back, they have to separate, he's got the kids. And because they don't want them to get infected, it's a really, really difficult working situation for a lot of families out there to try to make it through this. One of the things at Red Hat is, we just have to recognize that it's okay to slow things down a little bit. Let our engineers not feel the pressure that they have to do both childcare and school-at-home and caring for sick relatives or sick family, as well as meet all of your deadlines, it's kind of too much. We've been really... We're trying to be very compassionate with our folks letting them know that we have their back, and it's going to be okay as we try to get ourselves through this ridiculously different time that we've never seen anything like this, like I said. From an engineering perspective, I think work-from-home has been, it's okay for some people. If you have a larger home, I think it's a little easier maybe to find a room that you can go into and do your work. For some, no, if they're in an apartment, or you're sharing with a bunch of friends, it's not your workplace. And it can be really challenging to figure out how to work for eight hours a day with sort of a lot of distractions or just feeling confined and it's just been really difficult for anybody that wants to try to get out, you go a little stir-crazy. The good thing I guess is that engineering is naturally lends itself to being able to be remote and work from home. We have an advantage that way, than other industries, which is great. But it's definitely been really challenging for our teams to be able to cope with this and all we can do is just be really understanding. >> Tim, we appreciate the stories, they're definitely everyone's working through some challenging times. Want to give you the final word as to really takeaways as to what should people be watching? What things should people be going back and looking at from an automation standpoint as they leave Red Hat Summit 2020? >> We're just going to continue to work with the community, work with our partners, get more certified content and continue to scale, the best way that we can for all of our users and our customers. That is the key focus. We want to continue automating and providing all of that flexibility. If you want all 4000 modules and a big download, we certainly are... We're going to continue to give you that option. But if you want to be able to start customizing what you download, maybe only relying on certified content, instead of community content, we're going to give you that option now as well, so that you know what you're running. And with the analytics, we're just scratching the surface here. We're getting some great data. It's helping us to develop new ways of insights into how your systems are running. And that'll get very exciting as we go forward. I know that we've seen like a Forex increase already in the amount of insights attached to REL, which is really great, and for now, at least in the hundreds of customers that are using the AI, I think as we show more value there, you'll get a lot more customers to provide some of their data which will allow us then collectively to come up with some really great analytics to help people become more efficient with your automation. >> Well, Tim Kramer, thank you so much for the updates. And thank you to everything your team's doing. And just a reminder to the audience, of course, these communities not only are important technical resources, but many of them you've made friends with over the years. If you need help, reach out to the community. There are so many good stories that can be found amongst these communities helping each other through these challenging times. Much more coverage from Red Hat Summit 2020. I'm Stu Miniman, and thank you as always for watching theCube. (gentle upbeat music)

Published Date : Apr 29 2020

SUMMARY :

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Tim Cramer, Red Hat | Red Hat Summit 2020


 

>> From around the globe, it's theCube with digital coverage of Red Hat Summit 2020, brought to you by Red Hat. >> Welcome back. I'm Stu Miniman, and this is the cubes coverage of Red Hat Summit 2020. Of course, this year's event happening digitally, we're talking to Red Hat executives, partners, customers, where they are around the globe, bringing them remotely into this digital event. And really important topic, of course, has been Automation for a long time, I think back to my career automation is something we've been talking about for decades, but even more important in today's age. Happy to welcome back to the program, Tim Kramer with Red Hat, Vice President of Engineering is that I don't have listed view here. But since we last talked to him at Ansible Fest, has been a little expansion in the scope of what you're working on. First of all, welcome back, and tell us what's new in your world? >> All right, thanks a lot. Yeah, there's been rather substantial change in roles. I'm now in charge actually, of all of the engineering within Red Hat. All the development engineering site includes: the middleware teams, Red Hat Enterprise Linux, of course management and automation, the new team that we just brought over from IBM doing Advanced Container Management. I'm basically running the whole thing and openShift of course. >> Excellent. Just a few things to keep you busy. Congratulations on that and love your support in the the Boston "Hello World" rella eight shirt that of course we saw last year at summit. I know one of the things being digital is people do miss some of the t-shirts. I know my family was quite fond of the "May The Fourth Be With You" shirts, that Red Hat did one year at summit. Of course, celebrating Star Wars Day, highly celebrated in in the Middleman household. But Tim, let's talk about Ansible. This brings our audience up to speed, what's happening that some of the latest pieces, and of course, it's been one of the great success stories. Ansible was a lot of adoption before the acquisition, but really accelerated over the last few years? >> I think it's been very exciting. We talked a lot about some of the cool things that we're going to be working on it Ansible Fest, and we showed a lot of demos. We're actually now bringing a lot of those technologies to light. And the main thing that we've been focused on really, is let's make sure that we're continuing to add really great value to the Ansible subscription. And especially for our customers, and any users actually, we want to make sure that we can continue to scale with the community and partners that are part of Ansible. And we are also um, (mumbles) Freezing. We just start that question again, fix that one in post? Sorry. >> Just stay in. It's okay, we'll pick it up there. They can do a trend, though. Tim, I'll start the question again? >> Okay. >> We'll start this. I'll reframe the question again. Then I'll cut your screen and you'll go, and... Tim, let's focus specifically on the updates on what's happening in Ansible. >> At Ansible Fest, we talked a lot about technology to come and showed a few demos of the possibilities. What we have done since then is actually bring all of that technology to life and to expand it. One thing that Red Hat has really done is continue to invest heavily in Ansible, to make sure that we can bring new capabilities and new value to the subscription for everyone. Some of the things that have been happening since summit, which of course we are in, and since Ansible Fest, since we last talked was it, the community continues to scale at a really rapid rate. It's almost hard to keep up. And the number of modules that we have had is grown just tremendously. We have well over 3000 modules now that are available, and as customers and partners and also just casual users are looking through that, it's difficult to figure out: what's really supported? What's really rock solid? What can I count on? And what is, maybe sort of that Wild West community, I'm just trying out some stuff with Ansible and see how it goes. We've been focusing on a lot, is a place that you can come to the Ansible automation platform and the hub where you can now get this content and you can rely on the fact that it's going to be certified by partners, tested by partners, they're always keeping up with the latest updates. A great example of this is, let's just take NetApp or F5, or Cisco as good examples, across the various spaces, we absolutely in the Ansible engineering team are not experts on all of the latest changes, the new hardware coming out, the new software upgrades that they're making. And our ability to keep up with that is pretty difficult. We just can't do it, but they sure can. And their customers, and our customers are both demanding that we give them more content, better content, and we need to be able to do it at the rate that our partners want to be able to provide that kind. As an example, normally we were kind of slowing Ansible down and trying to do one release every six months. But if a new piece of software, a new switch or a new disk array or anything comes out in the meantime, all of our customers had to wait for that next six months release, that was not very convenient. And having an expectation that our partners are going to line up on our schedule is, oh! That didn't work out so well for them. We've created the certified content. And we now have the goals to have 50 certified partners. Back at first, I think we had three or four. We're now up to 30, our goal is to hit 50. We had about 100 modules that we showed at fest that were certified, we now have over 1200 modules that are certified content. And these are our partners, creating this content and making it stable and secure for everyone to use. So that, I think, far >> (mumbles) >> That was the coolest thing that we've done. >> Yeah, it's great to see that progress. Congratulations on the momentum since Ansible Fest. One of the other things talked about that back at that show, we talked about how analytics and automation, how those are going together, how's adoption been? Is this impossibly met? >> Adoption on the analytic side has been... It's been taking off. It was pretty nascent. I can tell you that, that we've grown by about five X there, but we started a little bit small. We had a few customers that signed up early on to do it. I think probably the more impressive thing is that, we have a couple of customers in markets that you would traditionally think, we're not going to get their data, they're more concerned about what we're sharing, but we have a major bank, we have a major manufacturer that have well over 10,000 systems providing data back into Red Hat that allows us then to analyze and provide a bunch of analytics back on their running estate. And I think that's amazing, seeing the big customers that are coming in from Marcus that you might think, we're probably not going to get a lot of uptake has been really exciting to me. >> All right, you talked a bit about how Ansible fits into the ecosystem, of course being at summit, want to understand a bit more how Ansible the latest of how it's fitting into the rest of the Red Hat portfolio. I've got interviews with Stephanie Shiraz, talking about you, Raul and Joe Fitzgerald, talking about ACM, your group I know is heavily involved working on a lot of those pieces. Help us understand how this is kind of a seamless portfolio. >> I think that's one of the most important things that we do within Red Hat team, is that we have to share the sufficiency across all the product groups and make them better and provide an additional enhanced value there. We've done a lot on the rail side, probably one of the maybe lesser known thing is that, we've been working really closely on openShift. And actually, we have a lot of customers now that really want the Ansible automation hub available on openShift as a first-class application. We're doing things, we're writing operators for those so that we can automate the updates and upgrades and back up and all of that important functionality, so that it's really easy, than to manage your Ansible automation hub, running on openShift, that's one big thing. And then we're going to integrate that really well into the advanced container management, that the team from IBM that came over is working towards. I have a really close partnership with ACM team to make sure that we can start to not only gather lists of affected systems, but then take that list and do a bunch of automations against it. >> (mumbles) >> That's one. On the real side, we've done a lot. We introduced at last summit rally, and we talked about having insights as part of that. Since then, we've been adding more and more capabilities into insights, and to enhance that value of the subscription route. We looked at adding in, well, advisor is now what we used to call insights. It's just something that advises you about problems or issues that may be occurring in your URL instances that are running on prem. We've also added in a drift service, so you can tell if your configurations are sort of drifting apart. We've added in a compliance checker, so you can define some kind of a policy or compliance that you want to enforce on all of your running instances, and we make sure that you're still compliant. We also have a vulnerability detector, which you'd kind of expect, so any nasty security issues that come along, we can pop those up and show you right away. And probably some of the... One of the newer things is, we allow you to do patching. And you can do that patching, right from cloud@redhat.com. We also have another new very exciting feature, which is Subscription Watch, also on cloud@redhat.com. And what this allows you to do is to see and manage all of your subscriptions across your entire hybrid estate. From what you're running on prem, to what you're running in any of the public clouds, we can actually track that for you. You can see what kind of usage you have. And then, make better economic decisions for yourself, and then be able to easily expand that usage if you want to, it used to be a little bit more difficult to do that. We're trying to make subscriptions just like as much in the background as possible to make it easier for our customers. >> Tim, one of one of the big changes customers have to go through is moving from, their environment in their data centers, to the leverage of SaaS and managing things that are outside of their control and the public cloud. You've got an engineering development team, and you've got software that went from, mostly going in customers data centers too, you've got SaaS offerings, you're living in the public cloud. Want to understand, what's changing in your world? What advice would you give to other people as to kind of the learnings that Red Hat has had going through those pieces? >> It's actually a kind of a neat story, because after we change to start making a lot of our services that we had just only shipping products on prem into cloud based services, we had to develop this platform to be able to host all of these services. We started with the insights platform, because we already had that running out in the public cloud. So that was the obvious first thing to base everything on. But we had to build out that platform so that it could support all these services, the ones I just talked about, that are with REL are really good examples. Between a policy, compliance drift, all of these different kinds of services that we're offering, we had to build out that set of capabilities and services in what we're calling sort of the cloud@redhat.com platform. What I'm seeing is that a lot of customers are going through some of these same kinds of thoughts. Like they have a myriad, let's say of applications that are running that they're trying to provide back into their their own company. Different divisions of a company, they have things that are running in the cloud, some things that are running on prem, and they want to start to be able to offer a more cohesive set of services, consolidate some of these, share some of the engineering effort that they have across their various teams. This is exactly the journey that we went through to get to cloud@redhat.com. Finding a surprising number of customers that are actually really interested just in that story, about how we did that. One of the things that we've found is, we've been working with the folks at the open innovation labs within Red Hat. And this is one of the transformation stories that they see constantly as well. We've worked with them and shared this, they're a great resource to help customers kind of think through that problem and get them into a new kind of a platform. But it's quite a journey. We've been really focused on the infrastructure and on prem. Moving to the cloud was a big. But I'll tell you it engineering can move so much faster in a SaaS service than it can with on prem software delivery. It's been remarkable how quickly we could get there. >> Tim, one other thing, if I look at Red Hat, you're a global company, most development organizations are highly distributed to begin with. So many companies today are now having to rapidly figure out how do I manage people that are working from home? How do I live in these environments? From an automation tooling, we'd love to hear any advice you have there, as well as just anything else from your engineering experience in your teams that other people might be able to learn from, as they're dealing with today's landscape. >> To be honest, this is a... We have never seen anything like this in our history, with this kind of pandemic that's happening worldwide. It's shifting everything about business. And it has been challenging just within Red Hat engineering for how we can manage the engineers and their expectations and how difficult it can be to work from home. I have amazing stories from my own engineers. I had an engineer who's in Spain and his wife is a nurse. She's on like 18-hour shifts, the hospital comes back, they have to separate, he's got the kids. And because they don't want them to get infected, it's a really, really difficult working situation for a lot of families out there to try to make it through this. One of the things at Red Hat is, we just have to recognize that it's okay to slow things down a little bit. Let our engineers not feel the pressure that they have to do both childcare and school-at-home and caring for sick relatives or sick family, as well as meet all of your deadlines, it's kind of too much. We've been really... We're trying to be very compassionate with our folks letting them know that we have their back, and it's going to be okay as we try to get ourselves through this ridiculously different time that we've never seen anything like this, like I said. From an engineering perspective, I think work-from-home has been, it's okay for some people. If you have a larger home, I think it's a little easier maybe to find a room that you can go into and do your work. For some, no, if they're in an apartment, or you're sharing with a bunch of friends, it's not your workplace. And it can be really challenging to figure out how to work for eight hours a day with sort of a lot of distractions or just feeling confined and it's just been really difficult for anybody that wants to try to get out, you go a little stir-crazy. The good thing I guess is that engineering is naturally lends itself to being able to be remote and work from home. We have an advantage that way, than other industries, which is great. But it's definitely been really challenging for our teams to be able to cope with this and all we can do is just be really understanding. >> Tim, we appreciate the stories, they're definitely everyone's working through some challenging times. Want to give you the final word as to really takeaways as to what should people be watching? What things should people be going back and looking at from an automation standpoint as they leave Red Hat Summit 2020? >> We're just going to continue to work with the community, work with our partners, get more certified content and continue to scale, the best way that we can for all of our users and our customers. That is the key focus. We want to continue automating and providing all of that flexibility. If you want all 4000 modules and a big download, we certainly are... We're going to continue to give you that option. But if you want to be able to start customizing what you download, maybe only relying on certified content, instead of community content, we're going to give you that option now as well, so that you know what you're running. And with the analytics, we're just scratching the surface here. We're getting some great data. It's helping us to develop new ways of insights into how your systems are running. And that'll get very exciting as we go forward. I know that we've seen like a Forex increase already in the amount of insights attached to REL, which is really great, and for now, at least in the hundreds of customers that are using the AI, I think as we show more value there, you'll get a lot more customers to provide some of their data which will allow us then collectively to come up with some really great analytics to help people become more efficient with your automation. >> Well, Tim Kramer, thank you so much for the updates. And thank you to everything your team's doing. And just a reminder to the audience, of course, these communities not only are important technical resources, but many of them you've made friends with over the years. If you need help, reach out to the community. There are so many good stories that can be found amongst these communities helping each other through these challenging times. Much more coverage from Red Hat Summit 2020. I'm Stu Miniman, and thank you as always for watching theCube. (gentle upbeat music)

Published Date : Apr 15 2020

SUMMARY :

brought to you by Red Hat. I think back to my career automation is something the new team that we just brought over from IBM and of course, it's been one of the great success stories. a lot of those technologies to light. Tim, I'll start the question again? on the updates on what's happening in Ansible. all of that technology to life and to expand it. One of the other things talked about that back at that show, we have a couple of customers in markets that you would how Ansible the latest of how it's fitting to make sure that we can start to not only One of the newer things is, we allow you to do patching. Want to understand, what's changing in your world? One of the things that we've found is, we've been working to learn from, as they're dealing with today's landscape. One of the things at Red Hat is, we just have to recognize Want to give you the final word as to really takeaways and continue to scale, the best way that we can And just a reminder to the audience,

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Grant Courville, Blackberry QNX | AWS re:Invent 2019


 

>>LA from Las Vegas. It's the cube covering AWS reinvent 2019 brought to you by Amazon web services and along with its ecosystem partners. >>Welcome back to Vegas, Lisa Martin with John farrier. We are live at AWS reinvent in the expo hall at the sands convention center. There's tons of people in here. You could probably hear some of the background AWS expecting 65,000 or so folks. John, how many of those 65,000 and have you talked to in the last two days? >>Well, I can hear all the conversations happening at once. It's about hybrid cloud, IOT edge data, machine learning. my head's going to come. >>I was going to say lots of cool stuff. John and I are pleased to be joined by Greg Coralville, the VP of products and strategy for Blackberry Q. Next group. Welcome to the program >>to be here with 65,000 of our closest friends. >>His friends. Exactly. So Blackberry, cute X. What's it all about? >>What's it all about? Well, we do software. We do embedded software for mission critical systems at this event, at the AWS reinvent over showing a software and a really cool car, a karma, and we're connecting it to the AWS IOT backend services and showing some really, really cool use cases. Some of which are near term summer, which are a bit longer term are pretty exciting. Take a quick minute to describe Kunis. Is background acquired by Blackberry system history legacy? Exactly. Just take a quick minute to explain that. So we were founded in 1980 and then developing software for mission critical devices and medical, industrial. And then we started developing software for automotive in 1998 so we've been in automotive for about 20 years and developing originally an infotainment and then digital instrument clusters, telematic systems, gateways, safety systems, acoustics systems, pretty much becoming the software platform in the car because in the car, the car, the software is to be reliable, safe, secure. >>So we're trusted to deliver that. In automotive, we were acquired by Blackberry in 2010 and we're bringing the best of Blackberry and automotive and all of our other markets. So Lisa and I always talk about IOT is RPA automation. All this stuff's going on. But one of the things that comes up is we're trying to grok what's the software development environment in the cloud, in the car, and a Amazon one by having great API APIs. Yep. That was one of their core design principles. Is there a similar design principle from a car standpoint? Because if I'm an app developer, I just love, I have my mobile app sit on the car, right? But I don't want to have to become an expert on all the nuances of is there a connector? So is there going to be multiple platforms? What's the, what's the principle? Can you explain that a great question and great observation. >>So cars traditionally have been proprietary, pretty much closed systems and started open up with CarPlay and Android auto or all of a sudden you saw your mobile device being able to communicate with the car and now I could run Android apps, I could run iOS apps and started to open it up a bit. And now what you've seen is cars are becoming more connected, they're becoming more automated, eventually autonomous. Um, they're definitely, and what you're seeing in the car is in order for that car to really evolve and to offer connected services and shared mobility and the electrification that's occurring, the automotive industry is going through a disruption. We've all heard that and it really is true. So to the point where the electronics in the car, the networks in the car, the software in the car, it's getting completely redesigned and you're seeing a lot more high end processors. >>You're seeing safety critical systems, which have always been in cars, but now you're seeing a lot more complexity. And that speaks to exactly what we do. So where that car's going, if you think about it, is moving to more of a software platform. You have applications and mobile devices. Why? Because you've got Android and you've got iOS. That car is moving to that sort of a common platform where with the help of AWS connected services, the cubix Blackberry Punic software platform in the car, all of a sudden that'll open the door to that kind of environment to applications, to connected services. And that's exactly where it's going. So connectivities, it's here and it's going to be predominant through a pretty much all the vehicles coming off the line in the coming years. So you're going to see the connectivity and now we can bring the services and the apps to that vehicle. But at the same time you got to keep it safe, got to keep it secure. Gotta keep it reliable. You know, it's the classic mobile device, bingo literal device on wheels, right of two ton mobile device on wheels. >>Doc disruption sounds really cool and it's consumers. We just had this expectation that we can have whatever I want, the whole experience I want. And obviously as everything evolves, we want it to be safer and safer. And as there's laws and regulations that govern, Hey, you're going to get hefty fines if you're seeing with this device and you're driving. But disruption is really challenging, right? We talked, we got some great examples yesterday on stage with Andy Jassy of Goldman Sachs, right? How many years old are they and how they have leveraged disruption to revolutionize their consumer business or healthcare revolutionizing. I'd love to get your perspective on what are some of the automakers that are bleeding edge going, we get it. We want to work with you guys so that they understand that this the, you know, the, the mobile devices, the connected device on wheels is going to be transformative for their business. >>Good point. So first of all, every automaker we work with and we work, we work with almost 50 auto makers and we're over a hundred. We're in over 150 million vehicles and multiple systems in the cars. They're all putting safety first. That's never really changed. But that remains primary, primary objective. And to your point is how do you maintain that safety net reliability while at the same time opening the door to connectivity, making sure that vehicle is secure and resilient to attacks and whatnot. And you've seen some of those attacks in the past. And the industry is learning. Um, but that's, that's exactly what, that's what speaks to us and what we do. Same thing with AWS. If you think about what we do, we're plumbers. We, we build plumbing in the car, AWL splits, plumbing in the cloud. And I've had that call, those conversations with AWS and they're like, yeah, we're plumbers. >>And I said, so are we, we're going to get along great. But to your point, we have to keep our eye on security. Our definitely our eye on privacy and safety. And that's exactly what we do. As much as we all want the consumer apps and the connected experience at the same time, we can't compromise on that. So the good thing in automotive is there's a automotive safety standards, ISO two, six, two, six, two and whatnot, which we've certified our products to and we're going to keep doing that and keep delivering that software in the car. But that's awesome for 0.2 ton mobile device on wheels. So we got to always be aware of that. Great opportunity. People want more conduct and safety too. And that's a huge thing. Security and safety. I want to get to that in a second, but I got to ask you, um, what is the relationship that you guys have with Amazon? >>Could you explain that? And what are you guys doing at reinvent this year? Is your leg a presentation demo? Take a minute to explain the relationship between queen Nixon and Amazon web services and what you're showing here. Well, we're in the connected home exhibit. In fact, we're in the quote unquote garage where we've got a vehicle, a beautiful karma Rivero GT. And I was told it's the first time there's actually a car at reinvent. So that was pretty cool. And it's a cool car if you get a chance, come on over. And what we've done is we've taken the karma vehicle and we've actually connected it to AWS IOT. So if you think about what we do, we do software in the car, as I was saying earlier. And then we worked with the Amazon team, with the AWS team to say, okay, what can we do? So one of the things we're doing is we're doing battery monitoring and prediction in terms of the life of the battery. >>That's one of the things that we're doing. The other thing we're doing is personalized cockpit, which is, which is pretty exciting. And, and the last thing we're doing is kind of a business to business demonstration, um, where it's data orchestrations. If you think about the vehicle, there's a lot of sensors on the vehicle, a lot of information available on the vehicle. And what we're doing with AWS is pulling information from the vehicle, putting it in the cloud. And then we've got a few examples that we're using. So one of them is an application for an auto detailing company where they might want, you might want to have your vehicle detailed where we can make the position of your vehicle available, GPS, the VIN number. So the identify the identification of the vehicle. Um, and then you could actually contract with that expert detailings what we called them to come to your vehicle, clean the vehicle, detail your vehicle within a finite period of time securely. >>And then you'll get notified when it's done and whatnot. We're doing facial recognition in the vehicle and we also put some ML in machine learning in the car. We're actually showing gesture recognition where I can fold the mirrors with a, with a peace sign or victory signs. I could have the mirrors fold in. Uh, I can, I can interact with the infotainment system. I can personalize the music and whatnot. So really personalizing the cockpit. But all through the power of AWS. Sorry, what are we going to have to the car flying cars? Come on Jetsons flyers. I love this coming. Maybe not the flying carpet. Wow. Okay. Flying cars. Fine. I mean, I always say anything else that's in star Trek or star Wars will be invented. So I'm respecting some flying vehicles. All fun aside. Yeah. Now the serious conversation is safety and security. >>Worst case scenario, my car is hacked. Take over. This is a fear. Again, it's the worst. It's a doom season here. Those stories are straight. All IOT device. It's a car. How do you guys view the security posture? Um, good question. This is concerned. It might be on people's mind. Yeah. And that's what really speaks to where our company has been for almost four decades now. You know, when people would ask me, Hey, where would I find Punic software? Blackberry Punic software, I'd say almost everywhere, but the desktop. So where things have to be reliable, safe, secure work all the time. That's where you'll find our software. So factory floor, we're in laser eye surgery. Machines are in patient monitoring devices, MRI machines. And so essentially those areas which are safety critical, where safety, security and reliability, you know, our top real really industrial IOT thing, big time, big time. >>And that's the cool thing about walking around reinvent. There's all kinds of industrial devices and control. So if you go to the car now, if you think about the vehicle, same fundamental needs, reliability, safety, security, and we're trusted to deliver an automotive. So security is one of those things. It's not static. So when you, when you, when you make something that's secure, you're really building something that's resilient to attacks. So you'd be as resilient as possible to prevent attacks. And then you do whatever you can to prevent any malicious act or actions on that. So we will monitor what's going on in the system. We'll monitor any communications going to the car, for instance. So the minute we detect something a bit of normal, we can take action based on that. So that, that's absolutely key, especially given the cars connected and more and more becoming connected. >>What's the opportunity is in a trucking industry, when I think of the number of sensors on trucks, the regulations that you know for drivers safety in terms of how many hours they actually have to be able to can drive. What's the opportunity there for Q next? >>Good question. So everything we're doing in the car, which I should generalize and say a vehicle applies to trucks. So if you think about trucking or vehicles or drones or anything like that, you have multiple sensors that you have to interact with. You have to interpret that information, you have to take action based on that information. So if we look at trucking specifically, everybody knows a major shortage of truck truck, truck drivers. So when people ask me about autonomous cars and Hey, when are we going to see autonomy's vehicles? I always look at trucking and we're working with companies, trucking companies that are using our technology. And one of the first use cases that they're putting forward is something called platooning, where you'll actually have the first truck on the road with a driver and any other trucks on the road. We'll be operating autonomously essentially following like a train if you want on a highway, and then they'll have a starting location and a drop off location and that all of a sudden becomes a real world scenario, which makes use of the same sensors, LIDAR, radar cameras, et cetera. >>So from a trucking perspective, we look at it very similar to a car and automotive perspective because they need the same fundamental technologies. So pretty exciting. Like I said, what we do applies all over the place and again, all going to be connected. But grant, thanks for coming on. I really appreciate, I want to get your final thoughts, at least from my perspective on developers. When you see deep racer, you see that trend. It's kind of, they've got LIDAR, it's kind of a toy, but people geeking out on this. And so I would imagine that we're going to see an emergence of a software development environment where as a controlled sandboxes, cause yeah, they've got the concern with the industrial equipment. Exactly. Yeah. How do you balance that old school industrial mindset of, you know, IOT with the new rapid agile product development? Yeah. And to your point, we're going through that transition now. >>So this is where things like Sage maker come into play where I can develop out and develop and refine machine learning models in the cloud. You still have those tight control loops that you need and there's tools for that. So that's the deeply embedded stuff that's controlling actuators and whatnot. You still need that. But to your point, you need to be more iterative. You need to be more agile, need to develop according to the safety standards and the various industries that they might be in. So it's that is evolving and it's evolving at exactly the right pace. Really glad to see that evolution. But to your point, all of these devices are going to become interconnected. There's going to be new opportunities. And from a developer perspective, you know, we can't hire enough developers. No one can. It's really exciting whether it's IOT cloud developers or embedded developers. >>There's such an exciting future ahead. And I got to ask, this is just popped in my head. So I want to ask, cause I'm curious, um, spectrum and RF power is great, but you need connectivity to make an IOT device work, right? How do you guys, how does the car folks look at conductivity? Just when they get to a spot they can connect. So is it managing the spectrum? How are cars thinking about the connectivity? So we work very closely with the modem vendors. For instance, in today in cars you'll see Bluetooth, you'll see wifi, you'll see 4g. Obviously there's the emergence of 5g. Um, vehicle to vehicle communications is through something called DSRC. Essentially wifi 5g is going to come along, so now you're going to be able to have throughput and also what's called low latency. So quick turn around on your messages and the information being exchanged. >>So that too is evolving from a, from a QA software perspective, we'll make use of whatever modems there. But to your point, we also have to deal with the cases where I've lost connectivity. I still need that V vehicle to operate safely. And especially if you consider that the systems might be, um, uh, the systems might be connected or we don't want to make, make it such that they're dependent on that connectivity. So you have to have fail over scenarios and whatnot, but cars will become connected, devices will become connected. We're going to take advantage of that connectivity, but not be dependent on that connectivity. >>Well, Greg, please let me know when that, uh, personalized service is available so that my car can be found and detailed. They'd find it right in my driveway going lady, please. It's been a pleasure, a really cool stuff. Blackberry Kunis thank you for joining John. We'll be, we'll have to go check out that car for John furrier. I'm Lisa Martin. You're watching the cube live in Vegas at AWS. Reinvent 19. Thanks for watching.

Published Date : Dec 5 2019

SUMMARY :

AWS reinvent 2019 brought to you by Amazon web services We are live at AWS reinvent in the expo hall at the sands convention center. Well, I can hear all the conversations happening at once. John and I are pleased to be joined by Greg Coralville, in the car, the car, the software is to be reliable, safe, secure. So is there going to be multiple platforms? So to the point where the electronics in the car, the networks in the car, So where that car's going, if you think about it, is moving to more of of the automakers that are bleeding edge going, we get it. And the industry is learning. So the good thing in automotive is there's a automotive safety standards, So one of the things we're doing is we're doing battery monitoring and prediction in terms of the So one of them is an application for an auto detailing company where they might want, you might want to have your vehicle So really personalizing the cockpit. And that's what really speaks to where our company has been So the minute we detect something a bit of normal, we can take action based on that. What's the opportunity is in a trucking industry, when I think of the number of sensors So if you think about trucking or vehicles or drones or anything like that, the place and again, all going to be connected. So that's the deeply embedded stuff that's controlling actuators and whatnot. So is it managing the spectrum? So you have to have fail over scenarios and whatnot, but cars will become connected, Blackberry Kunis thank you for joining John.

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Around theCUBE, Unpacking AI Panel, Part 2 | CUBEConversation, October 2019


 

