(upbeat music) >> Welcome back to The Cubes coverage of WIDS 2023 the eighth Annual Women in Data Science Conference which is held at Stanford University. I'm your host, Lisa Martin. I'm really excited to be having some great co-hosts today. I've got Hannah Freytag with me, who is a data journalism master student at Stanford. We have yet another inspiring woman in technology to bring to you today. Kelly Hoang joins us, data scientist at Gilead. It's so great to have you, Kelly. >> Hi, thank you for having me today. I'm super excited to be here and share my journey with you guys. >> Let's talk about that journey. You recently got your PhD in information sciences, congratulations. >> Thank you. Yes, I just graduated, I completed my PhD in information sciences from University of Illinois Urbana-Champaign. And right now I moved to Bay Area and started my career as a data scientist at Gilead. >> And you're in better climate. Well, we do get snow here. >> Kelly: That's true. >> We proved that the last... And data science can show us all the climate change that's going on here. >> That's true. That's the topic of the data fund this year, right? To understand the changes in the climate. >> Yeah. Talk a little bit about your background. You were mentioning before we went live that you come from a whole family of STEM students. So you had that kind of in your DNA. >> Well, I consider myself maybe I was a lucky case. I did grew up in a family in the STEM environment. My dad actually was a professor in computer science. So I remember when I was at a very young age, I already see like datas, all of these computer science concepts. So grew up to be a data scientist is always something like in my mind. >> You aspired to be. >> Yes. >> I love that. >> So I consider myself in a lucky place in that way. But also, like during this journey to become a data scientist you need to navigate yourself too, right? Like you have this roots, like this foundation but then you still need to kind of like figure out yourself what is it? Is it really the career that you want to pursue? But I'm happy that I'm end up here today and where I am right now. >> Oh, we're happy to have you. >> Yeah. So you' re with Gilead now after you're completing your PhD. And were you always interested in the intersection of data science and health, or is that something you explored throughout your studies? >> Oh, that's an excellent question. So I did have background in computer science but I only really get into biomedical domain when I did my PhD at school. So my research during my PhD was natural language processing, NLP and machine learning and their applications in biomedical domains. And then when I graduated, I got my first job in Gilead Science. Is super, super close and super relevant to what my research at school. And at Gilead, I am working in the advanced analytics department, and our focus is to bring artificial intelligence and machine learning into supporting clinical decision making. And really the ultimate goal is how to use AI to accelerate the precision medicine. So yes, it's something very like... I'm very lucky to get the first job that which is very close to my research at school. >> That's outstanding. You know, when we talk about AI, we can't not talk about ethics, bias. >> Kelly: Right. >> We know there's (crosstalk) Yes. >> Kelly: In healthcare. >> Exactly. Exactly. Equities in healthcare, equities in so many things. Talk a little bit about what excites you about AI, what you're doing at Gilead to really influence... I mean this, we're talking about something that's influencing life and death situations. >> Kelly: Right. >> How are you using AI in a way that is really maximizing the opportunities that AI can bring and maximizing the value in the data, but helping to dial down some of the challenges that come with AI? >> Yep. So as you may know already with the digitalization of medical records, this is nowaday, we have a tremendous opportunities to fulfill the dream of precision medicine. And what I mean by precision medicines, means now the treatments for people can be really tailored to individual patients depending on their own like characteristic or demographic or whatever. And nature language processing and machine learning, and AI in general really play a key role in that innovation, right? Because like there's a vast amount of information of patients and patient journeys or patient treatment is conducted and recorded in text. So that's why our group was established. Actually our department, advanced analytic department in Gilead is pretty new. We established our department last year. >> Oh wow. >> But really our mission is to bring AI into this field because we see the opportunity now. We have a vast amount of data about patient about their treatments, how we can mine these data how we can understand and tailor the treatment to individuals. And give everyone better care. >> I love that you brought up precision medicine. You know, I always think, if I kind of abstract everything, technology, data, connectivity, we have this expectation in our consumer lives. We can get anything we want. Not only can we get anything we want but we expect whoever we're engaging with, whether it's Amazon or Uber or Netflix to know enough about me to get me that precise next step. I don't think about precision medicine but you bring up such a great point. We expect these tailored experiences