(upbeat music) >> From our studios in the heart of Silicon Valley, Palo Alto, California, this is a CUBE Conversation. >> Welcome everyone to this special CUBE Conversation Around the CUBE segment, Unpacking AI, number two, sponsored by Juniper Networks. We've got a great lineup here to go around the CUBE and unpack AI. We have Ken Jennings, all-time Jeopardy champion with us. Celebrity, great story there, we'll dig into that. John Hinson, director of AI at Evotek and Charna Parkey, who's the applied scientist at Textio. Thanks for joining us here for Around the CUBE Unpacking AI, appreciate it. First question I want to get to, Ken, you're notable for being beaten by a machine on Jeopardy. Everyone knows that story, but it really brings out the question of AI and the role AI is playing in society around obsolescence. We've been hearing gloom and doom around AI replacing people's jobs, and it's not really that way. What's your take on AI and replacing people's jobs? >> You know, I'm not an economist, so I can't speak to how easy it's going to be to retrain and re-skill tens of millions of people once these clerical and food prep and driving and whatever jobs go away, but I can definitely speak to the personal feeling of being in that situation, kind of watching the machine take your job on the assembly line and realizing that the thing you thought made you special no longer exists. If IBM throws enough money at it, your skill essentially is now obsolete. And it was kind of a disconcerting feeling. I think that what people need is to feel like they matter, and that went away for me very quickly when I realized that a black rectangle can now beat me at a game show. >> Okay John, what's your take on AI replacing jobs? What's your view on this? >> I think, look, we're all going to have to adapt. There's a lot of changes coming. There's changes coming socially, economically, politically. I think it's a disservice to us all to get to too indulgent around the idea that these things are going to change. We have to absorb these things, we have to be really smart about how we approach them. We have to be very open-minded about how these things are going to actually change us all. But ultimately, I think it's going to be positive at the end of the day. It's definitely going to be a little rough for a couple of years as we make all these adjustments, but I think what AI brings to the table is heads above kind of where we are today. >> Charna, your take around this, because the role of humans versus machines are pretty significant, they help each other. But is AI going to dominate over humans? >> Yeah, absolutely. I think there's a thing that we see over and over again in every bubble and collapse where, you know, in the automotive industry we certainly saw a bunch of jobs were lost, but a bunch of jobs were gained. And so we're just now actually getting into the phase where people are realizing that AI isn't just replacement, it has to be augmentation, right? We can't simply use images to replace recognition of people, we can't just use black box to give our FICO credit scores, it has to be inspectable. So there's a new field coming up now called explainable AI that actually is where we're moving towards and it's actually going to help society and create jobs. >> All right so let's stay on that next point for the next round, explainable AI. This points to a golden age. There's a debate around are we in a bubble or a golden age. A lot of people are negative right now on tech. You can see all the tech backlash. Amazon, the big tech companies like Apple and Facebook, there's a huge backlash around this so-called tech for society. Is this an indicator of a golden age coming? >> I think so, absolutely. We can take two examples of this. One would be where, you remember when Amazon built a hiring algorithm based upon their own resume data and they found that it was discriminating against women because they had only had men apply for it. Now with Textio we're building augmented writing across the audience and not from a single company and so companies like Johnson and Johnson are increasing the pipeline by more than nine percent which converts to 90,000 more women applying for their jobs. And so part of the difference there is one is explainable, one isn't, and one is using the right data set representing the audience that is consuming it and not a single company's hiring. So I think we're absolutely headed into more of a golden age, and I think these are some of the signs that people are starting to use it in the right way. >> John, what's your take? Obviously golden age doesn't look that to us right now. You see Facebook approving lies as ads, Twitter banning political ads. AI was supposed to solve all these problems. Is there light at the end of this dark tunnel we're on? >> Yeah, golden age for sure. I'm definitely a big believer in that. I think there's a new era amongst us on how we handle data in general. I think the most important thing we have here though is education around what this stuff is, how it works, how it's affecting our lives individually and at the corporate level. This is a new era of informing and augmenting literally everything we do. I see nothing but positives coming out of this. We have to be obviously very careful with our approaching all the biases that already exist today that are only going to be magnified with these types of algorithms at mass scale. But ultimately if we can get over that hurdle, which I believe collectively we all need to do together, I think we'd live in much better, less wasteful world just by approaching the data that's already at hand. >> Ken, what's your take on this? It's like a daily double question. Is it going to be a golden age? >> Laughs >> It's going to come sooner or later. We have to have catastrophe before, we have to have reality hit us in the face before we realize that tech is good, and shaping it? It's pretty ugly right now in some of the situations out there, especially in the political scene with the election in the US. You're seeing some negative things happening. What's your take on this? >> I'm much more skeptical than John and Charna. I feel like that kind of just blinkered, it's going to be great, is something you have to actually be in the tech industry and hearing all day to actually believe. I remember seeing kind of lay-person's exposure to Watson when Watson was on Jeopardy and hearing the questions reporters would ask and seeing the memes that would appear, and everyone's immediate reaction just to something as innocuous as a AI algorithm playing on a game show was to ask, is this Skynet from Terminator 2? Is this the computer from The Matrix? Is this HAL pushing us out of the airlock? Everybody immediately first goes to the tech is going to kill us. That's like everybody's first reaction, and it's weird. I don't know, you might say it's just because Hollywood has trained us to expect that plot development, but I almost think it's the other way around. Like that's a story we tell because we're deeply worried about our own meaning and obsolescence when we see how little these skills might be valued in 10, 20, 30 years. >> I can't tell you how much, by the way, Star Trek, Star Wars and Terminators probably affected the nomenclature of the technology. Everyone references Skynet. Oh my God, we're going to be taken over and killed by aliens and machines. This is a real fear. I thinks it's an initial reaction. You felt that Ken, so I've got to ask you, where do you think the crossover point is for people to internalize the benefits of say, AI for instance? Because people will say hey, look back at life before the iPhone, look at life before these tools were out there. Some will say society's gotten better, but yet there's this surveillance culture, things... And on and on. So what do you guys think the crossover point is for the reaction to change from oh my God, it's Skynet, gloom and doom to this actually could be good? >> It's incredibly tricky because as we've seen, the perception of AI both in and out of the industry changes as AI advances. As soon as machine learning can actually do a task, there's a tendency to say there's this no true Scotsman problem where we say well, that clearly can't be AI because I see how the trick worked. And yeah, humans lose at chess now. So when these small advances happen, the reaction is often oh, that's not really AI. And by the same token, it's not a game-changer when your email client can start to auto-complete your emails. That's a minor convenience to you. But you don't think oh, maybe Skynet is good. I really do think it's going to have to be, maybe the inflection point is when it starts to become so disruptive that actually public policy has to change. So we get serious about >> And public policy has started changing. >> whatever their reactions are. >> Charna, your thoughts. >> The public policy has started changing though. We just saw, I think it was in September, where California banned the use of AI in the body cameras, both real-time and after the fact. So I think that's part of the pivot point that we're actually seeing is that public policy is changing.` The state of Washington currently has a task force for AI who's making a set of recommendations for policy starting in December. But I think part of what we're missing is that we don't have enough digital natives in office to even attempt to, to your point Ken, predict what we're even going to be able to do with it, right? There is this fear because of misunderstanding, but we also don't have a respect of our political climate right now by a lot of our digital natives, and they need to be there to be making this policy. >> John, weigh in on this because you're director of AI, you're seeing positive, you have to deal with the uncertainty as well, the growth of machine learning. And just this week Google announced more TensorFlow for everybody. You're seeing Open Source. So there's a tech push, almost a democratization, going on with AI. So I think this crossover point might be sooner in front of us than people think. What's your thoughts? >> Yeah it's here right now. All these things can be essentially put into an environment. You can see these into products, or making business decisions or political decisions. These are all available right now. They're available today and its within 10 to 15 lines of code. It's all about the data sets, so you have to be really good stewards of the data that you're using to train your models. But I think the most important thing, back to the Skynet and all this science-fiction side, we have to collectively start telling the right stories. We need better stories than just this robots are going to take us over and destroy all of our jobs. I think more interesting stories really revolve around, what about public defenders who can have this informant augmentation algorithm that's going to help them get their job done? What about tailor-made medicine that's going to tell me exactly what the conditions are based off of a particular treatment plan instead of guessing? What about tailored education that's going to look at all of my strengths and weaknesses and present a plan for me? These are things that AI can do. Charna's exactly right, where if we don't get this into the right political atmosphere that's helping balance the capitalist side with the social side, we're going to be in trouble. So that's got to be embedded in every layer of enterprise as well as society in general. It's here, it's now, and it's real. >> Ken, before we move on to the ethics question, I want to get your thoughts on this because we have an Alexa at home. We had an Alexa at home; my wife made me get rid of it. We had an Apple device, what they're called... the Home pods, that's gone. I bought a Portal from Facebook because I always buy the earliest stuff, that's gone. We don't want listening devices in our house because in order to get that AI, you have to give up listening, and this has been an issue. What do you have to give to get? This has been a big question. What's your thoughts on all this? >> I was at an Amazon event where they were trumpeting how no technology had ever caught on faster than these personal digital assistants, and yet every time I'm in a use case, a household that's trying to use them, something goes terribly wrong. My friend had to rename his because the neighbor kids kept telling Alexa to do awful things. He renamed it computer, and now every time we use the word computer, the wall tells us something we don't want to know. >> (laughs) >> This is just anecdata, but maybe it speaks to something deeper, the fact that we don't necessarily like the feeling of being surveilled. IBM was always trying to push Watson as the star Trek computer that helpfully tells you exactly what you need to know in the right moment, but that's got downsides too. I feel like we're going to, if nothing else, we may start to value individual learning and knowledge less when we feel like a voice from the ceiling can deliver unto us the fact that we need. I think decision-making might suffer in that kind of a world. >> All right, this brings up ethics because I bring up the Amazon and the voice stuff because this is the new interface people want to have with machines. I didn't mention phones, Androids and Apple, they need to listen in order to make decisions. This brings up the ethics question around who sets the laws, what society should do about this, because we want the benefits of AI. John, you point out some of them. You got to give to get. Where are we on ethics? What's the opinion, what's the current view on this? John, we'll start with you on your ethics view on what needs to change now to move the ball faster. >> Data is gold. Data is gold at an exponential rate when you're talking about AI. There should be no situation where these companies get to collect data at no cost or no benefit to the end consumer. So ultimately we should have the option to opt out of any of these products and any of this type of surveillance wherever we can. Public safety is a little bit different situation, but on the commercial side, there is a lot of more expensive and even more difficult ways to train these models with a data set that isn't just basically grabbing everything our of your personal lives. I think that should be an option for consumers and that's one of those ethical check-marks. Again, ethics in general, the way that data's trained, the way that data's handled, the way models actually work, it has to be a primary reason for and approach of how you actually go about developing and delivering AI. That said, we cannot get over-indulgent in the fact that we can't do it because we're so fearful of the ethical outcomes. We have to find some middle ground and we have to find it quickly and collectively. >> Charna, what's your take on this? Ethics is super important to set the agenda for society to take advantage of all this. >> Yeah. I think we've got three ethical components here. We certainly have, as John mentioned, the data sets. However, it's also what behavior we're trying to change. So I believe the industry could benefit from a lot more behavioral science, so that we can understand whether or not the algorithms that we're building are changing behaviors that we actually want to change, right? And if we aren't, that's unethical. There is an entire field of ethics that needs to start getting put into our companies. We need an ethics board internally. A few companies are doing this already actually. I know a lot of the military companies do. I used to be in the defense industry, and so they've got a board of ethics before you can do things. The challenge is also though that as we're democratizing the algorithms themselves, people don't understand that you can't just get a set of data that represents the population. So this is true of image processing, where if we only used 100 images of a black woman, and we used 1,000 images of a white man because that was the distribution in our population, and then the algorithm could not detect the difference between skin tones for people of color, then we end up with situations where we end up in a police state where you put in an image of one black woman and it looks like ten of them and you can't distinguish between them. And yet, the confidence rate for the humans are actually higher, because they now have a machine backing their decision. And so they stop questioning, to your point, Ken, about what is the decision I'm making, they're like I'm so confident, this data told me so. And so there's a little bit of you need some expert in the loop and you also can't just have experts, because then you end up with Cambridge Analytica and all of the political things that happened there, not just in the US, but across 200 different elections and 30 different countries. And we are upset because it happened in the US, but this has been happening for years. So its just this ethical challenge of behavior change. It's not even AI and we do it all the time. Its why the cigarette industry is regulated (laughs). >> So Ken, what's your take on this? Obviously because society needs to have ethics. Who runs that? Companies? The law-makers? Someone's got to be responsible. >> I'm honestly a little pessimistic the general public will even demand this the way we're maybe hoping that they will. When I think about an example like Facebook, people just being able to, being willing to give away insane amounts of data through social media companies for the smallest of benefits: keeping in touch with people from high school they don't like. I mean, it really shows how little we value not being a product in this kind of situation. But I would like to see this kind of ethical decisions being made at the company-level. I feel like Google kind of surreptitiously moved away from it's little don't be evil mantra with the subtext that eh, maybe we'll be a little evil now. It just reminds me of Manhattan Project era thinking, where you could've gone to any of these nuclear scientists and said you're working on a real interesting puzzle here, it might advance the field, but like 200,000 civilians might die this summer. And I feel like they would've just looked at you and thought that's not really my bailiwick. I'm just trying to solve the fission problem. I would like to see these 10 companies actually having that kind of thinking internally. Not being so busy thinking if they can do something that they don't wonder if they should. >> That's a great point. This brings up the point of who is responsible. Almost as if who is less evil than the other person? Google, they don't do evil, but they're less evil than Amazon and Facebook and others. Who is responsible? The companies or the law-makers? Because if you look up some of the hearings in Washington, D.C., some of the law-makers we see up there, they don't know how the internet works, and it's pretty obvious that this is a problem. >> Yeah, well that's why Jack Dorsey of Twitter posted yesterday that he banned not just political ads, but also issue ads. This isn't something that they're making him do, but he understands that when you're using AI to target people, that it's not okay. At some point, while Mark is sitting on (laughs) this committee and giving his testimony, he's essentially asking to be regulated because he can't regulate himself. He's like well, everyone's doing it, so I'm going to do it too. That's not an okay excuse. We see this in the labor market though actually, where there's existing laws that prevent discrimination. It's actually the company's responsibility to make sure that the products that they purchase from any vendor isn't introducing discrimination into that process. So its not even the vendor that's held responsible, it's the company and their use of it. We saw in the NYPD actually that one of those image recognition systems came up and someone said well, he looked like, I forget the name of what the actor was, but some actor's name is what the perpetrator looked like and so they used an image of the actor to try and find the person who actually assaulted someone else. And that's, it's also the user problem that I'm super concerned about. >> So John, what's your take on this? Because these are companies are in business to make money, for profit, they're not the government. And who's the role, what should the government do? AI has to move forward. >> Yeah, we're all responsible. The companies are responsible. The companies that we work with, I have yet to interact with customers, or with our customers here, that have some insidious goal, that they're trying to outsmart their customers. They're not. Everyone's looking to do the best and deliver the most relevant products in the marketplace. The government, they absolutely... The political structure we have, it has to be really intelligent and it's got to get up-skilled in this space and it needs to do it quickly, both at the economy level, as well as for our defense. But the individuals, all of us as individuals, we are already subjected to this type of artificial intelligence in our everyday lives. Look at streaming, streaming media. Right now every single one of us goes out through a streaming source, and we're getting recommendations on what we should watch next. And we're already adapting to these things, I am. I'm like stop showing me all the stuff you know I want to watch, that's not interesting to me. I want to find something I don't know I want to watch, right? So we all have to get educated, we're all responsible for these things. And again, I see a much more positive side of this. I'm not trying to get into the fear-mongering side of all the things that could go wrong, I want to focus on the good stories, the positive stories. If I'm in a courtroom and I lose a court case because I couldn't afford the best attorney and I have the bias of a judge, I would certainly like artificial intelligence to make a determination that allows me to drive an appeal, as one example. Things like that are really creative in the world that we need to do. Tampering down this wild speculation we have on the markets. I mean, we are all victims of really bad data decisions right now, almost the worst data decisions. For me, I see this as a way to actually improve all those things. Fraud fees will be reduced. That helps everybody, right? Less speculation and these wild swings, these are all helpful things. >> Well Ken, John and Charna, thank- (audio feedback) >> Go ahead, finish. Get that word in. >> Sorry. I think that point you were making though John, is we are still a capitalist society, but we're no longer a shareholder capitalist society, we are a stakeholder capitalist society and the stakeholder is the society itself. It is us, it what we want to see. And so yes, I still want money. Obviously there are things that I want to buy, but I also care about well-being. I think it's that little shift that we're seeing that is actually you and I holding our own teams accountable for what they do. >> Yeah, culture first is a whole new shift going on in these companies that's a for-profit, mission-based. Ken, John, Charna, thanks for coming on Around the CUBE, Unpacking AI. Let's go around the CUBE Ken, John and Charna in that order, and just real quickly, unpacking AI, what's your final word? >> (laughs) I really... I'm interested in John's take that there's a democratization coming provided these tools will be available to everyone. I would certainly love to believe that. It seems like in the past, we've seen no, that access to these kind of powerful, paradigm-changing tools tend to be concentrated among a very small group of people and the benefits accrue to a very small group of people. But I hope that doesn't happen here. You know, I'm optimistic as well. I like the utopian side where we all have this amazing access to information and so many new problems can get solved with amazing amounts of data that we never could've touched before. Though you know, I think about that. I try to let that help me sleep at night, and not the fact that, you know... every public figure I see on TV is kind of out of touch about technology and only one candidate suggests the universal basic income, and it's kind of a crackpot idea. Those are the kind of things that keep me up at night. >> All right, John, final word. >> I think it's beautiful, AI's beautiful. We're on the cusp of a whole new world, it's nothing but positivity I see. We have to be careful. We're all nervous about it. None of us know how to approach these things, but as human beings, we've been here before. We're here all the time. And I believe that we can all collectively get a better lives for ourselves, for the environment, for everything that's out there. It's here, it's now, it's definitely real. I encourage everyone to hurry up on their own education. Every company, every layer of government to start really embracing these things and start paying attention. It's catching us all a little bit by surprise, but once you see it in production, you see it real, you'll be impressed. >> Okay, Charna, final word. >> I think one thing I want to leave people with is what we incentivize is what we end up optimizing for. This is the same for human behavior. You're training a new employee, you put incentives on the way that they sell, and that's, they game the system. AI's specifically find the optimum route, that is their job. So if we don't understand more complex cost functions, more complex representative ways of training, we're going to end up in a space, before we know it, that we can't get out of. And especially if we're using uninspectable AI. We really need to move towards augmentation. There are some companies that are implementing this now that you may not even know. Zillow, for example, is using AI to give you a cost for your home just by the photos and the words that you describe it, but they're also purchasing houses without a human in the loop in certain markets, based upon an inspection later by a human. And so there are these big bets that we're making within these massive corporations, but if you're going to do it as an individual, take a Coursera class on AI and take a Coursera class on ethics so that you can understand what the pitfalls are going to be, because that cost function is incredibly important. >> Okay, that's a wrap. Looks like we have a winner here. Charna, you got 18, John 16. Ken came in with 12, beaten again! (both laugh) Okay, Ken, seriously, great to have you guys on, a pleasure to meet everyone. Thanks for sharing on Around the CUBE Unpacking AI, panel number two. Thank you. >> Thanks a lot. >> Thank you. >> Thanks. I've been defeated by artificial intelligence again! (all laugh) (upbeat music)

Published Date : Oct 31 2019

SUMMARY :

in the heart of Silicon Valley, and the role AI is playing in society around obsolescence. and realizing that the thing you thought made you special I think it's going to be positive But is AI going to dominate over humans? in the automotive industry we certainly saw You can see all the tech backlash. that people are starting to use it in the right way. Obviously golden age doesn't look that to us right now. that are only going to be magnified Is it going to be a golden age? We have to have catastrophe before, the tech is going to kill us. for the reaction to change from I really do think it's going to have to be, And public policy their reactions are. and they need to be there to be making this policy. the growth of machine learning. So that's got to be embedded in every layer of because in order to get that AI, the wall tells us something we don't want to know. the fact that we don't necessarily like the feeling they need to listen in order to make decisions. that we can't do it because we're so fearful Ethics is super important to set the agenda for society There is an entire field of ethics that needs to start Obviously because society needs to have ethics. And I feel like they would've just looked at you in Washington, D.C., some of the law-makers we see up there, I forget the name of what the actor was, Because these are companies are in business to make money, and I have the bias of a judge, Get that word in. and the stakeholder is the society itself. Ken, John and Charna in that order, and the benefits accrue to a very small group of people. And I believe that we can all collectively and the words that you describe it, Okay, Ken, seriously, great to have you guys on, (upbeat music)

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Chris Powell, Commvault | Commvault GO 2019


 

>>Live from Denver, Colorado. It's the cube covering com vault go 2019 brought to you by Combalt. >>Hey, welcome back to the cube Lisa Martin with steam and man we are live on the show floor of comm vault go 2019 fourth annual event, a couple thousand customers here and Steve and I are welcoming back the COO of combo. Chris pal. Chris, welcome back. Thanks. Great to be here. We're excited to be here. We just came out of the keynote. Some interesting news to talk about but let's, let's to talk about what's happened. Combat is a 20 year young company, tremendous amount of acceleration in the last nine months. Lot of leadership changes he must be going to hold onto the table cause you got like the whiplash, right? So tell us, here we are at the fourth annual go news in terms of sales leadership changes go to market opportunities with metallic, with a new partner programs for the enterprise. Tell us what are some of the things that are exciting to you and how come vault is really in 20 FYE 2020 position? Like, Hey, we're listening to our customers and partners. >>Yeah, yeah. Well, and a lot of the things that you're seeing here at this show is just that it's, it's, it's market-driven. It's us responding to what we're seeing in the market, working with our partners. And a show like this is all about working with partners. Our customers and the, the announcements that we're making here are really releasing a completely new combo that the brand refresh that we've done just over the last month or so is been tied to a lot of the things that are changing with regards to the product portfolio. Uh, that Hedvig acquisition and a lot of the different leadership changes that you're seeing and the leadership changes are really driving a lot of this shift of focus. And really, I shouldn't say shift really extended focus for the organization from a technological standpoint as well as from working with our partners. >>Yeah, it's interesting. The news ahead of the show of metallic Convult now a SAS providers. So it's interesting to get you give us your, your view as a marketer. On the one hand you need to be the trusted enterprise supplier with a lot of customers. And the other one, you know, they've got cloud microservices, all the latest buzz words and you know sasses the model that a lot of customers want to be able to consume their software standpoint. So, so >>I know you have Rob Kalusi and who's going to be coming on. So I'll steal some of his thunder and I'll try not to steal too much to don't tell them the what excites me so much about the metallic product when leap, when we first started down this path, it was we, we really started looking at the market and the challenge that came from Sanjay when he just first entered the building really was we have industry leading technology. A lot of folks will talk about how we have industry leading technology. But if you really took a step back, you would have to have an honest view and say, sometimes they would say, well look, if it's a, if it's a really straight forward installation, maybe Commonwealth and might be a bit bring too much to the party, so why don't you look at some of the other solutions. >>And as we were talking to different customers out there, they were looking for SAS solutions and but they at the same time, they didn't want to make any compromises. And so much of the research that Rob and team working with Janet and with David, no, we're seeing is that as they were going out there, the Seuss solutions that were available today, and this sounds like marketing spin, right? But it's really what we were hearing back, that they weren't very good there, that they weren't SAS solutions. They're supposed to be easy. The customers really didn't see them as easy. They were running into scale issues, they were running into flexibility issues. So from the standpoint of building the solution, what we quickly realized is if we could reach Sanjay's challenge to us, which is bringing this fundamentally solid technology to a broader audience with a simplified use cases that there's a great opportunity for us to bring value to more companies. So that's, that's where this went. And then the beginning reviews of this as we brought this into beta and different people were seeing at different customers, different partners, they even came into the conversation a little bit pessimistic and they all left excited about what they were seeing. It's it's, it's really good. It's really good. >>So targeted towards mid market companies with around 2,500 or 500 to 2,500 employees. Give me just a little bit of a perspective on the choice that Commonweal is now offering the midmarket with complete backup and recovery. That's one of your flagship and metallic. >>So the the metallic offerings your men for some of the most common use cases that are out there. So 65 and the what we're, what we're trying to inject into the market and the target of 500 to 2,500 employees is really just where we see the sweet spot of most of the customers of those sizes are the ones that are looking at SAS solutions right now. But that's not to say as we've talked to larger enterprises, many of them are considering the addition of metallic as into their either subsidiaries or other areas of their business. And what Sanjay talks about, he sort of refers to as the data brain is really bringing this together where you can add SAS solutions onto your existing on prem solution. So if you're running combo complete, you can also be running metallic across other aspects of your business. So that's, that's one of the things that makes it powerful upmarket, but then we're also targeting the more common use cases that are more turnkey down-market. Yeah. >>Let's switch gears a little bit. So your team had a little bit of fun opening up the keynote. You had some of the stunt doubles a for Thor from Starwood and the woman has done both star Wars and Marvel on and talking about the unsung heroes behind the scenes. Kind of like your, your customers here. But there was another connection because they were vendors and con vault is, I believe it's the global Avengers and it has to do with sustainability, which I know is something near and dear to your heart. So explain a little bit about why that's important in what it is. >>So it's definitely a passion of mine and something that we accumbent are looking to every company as we're driving this should try to stand for something bigger than themselves. And as we look at this all started two years ago when we sponsored and I joined Robert Swan's expedition to the South pole. We were the data sponsor for that expedition and it was the first expedition to rely solely on renewable energy. And what has evolved from that from different conversations, we started having discussions throughout about the carbon footprint of data and with 5g the internet of things coming and more and more data on the horizon. The people that we're speaking with. And the reality I think that tech has come to is that we can't be part of the problem. We have to be part of the solution. So through a series of connections, we ended up speaking with the folks who were responsible for the UN global goals. Um, it's the 17 global goals around the world that were endorsed by all of the UN countries five years ago and there's 10 more years of it. And Kamahl is extremely proud to be joining some of the largest companies in the world. Coca Cola, Microsoft, Google, Salesforce, many in our industry and outside, obviously to sponsor one of the global global goals. But the way the program works is it 17 global goals and there's one company for each one of them in order to try to represent it and drive it forward. >>Chris, you actually took a few of us around the show floor before it opened last night. We know conferences can have a bit of an impact from a negative standpoint. So tell some of what Combolt's doing to make sure that this conference, you know, doesn't have such an impact. >>So as you mentioned before, it's about 2000 people that are here and I was shocked to learn and a lot of this is all in education. As you go through life, the, an event of this size typically will generate 25,000 pounds of rubbish of trash. So what we've done is partner with our good customer, which is the Gaylord Gaylord hotel systems and leaf put together a model where we're trying to minimize the overall footprint. So we donate a lot of what you see around here. Construction materials are donated to schools and local organizations. We're using all of the natural plants that will go back into the, uh, into the environment after this. Um, no plastic. I'm trying. And then the, uh, the cups you see here on the table are all plant based. So we're, we're trying to be very conscientious about everything that we're doing here at the show and minimize the footprint. >>When you're talking with customers, as I'm sure as cou are doing a lot, we talk, we often Sue and I and the rest of the cube crew. Sustainability is a topic that comes up at every event. We're, is that when you're talking with customers in any industry, whether it's healthcare or oil and gas, where is sustainability in >>terms of conversation? Is that one of the key things that comes up? That was also really important for Commonwealth to say, Hey, we want to be able to make sure that the technologies we're delivering are going to help our customers meet their sustainability goals. >>Absolutely. And it's, it's increasingly part of some, a number of RFPs. They will come in for Combalt. So they're there. Companies are looking to have us be able to really represent what our sustainability, what our corporate social responsibility systems are and what we put in place. And so we look at this through the lens of what do we do within our facilities? What do we do in events like this? And then also what can we do with our customers? So it's increasingly relevant and their sons of research, I'm sure you guys have seen the, the, as the millennial generation becomes more and more part of either significant influencers or decision makers, they're looking for companies that have a mission, you know, and that that stand for something all. >>So Chris, we're talking about sustainability is something you're passionate about. How does that tie into the broader brand discussion of Convolt companies going through, we talked about the executive change and you've got a lot of new products. So when people leave Combalt go 2019 how do you want them to think of Convult? >>That's a great question. I think what we're hoping that we were really using combo Alco as a combination of so many of the things that have been happening over the last couple of quarters. And certainly as I looked through what we're representing now, it's what are we as an organization, what's the story we're trying to tell? So we launched just in the last few weeks a new tagline, which is be ready. And that whole concept of data readiness is something that we're having within this show and it'll be in a lot of our messaging as we move forward. So this, I'm thinking of as the organization that enables you to be ready and then extending that should of saying, well what does that mean? And that's around how we protect the data, help you control where it resides, help you manage it for compliance and different regulatory needs, and then help you use it and get value from it. So that's the big takeaway we're hoping that people have. The other piece of this that we have each year is we expose people to such expertise here at the show. This is not combo talking about combo. 70% of our sessions in the breakout theaters are partners or customers or other influencers. So we want people to come here and really see convolve as data experts, as the people who are willing to work with them. >>Yeah. One little nugget you shared also, you've been growing. How many developers you bring from internal to the show. I have to think that Sanjay has a little bit of push from that based on his last. Yeah, yeah. >>Roll. Yeah. Certainly the DevOps community is increasingly, especially with some of the moves we've made in Hedvig, the dev community is going to be increasingly an audience for us to, to engage with. But the, we bring 45 developers to the show this year. It's about 40 from a combo and five more that have joined with Hedvig and they have 30 or 60 minute whiteboard sessions and they're completely jam packed. There's, I think last year there was over 150 whiteboard sessions over two days with customers just coming in and going through the details of this because a lot of organizations, they're there, they're faced with right now and in Sanjay's words, they have to move from something to something and they need people to be able to sit down and have honest conversations with them. Um, I joke with people sometimes that one of the terrible things that happened has happened to marketing with the advent of technology is we have to be truthful now when you know you can't, you can't just spin things. And so we're stuck having to tell the truth. But, but combo has a great truth that sets, we've got a really solid truth to tell. We just need to tell it. >>Well, and I love how marketing is so scientific these days. You're right, you have to tell the truth. But you also have, if you have the right foundation within your organization, the ability to access data actually glean insights from it, develop, whether it's a new partner program or new technologies, new routes to market. That's the power of that. Having visibility and access to the data can deliver to any type of organization. When you, when you talk with customers who've been, we've got some on the show today, Hey, we've been using Convolt for 10 years. When you talk to them today, this theme of be ready more than ready. How are they perceiving their foundation with combo and all of the changes that you've made, not just in the last 10 years, but in the last nine months alone. Which like customer feedback. Yeah, >>the customer feedback has been tremendous. I think they, they, so many customers are something that's so great about combo. Does our customers want us to succeed and they, they see this market shifting tremendously. They've been with us for a while and they want us to succeed. When they look at the changes that they're having to overcome, they're excited about really beginning to learn that as they move from something to something that we can help them on that journey. That they don't have to go somewhere else for that journey. So whether that's looking into SAS areas, whether it's modernizing their infrastructure, whether it's moving to multi-cloud and those environments, we, we have the right solutions in the right way for them to be able to make this transition for their company. So >>Chris, we're relatively early still in this show, so I hate to ask, but give us a little bit of a go forward. Lot of change in the last nine months. What should your customers be expecting from comm vault through the rest of the year? And by the time we come back to Convolt go 20, 20? >>Well, I think when you talk to Sanjay, he always says, puts me back on my heels a little bit and tells me that it's a, there's more coming, there's more coming, we're going to keep going. So it, Sanjay is a very dynamic leader and he's looking to make sure that the company isn't just driving to combo go and then it's going to sort of be smooth sailing with these things. I think this is an exciting time to be here at combo. This is an exciting time to be in the industry. So as we look forward to, um, the new leadership that's come in and some of the things they'll be able to do in terms of our go to market, I think we're going to be exciting. Avinash coming into this organization and his expertise, his skill set and all of the brilliant engineers he's, he's brought in to sort of join our industry leading engineering team. Uh, it's, it's going to be, uh, I can't wait to see what they come up with from a marketing standpoint. You know, we, we had a solid product for a number of years, but it's always challenging to sort of continue to tell a story and come up with new ways to tell it. As you get new things in your, in your box to be able to talk about, it's, it's great to be here. >>Well, Chris, we want to thank you for joining us on the queue today. We're excited about the next two days of all of the folks, leaders, new leaders, customers, partners that we're going to be talking to you and really unpacking what being ready means to them. So we thank you for your time and we look forward to a great event. Thanks very much for Steven. Amen. I am Lisa Martin. You're watching the Q from ball go 19.

Published Date : Oct 15 2019

SUMMARY :

It's the cube covering Lot of leadership changes he must be going to hold onto the table cause you got like the whiplash, Well, and a lot of the things that you're seeing here at this show is just that it's, So it's interesting to get you give us your, and the challenge that came from Sanjay when he just first entered the building really was we So from the standpoint of building the solution, is now offering the midmarket with complete backup and recovery. So 65 and the what we're, what we're trying to global Avengers and it has to do with sustainability, which I know is something near So it's definitely a passion of mine and something that we accumbent are looking to every So tell some of what Combolt's doing to make sure that this conference, So we donate a lot of what you see around here. We're, is that when you're talking with customers in any industry, to say, Hey, we want to be able to make sure that the technologies we're delivering are going to help our customers And so we look at this through the lens of what do we do within our facilities? So when people leave Combalt go 2019 how do you So that's the big takeaway we're hoping that people have. How many developers you bring from internal to the that happened has happened to marketing with the advent of technology is we have to be truthful now when you know you of the changes that you've made, not just in the last 10 years, but in the last nine months alone. that as they move from something to something that we can help them on that journey. And by the time we come back to Convolt go 20, 20? the things they'll be able to do in terms of our go to market, I think we're going to be exciting. So we thank you for your time and we look forward to a great event.

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David Appel, Raytheon & Gil Shneorson, Dell EMC | VMworld 2019


 

>> Announcer: Live from San Francisco, celebrating ten years of high-tech coverage, it's theCUBE! Covering VMworld, 2019. Brought to you by VMware and its ecosystem partners. >> Kay welcome back everyone, live CUBE coverage here at VMworld 2019 in San Francisco, we're in Moscone North lobby, I'm John Furrier. My cohost Stu Miniman. We're here with two great guests, David Appel, Vice President C2 Space and Intelligence and Defense, Civil Solutions at Raytheon, and Gil Shneorson, who's the senior vice president general manager of VxRail, of Dell EMC, great to have Raytheon, anything with space Stu and I get jacked up for that. Thanks for coming on. >> Yeah I appreciate it, thank you, I'm glad to be here. >> Gil, VxRail, got a customer here, impressive role out. Talk about the story. >> Well I think it starts with the fact that we have recently announced our support for Pivotal community services over VMware Cloud Foundation over VxRail which has actually the only Q-rated automated stacking industry that allows people to leverage containers and infrastructure as a service on one stack and we've been doing this for about three years now in a different way called Pivotal Ready Architecture and Raytheon has actually adopted that architecture to help their customer, the air force. And that's why we're here today together to talk about you know. >> Seriously modernization couldn't be a more important conversation in government solutions, you guys are a big provider, Raytheon, known for the tech chops, known for having good engineering. Talk about the solution, what you guys did, what's the use case, talk about the deployment. >> Yes with what's going on with the federal government for a while is the acquisition processes and what's taking sometimes years or decades to get software in the field is causing a lot of unmet requirements and needs of the ultimate user, the war fighters out in the field, to be met. So we've been on a journey for the last two years with Pivotal and Dell of how to help the air force, modernize the air force has gone under a transformation and a program called Kessel Run which is where we've deployed the Pivotal Ready Architecture to allow us to quickly deploy an infrastructure and allow us to focus on the end users and develop the capabilities that they need worldwide. And what took years and to now months and days so it's been a fantastic journey. >> Tell us what that means for the folks that might not know the pace of the procurement process. I mean some of this stuff is like 1995 procurement rules. I mean modernization these days is such an important part of it because the impact is significantly relevant. Share some color into the process. >> If you think about in the commercial world today where hundreds of applications be deployed overnight and updates on the what, hourly basis. In the government space it can literally take years to define a requirement, then you have to go through a budgeting cycle all the way up through congress and then you have to go through an acquisition cycle that could take a year to complete and so by the time you're actually fielding capability it is literally five years or more by the time the need was actually identified. And in that five years the technology probably changed which means your solution has probably changed from what's currently available. So shortening the cycles is what it's all about. >> And that's really about having the right product at the right time, not the old product five years ago. How fast things change, it's pretty important to have that nailed down. >> It's pretty amazing and you know I think you look at transformation and there's usually a trade off. What we have been working on and what we're announcing but really what we've been leaving over the last four years is a way to transform but stay close to your core. In other words transformation without trade offs. And so if you can get your VMware stack now running containers in a fully managed automated stack you don't have to change your skill set and you can do all of that and start innovating while staying very close to your core competency. You know you transform but you don't have to go too far and I think the story what Raytheon did is fairly amazing because they turned, you know, what did you tell me, a 50-year-old process, you know in like in less than half a year you turned automated systems that you know saves the US air force a lot of money. >> And lives too, are saved. I mean you're talking about people in the field, this is about people's lives too, I mean this is the money making. >> And it's been about transforming the culture of the way the DoD does software and the first example that Gil is mentioning was tanker planning which was the ability for the air force to refuel flight missions in the air, would typically take over eight hours to plan. And it was done by a white board. It was done manually. And in order to automate that and shrink the time, again that would have gone to that five year procurement cycle. We were able to deploy new applications using the Pivotal-ready architecture within 150 days and get those out worldwide to the field. That's done two things. It's from a financial perspective it's saving over $200,000 a day in just fuel costs from optimizing the tanker planning. But more importantly it's actually more efficient and protecting the safety of those flight crews. They're not in the air as long, they might not be in a hostile environment as long, so the security of the air force is even more important. >> As Pivotal always says they're outcome driven and that's pretty good outcome. I mean talk about the impact that you've had on everyone else around you because I'm sure there's some blockers in your way, people's feathers got ruffled, but then people see success they want to come copy it, right? So that's a pattern you see in a lot of government work. Hey there's a new way to do it, modern way. >> Yeah so our hindsight we're seeing it in two ways. One from a broader DoD perspective. The air force was out front here. They established this and from a DoD perspective what they're calling their Kessel Run initiative is really taking off. You're seeing other Kessel Run like programs being stood up like a program called Kobayashi Maru and Rogue Blue and a few others across DoD. So it's proliferating out across the DoD from a customer perspective, DoD customer perspective. From an industry perspective you know our competitors are quickly trying to catch up to us and they're trying to, you know, copy our playbook but we're continuing to innovate and continue on this journey so we're moving ahead with Pivotal and Dell. >> First of all David I think Pat Gelsinger must have been talking to your team because you're mashing up Star Wars and Star Trek with Kessel Run and Kobayashi there. But talk about mashing up, the stack that you're putting together, VxRail was really built around simplicity. It delivers that, that's what hyperconverged infrastructure does. You start talking about VCF and containers and PKS on that, Kubernetes nobody says is simple, but you know help us walk through, you know, how simple is it for you to leverage and deploy this. You've got organizational challenges and other things, so, you know, where is the solution, it sounds like you use the ready node, and where directionally is it headed? >> Yeah let me answer from this perspective. So we started this journey with Pivotal and the air force about two years ago. And at that time we started with a group of probably a dozen or less folks that actually even understood the technology or the products and the solutions that Dell and Pivotal bring forward. In those two years we're now up to over 100 people. Fully embracing the technology. It's creating an environment where it's easier for us to recruit and retain people because it's modern, it's not the old ways we used to do business. And we're finding that it's been very easy to deploy, very easy to train people up and very easy to operate. So from that perspective it's just been fantastic from not just the technology perspective but also the cultural transformation perspective. >> Yeah Gil I'd love you to comment on that because you know remember gosh when CI and HCI first rolled out you know the people that had those jobs were worried we were going to take their jobs away. Now when I hear your customer talking about, you know, it's easy to train them and even easier for me to recruit and retain, a powerful story. Are you hearing that across your customer base? >> Yeah I'll tell you what's a little different. In the past we have simplified things and we've made work somewhat go away but there was no alternative work. Today every developer, every IT person, they can't wait to go and be a dev ops person, right? So for IT when we come in and we say we're going to take this off your plate so you can free up your time, it really means something now, 'cause they know exactly what they want to do. They want to go and they want to be dev ops, they want to develop new apps, they want to move forward. And so it's very syngergistic in a way that we offload some of the burden from them and they actually do free up to do cooler stuff and then they like it. >> And they get to keep their traditional apps, with containers, gives them great capabilities. Not the throwaway. >> And that's a great point I think as I said before and it's really important to convey this, the transformation without trade offs is a big deal because they can keep the application. They can run the same environment. Right in our case they can do it you know at ease and in remote locations all over the world with less management. And at the same time they can innovate and manage those environments. And I think as long as we can keep that up we'll make a lot of people productive. >> Well I got to ask David the security question because one of the things that comes up all the time obviously Department of Defense, security's top of mind. Industrial IOT are now not just malware getting in for credit card information, you're talking about actual equipment, you're talking about flights in the air, hacking with physical things is a concern and it's a big IOT kind of conversation. You're in the middle of that, this is your world. What's your thoughts on the security? >> You know so we've obviously had to go through that in order to get authority to operate to push things into theater and one of the strongest benefits we've seen is the dev ops process and the platforms has all that security built in and all the testing as we're going through it. So the thousands of tests that are running as new threats are identified, the platform is updating with the latest patches or whatever it may be, so. >> John: On the automation stuff? >> On the automation side of it. So we're actually seeing a lot of the security, I don't want to call it risks go away, but our ability to mitigate them is being built into the software itself. So we haven't seen an issue yet where we haven't been able to get things authority to operate and push it out to the field, so. >> There's a high bar there too, obviously. >> It's a very high bar, very high bar, and that was part of the also the challenge of getting systems fielded in months and days versus years because of the ability to get that operations. >> Now this is a really big story I think. First of all Raytheon's a well-known brand, but, the modernization of getting stuff into theater and or into your production theater, military operations, that's a big deal, I mean, I think people don't really understand that aren't in government how fast this happens. I think that's a real testament to the solution, so I mean. >> Well the powerful thing to it is the national defense strategy is all about capability at the speed of relevance, and that's all about technology. Future wars aren't going to be decided by the size of your army or the size of your arsenal. It's going to be about how do you get data to decision makers faster and how do they can act faster. And that's where software and this infrastructure we're putting in place and putting capabilities in the hands of people that need it faster. That's what it's all about. >> And you know Secretary Matthis who was former Secretary of Defense said 48% of all the casualties are usually frontline war fighters. And that's where the technology edges so to speak. So again this is such a cutting edge topic, talk about it for days. How do you feel about this? This is pretty exciting. >> I'm just happy that every time I come into theCUBE, this is the second time I do it with a customer, you give me the opportunity to learn, you know, have a deeper relationship with one of my of probably now 7,000 customers. Which you know is really hard to keep up with these days and so you know we make technologies for people to use and when you see it in the field doing good it's a great thing. >> Well it's a transformation story. It's really a great transformation story. They have to, making a difference. >> Great, David, would love to hear, you know, what's on your ask for your partners that are deploying. Kind of give us a look forward roadmap that you can share. >> Yeah again I go back to everything we're about right now is speed and and getting capability faster. Currently in our marketplace right now we're fully embracing agile dev ops and everything it takes to deploy software from that perspective. Moving into things like artificial intelligence and machine learning and autonomy are the big things that are on our horizon from a technology perspective. And as our partners are in those areas and can help us bring more capability in that, that's going to help our end customer, the DoD, faster as well, so. >> What's the big takeaway from VMworld this year for you guys? What's the big observation? >> I'll be honest this is my first time at VMware. I'm amazed, I was at Dell Technology World a few months ago, I've really enjoyed it, I think it's a great event. And I'm just enjoying learning all the technologies so, it's, I've enjoyed the day. >> Gil what's your big takeaway? >> Well I'm part of the family. So I'm a little more familiar and even for me-- >> Whoever: You were briefed. >> No, no, even for me the rate of innovation that Vmworld puts out there is amazing. Right and you see how everything plugs together and you see how the vision keeps being, you know, completed, right, and we're in a good spot in the sense that we actually have what people need right now. And we do it better than everybody else. And you'd think that being number one in almost every category you'd be sitting there complacent and no, you know, we keep pushing the envelope, doing more innovating, more integrating more, so it's very exciting to see what's happening. >> Well great story here, Raytheon congratulations for your success I think it's super important to have a prepared military, certaintly, and saving lives and doing it in a modern way is kind of of a miracle these days in government, so congratulations. >> And I thank our partners for continuing to innovate 'cause that's helping us so. >> All right, great story, CUBE coverage here, Vmworld 2019, I'm John Furrier with Stu Miniman. We'll be back with more after this short break. (upbeat electronic music)

Published Date : Aug 28 2019

SUMMARY :

Brought to you by VMware and its ecosystem partners. of VxRail, of Dell EMC, great to have Raytheon, Talk about the story. to talk about you know. Talk about the solution, what you guys did, deployed the Pivotal Ready Architecture to allow might not know the pace of the procurement process. and so by the time you're actually fielding And that's really about having the right product And so if you can get your VMware stack I mean this is the money making. and protecting the safety of those flight crews. I mean talk about the impact that you've had and they're trying to, you know, copy our playbook but you know help us walk through, you know, and the air force about two years ago. Are you hearing that across your customer base? In the past we have simplified things And they get to keep their traditional apps, and in remote locations all over the world You're in the middle of that, this is your world. and all the testing as we're going through it. On the automation side of it. and that was part of the also the challenge the modernization of getting stuff into theater Well the powerful thing to it is And you know Secretary Matthis who was former and so you know we make technologies for people to use Well it's a transformation story. Kind of give us a look forward roadmap that you can share. and machine learning and autonomy are the big things And I'm just enjoying learning all the technologies Well I'm part of the family. and you see how the vision keeps being, you know, and saving lives and doing it in a modern way And I thank our partners for continuing to innovate We'll be back with more after this short break.

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Andy Miller, Sophos | AWS re:Inforce 2019


 

>> Live, from Boston, Massachusetts, it's theCUBE. Covering AWS re:Inforce 2019. Brought to you by Amazon Web Services and its ecosystem partners. >> Hello everyone, welcome back to theCUBE's live coverage in Boston, Massachusetts, here for two days, AWS Amazon Web Services re:Inforce, their inaugural conference around security. I'm John Furrier, Dave Vellante, our next guest Andy Miller. Senior director, global public cloud at Sophos. Based out of the UK and here in Burlington, Massachusetts. Welcome to theCUBE. >> Thank you. >> Looking good, love that jacket, nice color on you! (all laughing) >> I got the memo. >> You got the memo! >> Blue jacket! >> Thanks for having me, it's great to be here. It's great to be a part of AWS's first security event, security focused event, not by coincidence, happening right here where our US headquarters is. We're very excited to be a part of it. Wanted to share with you guys, I brought you a little gift. Socks are definitely a part of our-- >> Thank you, love the socks. >> Okay, I'm wearing them tomorrow. So we'll do a little close up on that. >> They're mostly clean. >> Thank you very much. Stu Miniman will love this, he loves socks. He'll replace his Star Wars socks with those. >> Thank you, Andy. >> Andy, thanks, so I want to get your impression of the show, obviously, inaugural event. And it's interesting, you look at Amazon, we've been covering Amazon for eight years with theCUBE, prior to that, just as a company, love the company, obviously, the success of cloud is a no-brainer. But re:Invent is their name of their global conference on the commercial side, for all their customers. And everything else they call summits. This is not a summit, this is not an Amazon Web Services summit, this is a branded event with the word re, not invent, but re:Inforce so gives that call out. Good call on their front? Is it needed? Why is this show so important, what's your opinion on that? >> I think it absolutely is, it's very helpful to customers to help them to understand their responsibilities when it comes to security in the cloud. And just like re:Invent was essentially reinventing the network into a digital environment, this is reinforcing their environment and understanding what their responsibilities are, where the cloud provider's very secure infrastructure ends and where their responsibilities with applications and data that resides in the cloud starts. >> What does your data show in terms of the evolving threat landscape? I mean, there's one school of thought that says okay, security in the cloud, actually, well it was a concern early on, people say oh it's better. That maybe raises the bar and lowers the ROI for the bad guys, but what are you seeing? But at the same time it's more global and distributed which opens up holes. What are your guys seeing? >> So, what we're seeing is that, the cloud's interesting in that there's not necessarily anything that is new or unique from an attack perspective. It's more of an attack surface perspective. And what I mean by that is is that, with an on premise environment, sometimes controls are very easy to place around new instances, new workloads being stood up, a change control process that is very controlled, key carded data centers and so forth. Cloud accounts operate very differently and one of the things that makes the cloud great is the speed at which you can go to market and stand up new resources, that also creates challenges for customers when it comes to visibility and securing those assets. >> Yeah, I mean the guy from Liberty Mutual today in the keynote, said his number one challenge is just keeping up with Amazon, the pace of change, you're seeing that in your client base? And how are they dealing with it? >> Absolutely, one of the conversations that I frequently have with customers when it comes to the visibility and keeping up with angle is, I frequently will say to customers, pull out your cloud bill, if you are aware of and know everything that is on that bill and where it came from, frankly I'd be very surprised. A lot of them struggle with that, with being able to keep up with that. And it's again a double edged sword, it's great as far as a business standpoint and being able to extend your business globally within minutes, but it's also a challenge for them from a security standpoint. >> And you talk about the challenges that businesses are up against when it comes to cloud security because on premises has decades of experiences dealing with security, the old days of perimeter based security, some still do that. Now the perimeter's pretty much gone away with cloud, cloud native has a different approach. So there seems to be a lot of questions around what to do, what are those challenges in cloud security specifically, that businesses face? >> So, you hit the first one, right? The first one is this concept of I build a castle and put a big wall around it and a moat around it, no longer exists, right? The perimeter is a memory. Another one is, as I mentioned before, the speed at which resources are added to the cloud, that's difficult for customers 'cause you can't see it, you can't secure it, right? If you don't know it exists. And then the third thing is really being able to understand how you make security happen within the cloud because those tools that you used on premise and in your own perimeter, don't necessarily exactly translate to the cloud. And it's important to have solutions that are designed for that and that not only work and operate well within the cloud but also don't take away the benefits of the cloud. If you have a solution that's going to slow you down or make it where you can't innovate at the speed of the cloud, you might as well keep it on prem, you're taking away all the benefit of the cloud. >> So, are you finding, a lot of times, the early cloud days with a lot of so called crapplications, just going to the cloud, okay. So maybe not as much credit card information, so maybe it's not as valuable, but are you seeing, people hitting the cloud more today than, say, certain on prem environments? Is it escalating, what does your data show? >> So, there was a study done not too long ago that showed past and projected cloud growth from 2017 to 2022. And what was interesting was the cloud services revenue growth was expected to grow by double, the cloud security spending was expected to grow by more than three times. And we think that was in large part of customers understanding their responsibilities in the shared security model, but also a product of exactly what you say, crapplications, right? One of our first customers that I think of was a convenience store chain, the very first things they moved, store locator and nutritional information applications. If something went wrong with those, yes, it's not great for your business if they can't find your store, but it's not credit card data, it's not personal information so on and so forth. As businesses start moving really key to the business applications, ERP systems, things like that, with real data that's at risk, that's where their focus on security is real strong. >> So there's a lot of confusion out there. And as I walk around the show floor here, I see, we secure the cloud, we the secure the cloud, no we secure the cloud! And I hear from Amazon we have a shared responsibility model, we secure the infrastructure, a lot of customers think, hey, Amazon has great security, so does Google, so does Microsoft, I'll put it in the cloud, I'll be good to go. Help us clear up some of that confusion, what's your point of view on that? >> Yeah, I think that when you look at it, customers were at one point extremely afraid of the cloud. And the cloud providers themselves did a great job of talking about why you could trust their infrastructure. In the process, I think customers have a difficult time understanding where their responsibility begins. And what we always like to say is, the cloud provider's responsible for the security of the cloud, you, Mr. Customer, are responsible for the security in the cloud. And the reason that's important is, the fact is the cloud providers could potentially provide the security in the cloud, but the measure of control that they would have over the applications that you build, the applications that you deploy, who you give access to and what you allow them to do would be so great, I don't think it would be a really positive experience for customers. >> Too many permutations. Just 'cause, criticism early on in cloud security wasn't that the security was bad, it was that, I couldn't enforce the edicts of my organization, there weren't enough features and now today, it's like you're drinking from this fire hose of features. So is that really the issue? It's up to you to figure out what works for your organization and then apply it. We heard today, you've got to opt in for things like encryption. Make sure you opt in to each availability zone. So that's a individual customer choice. Amazon provides the tools, okay, but then where do you pick up? Where does Sophos pick up? >> So, that's a great segue, so, as an example, our new Sophos Cloud Optics product does a great job with that, for instance uses the AWS CIS benchmarks. And that is a heavy heavy document that may be difficult for a customer to ingest, but we can run it against all of your workloads, your S3 buckets and see that you're in compliance with that CIS benchmark policy. That's a great place to start. Maybe you have some compliance regulations that you have to follow that have a security component to it such as BCI for example. And they would lead you towards things like identity and access management, they would lead you towards, am I following a good password policy? A good updating policy, am I sure that my S3 buckets are encrypted and not accessible to the internet without some sort of protection in place? All those things. >> The evolving cloud security landscape's changing on the threats side. You've got now detection, alerts, all these things are going on. You guys have some data on the cyber criminal activity. Up, down, is it more complex, harder to crack? Is there people cracking it? Certainly we know people are always trying, you can attack anything, we've seen foreign states enabling these groups out there, you've seen all kinds of cyber criminals, what's the data showing? >> So, the data shows, I think the most compelling thing. We did a study that we commissioned earlier this year where we placed workloads in 10 of AWS's most popular data centers around the world. And what we saw was, the first attempt to compromise one of those assets took all of 52 seconds. 52 seconds after we launched it there was an attempt to compromise it. More compelling was the fact that, on average it took a sum total of 40 minutes was the average time before an attempt to compromise took place. And, on top of that, once the asset was discovered, on average every 13 times every single minute of every single hour of every single day over a 30 day period, someone was attempting to compromise this. We ended up totalling over five million attempted compromises in a 30 day period on 10 assets. So, I think the biggest thing is not so much the techniques, but the level of automation that the bad guys have going on, they know that there are assets out there, that are not in a state that they necessarily should be and they are doing their level best to find them as absolutely quick as possible. >> What makes the cloud so attractive to the cyber criminals? >> I think the biggest thing is that as customers go from the crapplication into some real applications, they know that there is a lot of data there. They also know that customers are, well this is a newer platform for them, and they may be struggling with understanding exactly what they need to do differently than they did on prem in order to secure it. >> So follow up on that, how do you approach cloud security and how is different than on prem? >> So, the biggest difference is can it work within the fabric of the cloud? Is there tight integration with the things that the cloud providers offer? And do you not in any way hamper the great things about the cloud, scalability, the option to be available in a matter of seconds? If you are hampering that, then that's not security that's really going to work well, it's the whole benefit of the cloud in the first place, right? >> So sum up your cloud solution, what's the big problem that you guys solve? >> So, we have several different solutions that are available from a next generation firewall to our host protection. Our newest offering Sophos Cloud Optics, is really about helping them to gain that visibility, to understand exactly what they have running in the cloud, present a topology map that shows them how it connects, how it communicates, both internally and to the outside world. And then to constantly and continuously evaluate where they are in a security posture. >> So that's visibility into threats? >> Yep and for posture as well. >> Help look for quality alerts. >> Yep. >> Okay, so what's the customer orientation right now? Red, yellow, green? (he laughs) It seems to me it's always red. We asked someone earlier, what's a good day in security? And it's like, when we're still in business. There's a lot of pressure, again, hacking just shows you, it's easy to attack, certainly seconds to minutes, things are being compromised. It's going to happen on premise as well. What's the state of the union in your view? >> I think for customers there is a feeling sometimes and I think we as security vendors need to be careful about this, of not presenting the world as impossible to secure because I believe that it is absolutely possible to secure the world. I think there are some things that customers need to do, I think it's difficult for them sometimes to cut through some of the misinformation, the marketing spin and so on and so forth that's out there, but it's really incumbent upon them to look and read through the materials that are provided by the cloud providers to understand where their responsibilities begin and end. And then find the solutions that they've always used on prem and been successful with, that are ported to the cloud. And if they're not ported to the cloud to look for a different vendor. >> So why Sophos? >> So, Sophos has been around for 30 years. We have along history, we've been a security company, always a security company. And we have frankly what is a rather long track record in the cloud, we first ported our firewall to the cloud six years ago, we've continued to innovate in the cloud. We are able to do things that other vendors are not to support things that customers want to do, autoscaling, outbound gateway, things like that. And we continue to innovate that platform as well as add key pieces to our platform such as our Cloud Optics, which interestingly enough, came to us as we were shopping for it as a customer to support our own central infrastructure that runs in AWS. Our security guys thought, hey we need a product that will help us with visibility and posture management. And then they turned to the organization and said, hey this is great product, we ought to look at buying this company and that's how that acquisition came about. >> And so what's new with the company? What's going on, what are you guys doing? Got a lot here at Amazon, what other things you working on that's important to tell? >> Yeah, we're basically at this point, with that acquisition of Optics happened, it was a company called Avid Secure. That just went down in January this year, we released in the first week of April. Our own skinned Sophos version of the product. And we're really looking to continue that innovation. Our theme this year for our company was evolve. We feel that as the world evolves, security evolves and we have to evolve as well. And so there's a real focus on constantly evolving our products, innovating and trying to stay one step ahead of the bad guys, unfortunately. >> Andy, you've been around, we've been around, we've seen all waves come and go. Client server mainframe all the way back into those days to now. What do you think the most important story in the security industry is these days? What needs to be told that either is being told or needs to be amplified or isn't being told, what do you think's the high order bid in terms of the most important story? >> I think there's two fronts to that. One is as I mentioned, evolve was a big point of discussion in our internal meetings as well as our partner conferences. And helping customers to understand that their world has to evolve as well. The idea of a perimeter for instance, there are lot of companies that still try to stick to that idea of I can build a wall around my business. And the reality is is between mobile devices, between every employee practically has a laptop now, the idea of keeping that castle wall around your business is just unrealistic and so, customers have to understand that. They also have to understand that a migration to the cloud is inevitable and the sooner that they embrace that, the sooner they'll get the benefits of it and the sooner that they can begin the journey to the cloud. We feel it's inevitable. >> Andy, great insight, the evolving security threat landscape here on theCUBE. Live coverage covering AWS re:Inforce. Be right back with more after a short break, I'm John Furrier with Dave Vellante, we'll be right back.

Published Date : Jun 25 2019

SUMMARY :

Brought to you by Amazon Web Services Based out of the UK and here in Burlington, Massachusetts. Wanted to share with you guys, I brought you a little gift. So we'll do a little close up on that. Thank you very much. And it's interesting, you look at Amazon, and data that resides in the cloud starts. for the bad guys, but what are you seeing? is the speed at which you can go to market and being able to extend your business globally Now the perimeter's pretty much gone away with cloud, And then the third thing is really being able to understand the early cloud days with a lot of so called crapplications, the cloud security spending was expected to grow I'll put it in the cloud, I'll be good to go. the applications that you deploy, So is that really the issue? And they would lead you towards things landscape's changing on the threats side. in 10 of AWS's most popular data centers around the world. than they did on prem in order to secure it. And then to constantly and continuously evaluate for quality alerts. What's the state of the union in your view? that are provided by the cloud providers in the cloud, we first ported our firewall to the cloud We feel that as the world evolves, security evolves in the security industry is these days? and the sooner that they can begin the journey to the cloud. the evolving security threat landscape here on theCUBE.

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Day One Kickoff | AWS Public Sector Summit 2019


 

>> Announcer: Live from Washington D.C. It's theCUBE! Covering AWS Public Sector Summit. Brought to you by Amazon Web Services. >> Welcome back everyone to theCUBE's live coverage of AWS Public Sector here in beautiful Washington D.C. Springtime in D.C., there's no better time to be here. I'm your host, Rebecca Knight, co-hosting along with John Furrier, always so much fun to work with you. >> Great to see you. >> And this is a very exciting event for you in particular 'cause you've been doing a lot of great reporting around the modernization of IT in government. I'd love to have you just start riffing, John. What's on your mind right now coming into this show? What are some of the questions that're burning? >> I mean clearly the most important story that needs to be told and is being talked about here in D.C. in the tech world is, for this show specifically, is the JEDI contract, the Joint Enterprise Defense Initiative. It's a word that's not being kicked around at this show because-- >> Rebecca: Nothing to do with Star Wars. >> It's literally the elephant in the room because the contract's been waiting, Oracle's been dragging it on and Oracle's been part of apparently, my opinion from my reporting, is involved in some dirty under-handed tactics against Amazon. But it's being delayed because they're suing it. And Oracle's out. They have no chance of winning the deal, it's really Microsoft and Amazon are going to get a lion's share of the business. So you have, that's the biggest story in tech in D.C. in a long time, is the role of cloud computing is playing in reshaping how government, public sector operates. Combine that with the fact that a new generation of workers are coming in who have no dogma around IT technology, how it's bought or consumed and purchased, and the overcharging that's been going on for many many years, it's been called the Beltway Bandits for a reason because of the waste and sometimes corruption. So a new generation's upon us and Amazon is the leader in making the change happen. The deal they did with the CIA a few years ago really was the catalyst. And since then, public sector and the government has realized that there's advantages to cloud, not only for operating and serving society and its citizens but also competitiveness on a global scale. So a huge transformation, that's the story we're following. That's the story that we got into from the cloud side of the business here in D.C. and that is just raging and expanding and compounded by other factors like Facebook. Irresponsibility in how they managed the data there. Elections were tied in the balance. You're seeing Brexit in the UK. You're seeing counter-terrorism organizations using the dark web and other cyber security challenges at the United States. Literally digital war is happening so a lot of people, smart people, have recognized this and it's now for the first time coming out. >> Right, and I think the other thing that we're also starting to talk much more about is the regulation. I know that you're friendly with Kara Swisher and she bangs on about this all the time. But then she said in a column the other day the problem is is that they're now guns ablazing but do they really understand it? And also, is it too feeble, too little too late? >> I mean, Kara Swisher nailed her story in the New York Times and opinion piece. And I've had similar opinions. Look it. She's been around for a long time, I've been around for a long time. I remember when Bill Clinton was president, that's when the internet was upon us, the Department of Commerce did a good job with the domain name system, they shepherded the technology and they brought it out in a way that was responsible and let government and industry have a nice balancing act with each other and the government really didn't meddle too much. But there was responsibility back then and it wasn't moving as fast. So now you look at what's happening now, the government can't just not ignore the fact that YouTube is, in essence, its own state. And it's acting irresponsibly with how they're handling their situation. You got Facebook run by a 30-something-year-old, which essentially could be as large as a government. So there's no ethics, there's no thinking behind some of the consequences that they've become. So this begs the question, as a technology hock myself, I love tech, never seen tech I didn't like. I mean I love tech. But there's a point where you got to get in there and start shaping impact on ethics and society and we're seeing real examples of how this can wildfire out of control, how tech has just become uncontrollable in a way. >> Yes, no absolutely. And so who is going to be the one to do that? I know that on the show later you're going to be talking to Jay Carney who was obviously in the Obama administration, now here at AWS. It's a well-worn path from the public sector to technology. Susan Molinari, a couple of other, David Plouffe. That is the thing though, that these people really need to get it. Before they can lay down regulations and laws. >> Again, back to why we're here and stories we're trying to tell and uncover and extract is I think the big story that's emerging from this whole world is not just the impact of cloud, we talked about that, we're going to continue to cover that. It's the societal impact and this real there there, there's the intersection of public policy and technology and science where you don't have to be a programmer, you can be an architect of change and know how it works. Then being a coder and trying to codify a government or society. I think you're going to see a new kind of skillset emerge where there's some real critical thinking into how technology can be used for good. You're seeing the trends, Hackathon For Good here, you're seeing a lot of different events where you have inclusion and diversity, bringing more perspectives in. So you got the perfect storm right now for a sea change where it won't be led by the nerds, so to speak, but geeky digital generations will change it. I think that's going to be a big story. Not just workforce changeover but real disciplines around using machine-learning for ethics, societal impact. These are the storylines. I think this is going to be a big long 10-year, 20-year changeover. >> But what will it take though? For the best and the brightest of the nerds to want to go into public service rather than go work for the tech behemoths that are making these changes? I mean that's the thing, it's a war for talent and as we know and we've discussed a lot on theCUBE, there's a big skills gap. >> I think it's been talked about a lot on the web, the millennials want to work for a company that's mission-based. What more mission-based can you look for than so unto our public service right now? John F. Kennedy's famous line, "Ask not what your country can do for you, "what you can do for you country." That might have that appeal for the younger generation because we need it! So the evidence is there and you look at what's going on with our government. There's so many inefficiencies from healthcare to tax reform to policies. There's a huge opportunity to take that waste, and this is what cloud computing and AI and machine-learning can do, is create new capabilities and address those critical waste areas and again, healthcare is just one of many many many others in government where you can really reduce that slack with tech. So it's a great opportunity. >> And where would you say, and I know you've been reporting on this for a long time, where is the government in terms of all of this? I remember not very long ago when healthcare.gov was rolled out and it was revealed that many agencies were still using floppy disks. The government is, first of all is not this monolithic thing, it's many different agencies all with their own tech agendas and with their own processes and policies. So where do you place the government in terms of its modernization right now? >> On the elected officials side, it's weak. They're really not that smart when it comes to tech. Most of the people that are involved in the elected side of the Hill are either lawyers or some sort of major that's not technical. So you can see that with Sundar Pichai from Google and Mark Zuckerberg's testimony when the basic kind of questions they're asking, it's almost a joke. So I think one, the elected officials have to become more tech-savvy. You can't regulate and govern what you don't understand. I think that something that's pretty obvious to most digital natives. And then on the kind of working class, the Defense Department and these other agencies, there's real people in there that have a passion for change and I think there's change agents, Amazon's done really well there. I think that is a piece where you're going to see a movement, where you're going to see this digital native movement where people going to be like, "There's no excuse not to do this right." And I think there's new ways to do it, I think that's going to change. So that's that. On the business side, to how the government procures technology is literally like the '80s, it's like that movie "Hot Tub Time Machine" where you get thrown back. Everything is based on 1980s procurement, 1990s procurement. I mean, shipping manuals. So all these things have to change. How do you procure cloud? If you got to go through a six-month procurement process just to spit up some servers, that's not agility. So procurement's got to change. Competitiveness, what does that mean? This Oracle deal with JEDI highlights a lot of flaws in the government. Which is Oracle's using these rules around procurement to try to stall Amazon, it's kind of like a technicality but it's so irrelevant to the reality of the situation. So procurement has to change. >> Well one of the things you said about how there's a lot of pressure to get it right. And that is absolutely true because we are dealing with national security issues, people's lives, health, these really important topics. And yet the private sector doesn't always get it right the first time either. So how would you describe the government, the federal approach to how they start to implement these new technologies and experiment with other kinds of tools and techniques? >> Well I think there's obviously some agencies that have sensitive things. CIA's a poster child in my opinion of how to do it right. The JEDI, Department of Defense is emulating that and that's a good thing. The Department of Defense is also going multicloud as they put out in their statement. Amazon for the JEDI piece which is for troops in the field. I think that every agency's going to have its own workload and those workloads should decide which cloud to use based upon the architecture of the workload. 'Cause the data needs to be in the cloud, it needs to be real time. And to take the military example, you can't have lag in military, it's not a video game, it's real life, people die. Lag can literally kill people in the field. So technology can be a betterment there but technology to avoid fighting is another one. So you have all these things going on, I think the government's got to really design everything around the workload, their mission, their applications, rather than designing around here's your infrastructure, then decide. >> One of the things we talk about all the time, almost ad nauseam, on theCUBE is digital transformation. And so how do you think about those two, private sector versus public sector? What are the big differences in terms of these institutions on their own journeys of digital transformation? >> I think the government's slower. That's an easy one to talk about. I think there's a lot of moving parts involved, you mentioned some of the procurement things, so a lot of processes. It's the same kind of equation. People process technology, except the people that process is much more complicated on the public sector side than private sector, unless it's a big company. So imagine the biggest company in the private sector side, multiply that times a hundred, that's the government. So in each agency there's a lot of things going on there. But it's getting better. I think cloud has shown that you can actually do that, the people side of things going to be addressed by this new migration of new generation of people coming in saying, "I don't really care how you did it before, "this is how we're going to do it today." The processes are going to be optimized so there's some innovation around process improvement that's going to end on the wayside and the technology everyday is coming faster and faster. Recognition, facial recognition software. Look at that. AI. These are things that are just undeniable now, they have to be dealt with. What do you do to privacy? So again, back to process. So people process technology. >> AWS is a behemoth in cloud computing. What do you want to be hearing here at this conference? They're so far ahead of Google and Microsoft but we cannot count those two companies out, of course not. But what are you looking for for key messaging at this show? >> Well I'm looking forward to seeing Andy Jassy's Fireside Chat with Teresa Carlson tomorrow. I'm interested in some of the use cases coming out of Teresa Carlson's top customers in public sector, again it's global public sector so it's not just in North America here in the United States. I'm interested in also understanding what's real and what's not real around the fear, uncertainty and doubt that a lot of people have been putting on Amazon. Because I see Amazon posturing in a way that's saying go faster, make change and it's not so much that they want to monopolize the entire thing, they're just moving faster. And I think Andy Jassy yesterday saying that they welcome regulation is something that they're trying to push the regulators on. So I think they welcome change. So I want to understand if Amazon really wants to go faster or is there an agenda there. (laughs) What's going on? >> I know, methinks these tech titans are asking for a little too much regulation right now. I mean obviously Mark Zuckerberg has also said, "Please regulate us, I can't do this alone." And here we have Andy Jassy yesterday saying those same things. >> Andy Jassy said on stage yesterday with Kara Swisher, "We can't arrest people." So if their tech goes bad, they're only beholden to the consequences as a private entity. They're not the law so this is where again, back to top story here is that, what is the role of government? This change is here. It's not going away, it's only going to get faster. So the sooner the elected officials and all the agencies get out in front of the digital transformation, the sooner the better. Otherwise it's going to be a wrecking ball. >> Well I cannot wait to dig into more of this over the next two days with you, here at AWS Public Sector. >> All right. >> I'm Rebecca Knight for John Furrier, you are watching theCUBE. (upbeat music)

Published Date : Jun 11 2019

SUMMARY :

Brought to you by Amazon Web Services. Springtime in D.C., there's no better time to be here. I'd love to have you just start riffing, John. and is being talked about here in D.C. in the tech world is, and Amazon is the leader in making the change happen. is the regulation. and the government really didn't meddle too much. I know that on the show later I think this is going to be a big long 10-year, I mean that's the thing, it's a war for talent So the evidence is there So where do you place the government I think that's going to change. the federal approach to how they start to implement 'Cause the data needs to be in the cloud, One of the things we talk about all the time, the people side of things going to be addressed But what are you looking for for key messaging at this show? so it's not just in North America here in the United States. I know, methinks these tech titans They're not the law so this is where again, over the next two days with you, here at AWS Public Sector. you are watching theCUBE.

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Bob O’Donnell, Technalysis | Citrix Synergy 2019


 

>> Voiceover: Live, from Atlanta, Georgia, it's theCUBE, covering CITRIX Synergy, Atlanta 2019. Brought to you by: CITRIX. >> Welcome back to theCUBE. Lisa Martin with Keith Townsend coming to you live from Atlanta Georgia, our first day of coverage of Citrix Synergy 2019. Keith and I are very pleased to welcome you to theCUBE. For the first time, Bob O'Donnell, the founder and president of Technalysis. Bob, it's great to have you on theCUBE. >> Thank you. Great to be here I really appreciate it. It's my first chance to do theCUBE. It's exciting. >> We're so excited because you are no stranger to TV. Bloomberg, CNN, CNBC, Squawk Box, now theCUBE! >> Bob: And the now theCUBE! >> Keith: Most importantly- >> Bob: It completes the circle. >> He's a friend of Leo Laporte, which makes him a super star. >> All: (laughing) >> Well there you go. >> We're sitting in the presence of greatness. >> Oh, I don't know about that. But anyway, no, it's a pleasure to be here and it's nice to chat with you guys. It's a very interesting time that we're in. I mean, when we think about what's happening in the world. For years we've seen this move to cloud-based computing, and SaaS, and everything else. And everybody's excited about all of this stuff, and there's all these tools. And then on top of that, we thought, we have all these devices, right? We've got this amazing range of different devices we can use. But ironically, what it is, is we're in a state of too much of a good thing. It's too much. Even though if you think about it, you'd say, "Well, objectively, there's so much that "we could potentially do here. "I mean, we've got these tools that can do "this and this and this." But all of a sudden, "Well, except I got this one and this one, and this one. "And oh, by the way, if I want to send a message, "I can send it five different ways to Sunday, "and therefore if I want to read a message, "I have to be able to read it "five different ways from Sunday." And so, the challenge that you face is, and Citrix talked about it, I thought, quite nicely in their keynote this morning, is people get overwhelmed. And they just can't get productive with what they're trying to do. And so, what you need to do it figure out ways to turn that chaos into structure and order. And that's what they're trying to do with the workspace. And it looks pretty cool. >> Yeah, one of the offline conversations I had was you get all these tools. It's like somebody took a box of 10,000 Legos and just jumped it on your desk and said, "Build a masterpiece." And what I head this morning was the equivalent of what was like a Star Wars kid of like, "This is what you can build. Here's the directions, "and now you can start to deviate and customize it "for your environment." So one of the things that I'd love to get your input on is this concept of AI ML. This ideal of taking tasks and automating them. It's nothing new. We've tried this with macros and other areas. But the thing that was missing was, these tools were pretty dumb. >> Bob: Right. So the promise of ML AI should make these tools become real. What's your impression of the state of the technology versus what was presented today. >> Well, look, we're in very early days of AI and ML. There are some fascinating things out there. There's a lot of the high profile things that we hear about. The ImageNet and the ability to recognize every kind of dog known to mankind, and all the demos we've all seen at every other trade show. It really is, the fascinating part, exactly, to your point, is that the goal with AI and machine learning is to actually makes things understand. And it's fascinating because... I'll take a bit of a sidetrack but bring it back. When devices started to be able to recognize our words, we assumed, because we're human beings, that they recognized what we meant. But, no. There's a big jump between the words that you can transcribe, and what you actually mean. >> Yeah. That context. >> Context is everything. And context is something that, again as human beings, we take it for granted. But you can't take that for granted when it comes to technology and products. So, the beauty of AI as it starts to get deployed is how do we get the context around what it is that we're trying to do, what we meant to say. Of course, we all want that in real life: "What I meant to say was..." But, "what I meant to do was this." Or, "the task I want to do is that." So, taking that back to what Citrix is talking about is there are a lot of rote procedural things that people do in most organizations. And they gave the classic examples of proving the expense reports and this and that. So, clearly, some of those things they can pre-build. The micro apps, in a lot of ways, they really are macros. It's kind of a fancy macro. And that's fine, but the question is are they smart enough to kind of deviate, "Oh, well, there's a conditional branch "that it automatically builds in a macro "that I didn't have to think about "because it realizes in the context of what I'm doing "that it means something else." Or something like that. >> At the end of the day, I want to get the account balance, however that translates. As opposed to: take this column from row A and put it in row B. No, sometimes row A won't be the correct destination. I want the account balance. >> Right, right. >> And the other truth of the matter is we're still getting used to actually talking to our devices. We do that at home to some degree for people who have Alexas, unless they've decided to stop recording everything, and then that's a whole different subject. But, at work we don't. Interestingly, I remember when I first saw Cortana, for example, on a Windows machine. I thought, in a weird way, Cortana makes more sense because I should want... But it hasn't really happened. It hasn't played out. So there's some level of discomfort of talking to our devices and recognizing these things. So, I think there are cultural issues you still have to overcome. There are physical issues in the workplace, now. Now, when you have these open office environments, which doesn't take a rocket scientist to know that that was going to be a disaster. Whoever thought that was smart, man, let's take a look at where their degree came from. But that's the reality that people are in. So, you've got the physical environment challenges. You've got the cultural "how do I work with this?" environment. And then just starting to realize what it can actually do. And then, of course, you have the problem that it didn't recognize what it actually said. That's something stupid, and the original Siri problems that we all had. But, all of these things tie together because they're all different takes on what machine learning has the potential to do and what we think it should do, and what it can actually do. The one thing I will say is as we head towards 2020, I think we're going to start to finally see some of these things do what we thought they were going to do. They're going to start to have the context. They're going to start to have the intelligence. So, in the work space, it's going to have the ability to know what I mean when I say, "I need the account balance." Or, "I need to know where in the sales pipeline "this particular project is," or whatever task it is that I've got to deal with. And so, understanding that and then building the plumbing to do that is critical. One of the interesting things, if you look at what Citrix does, they're really all about plumbing. They have this ability to pull together all these different elements. From the beginning, what we started talking about. All these different applications over different types of network speeds and connections and make them all work. And yet, they present this very simplified, beautiful, nice little, you're like, "oh, this is great!" But, man, buried beneath there is a lot of stuff. And that's, to give them credit, that's what they're really good at doing. And companies now, the challenge is, a lot of companies have really old applications that they've got to kind of modernize in some way shape or form. And some of them are doing it on their own. They're doing the containerization and all the things we hear about as well. Some of them are wrapping them. Citrix, some of their original business, XenApp, was about app virtualization. Taking an old app and giving access in a modern way. So, again, it's doing that, but the other problem you have to bear in mind, excuse me, is that every company has a different combination of apps. They said 500 apps is normal. A lot of companies have more than that. >> Keith: Mhm. (affirmative) >> The problem is, it's not the same five hundred apps. This company has this set of 500 apps. This company has this set of 500 apps. This company has this set of 500 apps, and maybe 150 of them overlap, which means the long tail of 350 per company has to be dealt with and figured out. And that's, again, those are the problems that they're trying to solve and bring in to a unified environment. >> And also manage these growing expectations that all of us that are workers have from the consumer side of our lives. You mentioned Alexa and Siri, and we have these growing experiences that whether I'm talking to a device or I'm going on Amazon, I want it to know what I want. Don't show me something I've already purchased. And we have these expectations as humans and consumers that we want the apps when we get to work to understand the context and of course, we're asking a lot. In your opinion, where is Citrix in starting to help manage, helping their customers, rather, manage those growing expectations? >> I think Citrix has done a lot in that area. Even many, many years ago they were the first to come up with the notion of an enterprise app store. In the early days of the app store, they came out with this concept of, "We want to do an enterprise equivalent of that." When I download an app that I need to install on a work PC, make it easy to get at. So, from way back when they've been building on that. And then, the examples they gave today, the notification from the airline that your flight has changed, or whatever. Those are all the experiences that we're now used to thanks to cloud-based services. And their point is like, "Hey, why shouldn't we "have that at work, as well?" And so that's exactly what they're trying to work towards, is that notion of cloud-based notifications and services, and things, but related to the specific tasks I have to do. Because at the end of the day, they want to drive productivity. Because we all waste stupid amounts of time, and truth be told, the bigger the company you're at, the more time you waste because of just keeping up. I used to work at a big research firm of 1200 people, and literally half my day, every day, was just procedural stuff. I didn't actually work on the stuff that I thought I was hired to do, except for maybe half the day. And with a lot of people, that's very common. So, anything that can be done to reduce that and allow people to get through the procedural stuff a little bit more efficiently, and then actually let them do the work that they were hired to do and that they'd like to do, and oh, by the way, gives them more satisfaction. All of these things tie together. People tend to say, "Oh well, you know, "that's nice to do, this consumerization of IT, "that's nice." It's not just nice. It's actually practical. It's actually a real productivity enhancing capability. And I think Citrix has done an excellent job of driving that message. It's hard to to do because, again, the complexity of the plumbing necessary is super difficult. But their head and their heart are in the right place in terms of trying to achieve that. >> Well, it sounds absolutely like not a "nice to have," but business-critical. One of the stats that David Henshall, their CEO, said this morning, and Keith's been mentioning a number of times, is that he said there's 7 trillion dollars wasted on output because employees are not able to get to their functions that they were hired for in a timely manner. >> Right. >> So, there's a huge addressable market there of opportunity but also the consumerization that's personalization expectation is huge to not just making me, Lisa Martin, as an employee happy, but my business's customers that I'm dealing with. I think of a sales person, or even a call center support person. If they don't have access to that information, "She already called in about this problem 'with her cable ISP," that person is going to go turn, and go find another option that's going to fulfill their needs much better. >> That's absolutely right. And that was the interesting point that they made. And that's what they're trying to do with the intelligent work space is to move beyond just providing these apps, but actually personalizing it to each individual and being able to say, "All right, each of us are going to have a workspace." Sort of, it looks kind of like a news feed kind of a thing. Each one is going to be different though, based upon, obviously, the different tasks that we do, the order with which we do them, the manner with which we do them." So it does get personalized. The notifications, you know, I may want certain notifications that you don't really care about as much. But that's fine. We can each create that level of personalization and customization. And again, what Citrix is trying to do, and it was a key point that P.J. made, is, "Look, we're not just building an application. "We're building a platform." And that's... The significance of that is big. And remember, he came from Microsoft. He worked on Windows. He worked on Office. So, he's got a long history of working on building platform based tools that have tools that you can build on. That have APIs and ways for other people to add to. So, all of those are critical parts of how they tell that story, and how they get people enthralled enough to say, "Hey, I'm going to make the commitment to do it." Because look, it's a lot of work. Let's not kid ourselves. If I'm not a Citrix shop, but I go, "Damn, that's cool!" There's a fair amount of effort to make all this stuff actually happen. So, it's a commitment. But, once they get them hooked it's a pretty sticky type of environment. Especially as they continue to deliver value and personalization and customization. That, at the end of the day, drives productivity. And that's a pretty straight forward message: "Hey, we can save your workers time "and make them happier." Well, who doesn't want that, right? >> So, let's talk about engaging your customers. Like, I can look at this, and I can easily, say I can come to a conference like this and say, "Wow, I really want the output. I don't want "any of that employee experience stuff. "That stuff just sounds hard, "but the output I definitely want." Talk to me about the evolution of your customers as you walk them through if you want the output, here's what you have to do. And talk to me about, specifically, the success stories of where they didn't get it, and then after you've engaged them, they got it. >> Well, there's so many different variations out there. But, at the end of the day, every company out there is dealing with the fact that they have workers that work in a lot of places on a lot of devices and they have to allow them to get stuff done. And so, it's about how much are they willing to do to make that happen? But there's the psychology of it. There is the whole, "how much of this am I willing to outsource?" Versus, "I really want to keep it inside." So, it depends on the industry and the level of if they are a regulated industry, and all those things have an enormous impact on how they do this. But, if you think back, Citrix's original business was, a lot of it, was again, around desktop virtualization, and actually trying to get really old school stuff, I'm taking mainframe green screen stuff, to actually run on an old Windows PC. And that was kind of a lot of what they did, initially. And then, of course, they've built on from there. So, all along the way, you see different organizations. Citrix has been thought of more as more of the old school kind of enterprise software. Along with an SAP or an Oracle so something like that. I think they've done a particularly good job of being cloud native, cloud aware, and working with these cloud-based tools. Because early on, when we think about what happened with SaaS applications, people thought that was going to dramatically change how anybody did software. And it did, but not in the way people expected. So, I'm trying to get an answer, specifically, to your question, but I think what it is is what they're doing, and what companies who deploy it find is that they can take even these completely different types of software and services, and ServiceNow, and Salesforce, and Workday, and all these kinds of things that are dramatically different, but still, again, have overlapping functionality if I use all of them, and conflict or counteract or interact, or need to interact with other tools I already have that I'm working to change. So, again, what I think that what Citrix has done a good job is they're able to look at the wide range of stuff that people have in that 500 group of apps, or whatever it is, and be able to say, "All right, ten of those are cloud-based services. "But we've got 490 other ones we've got to deal with." And they have different levels of technologies to deal with those. So, what companies can do is they can also pick and choose. They can say, "Look, we're not going to get all 500 apps in our workspace." Maybe they just decide, "But we're going to do these twelve, "five of which are SaaS-based, "and then we've got a couple other critical ones "that we have to do, and that hits 80% of our workers." And they can tackle it that way. So, the bottom line is companies who... Look, it's a big investment up front. So the process is you have to psychologically say, "I'm willing to make an investment in," not obviously, just now, but their roadmap. What they're doing. What they're talking about. That's why they talk a lot about the future because if I buy into this ecosystem, I'm committed. Right? Again, I talking about that earlier: The stickiness question. So, companies who are doing this kind of thing, companies who are trying to make sense of all these applications have to be willing to make those big investments. It used to be, it used to have a huge Citrix server farms, as well. Obviously, with the development of the Cloud and Citrix Cloud, that's all changed. But, it's still a big investment, and they have to work to figure out ways to do this. And if they do, to finally get to, you know, they do see productivity savings. I mean, Citrix is, I don't remember the numbers, but they can qualify actual time saved when their solutions are installed, and that's the benefits that these companies get. So, they have to measure how much is my employee time worth versus the cost of getting these things deployed? >> Well, and I think that's going to be a differentiator for them. I wish we had more time because we could keep talking to you for a long time, but you got to add theCUBE to your list of TV: Bloomberg, CNBC, >> Bob: It's all there. Hey, I'm excited. >> Squawk Box, Now, theCUBE. Bob, it has been such a pleasure to have you on theCUBE. >> Thank you. >> We appreciate your time. >> Thanks so much. Appreciate being here, thank you. >> Our pleasure. For Keith Townsend, I am Lisa Martin. You're watching theCUBE, live from CITRIX Synergy 2019. Thanks for watching. (upbeat techno music)

Published Date : May 21 2019

SUMMARY :

Brought to you by: CITRIX. Bob, it's great to have you on theCUBE. Great to be here to TV. He's a friend of Leo Laporte, and it's nice to chat with you guys. So one of the things that I'd love to get the technology versus what was presented today. The ImageNet and the ability to recognize So, the beauty of AI as it starts to get deployed At the end of the day, And then just starting to realize what it can actually do. and bring in to a unified environment. and consumers that we want the apps when we get to work of the app store, they came out with this concept of, One of the stats that David Henshall, their CEO, and go find another option that's going to and how they get people enthralled enough to say, And talk to me about, specifically, And if they do, to finally get to, you know, Well, and I think that's going to be Bob: It's all there. to have you on theCUBE. Thanks so much. Thanks for watching.