in our personal lives. Why not expect that in medicine as well? And have a tailored treatment plan based on whatever you have, based on data, your genetics, and being able to use NLP, machine learning and AI to drive that is really exciting. >> Yeah. You recap it very well, but then you also bring up a good point about the challenges to bring AI into this field right? Definitely this is an emerging field, but also very challenging because we talk about human health. We are doing the work that have direct impact to human health. So everything need to be... Whatever model, machine learning model that you are building, developing you need to be precise. It need to be evaluated properly before like using as a product, apply into the real practice. So it's not like recommendation systems for shopping or anything like that. We're talking about our actual health. So yes, it's challenging that way. >> Yeah. With that, you already answered one of the next questions I had because like medical data and health data is very sensitive. And how you at Gilead, you know, try to protect this data to protect like the human beings, you know, who are the data in the end. >> The security aspect is critical. You bring up a great point about sensitive data. We think of healthcare as sensitive data. Or PII if you're doing a bank transaction. We have to be so careful with that. Where is security, data security, in your everyday work practices within data science? Is it... I imagine it's a fundamental piece. >> Yes, for sure. We at Gilead, for sure, in data science organization we have like intensive trainings for employees about data privacy and security, how you use the data. But then also at the same time, when we work directly with dataset, it's not that we have like direct information about patient at like very granular level. Everything is need to be kind of like anonymized at some points to protect patient privacy. So we do have rules, policies to follow to put that in place in our organization. >> Very much needed. So some of the conversations we heard, were you able to hear the keynote this morning? >> Yes. I did. I attended. Like I listened to all of them. >> Isn't it fantastic? >> Yes, yes. Especially hearing these women from different backgrounds, at different level of their professional life, sharing their journeys. It's really inspiring. >> And Hannah, and I've been talking about, a lot of those journeys look like this. >> I know >> You just kind of go... It's very... Yours is linear, but you're kind of the exception. >> Yeah, this is why I consider my case as I was lucky to grow up in STEM environment. But then again, back to my point at the beginning, sometimes you need to navigate yourself too. Like I did mention about, I did my pa... Sorry, my bachelor degree in Vietnam, in STEM and in computer science. And that time, there's only five girls in a class of 100 students. So I was not the smartest person in the room. And I kept my minority in that areas, right? So at some point I asked myself like, "Huh, I don't know. Is this really my careers." It seems that others, like male people or students, they did better than me. But then you kind of like, I always have this passion of datas. So you just like navigate yourself, keep pushing yourself over those journey. And like being where I am right now. >> And look what you've accomplished. >> Thank you. >> Yeah. That's very inspiring. And yeah, you mentioned how you were in the classroom and you were only one of the few women in the room. And what inspired or motivated you to keep going, even though sometimes you were at these points where you're like, "Okay, is this the right thing?" "Is this the right thing for me?" What motivated you to keep going? >> Well, I think personally for me, as a data scientist or for woman working in data science in general, I always try to find a good story from data. Like it's not, when you have a data set, well it's important for you to come up with methodologies, what are you going to do with the dataset? But I think it's even more important to kind of like getting the context of the dataset. Like think about it like what is the story behind this dataset? What is the thing that you can get out of it and what is the meaning behind? How can we use it to help use it in a useful way. To have in some certain use case. So I always have that like curiosity and encouragement in myself. Like every time someone handed me a data set, I always think about that. So it's helped me to like build up this kind of like passion for me. And then yeah. And then become a data scientist. >> So you had that internal drive. I think it's in your DNA as well. When you were one of five. You were 5% women in your computer science undergrad in Vietnam. Yet as Hannah was asking you, you found a lot of motivation from within. You embrace that, which is so key. When we look at some of the statistics, speaking of data, of women in technical roles. We've seen it hover around 25% the last few years, probably five to 10. I was reading some data from anitab.org over the weekend, and it shows that it's now, in 2022, the number of women in technical roles rose slightly, but it rose, 27.6%. So we're seeing the needle move slowly. But one of the challenges that still remains is attrition. Women who are leaving the role. You've got your PhD. You have a 10 month old, you've got more than one child. What would you advise to