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Ben Gibson, Nutanix & Monica Kumar, Nutanix | Nutanix .NEXT Conference 2019


 

>> Narrator: Live from Anaheim, California it's theCUBE covering Nutanix .NEXT 2019, brought to you by Nutanix. >> Welcome back, everyone, to theCUBE's live coverage of Nutanix .NEXT. We are wrapping a two-day show. I'm your host, Rebecca Knight, along with my co-host, John Furrier. We saved the best for last. We have Ben Gibson, Chief Marketing Officer and Monica Kumar, SVP Products and Solutions at Nutanix. Thank you both so much for coming on theCUBE. >> Thank you for having us. >> Yeah. >> So congratulations on a great show. 6,500 attendees and 20,000 were live streaming. We had Mark Hamill, Jessica Abel is speaking next. Energy, a great vibe. Congratulations, you both get a well-deserved vacation after this. But I want you to, Ben, close out the event and tell us a little bit about what you hope the attendees is come away with. >> Yeah thanks, and thanks to theCUBE for joining us here-- >> You are welcome. >> It's a long marathon, right, over the last two days. And thank you for the great coverage you provide for this event. Yeah, we're thrilled with the event, and for us, it really starts with getting even deeper, more connected with our customers, right? And so we do great keynotes and there's a lot of new product announcements which I know have been covered in good detail throughout the last two days. But at the core of it, it's how do we make our customers better positioned for how they do their jobs. So it's training and certification and networking with their peers, and you hear that all over the place. And so as excited as I've been over the last three days with the event and the grandeur of it all, the thing that really gets me pumped up the most is when I see these ad-hoc groups that just come together in a hallway, and they sit down. I go over and say, what're you guys up to? and we're like, well, this is like our AHV mashup group, and we get here and we talk about key challenges we have, key opportunities, best practices tips, and so it's that network effect for me above anything else is what is at the heart of this show. >> One of the highlights we pointed out yesterday and today in our intro was the community vibe you have here. You have a great loyal customer base, Net Promoter Score of 90 which is a monster number, congratulations. But it's a small intimate event, you guys were able to not make it a trade show but a conference that was intimate, content driven, content value with nice tracks. Lots of comments on the tracks. So a lot of good highlights. So my question to you Ben and Monica, what's your highlight so far? >> You know, I'll take this one. As a newbie, I'm one of the newest members of the team at Nutanix and this is my first .NEXT. Even though you say it's a small event, it's still 6,500 plus people and about 20,000 attendees online right. So I think it's still sizable, but the beauty is that we're still able to maintain that community feeling. And so for me the most exciting part was not only meeting with customers like our SisAdmins, DevOps folks, developers, IT directors, CIOs, partners, our own employees, we're like bringing everybody together here to discuss how we can make things better for the customers, and what are things that are working and how can we improve. So I think to me that's one of the biggest thing I'm taking away as I go back, is what we can take as a feedback and how we can do things better in how we bring products to the market. >> Ben, highlights for you? >> Yeah for me, well first of all, I got to interview my boyhood idol, Mark Hamill. (laughter) >> Pretty cool. >> And that was a lot of fun, right. And we've just gone through in an hour and half of great content, our Nutanix Mine announcement, that was great, we announced AHV support on frame. So that was exciting to me and then, the cool thing about our show is we like to mix it up with something that's really fun. And in my case and I know with many people in the arena, and I saw the meet and great afterwards, to bring out Mark Hamill. I had to contain myself because I am a big Star Wars geek at my core, and we had a great conversation. And you know when you feel the room, I felt the room of 6,500 hanging on his every word, right? And he talked about persistence in his career, how he started out, all the rejection he got earlier on. We talked about his career journey, so on a really fun way, it kinda connects with a lot of journeys we have with the professionals in the room that are going through a lot of change and rejection or taking a risk or a chance on new disruptive technology. >> Yeahm it's really been a home run. First of all, the theme of having of Star Wars and Mark here was really great because the demographic, we all love Star Wars, so nice connection-- >> Who doesn't? >> Nice connection to the tech audience but your customers consistently say in theCUBE and off theCUBE, in the hallways and other conversations that they took a bet with Nutanix and it paid off. And that's the rebel kind of mindset inside these cultures of pre-existing legacy, vendors, and so you guys are breaking through. This is a big part of the marketing, is to enable those rebels to be now the mainstream. >> Yeah it's, you know you're right, it's rebellion, you know, that's spreading and growing, but as a marketer here, there's plenty of conversation about how we differentiate, right, and the outcomes we create for the customers but then when I see one of our early customers, and we opened the conference, he shared a picture where he was flying in a Cessna plane over the Grand Canyon, and he had his iPhone, he was managing his clusters with Prism on his iPhone. And what he said was the outcome for me, yeah there's total cost of ownership, yes, there's high performance levels, you can go through the traditional outcomes that IT folks look at. But at the end of the day he said, I'm able to spend more time with my family, and that sounds kinda cheesy, but it's real, and you sense that and you learn about that when you're here with customers. And with Monica coming on board, yeah, we've always been great, I think, at marketing and communicating our technology advantage but it's about more than that, right? >> Yeah. >> Talk about about your role, you have a stellar career, you're now new to Nutanix, you're not new to the industry. What's your focus? What you're gonna be working on? >> As with everything we do at Nutanix, it's all about the customer, so we are obsessed with making sure that the customer has the best experience, whether it's with product quality or how we take our products to market. How we message it to connect to what problem that they need to solve. So I think the biggest challenge we have as a company, the opportunity is, we know the customers are moving to the cloud. Customers are embarking on journeys to a modernized infrastructure. They are embarking on journeys to be able to use multiple different clouds. There is a lot of complexity out there, so our opportunity is to simplify that complexity for the customer. So that's what I am going to undertake with Ben here, is come up with right solutions, the right packaging, the right messaging, the right offers for our customers that can make it easy for them to get on their journey that they choose to get on to the cloud. >> Rebecca and I were talking about on the kickoff yesterday, 10 years old, CUBE's ten years old, so we've been following you guys for a long time as well. You're growing up. You're still a young company, you've said you're a billion dollar startup. >> Yeah. >> That's the culture. What's next for you guys? What's the goal? What's the objective? Because you've built a great community organically, your content is on the mark at the conferences, also digitally, there's nice organic kind of discovery for your customers, are learning about Nutanix. Word of mouth is big, network effect you mentioned, new cultural, younger generation. So you got a lot of things working for you. What's next? >> Well, thank you. I agree with those things, (laughter) but I tell you, here's one thing I've been thinking about towards the opportunity. So if you look at the past year, and I talked about this in our recent investor day, that if you look at the amount of IT Spin tied to traditional three-tier data center architecture, storage, network, compute, running in separate silos, hundred billion plus in annual spin. Hyper conversions, great new modernizing infrastructure play, the market spend on that this year is probably five billion. So if you think about that, I think about only 5% of the legacy world been modernized. And I am not claiming a 100%, but I am claiming well north of an opportunity, well north of 5% to get there. So fundamentally, the first thing what's next is there's a lot of green field left to take advantage of here and for customers to understand the value, human value, as well as financial and operational value, of what we're up to here with our customers. And so that's next, and then at a higher level, and I know it's something Dheeraj and Sunil talk a lot about, it's, we've hyper-converged infrastructure, made that essentially invisible, much grander ambition, how do you hyper-converge clouds, how do you take the complexity Monica was just talking about and provide a lot of simplicity for App Mobility and the like and take that to the next level. So to me, there's still the core mission. We're just getting started right. >> You know I asked Sunil that question, I said, how do you make that happen? And he had a great comment. We weren't on camera, I wish he had said that on theCUBE. We were off theCUBE before. He said, "Well, people tasted Amazon, they tasted cloud, "and now they are gonna bring that "mojo to the enterprise on the premises, "because they realize the benefits of cloud by itself. "But they can't get everything to the cloud. "So they gotta get modernized on premises "and operating model, not so much a refresh." >> To add to that, if you think about the role of technology right, the role is to make our lives easier, whether it's at work or in our personal lives, so I think the next big frontier is all around automation. I think this whole move to the cloud is because people want to automate a lot of the mundane tasks, we've talked about that in the past with data and such. I think the same applies to infrastructure, so you're gonna see us really focused a lot more on, how can we help IT automate? A lot of the, you know, keeping the lights on type of tasks which could actually be easily be done by the machine or in the cloud or by the software, human beings then can focus on more important things. >> Right whether it's being over the Grand Canyon with your children or meaty tasks of our jobs. >> Exactly so it's about making IT become a service provider rather than a cost center. I think that's what we're gonna enable with our softwares, we continue to go forward. >> I'd love you to comment on Ayanna Howard, Dr. Ayanna Howard's keynote this morning, where she talked about actually smart machines working together with smart humans, and how that's really the collaborative AI, and that's really where the future is heading. How do you think about that, and how do you message that, and how do you approach that within Nutanix? >> Yeah I totally agree, it's not human versus the machine. It really is human plus the machine. It's the combination which is gonna be most powerful in how we adopt technology to make things better for us. Like I said, whether in our personal lives or work lives. I know a lot of examples in my own personal life that I can see how machines or softwares changed the things I used to do before which I don't do anymore. There's lots of examples, I know when growing up in India, we washed our clothes by hand and now we have, when I moved to U.S., we have the laundry machine, right? I mean, there's lots of small, small things that are happening now, we talk to our Alexas and we can command people, to call people, to turn the music on, to turn the lights off and what not. And I actually have benefited from those, my parents, I'll give you an example, I have older parents who live at home, and now it's amazing, my mom can say, Alexa turn off the light, or turn on the light if they have to wake in the middle of the night, guess what it's not dark anymore, the light gets turned on, it's a real use case, you know. (laughter) They won't trip and fall. So I'm like thank you Alexa (laughs). So I do think that power of machine and human is the combination where we're going next, and I think Sunil touched on it somewhat in his keynote too. We're talking about autonomous data centers, right. That's exactly what it is. We are injecting more of machine learning, more of AI technology in how we are analyzing the operations, and then how we act on the predictive intelligence that we're getting from the operations to fix things before they break. >> Ben, I want to ask you a question on the marketing side because one of the things that came out of the top stories that we identified here at the show was the move to software. It's a big part of Nutanix next generation shift and growth is gonna come from just software, not hardware, just a software company. And also Dheeraj mentioned that he has a new customer, Wall Street, (laughter) and so he has to manage that. He had a great answer on how he's gonna balance the short term Wall Street-ers and the long game that you guys play at the Nutanix, so you got the software transition, the middle of it, different economics, software economics are much more stronger than process improvement, box changing, changing boxes in a data center. So software's going to be a nice impact across the long game, but Wall Street may not understand that software, and as you guys go to the next level, from hiring and marketing software, how are you guys thinking about that? I know it's about a year under your belt now with software, what's the orientation? What's your posture for to the marketplace with the software play? >> That's a good question. I'm sure, you know, Dheeraj likes to talk about Wall Street and Main Street, right, and how do you balance the two. And yeah we are disrupting along established market. We are moving from hardware to software now rapidly in subscription-based consumption models, and we're doing all that at the same time we're growing at the rates we're growing. And so it's a lot of juggling in the air, right? >> And I'll throw channel in there too, you gotta channel the merging, your partner strategy is looking really good. The HPE relationship is I think a great signal, potentially, in more local expansion, more breadth channel marketing on the table (laughs). New things. >> I mean, the way I think about it, as a marketer here, is, you know, and Monica touched on this, how do we create and provide offers to market that take advantage of the freedom of choice of consumption of Nutanix, right. And then how do you take those to market through your sale organization, how do you increasingly take new offering and capability to market through the product itself, which is a well-worn practice in the SaaS world. And then the channel partners is a key part of this because the partners that really, and I met with many here this week that really on top of this, they want to build that value-added practices that are about providing new services and offerings on top of that software, and then to be able to offer it in effective ways. The marketer has think about how do we incentivize, how do we package, how do we message to bring these to the market. It's candidly a transition for us, but it's an exciting one. At the end-- >> And you guys, and you were open about it too, you recognize that it's happening. >> Yeah, and I see it, you know, those moves can be challenging, but those are also moves I think that Wall Street likes. >> Evaluational increase. >> So we're nearly finished with this conference, but we're already think ahead to the next one in Copenhagen. So talk a little about that, and then Nutanix Americas in 2020. >> Well good, so we're looking forward to taking the show across the pond to Copenhagen. We had a great, our Europe event last year in London was amazing, right. We had record turnout. We had close to, for a user conference, 35% of attendees were not even customers of Nutanix yet. And often for these conferences you see more existing users and then maybe some, and we so expect that trend to continue. We have a lot of traction across Europe, Copenhagen is a beautiful city. There'll be plenty new to announce there, so I can't leak anything early on that front yet. But that's gonna be exciting show. >> Come on. (laughter) >> It's taste. >> We won't tell anyone. >> And I'm sure he's gonna be hobnobbing with yet another celebrity in Copenhagen. I've renamed his title. He is the Chief Celebrity Officer at Nutanix now. >> Well, he and Mark Hamill are-- >> That's right. >> But we're best friends now. (laughter) >> And he was with Magic Johnson earlier. I have a long list of people he's been-- >> You're killing us. >> No, he is. (laughter) >> Yeah, Freddie Jackson. >> Well you know, all joking aside, it's customer experience. And if it's all business, it's all product and all technology, right, then you know, that's a certain level of experience, but part of this is the community and the happiness that we see in our customers is we make them happy, both in the technology we deliver, the partnership we enjoy with them, but then also some fun experiences we deliver to them. And that's the spirit of this show. >> Yeah you guys do a great job. I want it like highlight and also get your thoughts, and I want you to share with folks watching 'cause you guys do a great job on the content programs at your events, the mix and match up of the core meat on the tech bone, the solutions, but balance of guest hosts, guest celebrities kind of blend in the theme. What's the secret sauce? What's the playbook? What's the thinking behind lot of the content and how's that gonna translate digitally because you guys mix it up, it's not just all Nutanix all the time. You got partners, you got people from outside the industry, seems to reinforce, the threads kinda connect together. What's the, how do you guys think about that? >> Yeah well, the secret sauce at the core of this, Julie O'Brien, a woman named Erin Alonso on my team. We have a strong, small but mighty, very creative events team that understands that at the end of the day this is about learning, but it's also about show business too, right. And people want to come to relax, to learn, and to have fun too, and I think it's balancing the two. But it's not just, okay it's Mark Hamill, because he was in Star Wars. It's because we knew Mark had such a tight, iconic connection with our core demographic, in terms of the core customers we have, and I saw our customers, some with tears in their eyes when they were able to meet him afterwards. And so, okay there's, and I was joking hyper-convergence, I was talking to Mr. Hamill, I said, hyper-convergence, hyper-space, right, there's ways to connect the two together. But there's technology at the heart of both of that. So it's just a new and unique and surprising way, and one thing, I close with, we endeavor in marketing here when we run our campaigns, when we do our events, surprise and delight. Surprise and delight. It's inherent in the product with one click, and everything we do there, and we'd like to think it's inherent in our marketing and also an event like this. Surprise and delight. >> So Monica who'd your hero be up there on the stage? Who do you want to see at the next-- you boss is right here, (laughter) this is your chance to influence-- >> Oh my god, okay. If you really wanna know (laughs), he'll have to fly in from Bombay India, the movie star Shah Rukh Khan. He's got known as SRK. But he is a world-famous icon. So there you go, next one SRK. Talk to Sunil about it, he knows about SRK. >> We hear you. >> Note, noted. >> Well then Monica, thank you both so much for coming on theCUBE, always a pleasure. >> Thank you. >> Thank you. >> Thank you very much. >> I'm Rebecca Knight for John Furrier. You've been watching theCUBE's live coverage of Nutanix.NEXT (techno music)

Published Date : May 9 2019

SUMMARY :

brought to you by Nutanix. We saved the best for last. But I want you to, Ben, close out the event and you hear that all over the place. So my question to you Ben and Monica, And so for me the most exciting part was Yeah for me, well first of all, I got to interview and I saw the meet and great afterwards, First of all, the theme of having of Star Wars and so you guys are breaking through. and the outcomes we create for the customers you have a stellar career, you're now new to Nutanix, it's all about the customer, so we are obsessed so we've been following you guys for a long time as well. So you got a lot of things working for you. and the like and take that to the next level. I said, how do you make that happen? To add to that, if you think about the role of technology with your children or meaty tasks of our jobs. I think that's what we're gonna enable and how that's really the collaborative AI, the light gets turned on, it's a real use case, you know. and the long game that you guys play at the Nutanix, and Main Street, right, and how do you balance the two. you gotta channel the merging, And then how do you take those to market through and you were open about it too, Yeah, and I see it, you know, So we're nearly finished with this conference, taking the show across the pond to Copenhagen. (laughter) He is the Chief Celebrity Officer at Nutanix now. But we're best friends now. And he was with Magic Johnson earlier. No, he is. and all technology, right, then you know, and I want you to share with folks watching in terms of the core customers we have, So there you go, next one SRK. Well then Monica, thank you both so much I'm Rebecca Knight for John Furrier.

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Chris Kaddaras, Nutanix | Nutanix .NEXT Conference 2019


 

>> Narrator: Live from Anaheim, California. It's theCUBE, covering Nutanix .NEXT 2019. Brought to you by Nutanix. >> Cameraman: You're on camera. >> Welcome back everyone to theCUBE's live coverage of Nutanix .NEXT here in Anaheim, I'm your host Rebecca Knight, along with my co-host John Furrier, we are joined by Chris Kaddaras. He is the Senior Vice President Americas at Nutanix, thanks so much for coming on theCUBE. >> Well, thanks for having me. >> Rebecca: Returning to theCUBE I should say. >> Yes, good to be back. >> So you are relatively new to the Americas business. I wanna hear how you're adjusting and sort of observations that you've made about the enterprise customer and what's on their mind. >> Yeah, so it's an interesting journey 'cause I did spend the early part of my career in the Americas business with different companies so I started here in the Americas. You can tell by my accent, and I spent the last nine years in the AMEA business and getting reintroduced is really an interesting thing. Our customers have a much higher adoption rate of technology in the Americas than they do in some other parts of the world. So they're willing to take on new transformational technologies much earlier and deal with that risk seeing that they're gonna get those benefits so it's been a really exciting journey in the last month, month and a half to talk to customers who really embrace our technology because it's so transformational to what they've done in the past, and they're really seeing a lot of the benefits of that so it's been fun. >> What accounts for this difference in mindset, you say? >> You know, I think it has to do first off with in the Americas business, there's a lot of competition in the marketplace and when you get competition you get pressures that come with that competition. You have to evolve, you have to evolve how you deliver IT, how you deliver applications, and the business needs to evolve that supports that, so that pressure in the business environment creates a lot of new things and a lot of risk taking, a lot of transformation. A lot of things that have to happen for customers to deliver services to their end-user business sooner. >> That was a theme we were just talking about before you came on about your culture inside Nutanix and also your customer culture. They're risk takers, they're rebels. Like the Jedi Knight we saw on stage Mark Hamill. The Star Wars scene, which by the way was perfect. Great demographic to target there. Everyone loves Star Wars, in fact. But I gotta ask you, this show here is very intimate, not massive numbers. Not like the other big shows, your customers like coming here from what we've been hearing. You have a chance to sit down with them while they're here, what's the conversations that you're having with them? What's some of the new things that's emerging from their needs that you're hearing? >> Yeah, that's evolving, it's an interesting thing. I compare our customers to almost like a religious following, I know it's sometimes difficult to use religion in these conversations but it's really like that, these customers bought in, they're insurgents in what they're doing. They're really trying to evolve their organization because it's transformational, now what we're seeing at this show, because the numbers have gotten a lot bigger, last year we were like five thousand, the year before that we were another two thousand less than that so it's gotten a lot bigger, and our customers are coming back and saying we want you to be a bit more intimate, okay so we've had that in the past, we've had smaller teams, we've been really close to your engineering, we've been really close to you development roadmap. As you start to evolve into multiple products as you start to get bigger, you need to keep that intimacy with us, the customer because that's gonna give you the true north as to where you need to go, so we're getting that feedback, some of it's hard. Some of it's you're getting too big. You're getting too dispersed, you need to make sure you take care of us and what we need to do in our journey. But that's part of growing up as a company and that's the reason why we're here. To hear customer feedback. >> And you guys have that true north. Essentials, the enterprise opportunity. Multi-cloud right around the corner on top of your core business which is doing great by the way, got a great customer base. Getting beyond that core is critical. Building on that core, and this product risk potential, we talked with Sunil too, the next waves are coming so customers kind of want that assurance. So I gotta ask you, when you go out there and you're selling the customers and you tell them that Nutanix is the bridge to the future, what's the value proposition, I mean obviously we touched on the enablement side. Obviously consolidation's a side effect of the benefits of the technology you have. People love that, but what's the value proposition as the customers want the bridge to the future? Not just today's speeds and feeds and the greatest of today, what's the pitch with the enterprise and the multi-cloud? >> I think the biggest thing for our value proposition to a customer is to allow them to actually decide on a platform to build on. So instead of actually doing all the plumbing getting together and building these three tier architectures and figuring out how to build SaaS and compute farms and how they're gonna deal with multiple hypervisors, so let's get them out of that business, let's make it really simple. Develop a platform that they can launch off of. Now, that platform needs to think about new applications on those platforms so let's take it up a notch in regards to what we're looking at, let's forget about infrastructure, let's make it invisible as we've talked about in this conference. Let's look at how do we actually start to add services onto that platform that gives the customer choice, not locks the customer in. Which is the key thing that we have to do for our customers. Most of our competition today, it's a lock-in strategy, you pick the platform, you're locked in to the entire application set, locked in to the compute set, you're locked in to the storage set, you have no decision on hypervisor, and you don't have a lot of options around platforms and applications, so the good thing about Nutanix is we don't have the innovator's dilemma problem. We're not trying to protect a base. We're trying to help our customers and come from that optic of how do we allow our customers to have the most choice possible in building that platform for their new application so that's the discussion with our customers. It's invigorating for our customers. It's actually freeing for them to understand how we can do this versus what their options are in the marketplace today. >> So when they're at this conference and they're getting all this news about new products, lots of new announcements. How do you recommend that they wrap their brains around this and digest it and then execute on it? >> Yeah, it's hard, we're not doing a good job there today, just we're not. Now this is a journey of all of these companies like us, it's how do you go through that, I have the needle and going from a single product company to a multi-product platform company. Not many companies can do this. It's very difficult, so I understand what we're doing, what you do is come up with a lot of different products. A lot of different solutions for our customers and then you rationalize, right? We're right in the middle of that rationalization period where some products are features. We have to fold them together, right? Some products need to stand on their own. Some products need to be integrated into the core. All of those things are happening and the nice thing is you have to start with, let's just roll everything out. Let's get customers to tell us what we need to do, let's get our partners to inform us a little bit more. And then they'll educate us on the direction. It's not always our answer, right? When you're inside a company, if you think you have all the answers for the way the products need to be delivered, the way they need to be marketed to our customers, you're fooling yourself. So that's our direction today. >> Well Chris you guys have a good business to build on that's still relevant and cool for your customers and the enterprise which is great, you don't have to worry about product leadership. You got it there, as you guys, for you in particular and your customers you're also transitioning to software. You got the full stack, that's an advantage. You don't have to rely on other hypervisors, you mentioned that. We know who that is, Microsoft and VMware. Now you have a software business. So now the sales shifts to software which by the way is great from economics, the economics and valuations on software business are super high. >> Sure. >> So on the consumption side for customers this is gonna be something that you're gonna be involved in, you gotta bring Nutanix out to the field. You gotta roll it out for the customers. They're gonna consume Nutanix with software. How's that going, can you share some insight into the customer's orientation to the software model, what are some of the things that you're doing around kind of balancing that greatness of the leadership to the transitional software? >> That's a transition we started about a year ago, and some of the things that you may be bored with but we need to talk about is there's some real plumbing and structural work that we need to do internally so the first thing we did is we decided to make it pretty much open to our sales teams to be only compensated on software and they really don't have any discussion or care of what the underlying compute infrastructure needs to be so they need to be open to that. And that's one thing that's a little bit boring but once we actually did that, then the whole optics changed to how we actually go to market. So when we go to customers, we have discussions that are very open and when we're partnering in the marketplace with all of our OEM partners and all of our resale partners and all of our GSI partners it's a discussion around what's right for the customer here, what platform do you wanna consume, so that's the first move. The second thing is changing our licensing model to make it more inclusive for customers and what they want to achieve so moving our customers to a term based licensing model was really important. We've done that in the last year and then allowing our customers that consume very easily when you move to those terms so how do I consume a node of software? How does that work, how do I consume multiple products on top of that node? Let's make it simple, you know. Our previous go to market was relatively simple. It was just you buy X amount of Nutanix nodes. It came with hardware and software and customers really loved it. But as we transition to a software model it becomes a little more complex because you have multiple titles. Also, how do we allow our customers to do things like ELAs, what they may wanna consume have more agility around their software licensing mechanism. Get a lot more licenses up front. They don't have to buy every time. They can project what they're looking to do from a budget spend perspective and consume in a very frictionless way. So we're in the middle of really evolving our kind of enterprise type purchase agreement society, I wouldn't call it ELAs because ELAs in the marketplace have kind of got a bad name, right? There's a lot of things about that our other competitors do around true-ups that we don't plan on doing and we don't want to so we wanna work with our customers and partners as to how do you wanna buy those new enterprise price purchase agreements moving forward. >> I wanna ask you about Nutanix's brand awareness and brand identity because as you said earlier in this conversation you're hearing feedback from customers you're getting too big, and I think that so much of the beauty of the brand of Nutanix is this sort of renegade rebel kind of idea that this is who we are as a company. So when you hear that feedback you're getting too big, guys, you're becoming the man. How do you respond and what's the internal strategy there? >> Yeah, so the first response is I agree with them, right, because I see it as well, I've only been here for two and a half years and we're losing a little bit of connection. Now , I'm really comfortable to admit that. It's important that you actually admit that so that you can change, so the things that we're gonna do are a few things. We do have a customer advisory board that meets, right now it only meets once a year in certain markets and we need to actually increase the frequency of that, get more customer voices back into what we're doing, we got some really great feedback, constructive criticism from our customers this week, big customers that said you need to think about this and it was really refreshing to hear that. Sometimes difficult, we also have the voice of our customers which is our field organization, right, so our sales reps, our Ses, our services people, our customer success people, they're in front of customers every day. Out support people, providing that vehicle of feedback back through our executive teams, our engineering teams is really important, so we're formalizing that internally. We have some informal teams today but we're not getting the message through. They're not being heard well enough. Their voice isn't resounding as much as it should be. So we're gonna start to create and develop that within the company. >> So, growing pains, you have to fix those things. Software model, looking good, so things are clicking right now, net promoter score in the 90s which is pretty much unheard of. You have a great, loyal customer base. Good news there? >> Yeah, I mean great news, we're talking about first world problems here, right? We have a huge market, the market's growing at an incredible rate. It's all about how we take our fair share and more of that marketplace so these are the discussion that we're having. I'd rather be here than anywhere else in the world. Any other country >> Well, you're Chris, you're in sales, you're running all the fields. Sales and you guys got a humble culture with a heart, as Dheeraj talked about. You gotta be aggressive, you gotta be competitive, and you gotta go win those deals. You gotta win those competitive deals. This is a big opportunity for you guys. >> Yeah, and it's really from our perspective it's turned a bit into a two horse race at this point in time, we think we have the best choice solution for the marketplace for customers who want flexibility and choice. I can't imagine why you wouldn't at this point in time. Our competitors are strong, and they're good. They're good people, they work hard, they have great people and great technologies. Our entire value proposition around how to provide customers flexibility on what they're trying to achieve in their future and I think if we do that then we'll be in a good place. >> Well, my analysis on the opening yesterday was knowing, following you guys for 10 years knowing the competition, who could out-muscle you if you were head to head. You guys are faster and nimbler. You guys can be moving quicker, just be faster and innovate. >> Yeah, I think we're doing that on technology. We're doing that on our support structure with our NPS scores, we're clearly doing that on engineering new product. I mean coming out with an amazing product. Moving forward, I think we need to do a better job of how we align to our customers. As we've grown from a mid market company to an enterprise company to a global account company. These things come with complexities, right? You have to hire different people that have different skills, it's a scaling problem and those are things that we can easily do. I'm happy to do those and those are things that we are hiring new people that help us through that journey and it's really a fun thing to do and we're seeing a lot of positive results for our customers. >> Exciting times, well Chris Kaddaras thank you so much for coming back on theCUBE. >> Thanks for having me. >> I'm Rebecca Knight for John Furrier. You are watching theCUBE. (electronic music)

Published Date : May 9 2019

SUMMARY :

Brought to you by Nutanix. He is the Senior Vice President Americas Rebecca: Returning to theCUBE So you are relatively new to the Americas business. in the Americas business with different companies You have to evolve, you have to evolve You have a chance to sit down with them as to where you need to go, so we're of the benefits of the technology you have. to the storage set, you have no How do you recommend that they wrap their brains and the nice thing is you have to So now the sales shifts to software of the leadership to the transitional software? the things that you may be bored with So when you hear that feedback you're getting that said you need to think about this So, growing pains, you have to fix those things. We have a huge market, the market's Sales and you guys got a humble I can't imagine why you wouldn't at this point in time. Well, my analysis on the opening yesterday was and it's really a fun thing to do and we're thank you so much for coming back on theCUBE. You are watching theCUBE.

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Day 2 Show Analysis | Nutanix .NEXT Conference 2019


 

>> Announcer: Live from Anaheim, California. It's theCUBE, covering Nutanix.NEXT, 2019. Brought to you by Nutanix. >> Welcome back the theCUBE's live coverage of Nutanix.NEXT here in Anaheim California. I'm your host, Rebecca Knight. Along with my co-host John Furrier. Here we are, we're at day two, John, this conference, I gotta say it's pretty cool. 6500 people, we're steps away from Disneyland, and, you go to a lot of these things every year. I also do about a dozen or so for theCUBE. So in other words, we're veterans of this kind of thing. This does seem to have a different vibe and I think it really gets to the kind of company Nutanix is, and where it is in its journey. >> Nutanix is still a small company even though they're 10 years old, as Dheeraj talks about. The numbers aren't massive, I mean, we go to a lot of other shows where it's 15,000, Amazon Web Services just had an event in London, Dave Vellante was out there covering, Stu was covering Red Hat summit in Boston this week, tons of events going on. Amazon Web Services' summit in comparison was 12,500 people, 22,000 registered, that's a summit in London. It's not the re:Invent main conferences like 30,000 people. And that's always sold out, so they got a lot, in terms of attendees numbers they're still in the entry level, mid range growth. But I think that's okay, they like that culture and I think the story here at this show is intimacy, they would rather err on the side of better content and more intimate opportunities for their customers to really get the straight scoop. And I think it's less of a conference slash trade show, more of an intimate relationships where they can provide feedback, for customers to give feedback, and for Nutanix to figure out with the customers how to connect to them. So, I think the story here is, Nutanix is growing up as a company, they're 10 years old and they gotta go the next level and the management team has technical chops, and they have a long term view. They have that 20 mile stare, they can see out and they're trying to figure it out. I still think that the numbers are light on their forecast I still think that there's some sandbagging going on there, I'm not saying they're sandbagging, but I mean, I think, you look at Essentials, which is the enterprise and then multi-cloud, the numbers that we're seeing at Wikibon are much bigger, and Amazon reflects that. So I think they're being cautious but smart about how they execute off their success they've had in the first 10 years to go the next 10 to 20 years and I think that's clear in the management team, that they wanna build a durable company. >> Well exactly, and I think that that's what's really coming through, is that this is, as you said, they're growing up. This is a real coming of age moment for them, they've celebrated the 10 years. Okay, so what kind of company are we? Who do we want to be? And what's coming through is that from the technology side, they get it. They say, I'm sort of reminded of the Henry David Thoreau quote, our life is frittered away by detail, simplify simplify simplify, that's what customers want. They want this one click data recovery, they want their credentials to be assumed. You know who I am, I'm safe to be in here. Fixing things, dealing with that. So I think that they get that, that simplicity is key. They also get customer service. I mean their Net Promoter scores, as we've noted, are in the 90s, that's just unheard of. >> It's monster, monster numbers. >> It really is and so they get it. We need to be responsive to customers, we need to have a personal relationship with these, because it's not just organizations, it's people at the other end of these transactions. >> I mean, I think Nutanix, one of the stories that's popping out in the hallways as I walk around and talk to customers and people and the company and partners, is that Nutanix has a lot of headroom in their growth. I think Wall Street is interesting and you heard Dheeraj talk about that yesterday, about having a new customer, you asked him about his management style and he said quote, I have a new customer called Wall Street. And I have to balance that against mainstream enterprise which is his core business. And so he as a CEO and the company are dealing with this new stakeholder called public company customer retail stock buyers. That's a short term cycle and I think, if you look at their stock, they had a big knife edge drop in the past quarter. And I think the shorts are circling, it's a whole nother dynamic, it's a whole nother theater for Nutanix to deal with, and I think that's something that they gotta get used to. And he was clear, he said I'm addressing it, we're gonna balance it, but they gotta be thinking long term because this company has a lot more to do and their customer base are risk takers. Because everyone we talk to has this different style or persona. They're smart, they're usually engineering oriented, they love engineered solutions. And they're taking chances. And everyone who's taken the chance with Nutanix, has paid off. That seems to be the theme. And as we were talking before we came on camera, Mark Hamill, Jedi knight, you know, Star Wars, was on stage giving the keynote, their customer base, is a lot like the Jedi order, right? I mean they see themselves as, elite, technically, they're not afraid to take organizational risks and push that DevOps culture. And we heard that from Sunil, the chief product officer that they're really looking at, this new way to do things, like they did with hyperconvergence, they pioneered that, set the table on that and foundationally built that. They wanna take that same playbook of HCI, hyperconverged infrastructure, and apply it to the cloud. And provide an abstraction layer advantage and I think that is clearly their strategy and that's, to me, the top story here. >> I couldn't agree more and I also think that, what is also coming through is this idea of we don't wanna be safe. What's clear is that, consumer technologies have leapfrogged IT enterprise vendors. The things that we hold in our pockets are so much more sophisticated than what businesses and organizations, multi-billion dollar businesses and organizations, are using, what their employees are using on a day to day basis. So we expect a certain kind of design and ease of use, in our personal lives and they're bringing it to enterprises and think that that is really what's exciting and interesting about this company. >> What's interesting about their story is that, the consistent theme about the customers is that it's kind of a consolidation story but that's not the real story because back in the old days of IT, consolidation was the strategy. Consolidate vendors, consolidate footprint to reduce cost, clearly a cost reduction. With Nutanix what they get is they get consolidation, and they enable advantages so the real value of Nutanix is to be positioned for those new kinds of app developers, so. This is like, you get consolidation as a side benefit for enabling the value, and that's the theme that's coming out of all the customer testimonials and interviews is, we gotta do more, we gotta create more enablement for the app developers and we gotta provide more performant storage servers and software for the customers. And that's their main focus and they consolidation as a benefit. That's gonna scare a lot of people and customers that I've talked to said, hey I got all the stuff but I can't just throw it away tomorrow, I gotta move it out over time, so, this is the Nutanix sales challenge, how do you move faster with all that incumbent, legacy stuff in these datacenters, while enabling the multi-cloud capability? >> And we're gonna be talking about that more today with Chris Kaddaras on the show. We have a lot of great guests, we have the CIO, Wendy Pfeiffer, I was reading an article about her today, she answered an ad as a teenager to work for NASA. She had an idea for NASA and so we're gonna hear much more about her story, we've got a lot of great guests. >> Well what's your take? I mean, you've been here, you're getting immersed in. What's your take of the show, what's your analysis? >> Well, what's really interesting to me is that we're having this conversation against this backdrop where, the technology industry is really under fire. I mean, we heard Ayanna Howard here on the show yesterday and then she was up on the main stage today, talking about the good, the bad, and then the really scary elements of AI and how it really has these powers that can do a lot of wonderful things and help children with special needs and help workers be more productive and engaged and collaborate. But yet, there's also this much darker side that AI's really only as good as its creators. And then the other difficulty is that, because we have become so trusting of these machines, we disregard our own intuition. And that is a really scary element, so. What I think is exciting, and it goes back to this risk taking mentality, that Nutanix has, is, we're gonna talk about these things. We're just going to forget about them or they're gonna be a sideshow, this is really on the main stage, let's talk about our values, let's talk about the humanity of technology and this is really an important part of the conversation. >> It's interesting, the culture, we talked about the culture a lot yesterday. And you can see from the mix of the guests we've had here and how they're putting their content together across the show portfolio, it's not just speeds and feeds. There's a lot of tech for good angle but they're not tech for good stories like hey, look, here's a tech for good story. Look how good we are because we promote it. They're authentic people that have a great story that has a tech involvement. But it's not a pure Nutanix messaging kind of thing. >> Right, and it goes to back to their values, the humble, hungry, honest, and have a lot of heart. I mean I think that that is, you really see how important culture is, when it is top down. When Dheeraj embodies certain characteristics and traits, you see that employees then look up and they say okay, this is what we're about, this is who we are. >> You know, we also talked yesterday about our analysis in the keynote, what's interesting about culture is, there's also a culture shift going on inside their customer base. And again, it's back to this kind of Star Wars theme, Jedi knights and the revolution continuing for Nutanix, their opportunity is to continue to stay on the course, and this is gonna be a big bet for them, they gotta make some big bets on the technology side, which they're making, but also they have an opportunity because a lot of their installed base are rebels, right? So you have this rebellion IT guy, generational shift where you have DevOps coming in and Gene Kim who wrote the book on DevOps, runs the biggest DevOps event in the world, series of events, DevOps Enterprise Summit, he's even saying it's about 3% changeover. So I think there's a big tailwind coming for Nutanix. Around DevOps, operating models, in the enterprise and cloud where, the convergence of those two worlds coming together, and it's gonna be a younger generation, it's gonna be a different world. If that happens, I think that's gonna be something that Wall Street might not see. I think that's kind of an area. And that's gonna be a good tailwind for Nutanix. The other notable thing that I would point out from this show is, the presence of VMware visibly in the conversation. And I think Dheeraj was talking about, hey we don't mind talking about VMware because they validate the marketplace, they're the big 800 pound gorilla. And we're gonna continue to innovate around them. We don't need their Hypervisor, customers don't need to pay their vTax, that's his messaging, so that was a key notable. The other one was the challenge that Nutanix has, this is, again, might be a Wall Street insight for some of the Wall Street folks out there is that, their challenge has been getting new logos. Their cost to sales is a little bit high because they require POCs and once they get in there they usually win. And then their cost per sales, cost per order dollar on the sales side once they have a customer, is very low, they get more renewals and they have more net contract value so they have great customer economics on that side. The Hewlett Packard Enterprise deal for them, could bring them a tsunami of new logos. That could give them a lot of leverage and bring their customer base well above their 12,000 number now. And bring them up into a whole nother level. So I think the HPE deal will be a tell sign on the numbers, and if they can get more new logos in there, the big accounts that HP has through their channel, that's a big story. So VMware, HPE, culture, all the main story here. >> And of course we had HPE on the show yesterday, talking about that very development, so. We have lots more great content, great guests to come today, this has been just a ball hosting with you, so I'm really for another day. >> Very intimate show, I mean, Nutanix are a very intimate show they don't really care about the big numbers, they want the right numbers and that speaks to their culture. >> And they know their people. Because as we talked about many times, Mark Hamill, up on the stage yesterday, so, they know their community. Please stay tuned for more of the coverage from theCUBE of .NEXT here in Anaheim. I'm Rebecca Knight for John Furrier, stay tuned. (electronic music)

Published Date : May 9 2019

SUMMARY :

Brought to you by Nutanix. and I think it really gets to and I think the story here at this show is intimacy, from the technology side, they get it. it's people at the other end of these transactions. and people and the company and partners, and they're bringing it to enterprises and customers that I've talked to said, And we're gonna be talking about that more today I mean, you've been here, you're getting immersed in. and it goes back to this risk taking mentality, and how they're putting their content together and they say okay, this is what we're about, and if they can get more new logos in there, And of course we had HPE on the show yesterday, and that speaks to their culture. And they know their people.

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Allison Dew, Dell Technologies | Dell Technologies World 2019


 

>> Live from Las Vegas it's theCUBE, covering Dell Technologies World 2019 brought to you by Dell Technologies and its ecosystem partners. >> Okay welcome back everyone we are here live in Las Vegas with Dell Technology World 2019 and I'm John Furrier and my co-host Dave Vellante breaking down all the action, three days of wall-to-wall coverage. We go all day, all night here at Dell's great event. We're here with the CMO of Dell Technology Allison Dew, great to see you, thanks for coming on. >> My pleasure, it's nice to be here. >> Good to see you again, Allison. >> It's fun. >> What a show, action-packed as always. We got two sets, we call it the theCUBE content cannons. We're just firing off content, a lot of conversations, a lot of boxes being checked, but also growth, lookin' at the numbers. The business performance of Dell is strong. Leadership across all categories, large-scale, and an integrated approach with the products and the relationship with VMware paying off in big-time. Azure News, Microsoft integrating in, so a lot of great product leadership, business results, things are booming at Dell Technologies. >> They really are and you know, when you think about the journey for us in particular over the last three years since starting the EMC combination, and all of the things that are written about integrations, technology integrations of this scale and scope, and you look at what the teams together have successfully done, the business performance, the share growth across categories, and as of today, the true end-to-end solutions that we're announcing in partnership with VMware and Secureworks. And we tend to be a pretty humble culture, but I will say, I think it's a pretty impressive result, when you look at most integrations are focused on don't break anything, and not only did we not break anything, we've kept the trust of our customers, we've continued to grow the customer base, and now we're really focused on, how across the Dell Technologies family, primarily with VMware and Secureworks and Pivotal do we bring to life the solutions that solve our customers' biggest IT problems. Pretty amazing spot to be in. >> You know one of the luxuries of doing theCUBE for 10 years is that we've had conversations over 10 years and I remember many years ago when Michael was about to go private, we saw him in Austin, was a small Dell world back then, we had two conferences, and he was standing there alone. We approached him, Dave and I, and we had a long conversation with him, he was very approachable, and then when he talked about, when he did the private and then the acquisition at these points, everyone was pooh-poohing it at saying, it's a declining market, things are going, why would you want to do this? Obviously the scale benefits are showing, but the macroeconomic conditions of the marketplace, you couldn't be happier for. Public cloud drove a lot of application deployment, you have SAS businesses started, you have on-premise booming, refresh and infrastructure, a complete growth. >> Right. >> Yeah, there's actual growth there. >> Right. >> So the bet paid off. You as a marketer have to market this now, so what's your strategy because you have digital transformation as the kind of standard positioning posture, but as you have to market Dell Technology on the portfolio of capabilities, which is large, I can only imagine it's challenging. >> So let me actually back up, and to one of the points that you talked about, and then I'll answer your actual question. So I can't remember off the top of my head, but we very jokingly talk about, in the era since the PC was declared dead, we have sold billions of PCs right and it would be funnier if I could remember the number, but you know we used to joke around with Jeff Clark, ala Monty Python, I'm not dead yet. >> Yeah. >> And so you get this hype about what's happening in the industry, and the truth is it's actually a very different picture than some of that hype, and one of the reasons I think that's important is because obviously we've continued to take share on the PC business, we've continued to grow there, but we also believe that the hype sometimes applies to these other technology cycles as well. So if you go back a couple of years ago, it was everything was going to the public cloud. If you don't go to the public cloud you are a dinosaur. You don't know what you're doing. You're going to go out of business. The traditional infrastructure companies are going to go out of the business, and to be honest, that is also just nonsense, right. And so if you think about what's evolving, is we believe very firmly that we're going to see the continued growth of a hybrid cloud, multi-cloud world and it's not one thing or the other. And in fact, when you look at all of the research around the economics of doing one or the other, it all becomes workload-dependent. So for some workloads you should go to the public cloud. For some workloads, you should have it on-prem and that conversation may not be as interesting a headline, but it's the truth. >> It's reality actually. >> It's the truth. >> Well it's also reality, the workloads are dictating what the architecture should be or the solutions. That's what you're saying is a reality. >> Exactly, and so that's why we're so excited about the announcements that we had this morning with VMware, with Microsoft. We're really talking about a multi-cloud, hybrid cloud world, and across all of the solutions that we announced this morning. The key, continuity and what we're really focused on, sounds so hackneyed, is how do we make it simpler for our customers? How do you make it simpler to manage and deploy PCs? How do you make it simpler to manage and deploy your cloud environment, that's it. >> So let's talk about the show a little bit, let's see 15,000 attendees, 122 countries represented, 4,000 channel partners, 250 industry analysts and media folks, so pretty big numbers. You could see it in the hallways. It's not quiet. You're kind of doing a lot of this. >> It's actually sort of hard to pay attention to you guys with all the noise in the background. You must be used to it. I'm like a goldfish, like what's happening? >> Now the interesting thing to me is, and we were talking about you know, it's the transitions, consolidations, oh it's traditional infrastructure companies are dead, et cetera, et cetera. I'd observe that over the years the testament of today's leaders is they respond, they don't just sit back and say oh Unix is snake-oil. Do you remember that famous quote? Look at what Microsoft has done, but my point is Michael's keynote today, it wasn't about a bunch of products, it was about big visions, solving a lot of the world's problems, and really conveying that Dell is in a position to help these companies as a partner. I presume you had some input to that keynote, I just wonder. >> I hope so. (laughs) >> What the thinking was there? >> So there's a lot of conversation and it's, you don't have to go that far in the media to read everything about technology as a force of evil in the world. One of the things that you notice, Michael's keynote this morning and I'll come back to what we're doing about it again later this week, is we are putting a very firm stake in the ground that we believe that technology is overall a force for positive change in the world and we're having a conversation about that on Wednesday that I'll talk a little bit more about in a second. And there's a subtlety there, that I think sometimes again, may not be the most interesting headline but is true, which is technology in aggregate drives great progress in the world, however we as leaders, we as humans, also have a responsibility to drive the responsible use of technology and so you see some of the conversations that we're having later this week in the Guru sessions, for example, where Joy Bilal-Meany is talking about responsible use of AI and some of the inherent biases in AI. Those are the tough issues that leaders need to be tackling now. >> Yeah well and one of the other you know, you're right a trade press loves to pick up on it and pick at it but one of the things to talk about, of course, is jobs, automation affecting jobs, I know Erik Brynjolfsson is one of your speakers, he's been on theCUBE before, and the discussion we had was machines have always replaced humans. For the first time ever,now they're replacing humans in cognitive functions. So the the answer is not protect the past from the future it's educate people, find new ways to be creative. I mean, technology has always been-- >> That's right. >> Part of human good and human advancement. There's always a two-sided coin, but it's got to be managed. >> That's right, one of the conversations that I think gets lost is when we talk about, I am a Battlestar Galactica fan, the second one not the one from the 70s, so you know I always say jokingly-- >> Darn. >> Yeah, yeah. >> We're a little older. >> Did you watch the one from the 2,000s? >> Yes, of course. >> 2,000s are so good. You know the conversation about are the Cylons coming to get us? And is AI really the thing that's destroying what's happening for human populations? The reality is AI has been evolving for many years, so it's not actually new. What is new is the combination of AI and data and the compute power to make that real and I do think it requires a different conversation with societies, with employers about how do you continue to reeducate your employee base? What does that mean? And that is really meaty stuff that we need to be leaning into. On aside, you've got me thinking of this whole Battlestar Galactica. My mind's thinking Star Trek, Star Wars. I heard a rumor that you guys had so many unhappy employees because Game of Thrones was on yesterday. >> Yeah. >> That you actually rented a big screen? >> Yeah, we did. >> A lot of Game of Thrones fans? Are you in that mix? >> So yeah. >> No spoiler alerts. >> No, I won't say anything about what happened. But I'll tell you, so we have all of our employees who work at the show, have to get here on Saturday or Sunday at the very latest. And even me personally, we came to Las Vegas and I thought, well I can watch it in my hotel room and then my hotel room didn't have HBO and I thought I don't really want to watch it on my little HBO Go app that's about this big because we're all waiting for what's going to happen in episode three, and I won't tell you if you haven't seen it. >> It's a lot of battling. >> So exactly, so my team and I had this conversation about could we have a joint viewing of Game of Thrones and it's really my team who did all of the work, but it was super-fun and we had a party with a bunch of team, had a few beers and it was fun. >> That's a great culture. >> I just wanted to get that out there. I think, cool culture. Allison, you mentioned something about the press and stories for good and how people looking for headlines. You know we're not advertising, so we're not trying to chase the clickbait, it's about getting the story right and sometimes the boring story doesn't get the headlines. Or the page views, advertising. So we're in a world now where a lot of other people in the media, they're censoring posts, there was an incident on Forbes where I wrote a negative post about a company and they took it down, that was Oracle. A lot of journalists looking for stories just to put tech in a bad spot. >> Right. >> And there's a lot of tech for good, but a lot of people can't point to one thing saying that's an example for tech for good and there's some few out there missing children, exploited children, trafficking, all kinds of things, talk about that dynamic because this is changing how you market, how people consume. You have the role of open communities. >> Yep. >> Social networking. A lot of dynamics going on. How do you view all this? >> So first of all, I think so much of the conversation about tech for good or tech for bad actually indexes only on social media and media broadly, and perhaps that's because it's the media who are writing about that. And so there's sort of this loop that we get in and I do think there are real issues that we need to think about in terms of social media. You guys likely saw Kara Swisher had a an op-ed in the New York Times after the Sri Lankan bombings where she, long-term technology advocate, actually said after the Sri Lankan bombings when the government shut down all social media communications, I thought that was a good thing and so that probably actually did help with the immediate situation on the ground and yet is a very scary precedent, right? I'd like to to take the conversation and say what about media? Right, so there's a lot of work that we need to do in order to maintain media fairness and then there's a whole other conversation about technology that we're not talking about. Everything that we're doing in terms of medicine and indexing the human genome, and addressing deafness and Michael talked about that even this morning, there are these really big technology problems that were really leaning into, and yet we're either talking about Amazon drone delivery or what Facebook is doing. We need to talk about those, but let's talk about where technology is really struggling to address real problems. >> I just read an essay yesterday from Dana Boyd who wrote a great fascinating piece around extremism in social media. Media's being hijacked by these extreme groups and they're mixing up causation and correlation and conflating many things to just tell a story to support an initiatives, no curation. >> Right. >> And with social media everything's open so that just flies out there. And so that's a big problem. >> And then takes off, you know. >> So how do you deal with that as a CMO 'cause you're spending advertising dollars. You're trying to deploy capital. You now have a new open source kind of mindset around communities customers are shopping themselves now. >> Right, so this is going to sound possibly a little bit overly simplistic but what I am responsible for in my job is the reputation and brand of this company right. I think about other things in terms of how we think about media and everything but I want to make sure that we are spending our media dollars in a responsible way and yet also recognize that people can disagree with us and that's okay and be comfortable with, we can be both a media advertiser on a publication who might write a review where they don't like one of our products and I'm never going to be in the business of saying take down our media dollars because that sets a terrible precedent and frankly there are people who would say take down our media dollars so that's one thing that we're really focused on. And then the other is, we consistently year-over-year are recognized as one of the world's most ethical companies and I will tell you from the leadership with Michael across the board I believe that that is true. And we actually think about business in an ethical way and we behave in an ethical way and that's why frankly you're not reading those headlines about us which are a lot more problematic. >> It's a cultural thing you guys have. Michael's always been a direct-to-consumer. That's been a direct mail, back in the glory days, now-- >> We still do that actually. >> Cloud, SAS, he texts me all the time. Hey John, what's going on? So he's he's open. >> Yeah. >> He's also now with Cloud and SAS, it's a direct to consumer business. >> I love your positive attitude. You have a session tomorrow, Optimism and Happiness in the Digital Age, looking forward to that. I have a personal question. So you started out your career, I think, in East Asia studies, right? >> That's right, good memory. >> You speak multiple languages. >> Yeah. >> I think three languages? >> If you count English, three. >> Yes okay so you're trilingual. >> Trilingual, yeah. >> If you speak two, you're what? >> Bilingual. >> Speak one, you're what? >> Monolingual, American. (all laughing) American, I was like, I know this joke. >> I wonder how that affected sort of your career? >> Absolutely. >> In terms of getting into this business. >> I would first say that I was an incredibly naive undergraduate. I wanted to be an editor of a paper and I loved foreign languages. So I studied Japanese and French and that led me to going to Japan as a very naive 22 year old and I started working in this small Japanese ad agency. I was the only non-Japanese person in that company and of course I learned some functional things in terms of the art of advertising but what I actually learned was how to survive in an environment that was so different to mine. Even if you speak Japanese, it is a language of unsaid things and you have to constantly be figuring out what's actually happening here and so ironically that decision that I made at 18, very naively, to study Japanese is one of the things that sets the course of my life because I've always been, my entire career, in international jobs and I think if I ever had to come back to just being in an American job, I wouldn't know what to do with myself, I'd be so bored. And it's also one of the reasons when we talk about technology and education and AI and what are robots going to do, This is my personal opinion, somewhat controversial opinion which is of course we need to support STEM, of course I want to see more women in STEM. At the same time, I want to see us focus our children on critical thinking skills. How do you write well? How do you have an argument? How do you convince somebody? And that's because until I went to business school I was a liberal arts major born and bred and so that's not the pat answer that you expect from somebody in my job which is it's all about STEM. It's about STEM and more. >> Emotional quotient's a big thing we're seeing a lot. The whole self. That's a big part of the kids growing up being aware. >> Yeah. >> Socially emotional. Allison, thanks coming on theCUBE and sharing. >> My pleasure. >> Great insights here in theCUBE. We're here with the CMO, Allison Dew, with Dell Technologies. I'm John Furrier, Dave Vellante. Stay with us for more day one coverage after this short break. >> Awesome. (upbeat electronic music)

Published Date : Apr 29 2019

SUMMARY :

brought to you by Dell Technologies breaking down all the action, and the relationship with VMware paying off in big-time. and all of the things that are written You know one of the luxuries of doing theCUBE for 10 years So the bet paid off. and to one of the points that you talked about, than some of that hype, and one of the reasons I think the workloads are dictating about the announcements that we had this morning So let's talk about the show a little bit, to you guys with all the noise in the background. and we were talking about you know, I hope so. One of the things that you notice, and pick at it but one of the things to talk about, Part of human good and human advancement. and data and the compute power to make that real and I won't tell you if you haven't seen it. but it was super-fun and we had a party and sometimes the boring story doesn't get the headlines. but a lot of people can't point to one thing saying How do you view all this? and perhaps that's because it's the media and conflating many things so that just flies out there. So how do you deal with that as a CMO and I will tell you from the leadership with Michael That's been a direct mail, back in the glory days, now-- Cloud, SAS, he texts me all the time. it's a direct to consumer business. in the Digital Age, looking forward to that. American, I was like, I know this joke. and so that's not the pat answer that you expect That's a big part of the kids growing up being aware. Allison, thanks coming on theCUBE and sharing. We're here with the CMO, Allison Dew,

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Zongjie Diao & Mike Bundy | Cisco Live EU 2019


 

>> Live from Barcelona, Spain. It's the cue covering Sisqo. Live Europe, Brought to you by Cisco and its ecosystem partners. >> Come back. Everyone live here in Barcelona is the key. Exclusive coverage of Sisqo Live twenty nineteen. John for David Want my co host for the week, and Stupid Man was also here, doing interviews. Our next two guests is Mike Bundy, senior director of Global Cisco Lines with pure storage and Z, who's in charge of Christ Francisco. Welcome to the Cube. Thanks for joining >> us. Thank you for having us here. >> Also one, but we're in the definite zone. It's packed with people learning really use cases. Get rolling up the sleeves. Talk about the Cisco pure relationship. How do you guys fit into all this? What's the alliance? >> You understand? >> Sure. So we have a partnership with Cisco, primarily around a solution called flashback in the Converse infrastructure space. And most recently, we've evolved a new use case, an application together for our official intelligence that Z's business unit have just released a new platform that works with Cisco and in video to accomplish. You know, customer application needs mainly in machine learning, but but all aspects of our official intel it >> Hey, Eyes, obviously hot trend in machine learning. But today it's Cisco. The big story was, it's not about the data center as much anymore is. It's the data at the center of the value proposition, which spans the on premises I ot edge and multiple clouds. So data now is every where you gonna store it? So it's going to start in. The cloud is on premises. Data at the center means a lot of things you can programme with its gotta be addressable and has be smart and aware and take advantage of networking. So, with all that is a background backdrop, what is the A I approach? How should people think about a I in context to storing data using data, not just moving package from point A to point B? But you're storing it? You're pulling it out. You're in agreeing into apple cases. A lot of moving parts there. What's that? >> Yeah, you got a really good point here. When people think about machine learning traditional age, they just think about training. But we look at this more than Chinese. The whole did a pipeline that starts with collecting the data stored the data, analyze the data between the data and didn't deploy it and then for the data back. So it's really a vory. It's a cycle there, right? It's it's where you need to consider >> how you actually collect the data from the edge, how you store them in the speed that you can and give the data to the training side. So I believe way work was pure. We try to create this as a whole data pipeline and thinking about entire data movement and the star, which need that would look here. >> So we're in the definite zone, and I'm looking at the machine learning with Python ML library >> center >> Flow of Apache sparked a >> lot of this data >> science type stuff, but increasingly a ISA workload that's going mainstream. But what The trends that you guys are seeing in terms of, you know, traditional, I tease involvement is >> it's still sort of >> a I often an island. What are you seeing there? So I'll take a take a gas stab at it. So, really, every major company industry that we work with have you know, Aye, aye. Initiatives. It's the core of the future for their business. So, no, what we're trying to do is partner with I t to get ahead of the large infrastructure demands that will come from those smaller, innovative projects that Aeryn pilot mode so that they are a partner to the business and the data scientist, rather than, you know, a laggard in the business. The way that you know, sometimes there the reputation that that I guess we want to be the infrastructure solid, you know, like a cloud like experience for the data scientists. So they can worry more about the applications, the data, what it means the business and less about the infrastructure. Okay. And so you guys are trying to simplify that >> infrastructure, whether it's converged infrastructure. No other sort of unifying approaches is Are you seeing the shift of a sort of that heavy lifting of people out now? Shifting resource is, too. You work loads like a I Maybe you could discuss trends, are there? >> Yeah, absolutely. So I think I started was more like a data signs experiment. Right? You see, want to date, assigns a couple of data science experiment. Now it's really getting into ministry. More and more people report into that and us. Apologize. Mike, Mike, The way we start that questions my deep apology. I need a GP or something. >> Like, I need to >> store the data better. >> Your fortnight? Yes. >> So as Micah's had early on, right? It's it's not just the data scientist is actually all a challenge as well. And I think was Cisco, where twenty do was pure. Here is, you know, that Cisco thing. We're saying we're breach right. We want to bridge the gap between the data scientists and the it and make it not just as experiments, but a scale at production level and be wedded to actually, Crew will impact with the technology infrastructure that we can table >> might talk about yours position You guys have announced here in the cloud. Yes, he's seeing that software. Focus software is the key here. Or you can get to a software model. Aye, aye. And she learned Only we're talking about is software data is now available to be addressed and managing that software. Lifecycle. How is this Corolla software for you guys? With converge infrastructure at the San Francisco announce your downstage day, we'll converge infrastructure to the edge. >> Yeah, so if you look at the plant, one that we built, that's it's referenced by being called the data hub. The data hub has a very tight synergy, with all the applications referring to spark tenser PLO, etcetera, etcetera cafe. So we look it as the next generation analytics, and the platform has a super layer on top of all those applications because that that's going to really make the integration possible for the data scientists. They could go quicker and faster. What we're trying to do underneath that is used the data hub that no matter what the size, whether it's small data, large data transaction based or more bulk data warehouse type applications, you know the data hub in the flash blade solution or need handle all of that very, very different and probably more optimizing and easier than traditional legacy infrastructures, even tradition, even even even flash, you know, from some of our competitors. Because, you know, we've built this a purpose built application for that, you know, not trying to go backwards in terms of technology, >> I want to put both you guys on the spot for a question. We hear infrastructure is code for going on many, many years since the few started at nine years ago. Infrastructures code. Now it's here. The network's programmable infrastructures, programmable storages, programmable What a customer! Or someone asked you. How is infrastructure Network's in storage, Programmable. And what do I do? I'm used to provisional storage. I've got servers. I'm going cloud. What do I do? How do I become? A. I enabled that I could program the infrastructure. How do you guys answer that question? >> So a lot of that comes to the infrastructure management layer, right? How do you actually using policy and using the white infrastructure managing to make the right configuration want? And I think one thing from program eligibility is also flexibility. Instead of having just a fixed conflagration. What we're doing with pure here is really having that flexibility right where you can put pure Star Ridge different kind of star, which was different, kind off. Compute that you have. No matter. It's we're talking about two are used for you. That kind of computing power is different and connects with a different Star wars, depending on what the customer use cases. So that flexibility driven by the driven to the proper program ability that is managed by the infrastructure. Imagine a layer, and we're extending that So pure and Cisco's infrastructure management actually tying together it's really single pane of glass was in decide that we can actually manage both pure and Cisco. That's the program ability that we're talking >> about. Get pure storage and to end manageability. >> Where's the Cisco compute its A single pane of glass. >> So what do I buy? I want to get started. What? What do you got for me? What you have, it's pretty simple. Three basic components, you know, Cisco Compute and a platform for machine learning that's powered by and video GP. Use Cisco Flash Blade, which is the data hub and storage component and then network connectivity from the number one network provider in the world. Francisco. Very simple. It's askew. It's a solution. It's very, very skewed. It's very simple. It's data driven, so you know it's not tied to a specific skew. It's more flexible than that. So you have a better optimization of the network. You know you don't buy a one thousand Siri's ex. Okay, Only used fifty percent of it. It's very customized. Okay, so I can customize it for my whatever data science team or my workloads and provisioning for multipurpose. Same way of service provider would ifyou're a large organization >> trend trend around Breaking Silas has been being discussed heavily. Talk about multiple clouds on premise and cloud and edge all coming together. How should companies think about their data architecture on? Because Silas Air good for certain things to make multi cloud work and all this and to end and intent based networking and all the power of a eyes around the corner. You gotta have the date out there, right? It's gotta be horizontally scaleable of you. How do you break down those silos? Twitter advises air use cases or anarchic for architecture. >> You know what I think? It's a classic example of how it has evolved to not think just silos and be multi cloud. So you know, we've advocate is is you have a date, a platform that transpires the entire community, whether its development, test engineering production applications and that, you know, runs holistically across the entire organization that would include on from it would include integration with the cloud. Because most you know cos now require, That s so you could have different levels of high availability or lower cost if your data needs to be archived. So it's really, you know, building and thinking about The data is on platform across the across the company and not just you know, silos for >> replication never goes away. Never. It's gonna be around for a long, long time. >> Deaf tests never goes away. Yeah, >> you thought some >> s o i. D On top of that, We believe where you infrastructure should go is where the data goes, right? You want to follow that where the data is, And that's exactly why I want a partner was pure here because we see a lot of the data sitting today in the very important infrastructure which is built by pure storage and want to make sure that we're not just building a sidle box sitting there where you have for the data in there all the time, but actually connected our chips. Silver was pure storage in the most manageable way. And it's the same kind of manager layer you're not thinking about All have to manage all the Sala box or the shadow it that some day that time would have under their desks. Right. That's the least thing you want it. >> And the other thing that came up in the Kino today, which we've been seeing on the Cuban, all the experts reaffirm, is moving data cost money got late in sea. Costs also just cost to move traffic around, so moving compute to the edge of moving. Compute to the data has been a big hot trend. How is the computer equation changed? I got storage. I'm moving. I'm not just moving packets around. I'm storing it and moving it around. How does that changed the computers? It put more emphasis on the computer. >> Wait, It's definitely putting a lot more emphasis on computer. I think it's where you want to compute to happen, right? You can pull all the data and I want it happen in the centre place. That's fine if that's the way you want to manage it. If you have, if you have already simplify the data, you want to put it in that way. If you want to do it at the edge near where the data sources, you can also do the cleaning there. So we want to make sure that no matter how you want to manage it. We have the portfolio that can actually help you to manage. And >> his alternative alternate processors mentioned video first. Yeah, you would deal with them in other ways to you've got to take advantage of technologies like uber, Nettie says. Example. So you can move the containers where they need to be and have policy managers for the computer requirements. And also, you know, storage so you don't have contention or data and integrity issues. So embracing those technologies and a multi cloud world, it's very, very >> like. I want to ask you a question around customer trends. What are you seeing as a pattern from a customer standpoint as they prepare for a I and start re factory? Some of their end or resource is. Is there a certain use case that they set up with pure in terms of how they set up their storage? Is it different by customers? Are a common trend that you see >> there are some commonalities, you know, like take financial services want trading as an example. We have a number of customers that leverage our platform for that. Is this very you know, time sensitive, high availability data? So really, I think the customers the trend over all of that would be a step back. Take a look at your data and focus on how can I correlate, Organize that and really get it ready so that whatever platform used from a story standpoint, you're you're thinking about all aspects of data and get it in a format in a forum where you can manage and catalog, because that's kind of the sentence. >> I mean, it really highlights all the key things that would say it in storage for a long time. I availability integrity of the data. And now you got at patient developers programming with data. This's a hole with a P IIs. Now you're slinging FBI's around like it's Tom mentioned me its weight should be. This is like Nirvana finally got here. How far along are we in the progress? How far we earlier we moving the needle? Where the >> customers himself a partnership partnership. Deanna >> and General, You guys were going to say, You got you got storage, You got networking and compute all kind of working together. That's reflex school elastic like the cloud >> I my feeling, mike, contract me or you can disagree with me. I think right now, if we look at all the wood analysts saying what we're saying, I think most of the companies more than fifty percent of companies either have deployed a Emma or are considering implant off deploying that right. But having said that, we do see that we're seeing at a relatively early stage because the challenges off making a deployment at scale where data scientist and I'd really working together, right? You need that level of security in that level, off skill ofthe infrastructure and software involving Devon I. So my feeling is where stew At a relatively early stage, >> I think we are in the early adopter face. You know, we've had customers for last two years. They've really been driving this way, worked with about seven of the automated car, you know, driving Cos. But, you know, if you look at the data from Morgan Stanley and other analysts, is about a thirteen billion dollars infrastructure that's required for a eye over the next three years from twenty, nineteen, twenty, twenty one. So you know, that is probably six x seven x what it is today, so we haven't quite hit that. >> So people are doing their homework right now. You are the leader. >> Its leaders in the industry, not mastering everybody else is going to close that gap. So that's where you guys come into helping that scale way built this. This platform with Cisco on is really flashback for a I is around scale for, you know, tens and twenties of petabytes of data that will be required for >> these targeted solution for a I with all the integration pieces Francisco built in. Yes. Great. We'll keep track of a look sighting. We think it's cliche to say future proof, but this, in this case, literally is preparing for the future. The bridge? >> Yes. Future. Yes. You >> know, as the news is good, it's acute coverage. He live in Barcelona with more live coverage after this short break. Thanks for watching. I'm John Barrier, but David won't they stay with us. >> Thank you.

Published Date : Jan 29 2019

SUMMARY :

Live Europe, Brought to you by Cisco and its ecosystem partners. John for David Want my co host for the week, and Stupid Man was also here, How do you guys fit into all this? flashback in the Converse infrastructure space. Data at the center means a lot of things you can programme with its gotta be It's it's where you need to consider how you actually collect the data from the edge, how you store them in the speed that you can and give But what The trends that you guys are seeing in terms of, you know, traditional, I tease involvement is a partner to the business and the data scientist, rather than, you know, a laggard in the business. is Are you seeing the shift of a sort of that heavy lifting of people So I think I started was more like a data signs Yes. you know, that Cisco thing. How is this Corolla software for you guys? Yeah, so if you look at the plant, one that we built, that's it's referenced by being I want to put both you guys on the spot for a question. So that flexibility driven by the driven to the Get pure storage and to end manageability. So you have a better optimization of the network. How do you break down those silos? is on platform across the across the company and not just you know, It's gonna be around for a long, long time. Yeah, That's the least thing you want it. How does that changed the computers? That's fine if that's the way you want to manage it. So you can move the containers where they need to be and have policy managers I want to ask you a question around customer trends. a format in a forum where you can manage and catalog, because that's kind of the sentence. And now you got at patient developers programming with data. and General, You guys were going to say, You got you got storage, You got networking and compute all kind of working together. I my feeling, mike, contract me or you can disagree with me. So you know, that is probably six x seven x what it is today, You are the leader. So that's where you guys come into helping that scale way built this. We think it's cliche to say know, as the news is good, it's acute coverage.

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Rick Tracy, Xacta & John Wood, Telos | AWS Public Sector Summit 2018


 

>> Live from Washington DC, it's theCUBE. Covering AWS Public Sector Summit 2018. Brought to you by Amazon Web Services and it's ecosystem partners. >> Hey, welcome back everyone. This is theCUBE's exclusive coverage live in Washington DC at Amazon Web Services AWS Public Sector Summit. I mean, it's so jam-packed you can't even move. This is like the re:Invent for Public Sector even though it's a summit for Amazon Web Services. I'm here with Dave Vellante, my co-host. Our next guest is John Wood, Chairman and CEO of Telos, and Rick Tracy, Chief Security Officer and the co-inventor of Xacta, it's hot technology. John, great to see you, welcome to theCUBE. >> Thanks guys. >> Thanks for having us. >> I love to get the brain trust here, John you're, like, probably one of the most experienced cyber security gurus in the DC area still standing. (laughing) As we said last time on theCUBE. >> Always, always. >> Okay. (laughing) And you've got some patents here, with some core technology, so first of all, I want to, before we get into some of the cool features of the products, talk about the dynamic of public sector, because Amazon has these summits, and they're kind of like a recycled re:Invent. Small scale, still packed. Talk about what Public Sector Summit is, because this is a completely different ballgame in this world. >> Sure, it's a perfect age for the cloud, and what this summit does, is it provides a great venue for people to come, learn about what works, get best practices, find use cases and just see what the ecosystem's all about in terms of how to make it work with the cloud. >> Rick, so what's your take? >> Well, if there's any doubt about it, what, is it double the size of last year? I think there were 7,000 people here last year and Teresa said today 14,500. So, yeah, I mean, it suits us perfectly because this is our sweet spot. >> So, Dave and I are always amazed by Amazon in general, the slew of announcements, Teresa Carlson picking the reins up where Andy Jassy does that Amazon re:Invent which is just tons of content, so many new announcements. What's your guys take on the hot news for you guys, because you guys are a major sponsor and you're in the ecosystem, you've been doing a lot of business with Amazon. >> Sure. >> What's going on in the business? What's happening with Telos? Why is it so booming right now for you guys? >> Well, I think people realize that there is a way to use automation where security can help drive cloud adoption. So, Rick and I co-authored an article back in 2011 that talked about why the cloud was more secure and it went over kind of like a lead ballon. And then back in 2014 the agency made the decision, the CIA made the decision, arguably the most security conscious organization in the world, to go to the cloud. And so that was a big, big, big, deal. But what we do is we help drive the security automation and orchestration stuff so you can reduce the time it takes to get what's called your authority to operate. And so I think that's a big deal now. The use of automation is being used to enhance the mission, so that the mission owners can get to their mission using the cloud, much more quickly. >> And we heard from the most powerful sentence in the keynote this morning was, "The cloud on it's weakest day is more secure than Client Service Solutions." This is a practitioner saying that, a leader of an agency saying that, not Amazon or not Telos. >> Absolutely. >> And it's because of that automation, right? I mean, that's really a key factor. >> It's because of the automation. It's also because the cloud providers are making sure that they lock down their physical infrastructure. Guards, gates, guns. All of the physical infrastructure and the virtual infrastructure, they do a really good job of that. If you think about it, the US government, unfortunately, 80% of their spend is around maintaining old systems. Well, the cloud providers are keeping modern. Those old systems have a lot of weaknesses from a standpoint of cyber security flaws. So, with a modern technology like the cloud, there's a lot more you can do around automation to lock down much more quickly. >> And the standardization that you get with a cloud makes it's easier as well, because there's not so many variations of things that you have to figure out how to protect. So, the standardized services that everything's built on really helps. >> Yeah, and people are adopting cloud in kind of different ways, which makes it harder, too. But you get the benefits of scale and speed, certainly. But I got to just pick up on some big news that's happened just last night and today. Microsoft Azure suffered an 11 hour downtime across Europe. 11 hours Azure's down, Microsoft Azure. This is a huge concern. Downtime, security, these are issues, I mean, this is just like, so, what's going on with this? >> Well, the truth of the matter is, if you think about where Amazon is today, Amazon is light years ahead of the rest of the cloud guys. The reason for that is they made the decision early on to take the risk around cloud. As a result of that, they have so many lessons learned that are beyond all of the other cloud providers, that that wouldn't happen to Amazon today, because they'll be able to back up, replication and duplication if they have, and their environments. >> How big do you think that lead is? You know, there's a lot of debate in the industry that other guys are catching up. The other side of the coin is, no, actually the flywheel effect is a lot like Secretariat in the stretch run of the Belmont, you were talking about racing before. What's your sense of that lead, even subjectively. >> I think it's between 5 and 10 years. There was a, it was crickets in this world, in the public sector world for cloud up until, literally, the agency decided to adopt. So the CIA made that decision, that was, sort of, the shot heard around the world as it relates to cloud adoption. Not just for public sector but for commercial as well, 'cause if you look at Amazon's ramp up, right after that decision was made, their ramp up has been amazing. >> That was a watershed event, for sure. >> It was, and it was very well documented, I mean, I read the judges ruling on that when IBM tried to stop them and the judge eviscerated IBM. And of course IBM had no cloud at the time, they had to go out and spend two billion dollars on software. John has lots of opinions on that, but okay, so that leaves-- >> I'm on the right side of history on that call. >> I think you are, it was a pretty good call. What about, what should be practitioners be thinking about? You talked about the standardization. Where should they be focused? Is it on response, is it on analytics, is it on training? What should it be? >> Well, from our perspective it is, a lot of the focus is on analytics, right? So, a lot of data that we've helped our customers collect over time for this ATO process that John previously mentioned, our goal with IO, Xacta IO, is to help organizations leverage that data to do more through analytics, so there's this dashboard with ad hoc reporting and analytic capability that's going to allow them to blend asset data with risk-to-threat data, with other sorts of data that they're collecting for ATO, specifically for the ATO process, that they can use now for more robust cyber risk management. So, for me, analytics is huge moving forward. >> And that's a prioritization tool so they can focus on the things that matter, or maybe double-click on that? >> It could be, it could be a prioritization tool, but it could also be a tool that you use to anticipate what might happen, right? So, some analytics will help you determine this asset is vulnerable for these variety of reasons, therefore it has to go to the top of the sack for remediation. But also, using that data over time might help you understand that this plus this plus this is an indication that this bad thing is going to happen. And so, analytics, I think, falls into both categories. Probably it's more the forecasting and predictive is something that's going to come later but as you unmask more data and understand how to apply rules to that data, it will naturally come. So, Rick and I have worked together for many, many years and, over a quarter of a century, so the way I would say it is like this. Xacta 360 helps you to accelerate your authority to operate, but that's a point in time. The holy grail for us as security practitioners is all around continuous monitoring of your underlying risk. So, the data analytics that he's talking about, is where we come about and looking at Xacta IO. So, Xacta IO helps fulfill that mission of continuous compliance, which means that the ATO is no longer just relevant at that moment in time because we can do continuous monitoring now at scale, in hybrid environments, in the cloud, on prem. 'Cause our clients are huge, so they're going to be a combination of environments that they're sitting in, and they need to understand their underlying risk posture. They need to have, they're going to have all kinds of scanners, so we don't really care, we can ingest any kind of scanner that you have with Exact IO. As a result of that, the security professional can spend their time on the analysis and not the pedestrian stuff that's just kind of wasting time, like documentation and all that stuff. >> Yeah, for us, data's a means to an end, right? It's either to get an ATO or to help you understand where you need to be focusing your resources to remediate issues. So, for us, leveraging the data that's produced by many companies that are at this show. Their data is a means to help us get our job done. >> Were you able to have, one follow up, if I may, were you able to have an impact, to me, even, again, subjectively, on that number, whatever that number is, that we get infiltrated, the customer gets infiltrated, it's 300 days before they even realize it. Are you seeing an impact on that as a result of analytics, or is it too early days? >> I would say it's still early. But it's reasonable to expect that there will be benefits in terms of faster detection. And maybe it's not even detection at some point, hopefully, it's anticipating so that you're not detecting something bad already happened, it's avoiding it before it happens. >> Yeah, and let me say it this way, too. You know, if you listen to John Edwards, the CIO from the CIA, he talks about how the reason he loves the cloud is because it used to take the agency about a year to provision a server, now it's a few minutes, right? Well that's great, but if you can't get your authority to operate, 'cause that can take another 18 months, you're not going to get the benefit of the cloud, right? So what we do, is we help accelerate how fast you can get to that ATO so that guys like the agency and anybody else that wants to use the cloud can use it much more quickly, right? >> Yeah, and the continuous integration and all that monitoring is great for security but I've got to ask you a question. Analytics are super important, we all know data analysis now is in the center of the value proposition across the board, horizontally. Not just data warehousing, analytics that are used as instrumentation and variables into critical things like security. So, with that being said, if you believe that, the question is, how does that shape the architecture, if I'm in an agency or I'm a customer, I want to build a cloud architecture that's going to scale and do all those things, be up, not go down, and have security. How does the architecture change with the cloud formula for the decision maker? Because right now they're like, "Oh, should I do multi-cloud, should I just Amazon" So, the data is a critical architectural decision point. How do you guys see that shaping, what's your advice to practitioners around designing the cloud architecture for data in mind. Just use Amazon? (laughs) >> Well, yes. (laughs) Just use Amazon. I mean, all the tools that you need exist here, right, and so-- >> If all the tools you need in the cloud exist here. >> Alright, so rephrase another way. >> But John, the issue is you're not going to have all your stuff in the cloud if you're the air force or if you're the army, because you have 75 years of data that you got to push in. So over the next 10 years there's going to be this "hybrid" environment where you'll have some stuff in the cloud, some stuff in a hybrid world, some stuff on prem, right? >> How I secured that, so that's a great point. So, data's everywhere, so that means you're going to need to collect it and then measure certain things. What's the best way to secure it and then is that where Xacta fits in? I'm trying to put that together if I'm going to design my architecture and then go to procurement, whether it's on premise or multi-cloud. >> Well, there are lots of security products that people use to secure, whether you're on prem or whether you're in the cloud and our platform leverages that information to determine whether things are secure enough. So there's a distinction between cyber risk management and actually securing a database, right? So, there's so many granular point products that exist for different points along the security chain, lifecycle chain, if you will, that our objective is to ingest as much of that information and purpose it in a way that allows someone to understand whether they're actually secure or not. And so it's understanding your security posture, transforming that security information to risk so that you can prioritize, as you were talking about before. >> You're taking a platform mentality as opposed to a point product. >> We're taking an enterprise view of risk. So, the enterprise is, remember, it's on prem, and hybrid and cloud. If all your stuff is in the cloud, Amazon has the answer for you. None of our customers are in that situation. If you're a start up, Amazon's the way to go, period. But all of our customers have legacy. As a result of that it's an enterprise view of risk. That's why companies like Telos partner so well with Amazon because they're all about being close to the customer, they're all about using automation. We are as well. >> Alright, talk about the news you guys have, Xacta IO, you're the co-inventor of it, Jack. Talk about this product. What's the keys, what does it do, where's it applied to, you mentioned a little bit of getting past the authority time point there. What's the product about? The product is about ingesting massive amounts of information to facilitate the ATO process, one, but managing cyber risk more generically because not everybody has an ATO requirement. So, you asked a few seconds ago about, so you're taking a platform approach. Yes, we're blending three separate products that we currently have, taking that functionality and putting it on a very, very, robust platform that can exist on prem, it can exist in the cloud. To enable organizations to manage their cyber risk and if they choose, or they have a requirement, to deal with things like FedRAMP and risk management framework and cyber security framework and iso certification and things of that nature. The point is, not everyone has an ATO requirement but everyone has a need to manage their risk posture. So we're using our ability to ingest lots and lots of data from lots and lots of different sources. We're organizing that data in ways that allow an organization to understand compliance and/or risk and/or security, and visualize all that through some dashboard with ad hoc reporting that let's them blend that data across each other to get better insights about risk posture. >> And to visualize it in a way that makes sense to the user. >> Yes, so, if you're the CEO, you're going to want to see it a certain way. If you're the IT manager, you're going to want to see it a certain way. If you're a risk assessor, you're going to want to see it a different way. So that's kind of what we're talking about. >> I got to ask you one question, I know we got to go, but, a hardcore security practitioner once said to me that hardcore security practitioners, like you guys, when they were kids they used to dream about saving the world. So, I want to know, who's your favorite superhero? >> Superman. >> Superman? >> Spiderman. >> Alright, awesome. (laughing) >> That was a basic question for you guys. >> Thank you very much >> Yeah, that's the hardest question, see they're fast, they know. Star Trek or Star Wars? (laughing) >> Depends on the generation. >> We won't go there. theCUBE have 15 more minutes today. Okay, final question, what's this going to do for your business now you have new, opened up new windows with the new product integration. How's that going to change Telos, what does it do for you guys from a capabilities standpoint? >> Well, the big thing I'd suggest your listeners and your watchers to consider is, there's a new case study that just came out, it's published jointly by the CIA, Amazon and Telos, talking about why working together is really, really, really groundbreaking in terms of this movement to the cloud. 'Cause your public sector listeners and viewers are going to want to know about that because this ATO thing is really a problem. So this addresses a massive issue inside of the public sector. >> And final question, while you're here, just to get your thoughts, obviously there's a big change of the guard, if you will, from old guard to new guard, that's an Amazon term Andy Jassy uses. Also, we all saw the DOD deal, JEDI's right there on the table, a lot of people jockeying, kind of old school policy, lobbying, sales is changing. How is the landscape, from a vendor-supplies to the agencies changed and/or changing with this notion of how things were done in the past and the new school? So, three points, legislatively there's top cover, they understand the need to modernize, which is great. The executive branch understands the need to modernize through the IT modernization act as well as the cyber security executive order. And then lastly, there are use cases now that can show the way forward. Here's the problem. The IT infrastructure out there, the IT guys out there that do business in the government, many of them are not paid to be efficient, they're paid cost plus, they're paid time and material, that's no way to modernize. So, fundamentally, I think our customers understand that and they're going to revolutionize the move forward. >> And the rules are changing big time. Sole source, multi-source, I mean, Amazon's on record, I've got Teresa on record saying, "Look, if we don't want a sole source requirement, let everyone bid fairly." Let's see who wins. Who can bring a secret cloud to the table? No one else has that. >> In terms of past performance and customer use cases they're pretty much in the head, for sure. >> Great, Amazon kicking butt here, Telos, congratulations for a great event, thanks for coming on. >> Thanks a lot guys. >> I appreciate it. >> Alright, CUBE coverage here in DC, this is theCUBE, I'm John Furrier with Dave Vellante. Stay with us, we have more great interviews stacked up all day and all day tomorrow. Actually you have half day tomorrow until two 'o clock Eastern. Stay with us for more, we'll be right back. (upbeat music)