women who might be at that crossroads of not knowing should I continue my career in climbing the ladder, or do I just go be with my family or do something else? What's your advice to them in terms of staying the path? >> I think it's really down to that you need to follow your passion. Like in any kind of job, not only like in data science right? If you want to be a baker, or you want to be a chef, or you want to be a software engineer. It's really like you need to ask yourself is it something that you're really passionate about? Because if you really passionate about something, regardless how difficult it is, like regardless like you have so many kids to take care of, you have the whole family to take care of. You have this and that. You still can find your time to spend on it. So it's really like let yourself drive your own passion. Drive the way where you leading to. I guess that's my advice. >> Kind of like following your own North Star, right? Is what you're suggesting. >> Yeah. >> What role have mentors played in your career path, to where you are now? Have you had mentors on the way or people who inspired you? >> Well, I did. I certainly met quite a lot of women who inspired me during my journey. But right now, at this moment, one person, particular person that I just popped into my mind is my current manager. She's also data scientist. She's originally from Caribbean and then came to the US, did her PhDs too, and now led a group, all women. So believe it or not, I am in a group of all women working in data science. So she's really like someone inspire me a lot, like someone I look up to in this career. >> I love that. You went from being one of five females in a class of 100, to now having a PhD in information sciences, and being on an all female data science team. That's pretty cool. >> It's great. Yeah, it's great. And then you see how fascinating that, how things shift right? And now today we are here in a conference that all are women in data science. >> Yeah. >> It's extraordinary. >> So this year we're fortunate to have WIDS coincide this year with the actual International Women's Day, March 8th which is so exciting. Which is always around this time of year, but it's great to have it on the day. The theme of this International Women's Day this year is embrace equity. When you think of that theme, and your career path, and what you're doing now, and who inspires you, how can companies like Gilead benefit from embracing equity? What are your thoughts on that as a theme? >> So I feel like I'm very lucky to get my first job at Gilead. Not only because the work that we are doing here very close to my research at school, but also because of the working environment at Gilead. Inclusion actually is one of the five core values of Gilead. >> Nice. >> So by that, we means we try to create and creating a working environment that all of the differences are valued. Like regardless your background, your gender. So at Gilead, we have women at Gilead which is a global network of female employees, that help us to strengthen our inclusion culture, and also to influence our voices into the company cultural company policy and practice. So yeah, I'm very lucky to work in the environment nowadays. >> It's impressive to not only hear that you're on an all female data science team, but what Gilead is doing and the actions they're taking. It's one thing, we've talked about this Hannah, for companies, and regardless of industry, to say we're going to have 50% women in our workforce by 2030, 2035, 2040. It's a whole other ballgame for companies like Gilead to actually be putting pen to paper. To actually be creating a strategy that they're executing on. That's awesome. And it must feel good to be a part of a company who's really adapting its culture to be more inclusive, because there's so much value that comes from inclusivity, thought diversity, that ultimately will help Gilead produce better products and services. >> Yeah. Yes. Yeah. Actually this here is the first year Gilead is a sponsor of the WIDS Conference. And we are so excited to establish this relationship, and looking forward to like having more collaboration with WIDS in the future. >> Excellent. Kelly we've had such a pleasure having you on the program. Thank you for sharing your linear path. You are definitely a unicorn. We appreciate your insights and your advice to those who might be navigating similar situations. Thank you for being on theCUBE today. >> Thank you so much for having me. >> Oh, it was our pleasure. For our guests, and Hannah Freytag this is Lisa Martin from theCUBE. Coming to you from WIDS 2023, the eighth annual conference. Stick around. Our final guest joins us in just a minute.