Published Date : Jun 20 2018

SUMMARY :

Brought to you by Amazon Web Services and the co-inventor of one of the most experienced of the cool features Sure, it's a perfect age for the cloud, and Teresa said today 14,500. the hot news for you guys, so that the mission owners in the keynote this morning was, And it's because of It's because of the automation. that you have to figure But I got to just pick up on of the rest of the cloud guys. of debate in the industry the agency decided to adopt. and the judge eviscerated IBM. I'm on the right side You talked about the standardization. a lot of the focus is on analytics, right? of scanner that you have or to help you understand that we get infiltrated, the so that you're not detecting that guys like the agency that shape the architecture, I mean, all the tools that you need If all the tools you need data that you got to push in. What's the best way to secure it so that you can prioritize, as opposed to a point product. So, the enterprise is, remember, of getting past the that makes sense to the user. So that's kind of what I got to ask you one question, Alright, awesome. Yeah, that's the hardest question, How's that going to change Telos, inside of the public sector. change of the guard, if you will, And the rules are changing big time. and customer use cases Telos, congratulations for a great event, Actually you have half day tomorrow

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Adam Furtado, US Air Force | Cloud Foundry Summit 2018


 

>> Narrator: From Boston, Massachusetts, it's TheCUBE, covering Cloud Foundry Summit 2018. Brought to you by the Cloud Foundry Foundation. >> Hi, I'm Stu Miniman and this is theCUBE's coverage of Cloud Foundry Summit 2018. Always excited when we get to talk to some of the users. And joining me this segment is Adam Furtado, who is the Chief of Product with Kessel Run at US Air Force. Adam, you were saying you're not a big Star Wars guy, but was the name come from the derivation of the famous Millennium Falcon Kessel Run? Yes, I am a Star Wars geek, you know. >> It certainly was and the rest of our team are Star Wars nuts, so I've had to pick up things along the way so I like to joke that we're delivering capability to our users in 12 parsecs or quicker. >> Yeah, and if you're not a, whether you are or aren't a Star Wars fan, you look at it and say, parsecs is a measure of distance, not time. That's still infuriating for us to watch. Adam, tell us a little bit about your background and what your group does that the US Air Force that we don't need to explain the US Air Force. >> Sure, so my background is actually an intelligence professional as a warfighter enlisted in the Air Force for ten years. From there, I started working in IT systems and I got out of the Air Force and really was on the acquisition side of the house where we were the provider for capabilities for our warfighters. So, over that time, I learned a lot about how we struggle with getting capability to our users with any kind of speed or quality. Kessel Run is an effort to revolutionize the way that we build and deliver software to our warfighters and we are well on our way. >> That sounds like an awesome project. Can you give us just roughly how do you get your arms around how big this is, how many applications or people are involved in it or, you know, the scope of what you're doing. >> Sure. We set out to modernize the Air and Space Operation Center so we have AOCs all around the world that basically are where all the planning for air warfare takes place. So it's a large legacy system that is under a lens. So, they've really struggled in modernizing that baseline system. We've been designing a brand new system to modernize for about ten years and we just haven't been able to get it to the field for a ton of DoD bureaucratic and acquisitions reasons. So basically, Congress told us to figure something new out. So we had a small team that was tired of working this way and tired of not being able to provide this capability to the warfighters. We got together and we looked at industry to be quite frank. And found that the other bureaucratic regulated industries were able to take steps to move closer towards our digital transformation. So we kind of followed along and took some practices that we learned from them and tried to apply it to the government. >> Yeah, fascinating space. Governments' big focus this week at the show, there was the announcement about Cloud.gov. There is a whole track on government here. But, I want you to talk about your Cloud Foundry usage. Button General? How's the thinking of modernization, digitalization, there was a big Cloud First initiative from the federal government for a while. How do those forces play together? >> Sure, yeah, there's a ton of innovation type of activities taking place throughout the government and the DoD. With Cloud Foundry, we just found that because of our, we frankly have a lack of software development and engineering talent that's inherent to the Air Force. We have actually a career field for software developers that's been dwindling over the years. So being able to find that talent's been really hard. So with our Cloud Foundry commercial platform, being able to abstract the technical complexity that it does allows us to grow our software developers in a different way, focusing on identifying the character traits, the empathy and learning mindset that we can take and grow them by having that platform as a backbone to kind of be our foundation, I guess, is really was the emphasis of us going in this direction. It's really worked out so far. >> Yeah, just going through my head are all these discussions that we've had for years about how we need to go from monolithic, hierarchical to distributive architectures and that's been happening in the military a lot too. >> Very much so, yeah. What we're trying to replace is that massive monolithic system that takes us ten years to design and develop with no meaningful user input and at the end of the day, if we even get it out to the field, it's not the right thing. 96% of federal IT projects are over budget or over schedule and 40% of them never see a user at all, never get fielded. There's a lot of room for improvement in this space. We've been able to kind of tackle some of the, some of the easier things, but also tackle some more complex things. Similar to technology. But the policy, the testing of the security behind it as well that we've been kind of focusing on to move the entire DoD and entire Air Force forward. >> Yeah. So, security, I would think, is a major concern. How does that fit in to your thinking and how does security fit in to your architecture? >> We're always thinking about security. Cyber security is obviously really important to the DoD and our space. We feel that with, being able to automate more of the security with utilizing a platform and the pipelines that we have gets to a better place and we're more secure today than we were yesterday. We're always learning too, right? So, we're more secure today than we were literally yesterday. And we're going to be more secure tomorrow by learning how to move forward and learn more about cyber security. That's always something on our mind and we feel like we're in a good place. >> The majority of Cloud Foundry users are doing, they're a private or private hosted environment. Can you share, do you leverage public clouds at all? Or is it all kind of in-house data centers? How does that fit into the mix? >> So our unclassified developments is the AWS gov cloud and then we have hybrid solutions that we use on other networks. >> Okay, yeah. AWS just launched that, I believe it's their secret region, too, so that they're capable, but I guess your team or you can't talk about it, isn't leveraging it yet. >> Yeah, I'd rather not go there. (laughs) >> No worries. So, you're speaking at this show. What's your experience, what kind of things are you sharing and working on? >> We're really heavily relying on culture. So we had a couple of our team members speak this morning, giving more of an overview of our efforts and what we've been able to achieve so far. I'm focusing on how we can overcome some of the challenges that are inherent to the DoD. I mentioned earlier, native engineering development and talent. How we can change the way that we do organizational management. Our traditional hierarchal top down way of organizing doesn't breed innovation normally, right? So we're looking at different ways to organize our own team. So one of those reasons, all of our dev teams work in a balanced team concept with no uniforms, all on a first name basis. So we're basically taking, uniforms are really to strip the individualism away from people, but we kind of need that for creativity and to be able to solve conflicts, problems, and things like that. So we're really focusing on lifting the psychological safety needed to be creative and have our lowest ranking people feel as comfortable as our highest ranking people and IDA and coming up with ways to do things. >> That's fascinating actually. We've been talking a lot about relationships between the groups and the devs and the operators, but you start putting rank in there, which any company has some of that inherently, but the military very much is physical when you see them all the time. >> Absolutely. It's actually, our airmen have really adapted to it and they love it. It's one of those things where it's interesting, maybe a little bit different than commercial industry in that our airmen are our developers and our airmen are also our users so there's invested interest in improving things for the better for their fellow airmen. It's been really great to see and people have really dove in and embraced it. Developers are doing really well. >> What kind of lessons learned would you share? That you're sharing in your speech and talking to your peers. What kind of things would you share with them? >> I think the biggest thing I'm talking about today is to avoid getting in this trap of trying to find the perfect person with the right technical acumen. I think having a foundation is important, but more important is finding people who have empathy for users and learning mindsets and are able to get out of their comfort zone and learn new things. Building cloud innovative applications and 12 factor applications are inherently new to the DoD effectively. It's funny, we talk about how dev options, you know, innovative in our world when the commercial industry probably scoffs at that, but innovation is defined as the instruction of something new. It really is innovative in the DoD space to work in this way. We're seeing a lot of momentum throughout the services, and the DoD and we're really heading in the right direction. >> It's great to hear. Innovation and government can happen. We've done lots of interviews over the last few years to talk about it. Anything you'd like to share about ways that your organization or peer organizations are moving things forward that people might be surprised to hear about? >> I'd say the most important thing is finding the right people. A lot of the times, we've found that our most senior leadership in the government is very much interested in innovating and moving things forward in the right way and there's this innovation ecosystem below that is driving things. So it's basically the education that needs to happen at the middle level of that frozen middle. That sometimes can thwart innovation by a lack of that knowledge, I guess, or the lack of understanding of what we're doing. We've got what feels like a parade of education and trying to share the things we've learned with other people in the government. It helps us remove some of those bureaucratic barriers and then it's like really progress where we need to. >> Alright, Adam, last question I have for you. Something we're all struggling with, the pace of change these days. Seems every time you get on a new technology, the next one's there. You mentioned, you know, like, well, dev ops, we've been talking about for years but you're getting on. How does your organization look at that? How do you keep up with what's happening in the world? >> So I think, Cloud Foundry is an example of how these commercial solutions have helped us do that. Now, we say like, speed is the new security, we're able to be truly agile in that we're able to change and adapt to things as we need to. I think in the old model, it took us so long to adapt and get things out into the field that change was almost impossible. Whereas in this way of working, we're able to learn things every single day, keep our learning loops very short, and then react to them. So I think it's been a great way to take some of the things we've learned and implement them. >> Adam Furtado, I really appreciate you sharing your story from the US Air Force. Fascinating stuff. We'll be back with more coverage here at the Cloud Foundry Summit 2018. I'm Stu Miniman, thanks for watching theCUBE. (bouncy music)

Published Date : Apr 23 2018

SUMMARY :

Brought to you by the Cloud Foundry Foundation. Hi, I'm Stu Miniman and this is theCUBE's coverage and the rest of our team are Star Wars nuts, and what your group does that the US Air Force and I got out of the Air Force how do you get your arms around and tired of not being able to provide from the federal government for a while. and engineering talent that's inherent to the Air Force. and that's been happening in the military a lot too. and at the end of the day, and how does security fit in to your architecture? and the pipelines that we have How does that fit into the mix? and then we have hybrid solutions that we use so that they're capable, Yeah, I'd rather not go there. and working on? the psychological safety needed to be creative but the military very much is physical It's actually, our airmen have really adapted to it and talking to your peers. and are able to get out of their comfort zone We've done lots of interviews over the last few years So it's basically the education that needs to happen the pace of change these days. and then react to them. at the Cloud Foundry Summit 2018.

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Chad Sakac, Pivotal | Cloud Foundry Summit 2018


 

>> Announcer: From Boston, Massachusetts, it's the Cube. Covering Cloud Foundry Summit 2018. Brought to you by The Cloud Foundry Foundation, >> Hi I'm Stu Miniman and this is the Cube's coverage of the Cloud Foundry Summit 2018 here in Boston, Massachusetts. Happy to welcome back one of our earliest and favorite guests of the Cube Chad Sakac Who's at Pivotal now and he handles PKS and Dell technologies. Chad, great to see you, thanks for joining us, welcome to the Boston area, you come through this area a lot but it's great to see you. >> It's good to see you too. This is, by the way, my first CF summit. So it's interesting, you and I have talked together at Dell Technologies World, Dell EMC World, and EMC World for years. >> Stu: VMWorld. >> And VMWorld. This is a different scene. >> Alright Chad, this is my third time doing this show. I was at the first one back in 2014, last year we did the Cube there; every year it's like 'oh wait, there's this cool new technology; containers, maybe, how's Pivotal going to deal with that? This year, wait, Kubernetes, cloud natives everywhere. Maybe give us your point of view, as to how this fits in. >> So I feel like I'm a kid in a candy store. My job inside Pivotal is to drive PKS. Pivotal Container Service, that's built on top of Kubernetes. And there's a lot of Kubernetes action occurring here. If I had to net it out, I'd say a couple things. Number one, we've moved past the early hype cycle, and actually went through several hype cycles that blew up, so Docker is going to take over the world, not correct. What turned out to be correct is Docker would become the container standard, right? >> It's Mobi now, right? >> Right. Then, we went in to the battles of different cluster container managers. It's Swarm, it's Mesos Marathon, it's Kubernetes and there were lots of others, and then you get through that early hype period and things settle down to the point where they're actually productive, and everyone now kind of agrees, that Kubernetes is the standard container cluster manager for broad sets of workloads, great. Now the debate is Cloud Foundry, the structured PaaS-World, right? The structured platform opinionated, versus the little more wild west and open eco system of Kubernetes, and then early stage Kubernetes projects, like Istio and others, right? I think this has two chapters now, in front of us. Number one, and this is my focus I think for the next few years, is how do we make Kubernetes simple enough, easy enough, and frankly, enterprise ready. Not that it's not ready today, but a lot of Kubernetes projects that our customers are all over the map, difficult to sustain. We want to bring a lot of the lessons learned over the years of Cloud Foundry to Kubernetes. And I'm happy to say, that just a couple days ago, we released PKS 1.O.2 and 1.1, which we haven't announced the date but we've always said that we're going to be in constant compatibility with GKE, and the core Kubernetes. Since GKE shortly will have Kubernetes 1.10 support you can expect a 1.1 of PKS. So mission number one is make Kubernetes a great platform, and I am determined and stubborn, and will make PKS the best enterprise platform for customers that are putting workloads on Kubernetes. That said, Kubernetes isn't steady still and neither is the ecosystem. And you can see that there's a lot of discussion over what is the intersection between Cloud Foundry and Kubernetes? I think that over time it's inevitable that these things come together more. But again, I think that's going to occur over years. Not in a heartbeat. >> And even, I've been at the Kubernetes show and have been at this show a few times, it's not a monolithic stack, we're building distributed, lots of different pieces. You go to the Cloud Foundry, I'm sorry, the show that's Kub-Con, there's so many different projects there, I mean Istio was all the buzz, talk about the service national, there's all these little pieces there. And at this show, we're talking about Zip Car came and talked about they love everything in this eco system. They don't use some of the core components, but they use all these other pieces. As you and I've talked many times, Chad, people go read, Chad writes a little bit about some of these things to give you all the details there, but this stuff's pretty complicated. There's some in the Kubernetes community that's like it's never going to get simple. Remember when we thought Cloud computing was simple? And if you've been to any Amazon show and you go through, it is more complicated to configure a compute instance at Amazon, than it is to buy a Dell server these days. Because there's more options out there. Look, customers need options, many of them want things to be packaged and serviced and buy it as a service, but some love to put those pieces together and it's a spectrum and I loved at this show, Google and Microsoft up on stage, talking, 'hey, open communities, collaborating together'. Maybe not merging everything, but working together, understanding where things fit and it's not one or the other, it's many customers will choose both. >> You and I are both nerds at heart, I hope you don't take offense to that. >> I've already been doing Star Wars quotes this week. >> I wear it with pride. I'm always fascinated by the technology itself, but one thing that's been really cool about my experience alongside, and now inside Pivotal, and you can see it here at the CF Summit, is that the Pivotal obsession, is about the customer and the outcome. We build a platform that is an essential part of that, but teaching the world how to build better software is a noble mission. And the thing that's the most exciting for me is actually when the customers talk. So if you went to any of the customer discussions, did you see any of them, did you see the T-Mobile one? >> I saw T-Mobile up on the key note, I actually did an interview with T-Mobile. Had an interview with US Air Force. >> The Air Force One is amazing. >> Awesome. >> It's fascinating, from a technological standpoint, to say how do you use these tools? But it's the story of what you do with it, that actually matters so much more. I'll leave the, no, I won't leave the customer name out of it. So in talking with the T-Mobile crew, they love the Pivotal application service. So they are using it, it's an essential part of how T-Mobile works. They talked about it on stage, that's why I don't mind talking about it. And if you ask them, it's not an or. They also have massive projects, massive application workloads, that don't fit in PaaS, but are Docker images, they're currently doing some strange stuff with Swarm, and blah blah. And they're like 'Man, if you guys can basically deliver a great platform that we can consume instead of trying to construct and maintain, we trust you, you iterate with us, you work with us, we'll be able to focus more on the outcome. The thing that I'm actually going to be the most curious to hear feedback from customers over the next couple of years, is how do they navigate what workloads are best put into Kubernetes, how does Kubernetes sets of ecosystems start to not calcify, but firm up, right? It's going to be loose. But it will start to align more over time. >> Yeah our research team actually calls it, we need to get to a place where it's plastic. It should be not just scalable up and down but side to side a little bit more too. Once you have it, you can be able to go. >> Figuring out over time, and helping, with customers, figure out 'Hey, this is a Kafka or Crunchy data.' Post grass instance, or it's an ISV stack, or it's an application they've home grown, but they don't want it fully compartmentalized and put on paths, and they decide that they want to put it on Kubernetes, awesome. What is the value and the return of doing further work on that app to really make it Cloud Native, pull out all config, turn it into sets of small micro services, and then it's better fit for the PaaS part of PCF. Figuring out that formula over the next few years is going to be really cool. >> You mentioned culture. And that's been something you and I, Chad, lived through. It was the server vs the storage vs the network and the virtualization admin, and then the cloud admin. I talked to the US Air Force guy, and he was like, 'We actually have the people take off their uniforms, because rank would have a certain meaning inside there.' But you've got the Devs, you've got OPS, you've got still the infrastructure pieces on tub, what are you seeing from the customers you're talking to; what are some of the big challenges that are slowing people back from reaching this Utopia of fast, fast, fast, agile, inter-operable, wonderful times? >> How do I answer that one? That's a loaded question, brother. The biggest impediment is human nature. It's these damn humans, if we could just get all the humans out. >> Well everybody's mine, mine, mine. >> We'll go to low code, no code, eliminate all the humans, it'll be dreamy. >> I did one of those interviews today, too. Absolutely, you don't need all programmers, the business people can do it. >> The human tendency for control, and the need for control, I think it's probably deep seated in our, we're living in a world where we know intellectually that we don't have control over everything, but we hate that. Because we want to create control in our lives, that basically is the thing that sets up boundaries between people, and they get really hung up on their function. That's not new, the word's changed, like you said. Used to be server people vs storage people. Then it was virtualization teams vs the silo teams. And now it's the intersection of the DEV team and the DevOps team, the operations team. How do they intersect? The places where they're the most successful, is that they don't get hung up on that and the people blend the roles. Now the trick is, how do you do that in a big company? I wrote a blog, I'm not trying to advertise, virtualgeek.io I wrote a blog on this which was a synthesis of all the customer dialogues I've been having over the last few years. And the pattern I've seen that is most successful, is actually to recognize that there are stacks, and the stacks, I don't mean this particular technology choice, but the way that the whole stack driven by the business and the application and then the abstraction it sits on, and then you have to build your actual operations team underneath that. That creates a whole operational model which in itself is a stack, and just so it doesn't sound like I'm describing something that's nonsensical, a stack can be in big enterprises, there's a main frame based app, that's running on a main frame, that's being supported by a main frame operations team, and then right beside it there's another stack, which is all X86 workloads that are static. So they don't need an IAS they just need to run on a kernel mode VM abstraction. And then under that you've got the team that supports. Then you've got the workload that can be containerized, and don't need a full blown PaaS. And then you've got another one, which is a full blown application service model. Each one of those stacks ends up with different people, processes and tools, because they're mapped to the cultural operational model of that stack. And the thing that I'm trying to guide customers when I'm talking to them is, don't reject that; that's actually reality. Yes you should move as much as you can to the highest order abstraction you can. That's goodness and it pays dividends all the way down the stack. But don't go and say, that this workload, by definition has to go there. Or because you operate this way in this stack and this group operates this way, that by definition you're stupid and they're smart. The other rule is that- >> Chad, the answer to everything is server-less. >> By the way, I should have said that's another abstraction even to the right of the application service model. So the thing I've found, is a key kind of pattern of good, is that between the stacks, people and process are not allowed to transverse them, because the process is linked to how you operate. The only thing that goes between them, because in the end, for any customer, the stuff that touches all of those, is to become religious about one thing, which is that API's and data, and how those transit, those different stacks, that you have to be very clear on. Do you know what I mean? On the blog I drew a picture, but it was terrible. It was a terrible drawing. >> I've done whiteboards with you, Chad, I understand. Great, so. Sound's like you've got your hands full. Lots of us read the S1, so Pivotal's marching towards an IPO. You've only been there a very short time, you've know Pivotal since the beginning and all the pieces since Greenplum's part of the MC, Cloud Foundry part of VMware. Anything that you've learned since you've been inside Pivotal now that there's misconceptions? One of the things I always find is, we always learn about something the first time and then don't think it changes. >> It's funny actually, that's an insightful question. Having joined the team, it's weird because to many of them, I'm new, I'm a new Pivot. But to many of them they know that I've always been there. And I was reminding some of the originals, the crazy tortured path that we've taken to get to today. The original effort was hey, people are doing new things data's at the core of it. And that was the trigger for the Greenplum acquisition. And several of the people who are the senior leaders of Pivotal now came in through that. And then Paul Maritz was the CEO of VMware at the time, hey, I'm seeing people build new apps in new ways, by the way there's this crazy team inside VMware working on this thing called Cloud Foundry. And they were like a red headed stepchild. That's not PC, but like a black sheep? Or I don't know what metaphor you want to use, but basically they were working on something that had nothing to do with kernel mode virtualization at its core. >> Yeah it was a Cloud native peg in a VM square. >> And at the time, VMware isn't what they are now too. And then people forget this but I wrote a blog about it, so it's on the internet permanently. There was a Greenplum project, which was a great idea, that says people want to collaborate with data sets, and data scientists want to work together and it's really hard. Let's build a thing, which is like a social media portal, for Greenplum which was called Chorus. And the Chorus project was completely sideways. And they were like we don't know how we're going to get this thing on track on time, and they asked around the Valley, and people said hey, you should go talk to these guys, Pivotal Labs, up in San Francisco. What they do is they help people when they're stuck. They went, and I remember when Bill Cook and Scott Yara came back to Hoppington and said 'This was awesome, they've changed the way we think about how we build software, we think we should buy them.' And that got added, I remember when Paul Maritz said 'Spring is available.' it's like the most widely used modern JAVA framework, and that was also stuff in Spring Rif. All of these weird bits, in essence became the essence of Pivotal. You know what I've learned through that? Is these journeys are not in a straight line. Everyone's. >> Like our careers, Chad. >> Like our careers man. That's the first part, the second thing is, and this is going to be a challenge for Pivotal, honest, if we're very transparent as always, is Pivotal's brand is now so linked with Pivotal Cloud Foundry. And that's a good thing, like those customers raving about the business outcomes that they are getting. But inside Pivotal, the strategic change, the strategic pivot ha ha ha, to do a full embrace of Kubernetes versus the traditional opinionated versus plastic debates, I wouldn't say that we have 100% of the company fully embracing it yet, because companies are themselves, organic. But across the vast majority of the company it is something understood that it is an imperative for us. If we want to help the customers and the world build better software, we've got to do it for stuff that fits into PaaS, and stuff that doesn't. And so I've learned over the last few weeks about how many people share that passion that I have, and I think we can make something awesome with PKS. >> Alright, well with that Chad, we'll have to leave it there for now, looking forward to seeing you at more events. Congrats on the new role, I'm sure if people haven't already, Chad does have a new site for his blog, virtualgeek.io instead of the previous one. Chad, always a pleasure. Got the Cube here at Cloud Foundry Summit, I'm Stu Miniman, thanks for watching the Cube. (upbeat tempo)

Published Date : Apr 20 2018

SUMMARY :

Massachusetts, it's the Cube. and favorite guests of the Cube Chad Sakac This is, by the way, my first CF summit. And VMWorld. Pivotal going to deal with that? past the early hype cycle, and the core Kubernetes. fit and it's not one or the other, You and I are both nerds at heart, Star Wars quotes this week. is that the Pivotal obsession, I actually did an interview with T-Mobile. But it's the story of what you do with it, Once you have it, you can be able to go. What is the value and the return and the virtualization admin, How do I answer that one? eliminate all the humans, it'll be dreamy. the business people can do it. that basically is the thing that sets up Chad, the answer to is that between the stacks, and all the pieces since And several of the people Yeah it was a Cloud And at the time, VMware and the world build better software, instead of the previous one.

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Chad Dunn, Dell EMC | HCI: A Foundation For IT Transformation


 

>> Narrator: From the SiliconANGLE Media Office, in Boston, Massachusetts, it's theCUBE. Now, here are your hosts, Dave Vellante, and Stu Miniman. >> For several years now, the analysts at WikiBound have been talking about taking the cloud, the public cloud, operating model, and bringing it to your data, wherever that data lives. Hey everybody, this is Dave Vellante, and I'm here with my co-host, Stu Miniman. Welcome to HCI: A Foundation For IT Transformation. We're here with Chad Dunn, who's the Vice President of Product Management and Marketing, at Dell EMC. Chad, good to see you again. Thanks for coming on. >> Yeah, glad to be here, good to spend time with you guys. >> So, we talk a lot about, you know, VxRail, speaking of foundations. Give us a quick update. What is it, and what's new with VxRail? >> Okay, well big news in VxRail land, right, we just completed our transition under the 14th generation of Dell Power Edge servers, so this gives us a substantially more powerful platform, a substantially more predictable performance, and a lot more configuration options that make it fit a lot of different workloads that our customers have, so it really makes it prime time for HCI. >> So, where is the power and performance come from? Is that predominantly, kind of, new compute? >> That's a big piece of it. Some of that is software as well, right? vSAN underlies VxRail as a software defined storage layer, and we've seen pretty amazing increases in performance, just from software, from our 13G, to our 14G transition, but when we look at that performance now, on 14G servers, with the Intel Skylake chipset, we're seeing 2x performance over the last generation, and we're seeing latencies that are very, very low. And that has to do with, more and faster memory channels, more threads, overall faster processors, so really off the hook, in terms of the performance that we're seeing. >> Chad, when we look at HCI, it's really about the software layer, often, it gets overlooked, you know, what actually has to happen between the software and that underlying hardware? Are there optimizations, does it matter if I'm using the software, you know, what's optimized for that next generation Intel chip? >> Yeah, it's all about the software, or so our software vendor would say, but we know that when you're treating something as a system, you need that hardware and that software to work together, in perfect unison, as a system, and, you know, we've done a lot in this generation, working with the PowerEdge team to make sure that we have the right hardware, hooks, and design points that are focused on HCI. That goes from things like the devices that we use to boot up, and where we would execute the hypervisor kernel, to network connectivity, and really importantly, to the inband channels that we use to update all of the little pieces of firmware that operate the hardware inside the system, right? You need to be able to treat those as a system, update, lifecycle manage those, all in context of one another, so having direct and deep, meaningful access into that hardware is critically important when you're operating a system like this. >> When we've looked at, kind of, our cloud strategy, in general, it's about the data. We talk about data, it's things like predictability and latency, it's about, kind of, the power of the underlying thing, maybe, give us a little bit more specifics, as to what you're getting in this generation. >> So, the big difference here, above and beyond the performance, which is about 2x what we saw from the last generation, if we look at the same hardware, the same software, running on the two different pieces of hardware, about 100% better. But that's really just part of the story. It's the predictability of latency that's critically important. If you're going to migrate Tier 1 workloads under this infrastructure, you need to ensure that other workloads are not going to disturb that performance. So when we look at this, we look at how the IOs per second increases, and we look at the overall latency. How long does that latency line stay flat, right? So when we look at this generation, we see over 2x the IOPS, but the horizontal line where we look at the response time in latency, it stays flat nine times longer in this generation than in the last. So if you've got that sub-millisecond response time, even at very high IOPS, you can put a lot of different workloads on that same infrastructure, and still get predictable performance. >> I think, the other thing that people don't understand, is that, oh, HCI, it's just like, it's that little LEGO block you build, but it's not just one LEGO block, what have you seen from customers, what's kind of, the portfolio, what are the decisions that they have to make, to kind of, pick the right configuration? >> Sure, so yeah, when you're a kid and you get your first LEGO set, you get a lot of pretty generalized blocks, they're all, you know, square and some are rectangle, but not a lot of variability. When you get up into the big leagues of the LEGO Star Wars set, right, you've got a lot of specialized parts, and you can do really advanced, really cool things. That's really where we're at with HCI right now. If you want to really tune the infrastructure for the workloads that you have, you need a lot of variability in the processors you choose, the amount of memory, the speed of memory, and even the storage. It could be hybrid, some people still choose hybrid HDDs, but even within flash, people will choose SAS or SATA drives depending on the performance and cost benefits that they want to realize. So being able to scale up and down the processors, the memory, different types of storage, is critically important, so you can fit it into those different workloads. Also, a lot more people use this for VDI, and for high end imaging. So the ability to pack these things full of graphical processing units, and still be able to power and cool the things, is critically important. We have a lot of applications in those verticals where there's video processing and these are required. So, we don't just have one model of VxRail, we've got a number of different VxRail models, all of which can scale up, and then of course, HCI can intrinsically scale out. So that lets you really fine-tune it and get to that expert level, in terms of your LEGO building blocks. >> So Chad, a minute ago, you mentioned workloads. So as you're bringing this sort of 14th generation server technology to VxRail, how has it affected workloads, what are you seeing is the sweet spot for workloads? >> So if I were to think back a year, the question that every customer would ask, is how do I know which workload is right for HCI? And a lot of times they even lack the vocabulary and taxonomy to say, okay, that fits, that doesn't fit. What's happened in the meantime though, are the software's gotten so much better, the hardware's gotten so much faster and more predictable, that the question is, well, what workloads are not right for HCI yet? And there are very few that aren't. So, we've seen people generally start off with one workload, right? Maybe it's VDI, maybe it's a database, and then they start to move other, as they get comfortable with it, they move other workloads over to it. Obviously, we've got a big install block, or install base of VxBlock, and Vblock. We see a lot of those customers start to migrate workloads from there onto a layer of HCI. And more and more, those are becoming Tier One workloads. Crate & Barrel is a great example, a great customer of ours. They're moving their point of sale systems onto VxRail. Now for a retailer, your point of sale system, that's about as mission critical as you can possibly get, so they and others now have the confidence to start to move these things over. The only outliers that we see are some of these very big data applications that are hugely write intensive, and we actually usually end up selling a layer of hyper-converge with our Isilon arrays, to store that data, and then put a layer of hyper-converge compute around it, because in some ways, hyper-converged is just a better way to server, if you know what I mean. >> Wondering if you can talk about the business impact, what a customer's seeing, how are they quantifying the value of these systems, share some stories, or color there. >> Sure, it's all about operational expense savings, right? How much more efficiently am I going to be able to operate this infrastructure? It's not so much about capital acquisition costs. So when you look at the typical operational expense savings, and that comes from us doing all the lifecycle management of the hardware, of the software, of the cluster as a system, you see those costs go down. Really good example, is First Credit of British Columbia. Another one of our good customers. Now, they've deployed this, they've seen 30% OPEX savings and they've seen 50% power and space savings. You get a smaller package because you don't have separate storage array, separate servers, but, you also have really, one function that needs to operate your environment and that's the virtual administrator. He or she is the one that really operates everything, you don't have separate storage, separate compute, separate virtualization teams that have to look after the infrastructure. So, that first run is very easy, very fast to deploy, but it's day two through 700 and day 900 where you see that recurring operational expense saving where it really pays off for customers, all the updates and updates and life cycle management. >> Yeah, so Chad you talk about the success and all the customers. What about the customers that haven't looked at kind of the HCI space yet? What are they missing? You know, what do you say to those customers that maybe, you know, aren't sure if the waters right to jump in yet? >> So there's really three ways that you're going to encounter a customer who's going to consider HCI. You're either going to refresh a server, you know, your servers are up for maintenance and you're going to take a look at HCI as the next step in your evolution of your compute strategy. Or you're going to refresh your storage, and you're going to look at hyperconvergence as the next step in the evolution of your storage strategy. Or you've got that one workload that's probably net new and it's going to be, sort of, an isolated case and they need an infrastructure and they need to stand if up fast. That third case is really the one that drove the initial adoption of HCI, I can't tell you how many of our customers started with VDI. I mean, it's so cliched now to talk about VDI as killer app for HCI, but that's how so many people started. Because it's, you know, a very bound, isolated infrastructure and from there they get comfortable with it and they start to bring other workloads onto it. So, if you're thinking about refreshing your servers and if you're thinking about refreshing storage, it's time to kick the tires onto HCI. If you've got a workload that you need to stand up quickly and you don't know how big it's going to be, you know, one, two, three years down the road. It's another opportunity to look at HCI. Because you can start with a very small infrastructure, but you can grow it to a very very large one. >> What if we could talk a little bit about digital transformation, I mean, everybody's talking about digital transformation, and to us, digital transformation is all about how you leverage data and the edges exploding. We've envisioned sort of a three tier data model. You've got the edge, you've got maybe an aggregation point and you bring it back to the cloud. And that cloud can be a public cloud or it can be on-prem. So you've got to have some kind of cloud infrastructure to manage all this data. So where does this fit in the context of transformations and why does hardware matter? >> Yep, well let's go from the end and work back to the beginning. Hardware matters because of form factor, for one. As you start to push compute out to the edge, right, you want form factors that are small, don't consume a lot of power but, you know, still have a lot of processing power and can manipulate that data. Right, the whole internet of things phenomenon that is, creating all this data out at the edge, you know, presents us with a conundrum right? The data itself is not that valuable, the insights that we get from the data are immensely valuable. Bringing all that data back to the core to do something with is not cost effective. So, it's how do we turn the data at the edge into information and then how do we funnel that valuable information back to the core and leave the unvaluable data out where it is. hyper-converge fits really well there because you can have, you know, devices of very small form factors that are very quick to deploy, very easy to manage remotely. At the aggregation point you can have, simply, larger versions of the same thing or more of the same thing. And then finally at the core you can have very large clusters of hyperconverged appliances, like VxRail, to do your processing. Now the key is from an operational perspective you've still got a single pane of glass that manages everything. Right, it's still the same set of tools, it's still the same hardware and software lifecycle management process that happens out at the edge, at the aggregation point and at the core. So again, it comes back to the operational expense of making decisions closer to the data and then managing everything with a consistent set of tools. >> So I wondered if we could also talk about the competition and when Stu and I think about competition in this sphere we look at, first of all this all sort of software defined, everything can moved into software defined. So we see two vectors, one is head to head competition with other software defined suppliers, and the second big competitor is, hey, I'm just going to roll on my own. >> Chad Dunn: Right >> So let's start with the former, why Delium C vs vendor A, B, C or D? >> Sure, sure it really gets down to what your goal is as a customer and we obviously have multiple options within our own portfolio and those perfectly, you know, find solutions for a lot of people. But, you know, number one if you're a VMware user and you want to optimize around the VMware user experience, then VxRail is the way to go. Because we do co-engineer this with Vmware, it's not just a regular partnership, we have engineers and marketing people and product managers at Vmware that functionally role up to our team and so we do behave as one engineering and one product management organization to really optimize the user experience for VMware. Secondly, architecturally from a VCM perspective, this is a service that's baked into the kernal of vSphere. So, in terms of performance and the overhead that it creates on CPU, memory, et cetera. This is the best game in town. We can do more IO more predictably with flatter latency than really any other solution that's on the market in the HCI space. Every other one takes a virtual storage appliance approach where they have something running on top of the hypervisor. >> Dave Vellante: Right. >> The very long and circuitous data path, we'll performance test against solutions like that all day long, every day, that doesn't worry us at all. So, if you're a vSphere customer, VMware customer it's the most obvious choice and from a performance perspective you're not giving up anything right? We don't want users to have to sacrifice the storage functionality, the performance, the compute functionality. Just because it's hyper-converge and you scale out doesn't mean you can compromise on any to those axis. >> Okay, what about the guys who like to change their own oil in the car and the spark plugs and tune it up and they want to roll on their own. >> (laughs) It's been a long time since I've been able to work on my own car. So I encounter these kind of customers all the time. It's the build your own crowd and it's what they've been doing for a long time. And it's great, alright, I build my own computers at home and I have my own ESX server that I put together. I can't afford a VxRail. (laughing) There's no employee discount. So I'll tell you a story that will hopefully make sense, my first job when I got into this business, I went to Boston College, my first job and work study was to keep a spreadsheet that had all the MAC addresses and all the IP addresses for every host on the BC network and keep those in sync. >> You're really good at that I bet. >> I was excellent at that. That is not a skill set that is in demand right now. Or really even at that time. But when you think about what it means to take a software defined storage product like VMware vSAN and take an x86 server and put those together. Yes, you're getting to the same destination of running vSphere on a host with software defined storage. You're missing the systemness, right? We go to a lot of trouble to make sure we're managing all of things things in the context of the cluster level. All of the little pieces of firmware, and they're roughly 12 or so pieces of firmware that we have to take care of. From the BIOS to the drive controller firmware, the drives, the boss card, which is our boot media, the iDRAC firmware, the backplane, power supplies. In legacy EMC we spent 30 years building arrays. We had all those same challenges with all the different pieces of firmware and software that all had to function as a system, we did that. And we guaranteed that it would live up to 5/9ths of availability for the customer. That's exactly what we do when we deliver VxRail's hyperconverge. If you want to choose to build those things yourself that's fine if you have the skills and that's how you want to operate your business. The 5/9ths is now on you though. Right, because you're the one responsible for bringing all those parts together. So, yeah it's certainly a valid path for others but, the market is shifting and we see more often than not, people are moving towards a buy approach rather than build. >> You bring up a great point. I remember back in the early days before we even called it HCI, you think about vSAN, oh well is the storage admin going to buy it? Is the virtualization admin going to take that over? What's excited me about this wave is the oh, heres the cool stuff that companies are doing now that they're not spending their time keeping spreadsheets of MAC addresses. >> Chad Dunn: Yeah, yeah exactly. >> What is the kind of, you know, owner of this, look like in your environment? And any cool stories you're hearing from customers transforming their organization. >> By and large the operator is your virtual admin. The person who is at home in vCenter and vROps, you know, maybe even vRA if they're going full infrastructure as a service. That's really the user of this, and the dynamic you mention is similar to what we had with Vblock, right. Customers who went Vblock, who said, I'm going to change my operating model to a virtual administrator versus compute, storage, network. You know, customers who didn't change the operating model were not happy Vblock customers. Ones that did change the model did. And, I'll tell ya a real off script anecdote, recently I was traveling in Europe, and I started playing a game with the sales guy we were traveling with. Because in Europe, very often, they have more of an affinity to putting their logos on the sides of buildings in a lot of European cities. So, as we would go to these different cities and we went from Stockholm all the way down to Rome, to Switzerland, to Amsterdam. You know, we're just spotting VxRail customers, right, whose going to spot the most. And the one really interesting one is we checked into a hotel, you know, late night in Switzerland. Next morning we meet for breakfast and he goes, "Did you spot the rail customer?" I said "Who was it?" We went into the bathroom and they have these, you know, squeeze bottles that have the soap in the shower and it's a cosmetics company and they're located in Germany. And they do, obviously, a ton of business all over Europe, and they had outsourced a lot of their IT because, you know, their core competency is not IT, it's cosmetics. And they now have one guy that looks after all of IT for this company rather than outsource it to two different companies to manage all this and he runs it all on VxRail. So, transformative yes, to that company very transformative. But, at a very small scale, but that pattern sort of repeats itself the higher that you scale. >> Alright we're out of time but where can people go to get more information on this and other products your HTI strategy. >> If I were them I'd go to dellemc.com/hci. >> Excellent, Chad, thanks very much, Stu appreciate you co-hosting with me and check out videos on thecube.net, this and other videos will be up there. Thanks for watching everybody, Dave Vellante for Stu Miniman we'll see you next time! (techno music)

Published Date : Dec 19 2017

SUMMARY :

Narrator: From the SiliconANGLE Media Office, and bringing it to your data, wherever that data lives. So, we talk a lot about, you know, VxRail, and a lot more configuration options And that has to do with, more and faster memory channels, that operate the hardware inside the system, right? it's about, kind of, the power of the underlying thing, above and beyond the performance, for the workloads that you have, So Chad, a minute ago, you mentioned workloads. and then they start to move other, Wondering if you can talk about the business impact, of the cluster as a system, you see those costs go down. and all the customers. You're either going to refresh a server, you know, and you bring it back to the cloud. At the aggregation point you can have, simply, and the second big competitor is, and the overhead that it creates on CPU, memory, et cetera. VMware customer it's the most obvious choice and the spark plugs and tune it up and all the IP addresses for every host on the BC network and that's how you want to operate your business. I remember back in the early days What is the kind of, you know, owner of this, and the dynamic you mention is similar to get more information on this and other products Stu appreciate you co-hosting with me

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Data Science for All: It's a Whole New Game


 

>> There's a movement that's sweeping across businesses everywhere here in this country and around the world. And it's all about data. Today businesses are being inundated with data. To the tune of over two and a half million gigabytes that'll be generated in the next 60 seconds alone. What do you do with all that data? To extract insights you typically turn to a data scientist. But not necessarily anymore. At least not exclusively. Today the ability to extract value from data is becoming a shared mission. A team effort that spans the organization extending far more widely than ever before. Today, data science is being democratized. >> Data Sciences for All: It's a Whole New Game. >> Welcome everyone, I'm Katie Linendoll. I'm a technology expert writer and I love reporting on all things tech. My fascination with tech started very young. I began coding when I was 12. Received my networking certs by 18 and a degree in IT and new media from Rochester Institute of Technology. So as you can tell, technology has always been a sure passion of mine. Having grown up in the digital age, I love having a career that keeps me at the forefront of science and technology innovations. I spend equal time in the field being hands on as I do on my laptop conducting in depth research. Whether I'm diving underwater with NASA astronauts, witnessing the new ways which mobile technology can help rebuild the Philippine's economy in the wake of super typhoons, or sharing a first look at the newest iPhones on The Today Show, yesterday, I'm always on the hunt for the latest and greatest tech stories. And that's what brought me here. I'll be your host for the next hour and as we explore the new phenomenon that is taking businesses around the world by storm. And data science continues to become democratized and extends beyond the domain of the data scientist. And why there's also a mandate for all of us to become data literate. Now that data science for all drives our AI culture. And we're going to be able to take to the streets and go behind the scenes as we uncover the factors that are fueling this phenomenon and giving rise to a movement that is reshaping how businesses leverage data. And putting organizations on the road to AI. So coming up, I'll be doing interviews with data scientists. We'll see real world demos and take a look at how IBM is changing the game with an open data science platform. We'll also be joined by legendary statistician Nate Silver, founder and editor-in-chief of FiveThirtyEight. Who will shed light on how a data driven mindset is changing everything from business to our culture. We also have a few people who are joining us in our studio, so thank you guys for joining us. Come on, I can do better than that, right? Live studio audience, the fun stuff. And for all of you during the program, I want to remind you to join that conversation on social media using the hashtag DSforAll, it's data science for all. Share your thoughts on what data science and AI means to you and your business. And, let's dive into a whole new game of data science. Now I'd like to welcome my co-host General Manager IBM Analytics, Rob Thomas. >> Hello, Katie. >> Come on guys. >> Yeah, seriously. >> No one's allowed to be quiet during this show, okay? >> Right. >> Or, I'll start calling people out. So Rob, thank you so much. I think you know this conversation, we're calling it a data explosion happening right now. And it's nothing new. And when you and I chatted about it. You've been talking about this for years. You have to ask, is this old news at this point? >> Yeah, I mean, well first of all, the data explosion is not coming, it's here. And everybody's in the middle of it right now. What is different is the economics have changed. And the scale and complexity of the data that organizations are having to deal with has changed. And to this day, 80% of the data in the world still sits behind corporate firewalls. So, that's becoming a problem. It's becoming unmanageable. IT struggles to manage it. The business can't get everything they need. Consumers can't consume it when they want. So we have a challenge here. >> It's challenging in the world of unmanageable. Crazy complexity. If I'm sitting here as an IT manager of my business, I'm probably thinking to myself, this is incredibly frustrating. How in the world am I going to get control of all this data? And probably not just me thinking it. Many individuals here as well. >> Yeah, indeed. Everybody's thinking about how am I going to put data to work in my organization in a way I haven't done before. Look, you've got to have the right expertise, the right tools. The other thing that's happening in the market right now is clients are dealing with multi cloud environments. So data behind the firewall in private cloud, multiple public clouds. And they have to find a way. How am I going to pull meaning out of this data? And that brings us to data science and AI. That's how you get there. >> I understand the data science part but I think we're all starting to hear more about AI. And it's incredible that this buzz word is happening. How do businesses adopt to this AI growth and boom and trend that's happening in this world right now? >> Well, let me define it this way. Data science is a discipline. And machine learning is one technique. And then AI puts both machine learning into practice and applies it to the business. So this is really about how getting your business where it needs to go. And to get to an AI future, you have to lay a data foundation today. I love the phrase, "there's no AI without IA." That means you're not going to get to AI unless you have the right information architecture to start with. >> Can you elaborate though in terms of how businesses can really adopt AI and get started. >> Look, I think there's four things you have to do if you're serious about AI. One is you need a strategy for data acquisition. Two is you need a modern data architecture. Three is you need pervasive automation. And four is you got to expand job roles in the organization. >> Data acquisition. First pillar in this you just discussed. Can we start there and explain why it's so critical in this process? >> Yeah, so let's think about how data acquisition has evolved through the years. 15 years ago, data acquisition was about how do I get data in and out of my ERP system? And that was pretty much solved. Then the mobile revolution happens. And suddenly you've got structured and non-structured data. More than you've ever dealt with. And now you get to where we are today. You're talking terabytes, petabytes of data. >> [Katie] Yottabytes, I heard that word the other day. >> I heard that too. >> Didn't even know what it meant. >> You know how many zeros that is? >> I thought we were in Star Wars. >> Yeah, I think it's a lot of zeroes. >> Yodabytes, it's new. >> So, it's becoming more and more complex in terms of how you acquire data. So that's the new data landscape that every client is dealing with. And if you don't have a strategy for how you acquire that and manage it, you're not going to get to that AI future. >> So a natural segue, if you are one of these businesses, how do you build for the data landscape? >> Yeah, so the question I always hear from customers is we need to evolve our data architecture to be ready for AI. And the way I think about that is it's really about moving from static data repositories to more of a fluid data layer. >> And we continue with the architecture. New data architecture is an interesting buzz word to hear. But it's also one of the four pillars. So if you could dive in there. >> Yeah, I mean it's a new twist on what I would call some core data science concepts. For example, you have to leverage tools with a modern, centralized data warehouse. But your data warehouse can't be stagnant to just what's right there. So you need a way to federate data across different environments. You need to be able to bring your analytics to the data because it's most efficient that way. And ultimately, it's about building an optimized data platform that is designed for data science and AI. Which means it has to be a lot more flexible than what clients have had in the past. >> All right. So we've laid out what you need for driving automation. But where does the machine learning kick in? >> Machine learning is what gives you the ability to automate tasks. And I think about machine learning. It's about predicting and automating. And this will really change the roles of data professionals and IT professionals. For example, a data scientist cannot possibly know every algorithm or every model that they could use. So we can automate the process of algorithm selection. Another example is things like automated data matching. Or metadata creation. Some of these things may not be exciting but they're hugely practical. And so when you think about the real use cases that are driving return on investment today, it's things like that. It's automating the mundane tasks. >> Let's go ahead and come back to something that you mentioned earlier because it's fascinating to be talking about this AI journey, but also significant is the new job roles. And what are those other participants in the analytics pipeline? >> Yeah I think we're just at the start of this idea of new job roles. We have data scientists. We have data engineers. Now you see machine learning engineers. Application developers. What's really happening is that data scientists are no longer allowed to work in their own silo. And so the new job roles is about how does everybody have data first in their mind? And then they're using tools to automate data science, to automate building machine learning into applications. So roles are going to change dramatically in organizations. >> I think that's confusing though because we have several organizations who saying is that highly specialized roles, just for data science? Or is it applicable to everybody across the board? >> Yeah, and that's the big question, right? Cause everybody's thinking how will this apply? Do I want this to be just a small set of people in the organization that will do this? But, our view is data science has to for everybody. It's about bring data science to everybody as a shared mission across the organization. Everybody in the company has to be data literate. And participate in this journey. >> So overall, group effort, has to be a common goal, and we all need to be data literate across the board. >> Absolutely. >> Done deal. But at the end of the day, it's kind of not an easy task. >> It's not. It's not easy but it's maybe not as big of a shift as you would think. Because you have to put data in the hands of people that can do something with it. So, it's very basic. Give access to data. Data's often locked up in a lot of organizations today. Give people the right tools. Embrace the idea of choice or diversity in terms of those tools. That gets you started on this path. >> It's interesting to hear you say essentially you need to train everyone though across the board when it comes to data literacy. And I think people that are coming into the work force don't necessarily have a background or a degree in data science. So how do you manage? >> Yeah, so in many cases that's true. I will tell you some universities are doing amazing work here. One example, University of California Berkeley. They offer a course for all majors. So no matter what you're majoring in, you have a course on foundations of data science. How do you bring data science to every role? So it's starting to happen. We at IBM provide data science courses through CognitiveClass.ai. It's for everybody. It's free. And look, if you want to get your hands on code and just dive right in, you go to datascience.ibm.com. The key point is this though. It's more about attitude than it is aptitude. I think anybody can figure this out. But it's about the attitude to say we're putting data first and we're going to figure out how to make this real in our organization. >> I also have to give a shout out to my alma mater because I have heard that there is an offering in MS in data analytics. And they are always on the forefront of new technologies and new majors and on trend. And I've heard that the placement behind those jobs, people graduating with the MS is high. >> I'm sure it's very high. >> So go Tigers. All right, tangential. Let me get back to something else you touched on earlier because you mentioned that a number of customers ask you how in the world do I get started with AI? It's an overwhelming question. Where do you even begin? What do you tell them? >> Yeah, well things are moving really fast. But the good thing is most organizations I see, they're already on the path, even if they don't know it. They might have a BI practice in place. They've got data warehouses. They've got data lakes. Let me give you an example. AMC Networks. They produce a lot of the shows that I'm sure you watch Katie. >> [Katie] Yes, Breaking Bad, Walking Dead, any fans? >> [Rob] Yeah, we've got a few. >> [Katie] Well you taught me something I didn't even know. Because it's amazing how we have all these different industries, but yet media in itself is impacted too. And this is a good example. >> Absolutely. So, AMC Networks, think about it. They've got ads to place. They want to track viewer behavior. What do people like? What do they dislike? So they have to optimize every aspect of their business from marketing campaigns to promotions to scheduling to ads. And their goal was transform data into business insights and really take the burden off of their IT team that was heavily burdened by obviously a huge increase in data. So their VP of BI took the approach of using machine learning to process large volumes of data. They used a platform that was designed for AI and data processing. It's the IBM analytics system where it's a data warehouse, data science tools are built in. It has in memory data processing. And just like that, they were ready for AI. And they're already seeing that impact in their business. >> Do you think a movement of that nature kind of presses other media conglomerates and organizations to say we need to be doing this too? >> I think it's inevitable that everybody, you're either going to be playing, you're either going to be leading, or you'll be playing catch up. And so, as we talk to clients we think about how do you start down this path now, even if you have to iterate over time? Because otherwise you're going to wake up and you're going to be behind. >> One thing worth noting is we've talked about analytics to the data. It's analytics first to the data, not the other way around. >> Right. So, look. We as a practice, we say you want to bring data to where the data sits. Because it's a lot more efficient that way. It gets you better outcomes in terms of how you train models and it's more efficient. And we think that leads to better outcomes. Other organization will say, "Hey move the data around." And everything becomes a big data movement exercise. But once an organization has started down this path, they're starting to get predictions, they want to do it where it's really easy. And that means analytics applied right where the data sits. >> And worth talking about the role of the data scientist in all of this. It's been called the hot job of the decade. And a Harvard Business Review even dubbed it the sexiest job of the 21st century. >> Yes. >> I want to see this on the cover of Vogue. Like I want to see the first data scientist. Female preferred, on the cover of Vogue. That would be amazing. >> Perhaps you can. >> People agree. So what changes for them? Is this challenging in terms of we talk data science for all. Where do all the data science, is it data science for everyone? And how does it change everything? >> Well, I think of it this way. AI gives software super powers. It really does. It changes the nature of software. And at the center of that is data scientists. So, a data scientist has a set of powers that they've never had before in any organization. And that's why it's a hot profession. Now, on one hand, this has been around for a while. We've had actuaries. We've had statisticians that have really transformed industries. But there are a few things that are new now. We have new tools. New languages. Broader recognition of this need. And while it's important to recognize this critical skill set, you can't just limit it to a few people. This is about scaling it across the organization. And truly making it accessible to all. >> So then do we need more data scientists? Or is this something you train like you said, across the board? >> Well, I think you want to do a little bit of both. We want more. But, we can also train more and make the ones we have more productive. The way I think about it is there's kind of two markets here. And we call it clickers and coders. >> [Katie] I like that. That's good. >> So, let's talk about what that means. So clickers are basically somebody that wants to use tools. Create models visually. It's drag and drop. Something that's very intuitive. Those are the clickers. Nothing wrong with that. It's been valuable for years. There's a new crop of data scientists. They want to code. They want to build with the latest open source tools. They want to write in Python or R. These are the coders. And both approaches are viable. Both approaches are critical. Organizations have to have a way to meet the needs of both of those types. And there's not a lot of things available today that do that. >> Well let's keep going on that. Because I hear you talking about the data scientists role and how it's critical to success, but with the new tools, data science and analytics skills can extend beyond the domain of just the data scientist. >> That's right. So look, we're unifying coders and clickers into a single platform, which we call IBM Data Science Experience. And as the demand for data science expertise grows, so does the need for these kind of tools. To bring them into the same environment. And my view is if you have the right platform, it enables the organization to collaborate. And suddenly you've changed the nature of data science from an individual sport to a team sport. >> So as somebody that, my background is in IT, the question is really is this an additional piece of what IT needs to do in 2017 and beyond? Or is it just another line item to the budget? >> So I'm afraid that some people might view it that way. As just another line item. But, I would challenge that and say data science is going to reinvent IT. It's going to change the nature of IT. And every organization needs to think about what are the skills that are critical? How do we engage a broader team to do this? Because once they get there, this is the chance to reinvent how they're performing IT. >> [Katie] Challenging or not? >> Look it's all a big challenge. Think about everything IT organizations have been through. Some of them were late to things like mobile, but then they caught up. Some were late to cloud, but then they caught up. I would just urge people, don't be late to data science. Use this as your chance to reinvent IT. Start with this notion of clickers and coders. This is a seminal moment. Much like mobile and cloud was. So don't be late. >> And I think it's critical because it could be so costly to wait. And Rob and I were even chatting earlier how data analytics is just moving into all different kinds of industries. And I can tell you even personally being effected by how important the analysis is in working in pediatric cancer for the last seven years. I personally implement virtual reality headsets to pediatric cancer hospitals across the country. And it's great. And it's working phenomenally. And the kids are amazed. And the staff is amazed. But the phase two of this project is putting in little metrics in the hardware that gather the breathing, the heart rate to show that we have data. Proof that we can hand over to the hospitals to continue making this program a success. So just in-- >> That's a great example. >> An interesting example. >> Saving lives? >> Yes. >> That's also applying a lot of what we talked about. >> Exciting stuff in the world of data science. >> Yes. Look, I just add this is an existential moment for every organization. Because what you do in this area is probably going to define how competitive you are going forward. And think about if you don't do something. What if one of your competitors goes and creates an application that's more engaging with clients? So my recommendation is start small. Experiment. Learn. Iterate on projects. Define the business outcomes. Then scale up. It's very doable. But you've got to take the first step. >> First step always critical. And now we're going to get to the fun hands on part of our story. Because in just a moment we're going to take a closer look at what data science can deliver. And where organizations are trying to get to. All right. Thank you Rob and now we've been joined by Siva Anne who is going to help us navigate this demo. First, welcome Siva. Give him a big round of applause. Yeah. All right, Rob break down what we're going to be looking at. You take over this demo. >> All right. So this is going to be pretty interesting. So Siva is going to take us through. So he's going to play the role of a financial adviser. Who wants to help better serve clients through recommendations. And I'm going to really illustrate three things. One is how do you federate data from multiple data sources? Inside the firewall, outside the firewall. How do you apply machine learning to predict and to automate? And then how do you move analytics closer to your data? So, what you're seeing here is a custom application for an investment firm. So, Siva, our financial adviser, welcome. So you can see at the top, we've got market data. We pulled that from an external source. And then we've got Siva's calendar in the middle. He's got clients on the right side. So page down, what else do you see down there Siva? >> [Siva] I can see the recent market news. And in here I can see that JP Morgan is calling for a US dollar rebound in the second half of the year. And, I have upcoming meeting with Leo Rakes. I can get-- >> [Rob] So let's go in there. Why don't you click on Leo Rakes. So, you're sitting at your desk, you're deciding how you're going to spend the day. You know you have a meeting with Leo. So you click on it. You immediately see, all right, so what do we know about him? We've got data governance implemented. So we know his age, we know his degree. We can see he's not that aggressive of a trader. Only six trades in the last few years. But then where it gets interesting is you go to the bottom. You start to see predicted industry affinity. Where did that come from? How do we have that? >> [Siva] So these green lines and red arrows here indicate the trending affinity of Leo Rakes for particular industry stocks. What we've done here is we've built machine learning models using customer's demographic data, his stock portfolios, and browsing behavior to build a model which can predict his affinity for a particular industry. >> [Rob] Interesting. So, I like to think of this, we call it celebrity experiences. So how do you treat every customer like they're a celebrity? So to some extent, we're reading his mind. Because without asking him, we know that he's going to have an affinity for auto stocks. So we go down. Now we look at his portfolio. You can see okay, he's got some different holdings. He's got Amazon, Google, Apple, and then he's got RACE, which is the ticker for Ferrari. You can see that's done incredibly well. And so, as a financial adviser, you look at this and you say, all right, we know he loves auto stocks. Ferrari's done very well. Let's create a hedge. Like what kind of security would interest him as a hedge against his position for Ferrari? Could we go figure that out? >> [Siva] Yes. Given I know that he's gotten an affinity for auto stocks, and I also see that Ferrari has got some terminus gains, I want to lock in these gains by hedging. And I want to do that by picking a auto stock which has got negative correlation with Ferrari. >> [Rob] So this is where we get to the idea of in database analytics. Cause you start clicking that and immediately we're getting instant answers of what's happening. So what did we find here? We're going to compare Ferrari and Honda. >> [Siva] I'm going to compare Ferrari with Honda. And what I see here instantly is that Honda has got a negative correlation with Ferrari, which makes it a perfect mix for his stock portfolio. Given he has an affinity for auto stocks and it correlates negatively with Ferrari. >> [Rob] These are very powerful tools at the hand of a financial adviser. You think about it. As a financial adviser, you wouldn't think about federating data, machine learning, pretty powerful. >> [Siva] Yes. So what we have seen here is that using the common SQL engine, we've been able to federate queries across multiple data sources. Db2 Warehouse in the cloud, IBM's Integrated Analytic System, and Hortonworks powered Hadoop platform for the new speeds. We've been able to use machine learning to derive innovative insights about his stock affinities. And drive the machine learning into the appliance. Closer to where the data resides to deliver high performance analytics. >> [Rob] At scale? >> [Siva] We're able to run millions of these correlations across stocks, currency, other factors. And even score hundreds of customers for their affinities on a daily basis. >> That's great. Siva, thank you for playing the role of financial adviser. So I just want to recap briefly. Cause this really powerful technology that's really simple. So we federated, we aggregated multiple data sources from all over the web and internal systems. And public cloud systems. Machine learning models were built that predicted Leo's affinity for a certain industry. In this case, automotive. And then you see when you deploy analytics next to your data, even a financial adviser, just with the click of a button is getting instant answers so they can go be more productive in their next meeting. This whole idea of celebrity experiences for your customer, that's available for everybody, if you take advantage of these types of capabilities. Katie, I'll hand it back to you. >> Good stuff. Thank you Rob. Thank you Siva. Powerful demonstration on what we've been talking about all afternoon. And thank you again to Siva for helping us navigate. Should be give him one more round of applause? We're going to be back in just a moment to look at how we operationalize all of this data. But in first, here's a message from me. If you're a part of a line of business, your main fear is disruption. You know data is the new goal that can create huge amounts of value. So does your competition. And they may be beating you to it. You're convinced there are new business models and revenue sources hidden in all the data. You just need to figure out how to leverage it. But with the scarcity of data scientists, you really can't rely solely on them. You may need more people throughout the organization that have the ability to extract value from data. And as a data science leader or data scientist, you have a lot of the same concerns. You spend way too much time looking for, prepping, and interpreting data and waiting for models to train. You know you need to operationalize the work you do to provide business value faster. What you want is an easier way to do data prep. And rapidly build models that can be easily deployed, monitored and automatically updated. So whether you're a data scientist, data science leader, or in a line of business, what's the solution? What'll it take to transform the way you work? That's what we're going to explore next. All right, now it's time to delve deeper into the nuts and bolts. The nitty gritty of operationalizing data science and creating a data driven culture. How do you actually do that? Well that's what these experts are here to share with us. I'm joined by Nir Kaldero, who's head of data science at Galvanize, which is an education and training organization. Tricia Wang, who is co-founder of Sudden Compass, a consultancy that helps companies understand people with data. And last, but certainly not least, Michael Li, founder and CEO of Data Incubator, which is a data science train company. All right guys. Shall we get right to it? >> All right. >> So data explosion happening right now. And we are seeing it across the board. I just shared an example of how it's impacting my philanthropic work in pediatric cancer. But you guys each have so many unique roles in your business life. How are you seeing it just blow up in your fields? Nir, your thing? >> Yeah, for example like in Galvanize we train many Fortune 500 companies. And just by looking at the demand of companies that wants us to help them go through this digital transformation is mind-blowing. Data point by itself. >> Okay. Well what we're seeing what's going on is that data science like as a theme, is that it's actually for everyone now. But what's happening is that it's actually meeting non technical people. But what we're seeing is that when non technical people are implementing these tools or coming at these tools without a base line of data literacy, they're often times using it in ways that distance themselves from the customer. Because they're implementing data science tools without a clear purpose, without a clear problem. And so what we do at Sudden Compass is that we work with companies to help them embrace and understand the complexity of their customers. Because often times they are misusing data science to try and flatten their understanding of the customer. As if you can just do more traditional marketing. Where you're putting people into boxes. And I think the whole ROI of data is that you can now understand people's relationships at a much more complex level at a greater scale before. But we have to do this with basic data literacy. And this has to involve technical and non technical people. >> Well you can have all the data in the world, and I think it speaks to, if you're not doing the proper movement with it, forget it. It means nothing at the same time. >> No absolutely. I mean, I think that when you look at the huge explosion in data, that comes with it a huge explosion in data experts. Right, we call them data scientists, data analysts. And sometimes they're people who are very, very talented, like the people here. But sometimes you have people who are maybe re-branding themselves, right? Trying to move up their title one notch to try to attract that higher salary. And I think that that's one of the things that customers are coming to us for, right? They're saying, hey look, there are a lot of people that call themselves data scientists, but we can't really distinguish. So, we have sort of run a fellowship where you help companies hire from a really talented group of folks, who are also truly data scientists and who know all those kind of really important data science tools. And we also help companies internally. Fortune 500 companies who are looking to grow that data science practice that they have. And we help clients like McKinsey, BCG, Bain, train up their customers, also their clients, also their workers to be more data talented. And to build up that data science capabilities. >> And Nir, this is something you work with a lot. A lot of Fortune 500 companies. And when we were speaking earlier, you were saying many of these companies can be in a panic. >> Yeah. >> Explain that. >> Yeah, so you know, not all Fortune 500 companies are fully data driven. And we know that the winners in this fourth industrial revolution, which I like to call the machine intelligence revolution, will be companies who navigate and transform their organization to unlock the power of data science and machine learning. And the companies that are not like that. Or not utilize data science and predictive power well, will pretty much get shredded. So they are in a panic. >> Tricia, companies have to deal with data behind the firewall and in the new multi cloud world. How do organizations start to become driven right to the core? >> I think the most urgent question to become data driven that companies should be asking is how do I bring the complex reality that our customers are experiencing on the ground in to a corporate office? Into the data models. So that question is critical because that's how you actually prevent any big data disasters. And that's how you leverage big data. Because when your data models are really far from your human models, that's when you're going to do things that are really far off from how, it's going to not feel right. That's when Tesco had their terrible big data disaster that they're still recovering from. And so that's why I think it's really important to understand that when you implement big data, you have to further embrace thick data. The qualitative, the emotional stuff, that is difficult to quantify. But then comes the difficult art and science that I think is the next level of data science. Which is that getting non technical and technical people together to ask how do we find those unknown nuggets of insights that are difficult to quantify? Then, how do we do the next step of figuring out how do you mathematically scale those insights into a data model? So that actually is reflective of human understanding? And then we can start making decisions at scale. But you have to have that first. >> That's absolutely right. And I think that when we think about what it means to be a data scientist, right? I always think about it in these sort of three pillars. You have the math side. You have to have that kind of stats, hardcore machine learning background. You have the programming side. You don't work with small amounts of data. You work with large amounts of data. You've got to be able to type the code to make those computers run. But then the last part is that human element. You have to understand the domain expertise. You have to understand what it is that I'm actually analyzing. What's the business proposition? And how are the clients, how are the users actually interacting with the system? That human element that you were talking about. And I think having somebody who understands all of those and not just in isolation, but is able to marry that understanding across those different topics, that's what makes a data scientist. >> But I find that we don't have people with those skill sets. And right now the way I see teams being set up inside companies is that they're creating these isolated data unicorns. These data scientists that have graduated from your programs, which are great. But, they don't involve the people who are the domain experts. They don't involve the designers, the consumer insight people, the people, the salespeople. The people who spend time with the customers day in and day out. Somehow they're left out of the room. They're consulted, but they're not a stakeholder. >> Can I actually >> Yeah, yeah please. >> Can I actually give a quick example? So for example, we at Galvanize train the executives and the managers. And then the technical people, the data scientists and the analysts. But in order to actually see all of the RY behind the data, you also have to have a creative fluid conversation between non technical and technical people. And this is a major trend now. And there's a major gap. And we need to increase awareness and kind of like create a new, kind of like environment where technical people also talks seamlessly with non technical ones. >> [Tricia] We call-- >> That's one of the things that we see a lot. Is one of the trends in-- >> A major trend. >> data science training is it's not just for the data science technical experts. It's not just for one type of person. So a lot of the training we do is sort of data engineers. People who are more on the software engineering side learning more about the stats of math. And then people who are sort of traditionally on the stat side learning more about the engineering. And then managers and people who are data analysts learning about both. >> Michael, I think you said something that was of interest too because I think we can look at IBM Watson as an example. And working in healthcare. The human component. Because often times we talk about machine learning and AI, and data and you get worried that you still need that human component. Especially in the world of healthcare. And I think that's a very strong point when it comes to the data analysis side. Is there any particular example you can speak to of that? >> So I think that there was this really excellent paper a while ago talking about all the neuro net stuff and trained on textual data. So looking at sort of different corpuses. And they found that these models were highly, highly sexist. They would read these corpuses and it's not because neuro nets themselves are sexist. It's because they're reading the things that we write. And it turns out that we write kind of sexist things. And they would sort of find all these patterns in there that were sort of latent, that had a lot of sort of things that maybe we would cringe at if we sort of saw. And I think that's one of the really important aspects of the human element, right? It's being able to come in and sort of say like, okay, I know what the biases of the system are, I know what the biases of the tools are. I need to figure out how to use that to make the tools, make the world a better place. And like another area where this comes up all the time is lending, right? So the federal government has said, and we have a lot of clients in the financial services space, so they're constantly under these kind of rules that they can't make discriminatory lending practices based on a whole set of protected categories. Race, sex, gender, things like that. But, it's very easy when you train a model on credit scores to pick that up. And then to have a model that's inadvertently sexist or racist. And that's where you need the human element to come back in and say okay, look, you're using the classic example would be zip code, you're using zip code as a variable. But when you look at it, zip codes actually highly correlated with race. And you can't do that. So you may inadvertently by sort of following the math and being a little naive about the problem, inadvertently introduce something really horrible into a model and that's where you need a human element to sort of step in and say, okay hold on. Slow things down. This isn't the right way to go. >> And the people who have -- >> I feel like, I can feel her ready to respond. >> Yes, I'm ready. >> She's like let me have at it. >> And the people here it is. And the people who are really great at providing that human intelligence are social scientists. We are trained to look for bias and to understand bias in data. Whether it's quantitative or qualitative. And I really think that we're going to have less of these kind of problems if we had more integrated teams. If it was a mandate from leadership to say no data science team should be without a social scientist, ethnographer, or qualitative researcher of some kind, to be able to help see these biases. >> The talent piece is actually the most crucial-- >> Yeah. >> one here. If you look about how to enable machine intelligence in organization there are the pillars that I have in my head which is the culture, the talent and the technology infrastructure. And I believe and I saw in working very closely with the Fortune 100 and 200 companies that the talent piece is actually the most important crucial hard to get. >> [Tricia] I totally agree. >> It's absolutely true. Yeah, no I mean I think that's sort of like how we came up with our business model. Companies were basically saying hey, I can't hire data scientists. And so we have a fellowship where we get 2,000 applicants each quarter. We take the top 2% and then we sort of train them up. And we work with hiring companies who then want to hire from that population. And so we're sort of helping them solve that problem. And the other half of it is really around training. Cause with a lot of industries, especially if you're sort of in a more regulated industry, there's a lot of nuances to what you're doing. And the fastest way to develop that data science or AI talent may not necessarily be to hire folks who are coming out of a PhD program. It may be to take folks internally who have a lot of that domain knowledge that you have and get them trained up on those data science techniques. So we've had large insurance companies come to us and say hey look, we hire three or four folks from you a quarter. That doesn't move the needle for us. What we really need is take the thousand actuaries and statisticians that we have and get all of them trained up to become a data scientist and become data literate in this new open source world. >> [Katie] Go ahead. >> All right, ladies first. >> Go ahead. >> Are you sure? >> No please, fight first. >> Go ahead. >> Go ahead Nir. >> So this is actually a trend that we have been seeing in the past year or so that companies kind of like start to look how to upscale and look for talent within the organization. So they can actually move them to become more literate and navigate 'em from analyst to data scientist. And from data scientist to machine learner. So this is actually a trend that is happening already for a year or so. >> Yeah, but I also find that after they've gone through that training in getting people skilled up in data science, the next problem that I get is executives coming to say we've invested in all of this. We're still not moving the needle. We've already invested in the right tools. We've gotten the right skills. We have enough scale of people who have these skills. Why are we not moving the needle? And what I explain to them is look, you're still making decisions in the same way. And you're still not involving enough of the non technical people. Especially from marketing, which is now, the CMO's are much more responsible for driving growth in their companies now. But often times it's so hard to change the old way of marketing, which is still like very segmentation. You know, demographic variable based, and we're trying to move people to say no, you have to understand the complexity of customers and not put them in boxes. >> And I think underlying a lot of this discussion is this question of culture, right? >> Yes. >> Absolutely. >> How do you build a data driven culture? And I think that that culture question, one of the ways that comes up quite often in especially in large, Fortune 500 enterprises, is that they are very, they're not very comfortable with sort of example, open source architecture. Open source tools. And there is some sort of residual bias that that's somehow dangerous. So security vulnerability. And I think that that's part of the cultural challenge that they often have in terms of how do I build a more data driven organization? Well a lot of the talent really wants to use these kind of tools. And I mean, just to give you an example, we are partnering with one of the major cloud providers to sort of help make open source tools more user friendly on their platform. So trying to help them attract the best technologists to use their platform because they want and they understand the value of having that kind of open source technology work seamlessly on their platforms. So I think that just sort of goes to show you how important open source is in this movement. And how much large companies and Fortune 500 companies and a lot of the ones we work with have to embrace that. >> Yeah, and I'm seeing it in our work. Even when we're working with Fortune 500 companies, is that they've already gone through the first phase of data science work. Where I explain it was all about the tools and getting the right tools and architecture in place. And then companies started moving into getting the right skill set in place. Getting the right talent. And what you're talking about with culture is really where I think we're talking about the third phase of data science, which is looking at communication of these technical frameworks so that we can get non technical people really comfortable in the same room with data scientists. That is going to be the phase, that's really where I see the pain point. And that's why at Sudden Compass, we're really dedicated to working with each other to figure out how do we solve this problem now? >> And I think that communication between the technical stakeholders and management and leadership. That's a very critical piece of this. You can't have a successful data science organization without that. >> Absolutely. >> And I think that actually some of the most popular trainings we've had recently are from managers and executives who are looking to say, how do I become more data savvy? How do I figure out what is this data science thing and how do I communicate with my data scientists? >> You guys made this way too easy. I was just going to get some popcorn and watch it play out. >> Nir, last 30 seconds. I want to leave you with an opportunity to, anything you want to add to this conversation? >> I think one thing to conclude is to say that companies that are not data driven is about time to hit refresh and figure how they transition the organization to become data driven. To become agile and nimble so they can actually see what opportunities from this important industrial revolution. Otherwise, unfortunately they will have hard time to survive. >> [Katie] All agreed? >> [Tricia] Absolutely, you're right. >> Michael, Trish, Nir, thank you so much. Fascinating discussion. And thank you guys again for joining us. We will be right back with another great demo. Right after this. >> Thank you Katie. >> Once again, thank you for an excellent discussion. Weren't they great guys? And thank you for everyone who's tuning in on the live webcast. As you can hear, we have an amazing studio audience here. And we're going to keep things moving. I'm now joined by Daniel Hernandez and Siva Anne. And we're going to turn our attention to how you can deliver on what they're talking about using data science experience to do data science faster. >> Thank you Katie. Siva and I are going to spend the next 10 minutes showing you how you can deliver on what they were saying using the IBM Data Science Experience to do data science faster. We'll demonstrate through new features we introduced this week how teams can work together more effectively across the entire analytics life cycle. How you can take advantage of any and all data no matter where it is and what it is. How you could use your favorite tools from open source. And finally how you could build models anywhere and employ them close to where your data is. Remember the financial adviser app Rob showed you? To build an app like that, we needed a team of data scientists, developers, data engineers, and IT staff to collaborate. We do this in the Data Science Experience through a concept we call projects. When I create a new project, I can now use the new Github integration feature. We're doing for data science what we've been doing for developers for years. Distributed teams can work together on analytics projects. And take advantage of Github's version management and change management features. This is a huge deal. Let's explore the project we created for the financial adviser app. As you can see, our data engineer Joane, our developer Rob, and others are collaborating this project. Joane got things started by bringing together the trusted data sources we need to build the app. Taking a closer look at the data, we see that our customer and profile data is stored on our recently announced IBM Integrated Analytics System, which runs safely behind our firewall. We also needed macro economic data, which she was able to find in the Federal Reserve. And she stored it in our Db2 Warehouse on Cloud. And finally, she selected stock news data from NASDAQ.com and landed that in a Hadoop cluster, which happens to be powered by Hortonworks. We added a new feature to the Data Science Experience so that when it's installed with Hortonworks, it automatically uses a need of security and governance controls within the cluster so your data is always secure and safe. Now we want to show you the news data we stored in the Hortonworks cluster. This is the mean administrative console. It's powered by an open source project called Ambari. And here's the news data. It's in parquet files stored in HDFS, which happens to be a distributive file system. To get the data from NASDAQ into our cluster, we used IBM's BigIntegrate and BigQuality to create automatic data pipelines that acquire, cleanse, and ingest that news data. Once the data's available, we use IBM's Big SQL to query that data using SQL statements that are much like the ones we would use for any relation of data, including the data that we have in the Integrated Analytics System and Db2 Warehouse on Cloud. This and the federation capabilities that Big SQL offers dramatically simplifies data acquisition. Now we want to show you how we support a brand new tool that we're excited about. Since we launched last summer, the Data Science Experience has supported Jupyter and R for data analysis and visualization. In this week's update, we deeply integrated another great open source project called Apache Zeppelin. It's known for having great visualization support, advanced collaboration features, and is growing in popularity amongst the data science community. This is an example of Apache Zeppelin and the notebook we created through it to explore some of our data. Notice how wonderful and easy the data visualizations are. Now we want to walk you through the Jupyter notebook we created to explore our customer preference for stocks. We use notebooks to understand and explore data. To identify the features that have some predictive power. Ultimately, we're trying to assess what ultimately is driving customer stock preference. Here we did the analysis to identify the attributes of customers that are likely to purchase auto stocks. We used this understanding to build our machine learning model. For building machine learning models, we've always had tools integrated into the Data Science Experience. But sometimes you need to use tools you already invested in. Like our very own SPSS as well as SAS. Through new import feature, you can easily import those models created with those tools. This helps you avoid vendor lock-in, and simplify the development, training, deployment, and management of all your models. To build the models we used in app, we could have coded, but we prefer a visual experience. We used our customer profile data in the Integrated Analytic System. Used the Auto Data Preparation to cleanse our data. Choose the binary classification algorithms. Let the Data Science Experience evaluate between logistic regression and gradient boosted tree. It's doing the heavy work for us. As you can see here, the Data Science Experience generated performance metrics that show us that the gradient boosted tree is the best performing algorithm for the data we gave it. Once we save this model, it's automatically deployed and available for developers to use. Any application developer can take this endpoint and consume it like they would any other API inside of the apps they built. We've made training and creating machine learning models super simple. But what about the operations? A lot of companies are struggling to ensure their model performance remains high over time. In our financial adviser app, we know that customer data changes constantly, so we need to always monitor model performance and ensure that our models are retrained as is necessary. This is a dashboard that shows the performance of our models and lets our teams monitor and retrain those models so that they're always performing to our standards. So far we've been showing you the Data Science Experience available behind the firewall that we're using to build and train models. Through a new publish feature, you can build models and deploy them anywhere. In another environment, private, public, or anywhere else with just a few clicks. So here we're publishing our model to the Watson machine learning service. It happens to be in the IBM cloud. And also deeply integrated with our Data Science Experience. After publishing and switching to the Watson machine learning service, you can see that our stock affinity and model that we just published is there and ready for use. So this is incredibly important. I just want to say it again. The Data Science Experience allows you to train models behind your own firewall, take advantage of your proprietary and sensitive data, and then deploy those models wherever you want with ease. So summarize what we just showed you. First, IBM's Data Science Experience supports all teams. You saw how our data engineer populated our project with trusted data sets. Our data scientists developed, trained, and tested a machine learning model. Our developers used APIs to integrate machine learning into their apps. And how IT can use our Integrated Model Management dashboard to monitor and manage model performance. Second, we support all data. On premises, in the cloud, structured, unstructured, inside of your firewall, and outside of it. We help you bring analytics and governance to where your data is. Third, we support all tools. The data science tools that you depend on are readily available and deeply integrated. This includes capabilities from great partners like Hortonworks. And powerful tools like our very own IBM SPSS. And fourth, and finally, we support all deployments. You can build your models anywhere, and deploy them right next to where your data is. Whether that's in the public cloud, private cloud, or even on the world's most reliable transaction platform, IBM z. So see for yourself. Go to the Data Science Experience website, take us for a spin. And if you happen to be ready right now, our recently created Data Science Elite Team can help you get started and run experiments alongside you with no charge. Thank you very much. >> Thank you very much Daniel. It seems like a great time to get started. And thanks to Siva for taking us through it. Rob and I will be back in just a moment to add some perspective right after this. All right, once again joined by Rob Thomas. And Rob obviously we got a lot of information here. >> Yes, we've covered a lot of ground. >> This is intense. You got to break it down for me cause I think we zoom out and see the big picture. What better data science can deliver to a business? Why is this so important? I mean we've heard it through and through. >> Yeah, well, I heard it a couple times. But it starts with businesses have to embrace a data driven culture. And it is a change. And we need to make data accessible with the right tools in a collaborative culture because we've got diverse skill sets in every organization. But data driven companies succeed when data science tools are in the hands of everyone. And I think that's a new thought. I think most companies think just get your data scientist some tools, you'll be fine. This is about tools in the hands of everyone. I think the panel did a great job of describing about how we get to data science for all. Building a data culture, making it a part of your everyday operations, and the highlights of what Daniel just showed us, that's some pretty cool features for how organizations can get to this, which is you can see IBM's Data Science Experience, how that supports all teams. You saw data analysts, data scientists, application developer, IT staff, all working together. Second, you saw how we support all tools. And your choice of tools. So the most popular data science libraries integrated into one platform. And we saw some new capabilities that help companies avoid lock-in, where you can import existing models created from specialist tools like SPSS or others. And then deploy them and manage them inside of Data Science Experience. That's pretty interesting. And lastly, you see we continue to build on this best of open tools. Partnering with companies like H2O, Hortonworks, and others. Third, you can see how you use all data no matter where it lives. That's a key challenge every organization's going to face. Private, public, federating all data sources. We announced new integration with the Hortonworks data platform where we deploy machine learning models where your data resides. That's been a key theme. Analytics where the data is. And lastly, supporting all types of deployments. Deploy them in your Hadoop cluster. Deploy them in your Integrated Analytic System. Or deploy them in z, just to name a few. A lot of different options here. But look, don't believe anything I say. Go try it for yourself. Data Science Experience, anybody can use it. Go to datascience.ibm.com and look, if you want to start right now, we just created a team that we call Data Science Elite. These are the best data scientists in the world that will come sit down with you and co-create solutions, models, and prove out a proof of concept. >> Good stuff. Thank you Rob. So you might be asking what does an organization look like that embraces data science for all? And how could it transform your role? I'm going to head back to the office and check it out. Let's start with the perspective of the line of business. What's changed? Well, now you're starting to explore new business models. You've uncovered opportunities for new revenue sources and all that hidden data. And being disrupted is no longer keeping you up at night. As a data science leader, you're beginning to collaborate with a line of business to better understand and translate the objectives into the models that are being built. Your data scientists are also starting to collaborate with the less technical team members and analysts who are working closest to the business problem. And as a data scientist, you stop feeling like you're falling behind. Open source tools are keeping you current. You're also starting to operationalize the work that you do. And you get to do more of what you love. Explore data, build models, put your models into production, and create business impact. All in all, it's not a bad scenario. Thanks. All right. We are back and coming up next, oh this is a special time right now. Cause we got a great guest speaker. New York Magazine called him the spreadsheet psychic and number crunching prodigy who went from correctly forecasting baseball games to correctly forecasting presidential elections. He even invented a proprietary algorithm called PECOTA for predicting future performance by baseball players and teams. And his New York Times bestselling book, The Signal and the Noise was named by Amazon.com as the number one best non-fiction book of 2012. He's currently the Editor in Chief of the award winning website, FiveThirtyEight and appears on ESPN as an on air commentator. Big round of applause. My pleasure to welcome Nate Silver. >> Thank you. We met backstage. >> Yes. >> It feels weird to re-shake your hand, but you know, for the audience. >> I had to give the intense firm grip. >> Definitely. >> The ninja grip. So you and I have crossed paths kind of digitally in the past, which it really interesting, is I started my career at ESPN. And I started as a production assistant, then later back on air for sports technology. And I go to you to talk about sports because-- >> Yeah. >> Wow, has ESPN upped their game in terms of understanding the importance of data and analytics. And what it brings. Not just to MLB, but across the board. >> No, it's really infused into the way they present the broadcast. You'll have win probability on the bottom line. And they'll incorporate FiveThirtyEight metrics into how they cover college football for example. So, ESPN ... Sports is maybe the perfect, if you're a data scientist, like the perfect kind of test case. And the reason being that sports consists of problems that have rules. And have structure. And when problems have rules and structure, then it's a lot easier to work with. So it's a great way to kind of improve your skills as a data scientist. Of course, there are also important real world problems that are more open ended, and those present different types of challenges. But it's such a natural fit. The teams. Think about the teams playing the World Series tonight. The Dodgers and the Astros are both like very data driven, especially Houston. Golden State Warriors, the NBA Champions, extremely data driven. New England Patriots, relative to an NFL team, it's shifted a little bit, the NFL bar is lower. But the Patriots are certainly very analytical in how they make decisions. So, you can't talk about sports without talking about analytics. >> And I was going to save the baseball question for later. Cause we are moments away from game seven. >> Yeah. >> Is everyone else watching game seven? It's been an incredible series. Probably one of the best of all time. >> Yeah, I mean-- >> You have a prediction here? >> You can mention that too. So I don't have a prediction. FiveThirtyEight has the Dodgers with a 60% chance of winning. >> [Katie] LA Fans. >> So you have two teams that are about equal. But the Dodgers pitching staff is in better shape at the moment. The end of a seven game series. And they're at home. >> But the statistics behind the two teams is pretty incredible. >> Yeah. It's like the first World Series in I think 56 years or something where you have two 100 win teams facing one another. There have been a lot of parity in baseball for a lot of years. Not that many offensive overall juggernauts. But this year, and last year with the Cubs and the Indians too really. But this year, you have really spectacular teams in the World Series. It kind of is a showcase of modern baseball. Lots of home runs. Lots of strikeouts. >> [Katie] Lots of extra innings. >> Lots of extra innings. Good defense. Lots of pitching changes. So if you love the modern baseball game, it's been about the best example that you've had. If you like a little bit more contact, and fewer strikeouts, maybe not so much. But it's been a spectacular and very exciting World Series. It's amazing to talk. MLB is huge with analysis. I mean, hands down. But across the board, if you can provide a few examples. Because there's so many teams in front offices putting such an, just a heavy intensity on the analysis side. And where the teams are going. And if you could provide any specific examples of teams that have really blown your mind. Especially over the last year or two. Because every year it gets more exciting if you will. I mean, so a big thing in baseball is defensive shifts. So if you watch tonight, you'll probably see a couple of plays where if you're used to watching baseball, a guy makes really solid contact. And there's a fielder there that you don't think should be there. But that's really very data driven where you analyze where's this guy hit the ball. That part's not so hard. But also there's game theory involved. Because you have to adjust for the fact that he knows where you're positioning the defenders. He's trying therefore to make adjustments to his own swing and so that's been a major innovation in how baseball is played. You know, how bullpens are used too. Where teams have realized that actually having a guy, across all sports pretty much, realizing the importance of rest. And of fatigue. And that you can be the best pitcher in the world, but guess what? After four or five innings, you're probably not as good as a guy who has a fresh arm necessarily. So I mean, it really is like, these are not subtle things anymore. It's not just oh, on base percentage is valuable. It really effects kind of every strategic decision in baseball. The NBA, if you watch an NBA game tonight, see how many three point shots are taken. That's in part because of data. And teams realizing hey, three points is worth more than two, once you're more than about five feet from the basket, the shooting percentage gets really flat. And so it's revolutionary, right? Like teams that will shoot almost half their shots from the three point range nowadays. Larry Bird, who wound up being one of the greatest three point shooters of all time, took only eight three pointers his first year in the NBA. It's quite noticeable if you watch baseball or basketball in particular. >> Not to focus too much on sports. One final question. In terms of Major League Soccer, and now in NFL, we're having the analysis and having wearables where it can now showcase if they wanted to on screen, heart rate and breathing and how much exertion. How much data is too much data? And when does it ruin the sport? >> So, I don't think, I mean, again, it goes sport by sport a little bit. I think in basketball you actually have a more exciting game. I think the game is more open now. You have more three pointers. You have guys getting higher assist totals. But you know, I don't know. I'm not one of those people who thinks look, if you love baseball or basketball, and you go in to work for the Astros, the Yankees or the Knicks, they probably need some help, right? You really have to be passionate about that sport. Because it's all based on what questions am I asking? As I'm a fan or I guess an employee of the team. Or a player watching the game. And there isn't really any substitute I don't think for the insight and intuition that a curious human has to kind of ask the right questions. So we can talk at great length about what tools do you then apply when you have those questions, but that still comes from people. I don't think machine learning could help with what questions do I want to ask of the data. It might help you get the answers. >> If you have a mid-fielder in a soccer game though, not exerting, only 80%, and you're seeing that on a screen as a fan, and you're saying could that person get fired at the end of the day? One day, with the data? >> So we found that actually some in soccer in particular, some of the better players are actually more still. So Leo Messi, maybe the best player in the world, doesn't move as much as other soccer players do. And the reason being that A) he kind of knows how to position himself in the first place. B) he realizes that you make a run, and you're out of position. That's quite fatiguing. And particularly soccer, like basketball, is a sport where it's incredibly fatiguing. And so, sometimes the guys who conserve their energy, that kind of old school mentality, you have to hustle at every moment. That is not helpful to the team if you're hustling on an irrelevant play. And therefore, on a critical play, can't get back on defense, for example. >> Sports, but also data is moving exponentially as we're just speaking about today. Tech, healthcare, every different industry. Is there any particular that's a favorite of yours to cover? And I imagine they're all different as well. >> I mean, I do like sports. We cover a lot of politics too. Which is different. I mean in politics I think people aren't intuitively as data driven as they might be in sports for example. It's impressive to follow the breakthroughs in artificial intelligence. It started out just as kind of playing games and playing chess and poker and Go and things like that. But you really have seen a lot of breakthroughs in the last couple of years. But yeah, it's kind of infused into everything really. >> You're known for your work in politics though. Especially presidential campaigns. >> Yeah. >> This year, in particular. Was it insanely challenging? What was the most notable thing that came out of any of your predictions? >> I mean, in some ways, looking at the polling was the easiest lens to look at it. So I think there's kind of a myth that last year's result was a big shock and it wasn't really. If you did the modeling in the right way, then you realized that number one, polls have a margin of error. And so when a candidate has a three point lead, that's not particularly safe. Number two, the outcome between different states is correlated. Meaning that it's not that much of a surprise that Clinton lost Wisconsin and Michigan and Pennsylvania and Ohio. You know I'm from Michigan. Have friends from all those states. Kind of the same types of people in those states. Those outcomes are all correlated. So what people thought was a big upset for the polls I think was an example of how data science done carefully and correctly where you understand probabilities, understand correlations. Our model gave Trump a 30% chance of winning. Others models gave him a 1% chance. And so that was interesting in that it showed that number one, that modeling strategies and skill do matter quite a lot. When you have someone saying 30% versus 1%. I mean, that's a very very big spread. And number two, that these aren't like solved problems necessarily. Although again, the problem with elections is that you only have one election every four years. So I can be very confident that I have a better model. Even one year of data doesn't really prove very much. Even five or 10 years doesn't really prove very much. And so, being aware of the limitations to some extent intrinsically in elections when you only get one kind of new training example every four years, there's not really any way around that. There are ways to be more robust to sparce data environments. But if you're identifying different types of business problems to solve, figuring out what's a solvable problem where I can add value with data science is a really key part of what you're doing. >> You're such a leader in this space. In data and analysis. It would be interesting to kind of peek back the curtain, understand how you operate but also how large is your team? How you're putting together information. How quickly you're putting it out. Cause I think in this right now world where everybody wants things instantly-- >> Yeah. >> There's also, you want to be first too in the world of journalism. But you don't want to be inaccurate because that's your credibility. >> We talked about this before, right? I think on average, speed is a little bit overrated in journalism. >> [Katie] I think it's a big problem in journalism. >> Yeah. >> Especially in the tech world. You have to be first. You have to be first. And it's just pumping out, pumping out. And there's got to be more time spent on stories if I can speak subjectively. >> Yeah, for sure. But at the same time, we are reacting to the news. And so we have people that come in, we hire most of our people actually from journalism. >> [Katie] How many people do you have on your team? >> About 35. But, if you get someone who comes in from an academic track for example, they might be surprised at how fast journalism is. That even though we might be slower than the average website, the fact that there's a tragic event in New York, are there things we have to say about that? A candidate drops out of the presidential race, are things we have to say about that. In periods ranging from minutes to days as opposed to kind of weeks to months to years in the academic world. The corporate world moves faster. What is a little different about journalism is that you are expected to have more precision where people notice when you make a mistake. In corporations, you have maybe less transparency. If you make 10 investments and seven of them turn out well, then you'll get a lot of profit from that, right? In journalism, it's a little different. If you make kind of seven predictions or say seven things, and seven of them are very accurate and three of them aren't, you'll still get criticized a lot for the three. Just because that's kind of the way that journalism is. And so the kind of combination of needing, not having that much tolerance for mistakes, but also needing to be fast. That is tricky. And I criticize other journalists sometimes including for not being data driven enough, but the best excuse any journalist has, this is happening really fast and it's my job to kind of figure out in real time what's going on and provide useful information to the readers. And that's really difficult. Especially in a world where literally, I'll probably get off the stage and check my phone and who knows what President Trump will have tweeted or what things will have happened. But it really is a kind of 24/7. >> Well because it's 24/7 with FiveThirtyEight, one of the most well known sites for data, are you feeling micromanagey on your people? Because you do have to hit this balance. You can't have something come out four or five days later. >> Yeah, I'm not -- >> Are you overseeing everything? >> I'm not by nature a micromanager. And so you try to hire well. You try and let people make mistakes. And the flip side of this is that if a news organization that never had any mistakes, never had any corrections, that's raw, right? You have to have some tolerance for error because you are trying to decide things in real time. And figure things out. I think transparency's a big part of that. Say here's what we think, and here's why we think it. If we have a model to say it's not just the final number, here's a lot of detail about how that's calculated. In some case we release the code and the raw data. Sometimes we don't because there's a proprietary advantage. But quite often we're saying we want you to trust us and it's so important that you trust us, here's the model. Go play around with it yourself. Here's the data. And that's also I think an important value. >> That speaks to open source. And your perspective on that in general. >> Yeah, I mean, look, I'm a big fan of open source. I worry that I think sometimes the trends are a little bit away from open source. But by the way, one thing that happens when you share your data or you share your thinking at least in lieu of the data, and you can definitely do both is that readers will catch embarrassing mistakes that you made. By the way, even having open sourceness within your team, I mean we have editors and copy editors who often save you from really embarrassing mistakes. And by the way, it's not necessarily people who have a training in data science. I would guess that of our 35 people, maybe only five to 10 have a kind of formal background in what you would call data science. >> [Katie] I think that speaks to the theme here. >> Yeah. >> [Katie] That everybody's kind of got to be data literate. >> But yeah, it is like you have a good intuition. You have a good BS detector basically. And you have a good intuition for hey, this looks a little bit out of line to me. And sometimes that can be based on domain knowledge, right? We have one of our copy editors, she's a big college football fan. And we had an algorithm we released that tries to predict what the human being selection committee will do, and she was like, why is LSU rated so high? Cause I know that LSU sucks this year. And we looked at it, and she was right. There was a bug where it had forgotten to account for their last game where they lost to Troy or something and so -- >> That also speaks to the human element as well. >> It does. In general as a rule, if you're designing a kind of regression based model, it's different in machine learning where you have more, when you kind of build in the tolerance for error. But if you're trying to do something more precise, then so much of it is just debugging. It's saying that looks wrong to me. And I'm going to investigate that. And sometimes it's not wrong. Sometimes your model actually has an insight that you didn't have yourself. But fairly often, it is. And I think kind of what you learn is like, hey if there's something that bothers me, I want to go investigate that now and debug that now. Because the last thing you want is where all of a sudden, the answer you're putting out there in the world hinges on a mistake that you made. Cause you never know if you have so to speak, 1,000 lines of code and they all perform something differently. You never know when you get in a weird edge case where this one decision you made winds up being the difference between your having a good forecast and a bad one. In a defensible position and a indefensible one. So we definitely are quite diligent and careful. But it's also kind of knowing like, hey, where is an approximation good enough and where do I need more precision? Cause you could also drive yourself crazy in the other direction where you know, it doesn't matter if the answer is 91.2 versus 90. And so you can kind of go 91.2, three, four and it's like kind of A) false precision and B) not a good use of your time. So that's where I do still spend a lot of time is thinking about which problems are "solvable" or approachable with data and which ones aren't. And when they're not by the way, you're still allowed to report on them. We are a news organization so we do traditional reporting as well. And then kind of figuring out when do you need precision versus when is being pointed in the right direction good enough? >> I would love to get inside your brain and see how you operate on just like an everyday walking to Walgreens movement. It's like oh, if I cross the street in .2-- >> It's not, I mean-- >> Is it like maddening in there? >> No, not really. I mean, I'm like-- >> This is an honest question. >> If I'm looking for airfares, I'm a little more careful. But no, part of it's like you don't want to waste time on unimportant decisions, right? I will sometimes, if I can't decide what to eat at a restaurant, I'll flip a coin. If the chicken and the pasta both sound really good-- >> That's not high tech Nate. We want better. >> But that's the point, right? It's like both the chicken and the pasta are going to be really darn good, right? So I'm not going to waste my time trying to figure it out. I'm just going to have an arbitrary way to decide. >> Serious and business, how organizations in the last three to five years have just evolved with this data boom. How are you seeing it as from a consultant point of view? Do you think it's an exciting time? Do you think it's a you must act now time? >> I mean, we do know that you definitely see a lot of talent among the younger generation now. That so FiveThirtyEight has been at ESPN for four years now. And man, the quality of the interns we get has improved so much in four years. The quality of the kind of young hires that we make straight out of college has improved so much in four years. So you definitely do see a younger generation for which this is just part of their bloodstream and part of their DNA. And also, particular fields that we're interested in. So we're interested in people who have both a data and a journalism background. We're interested in people who have a visualization and a coding background. A lot of what we do is very much interactive graphics and so forth. And so we do see those skill sets coming into play a lot more. And so the kind of shortage of talent that had I think frankly been a problem for a long time, I'm optimistic based on the young people in our office, it's a little anecdotal but you can tell that there are so many more programs that are kind of teaching students the right set of skills that maybe weren't taught as much a few years ago. >> But when you're seeing these big organizations, ESPN as perfect example, moving more towards data and analytics than ever before. >> Yeah. >> You would say that's obviously true. >> Oh for sure. >> If you're not moving that direction, you're going to fall behind quickly. >> Yeah and the thing is, if you read my book or I guess people have a copy of the book. In some ways it's saying hey, there are lot of ways to screw up when you're using data. And we've built bad models. We've had models that were bad and got good results. Good models that got bad results and everything else. But the point is that the reason to be out in front of the problem is so you give yourself more runway to make errors and mistakes. And to learn kind of what works and what doesn't and which people to put on the problem. I sometimes do worry that a company says oh we need data. And everyone kind of agrees on that now. We need data science. Then they have some big test case. And they have a failure. And they maybe have a failure because they didn't know really how to use it well enough. But learning from that and iterating on that. And so by the time that you're on the third generation of kind of a problem that you're trying to solve, and you're watching everyone else make the mistake that you made five years ago, I mean, that's really powerful. But that doesn't mean that getting invested in it now, getting invested both in technology and the human capital side is important. >> Final question for you as we run out of time. 2018 beyond, what is your biggest project in terms of data gathering that you're working on? >> There's a midterm election coming up. That's a big thing for us. We're also doing a lot of work with NBA data. So for four years now, the NBA has been collecting player tracking data. So they have 3D cameras in every arena. So they can actually kind of quantify for example how fast a fast break is, for example. Or literally where a player is and where the ball is. For every NBA game now for the past four or five years. And there hasn't really been an overall metric of player value that's taken advantage of that. The teams do it. But in the NBA, the teams are a little bit ahead of journalists and analysts. So we're trying to have a really truly next generation stat. It's a lot of data. Sometimes I now more oversee things than I once did myself. And so you're parsing through many, many, many lines of code. But yeah, so we hope to have that out at some point in the next few months. >> Anything you've personally been passionate about that you've wanted to work on and kind of solve? >> I mean, the NBA thing, I am a pretty big basketball fan. >> You can do better than that. Come on, I want something real personal that you're like I got to crunch the numbers. >> You know, we tried to figure out where the best burrito in America was a few years ago. >> I'm going to end it there. >> Okay. >> Nate, thank you so much for joining us. It's been an absolute pleasure. Thank you. >> Cool, thank you. >> I thought we were going to chat World Series, you know. Burritos, important. I want to thank everybody here in our audience. Let's give him a big round of applause. >> [Nate] Thank you everyone. >> Perfect way to end the day. And for a replay of today's program, just head on over to ibm.com/dsforall. I'm Katie Linendoll. And this has been Data Science for All: It's a Whole New Game. Test one, two. One, two, three. Hi guys, I just want to quickly let you know as you're exiting. A few heads up. Downstairs right now there's going to be a meet and greet with Nate. And we're going to be doing that with clients and customers who are interested. So I would recommend before the game starts, and you lose Nate, head on downstairs. And also the gallery is open until eight p.m. with demos and activations. And tomorrow, make sure to come back too. Because we have exciting stuff. I'll be joining you as your host. And we're kicking off at nine a.m. So bye everybody, thank you so much. >> [Announcer] Ladies and gentlemen, thank you for attending this evening's webcast. If you are not attending all cloud and cognitive summit tomorrow, we ask that you recycle your name badge at the registration desk. Thank you. Also, please note there are two exits on the back of the room on either side of the room. Have a good evening. Ladies and gentlemen, the meet and greet will be on stage. Thank you.

Published Date : Nov 1 2017

SUMMARY :

Today the ability to extract value from data is becoming a shared mission. And for all of you during the program, I want to remind you to join that conversation on And when you and I chatted about it. And the scale and complexity of the data that organizations are having to deal with has It's challenging in the world of unmanageable. And they have to find a way. AI. And it's incredible that this buzz word is happening. And to get to an AI future, you have to lay a data foundation today. And four is you got to expand job roles in the organization. First pillar in this you just discussed. And now you get to where we are today. And if you don't have a strategy for how you acquire that and manage it, you're not going And the way I think about that is it's really about moving from static data repositories And we continue with the architecture. So you need a way to federate data across different environments. So we've laid out what you need for driving automation. And so when you think about the real use cases that are driving return on investment today, Let's go ahead and come back to something that you mentioned earlier because it's fascinating And so the new job roles is about how does everybody have data first in their mind? Everybody in the company has to be data literate. So overall, group effort, has to be a common goal, and we all need to be data literate But at the end of the day, it's kind of not an easy task. It's not easy but it's maybe not as big of a shift as you would think. It's interesting to hear you say essentially you need to train everyone though across the And look, if you want to get your hands on code and just dive right in, you go to datascience.ibm.com. And I've heard that the placement behind those jobs, people graduating with the MS is high. Let me get back to something else you touched on earlier because you mentioned that a number They produce a lot of the shows that I'm sure you watch Katie. And this is a good example. So they have to optimize every aspect of their business from marketing campaigns to promotions And so, as we talk to clients we think about how do you start down this path now, even It's analytics first to the data, not the other way around. We as a practice, we say you want to bring data to where the data sits. And a Harvard Business Review even dubbed it the sexiest job of the 21st century. Female preferred, on the cover of Vogue. And how does it change everything? And while it's important to recognize this critical skill set, you can't just limit it And we call it clickers and coders. [Katie] I like that. And there's not a lot of things available today that do that. Because I hear you talking about the data scientists role and how it's critical to success, And my view is if you have the right platform, it enables the organization to collaborate. And every organization needs to think about what are the skills that are critical? Use this as your chance to reinvent IT. And I can tell you even personally being effected by how important the analysis is in working And think about if you don't do something. And now we're going to get to the fun hands on part of our story. And then how do you move analytics closer to your data? And in here I can see that JP Morgan is calling for a US dollar rebound in the second half But then where it gets interesting is you go to the bottom. data, his stock portfolios, and browsing behavior to build a model which can predict his affinity And so, as a financial adviser, you look at this and you say, all right, we know he loves And I want to do that by picking a auto stock which has got negative correlation with Ferrari. Cause you start clicking that and immediately we're getting instant answers of what's happening. And what I see here instantly is that Honda has got a negative correlation with Ferrari, As a financial adviser, you wouldn't think about federating data, machine learning, pretty And drive the machine learning into the appliance. And even score hundreds of customers for their affinities on a daily basis. And then you see when you deploy analytics next to your data, even a financial adviser, And as a data science leader or data scientist, you have a lot of the same concerns. But you guys each have so many unique roles in your business life. And just by looking at the demand of companies that wants us to help them go through this And I think the whole ROI of data is that you can now understand people's relationships Well you can have all the data in the world, and I think it speaks to, if you're not doing And I think that that's one of the things that customers are coming to us for, right? And Nir, this is something you work with a lot. And the companies that are not like that. Tricia, companies have to deal with data behind the firewall and in the new multi cloud And so that's why I think it's really important to understand that when you implement big And how are the clients, how are the users actually interacting with the system? And right now the way I see teams being set up inside companies is that they're creating But in order to actually see all of the RY behind the data, you also have to have a creative That's one of the things that we see a lot. So a lot of the training we do is sort of data engineers. And I think that's a very strong point when it comes to the data analysis side. And that's where you need the human element to come back in and say okay, look, you're And the people who are really great at providing that human intelligence are social scientists. the talent piece is actually the most important crucial hard to get. It may be to take folks internally who have a lot of that domain knowledge that you have And from data scientist to machine learner. And what I explain to them is look, you're still making decisions in the same way. And I mean, just to give you an example, we are partnering with one of the major cloud And what you're talking about with culture is really where I think we're talking about And I think that communication between the technical stakeholders and management You guys made this way too easy. I want to leave you with an opportunity to, anything you want to add to this conversation? I think one thing to conclude is to say that companies that are not data driven is And thank you guys again for joining us. And we're going to turn our attention to how you can deliver on what they're talking about And finally how you could build models anywhere and employ them close to where your data is. And thanks to Siva for taking us through it. You got to break it down for me cause I think we zoom out and see the big picture. And we saw some new capabilities that help companies avoid lock-in, where you can import And as a data scientist, you stop feeling like you're falling behind. We met backstage. And I go to you to talk about sports because-- And what it brings. And the reason being that sports consists of problems that have rules. And I was going to save the baseball question for later. Probably one of the best of all time. FiveThirtyEight has the Dodgers with a 60% chance of winning. So you have two teams that are about equal. It's like the first World Series in I think 56 years or something where you have two 100 And that you can be the best pitcher in the world, but guess what? And when does it ruin the sport? So we can talk at great length about what tools do you then apply when you have those And the reason being that A) he kind of knows how to position himself in the first place. And I imagine they're all different as well. But you really have seen a lot of breakthroughs in the last couple of years. You're known for your work in politics though. What was the most notable thing that came out of any of your predictions? And so, being aware of the limitations to some extent intrinsically in elections when It would be interesting to kind of peek back the curtain, understand how you operate but But you don't want to be inaccurate because that's your credibility. I think on average, speed is a little bit overrated in journalism. And there's got to be more time spent on stories if I can speak subjectively. And so we have people that come in, we hire most of our people actually from journalism. And so the kind of combination of needing, not having that much tolerance for mistakes, Because you do have to hit this balance. And so you try to hire well. And your perspective on that in general. But by the way, one thing that happens when you share your data or you share your thinking And you have a good intuition for hey, this looks a little bit out of line to me. And I think kind of what you learn is like, hey if there's something that bothers me, It's like oh, if I cross the street in .2-- I mean, I'm like-- But no, part of it's like you don't want to waste time on unimportant decisions, right? We want better. It's like both the chicken and the pasta are going to be really darn good, right? Serious and business, how organizations in the last three to five years have just And man, the quality of the interns we get has improved so much in four years. But when you're seeing these big organizations, ESPN as perfect example, moving more towards But the point is that the reason to be out in front of the problem is so you give yourself Final question for you as we run out of time. And so you're parsing through many, many, many lines of code. You can do better than that. You know, we tried to figure out where the best burrito in America was a few years Nate, thank you so much for joining us. I thought we were going to chat World Series, you know. And also the gallery is open until eight p.m. with demos and activations. If you are not attending all cloud and cognitive summit tomorrow, we ask that you recycle your

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Simon Wardley, Leading Edge Forum | Serverlessconf 2017


 

>> Narrator: From Hell's Kitchen in New York City, it's theCUBE. On the ground at Serverlessconf. Brought to you by SiliconANGLE Media. >> Hi I'm Stu Miniman, here with theCUBE at Serverlessconf in New York City, really excited to have on the program one of the keynote speakers and a first time guest on theCUBE, it's someone I've know through the interwebs and have read his stuff for many years, Simon Wardley who's a researcher with a leading edge firm, Simon, great to see you. Thanks so much for joining us. >> Thank you ever so much for inviting me. It's a delight to be here. >> Alright, so my understanding is thanks to this event, you've reached a lifelong career goal. You're now a Sith Lord? (laughing) >> Well, somebody basically took a quote of mine and put it on a Star Wars poster with The Empire at the bottom, so yes, it is absolutely there you are, I am a Sith Lord, so delightful. >> The quote was that Serverless will just fundamentally change the architecture of how we build things. Something along those lines, I believe. >> Absolutely, yes. >> Alright, so let's start there. There are so many, come on, we all got really excited when containers came out. We're going to talk to John Willis >> You did. (laughing) >> We're going to talk about unikernels. The industry as a whole, there's frothiness and buzz >> Okay. >> So Serverless, you know, how's it different? How's it the same? Why's it so important from your standpoint? >> So, really good questions. So, to explain that question, we have to start off with a subject that is dear to my heart which is mapping. So when we look at the value chain of any organization, the components in that value chain are evolving and they evolve from the genesis, the novel and new to custom built examples and eventually products and rental services and then commodity and utility services. And that process is driven by supply and demand competition. It happens not only to activities, but to practice and data, but we give them different terms. They have all of the same characteristics as when they evolve. Now, when you look at that evolving environment, what you discover is there are two basic forms of disruption. There is the highly unpredictable form, which either occurs due to the appearance of something novel and new, which we don't know what it's going to impact or to product substitution. So that's the Nokia versus Apple, sort of battle, you don't know which way it's going to go until after the battle. And there is a second form of disruption, which is much more anticipatable or predictable and that is the product to utility change. So we know that when things evolve from product to utility we're going to see a rapid period of change and then there's a punctuated equilibrium. Explotion of higher order systems. We're going to see co-evolution of practice, disruption of past companies stuck behind inertia barriers. Yes it's going to be a bad efficiency, no we're not going to save any money 'cause we're just going to do more stuff with it and we're going to have all these new things as well. And we can anticipate that in advance. So when you start looking at value chains of organization, it's always the shift from product to commodity and utility which makes the big transformation in industry. And so one of them was compute. Shifting from products, as in servers, to utility as in cloud. Unfortunately dreadful term, cloud, an awful word, you know it's not a wispy thing up in the sky, it is something very specific, the shift from compute to utility. >> Would you put virtualization along that continuum? >> Okay, so virtualization was one of the underlying components, which actually helped with that happen. >> Yes. >> And so you've also got the explosion of practices around that co-evolution of practice, things like DevOps. Well, the same transition is now happening in the platform space. So, we're moving away from a product stack, things like, LAMP and .NET, to much more utility-based code execution environments. And that's what we're getting with Lambda. And we're going to see an explosion of new things built on top, inertia barriers, companies stuck behind, they'll die off, It'll be a rapid change punctuated equilibrium. You'll get all sorts of new things built. So we're going through that big transformation. Now, these transformations have been going on for about 300 years, some of them impact micro scale economics, some macro, the biggest we call ages. And that all depends upon how widespread that component is in other value chains, so when we're talking about software, we're talking about a component which is in almost all other value chains, it's shifting from product to utility, massive change, highly predictable. This is what Serverless is about. So, will it change everything? Absolutely it will. >> Alright, so Simon, I'm wondering, if you've mapped out for Serverless, where's the land of economic expection, the land of happiness and the land of despair? (laughing) >> Well, okay, happiness, despair and expectation? >> Yes. >> Okay interesting one. So the land of despair will be getting stuck behind the inertia barriers, dismissing it, saying it's not going to impact, it's not going to impact, no, no, because there's a punctuated equilibrium, it'll surprise you because it's an exponential growth, so you'll think you've got loads and loads of time and 10 years from now, you're like, be panicking, oh my gosh, it's impacting, I can't get the skills for people to help me do the transformation. My entire industry and business model is starting to disappear, so that is the land of despair that's coming to people, that's easy to defend against because most people can't see the environment. They're going to just walk straight into that one. The land of happiness. Well, obviously other than being the utility providers who'll be extremely happy about the growth of their industry, another area of happiness will be some of the novel and new things built on top. So, we're bound to see the, sort, of, one person, two person company who builds a fuction which is sold through something like the marketplace and everybody uses and they sell it for a billion. So, we'll get the two person billion dollar company and I'm sure that will make them delightfully happy. So, that's despair, happiness, also inflated expectations. So one of the big lies will be, Serverless is going to save me money in terms of reducing my IT budget. I'm afraid not. This is Jevons Paradox, this is being going on since 1865. All that's going to happen is yes, it becomes more efficient but we'll do more stuff because we're in competition so we'll spend exactly the same as we've always done, but just doing vastly more. But none the less, loads of consultants will write reports about how it will save you money and lots of people will be disappointed. >> I want to poke at that for a second. (laughing) I don't disagree with Javons Paradox when it comes to power, but example, say you know, our host for this event, A Cloud Guru. >> Yeah. >> They're priced to deliver per user is way lower than if they'd have done this the traditional way and I've heard many examples here at the show already where they've said, oh if I had built it this way, you know, it's now an order of magnitude less dollars, so. >> Let's forget order of mag, let's go many orders of magnitude. So from now to say the 1980s, for a thousand dollars, I can get a million times more compute resource than I could back then. Has my IT budget reduced a million fold during that time? And the answer is >> Yeah. >> What, my IT budget has reduced a million fold? >> No, no, no my IT budget has not reduced a million fold. >> Not at all, because we've just ended up doing vastly more stuff. >> Yeah, yeah. >> So the point is, yes. >> Budgets are always flat, yes. >> So the point is yes, we will be able to do the same things but more efficiently, but your IT budget doesn't reduce because we end up doing more things. So we're in competition, say, you and me and say you evolve, you use these environments you don't reduce your IT spending, you do more things, I'm now having to spend more and more just to try and keep up with you. So eventually I'm forced to adopt to that new world. So what happens is the individual acts become more efficient, but because we do more, we don't save anything. >> You know, want to look at kind of, maps versus strategy. >> Okay. >> I guess one of the things, if I'm talking to the typical Enterprise CIO or Board and they say, oh, well, a year ago I heard about Serverless, or today I heard about Serverless, you know, the strategy is going to change greatly because this is changing so rapidly, how do you help companies understand when things are changing so fast, how do I set a strategy for today? How long do I keep it? How often do I revisit it? >> So, if you map an environment, like all maps, they're dynamic, so you're constantly adapting and changing them as the environment is changing. So, when you look at, you have the purpose of your company, you have the landscape you're operating in, there are a number of climatic patents, about 30 of them, which impact that environment, will change it, so you need to understand those. Then there's sort of university useful patents known as doctrine, then there's game play. Now, for most organizations, because they cannot see the environment, they cannot distinguish, or may just be completely oblivious to any of this, so when they were talking about change, if I look at how things evolve from genesis, custom built product commodity, most organizations will go genesis, that's an innovation, every custom built feature differentiation of a product's an innovation, every shift in product to utility is an innovation, so all they see is innovation, innovation, innovation. And therefore, it's very easy to get sucked in to one size fits all methods work. One size innovation programs, where in fact, the genesis you would be using something like a lightweight XP, the product development, much more lean enterprise, so SCRUM and MVP and the utility is much more outsourcing or Six Sigma. So you should be using multiple techniques and multiple methods and most organizations aren't in that position. And if they're not in that position, of being able to see the environment, it's difficult to see where to attack, it's difficult to understand why here over there, it's difficult to manipulate the market. So, what happens is most organizations work on gut feel, whatever's popular in HPR and just act. And you can call that strategy if you wish. >> Alright, so I wish we could talk for another couple of hours, but want to give you the final take away >> Yes. >> Serverless today, how should people be thinking about it and what should they be looking for over the next six to 12 months in this space? >> So, the key thing about Serverless is we're seeing a shift from platform from product to utility, so you should be developing skills in that space. And we're seeing co-evolution of practice. By that, we mean there is a new set of practices combining finance and development together. What those practices are, we don't know yet. You have to experiment and explore. That's why attending events and being involved in building stuff will help you discover those practices. So today if your company, well it depends on your position, so if you're a company which is behind the game, you, say, haven't gone into infractructure as a service, you're not doing DevOps, you're own people are resistant to this change cause the other vendors say you're going to lose their jobs and blah, then rather then embarking on a five to seven year program, 'cause that's how long it will take to do that, you should move up the stack and start with Serverless and learning those practices. 'Cause no one knows them well, so you can take your people who've got inertia and re-train them in that space overcoming that inertia and give yourself a path forward. So, depends on your position, but I think most companies should be experimenting in this space. >> Alright, well Simon Wardley, it's a pleasure to catch up with you today. >> Delight. >> Hope to have you back on theCUBE at another event soon. Thank you so much for watching theCUBE.

Published Date : Oct 14 2017

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Brought to you by SiliconANGLE Media. really excited to have on the program It's a delight to be here. Alright, so my understanding is thanks to this event, The Empire at the bottom, so yes, it is just fundamentally change the architecture of We're going to talk to John Willis (laughing) We're going to talk about unikernels. and that is the product to utility change. the underlying components, which actually it's shifting from product to utility, I can't get the skills for people to help to power, but example, say you know, and I've heard many examples here at the show So from now to say the 1980s, reduced a million fold. Not at all, because we've just ended up So eventually I'm forced to adopt to that new world. You know, want to look at kind of, the genesis you would be using something like a so you can take your people who've got inertia to catch up Hope to have you back on theCUBE

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