(upbeat music) >> Welcome back friends. It's theCUBE LIVE in Las Vegas at the Venetian Expo, covering the first full day of AWS re:Invent 2022. I'm Lisa Martin, and I have the privilege of working much of this week with Dave Vellante. >> Hey. Yeah, it's good to be with you Lisa. >> It's always good to be with you. Dave, this show is, I can't say enough about the energy. It just keeps multiplying as I've been out on the show floor for a few minutes here and there. We've been having great conversations about cloud migration, digital transformation, business transformation. You name it, we're talking about it. >> Yeah, and I got to say the soccer Christians are really happy. (Lisa laughing) >> Right? Because the USA made it through. So that's a lot of additional excitement. >> That's true. >> People were crowded around the TVs at lunchtime. >> They were, they were. >> So yeah, but back to data. >> Back to data. We have a couple of guests here. We're going to be talking a lot with customer challenges, how they're helping to overcome them. Please welcome Kevin Zawodzinski, VP of Sales Engineering at COMMVAULT. >> Thank you. >> And Paul Meighan, Director of Product Management at AWS. Guys, it's great to have you on the program. Thank you for joining us. >> Thanks for having us. >> Thanks for having us. >> Isn't it great to be back in person? >> Paul: It really is. >> Kevin: Hell, yeah. >> You cannot replicate this on virtual, you just can't. It's nice to see how excited people are to be back. There's been a ton of buzz on our program today about Adam's keynote this morning. Amazing. A lot of synergies with the direction, Paul, that AWS is going in and where we're seeing its ecosystem as well. Paul, first question for you. Talk about, you know, in the customer environment, we know AWS is very customer obsessed. Some of the main challenges customers are facing today is they really continue this business transformation, this digital transformation, and they move to cloud native apps. What are some of those challenges and how do you help them eradicate those? >> Well, I can tell you that the biggest contribution that we make is really by focusing on the fundamentals when it comes to running storage at scale, right? So Amazon S3 is unique, distributed architecture, you know, it really does deliver on those fundamentals of durability, availability, performance, security and it does it at virtually unlimited scale, right? I mean, you guys have talked to a lot of storage folks in the industry and anyone who's run an estate at scale knows that doing that and executing on those fundamentals day after day is just super hard, right? And so we come to work every day, we focus on the fundamentals, and that focus allows customers to spend their time thinking about innovation instead of on how to keep their data durably stored. >> Well, and you guys both came out of the storage world. >> Right. >> Yeah, yeah. >> It was a box world, (Kevin laughs) and it ain't no more. >> Kevin: That's right, absolutely. >> It's a service and a service of scale. >> Kevin: Yeah. So architecture matters, right? >> Yeah. >> Yeah. >> Paul, talk a little bit about, speaking of innovation, talk about the evolution of S3. It's been around for a while now. Everyone knows it, loves it, but how has AWS architected it to really help meet customers where they are? >> Paul: Right. >> Because we know, again, there's that customer first focus. You write the press release down the road, you then follow that. How is it evolving? >> Well, I can tell you that architecture matters a lot and the architecture of Amazon S3 is pretty unique, right? I think, you know, the most important thing to understand about the architecture of S3 is that it is truly a regional service. So we're laid out across a minimum of 3 Availability Zones, or AZs, which are physically separated and isolated and have a distance of miles between them to protect against local events like floods and fires and power interruption, stuff like that. And so when you give us an object, we distribute that data across that minimum of 3 Availability Zones and then within multiple devices within each AZ, right? And so what that means is that when you store data with us, your data is on storage that's able to tolerate the failure of multiple devices with no impact to the integrity of your data, which is super powerful. And then again, super hard to do when you're trying to roll your own. So that's sort of a, like an overview of the architecture. In terms of how we think about our roadmap, you know, 90% of our roadmap comes directly from what customers tell us matters, and that's a tenant of how we think about customer obsession at AWS and it really is how we drive a roadmap. >> Right, so speaking of customers Kevin, what are customers asking you guys- >> Yeah. >> for, how does it relate to what you're doing with S3? >> Yeah, it's a wonderful question and one that is actually really appropriate for us being at re:Invent, right? So we got, last three years we've had customers here with us on stage talking about it. First of all, 3 years ago we did a virtual session, unfortunately, but glad to be back as you mentioned, with Coca-Cola and theirs was about scale and scope and really about how can we protect hundreds of thousands of objects, petabyte to data, in a simple and secure way, right. Then last year we actually met with a ACT, Inc. as well and co-presented with them and really talked about how we could protect modern workloads and their modern workloads around whether it was Aurora or as well as EKS and how they continue to evolve as well. And, last but not least it's going to be, this year we're talking with Illinois State University as well about how they're going to continue to grow, adapt and really leverage AWS and ourselves to further their support of their teachers and their staff. So that is really helping us quite a bit to continue to move forward. And the things we're doing, again, with our customer base it's really around, focused on what's important to them, right? Customer obsession, how are we working with that? How are we making sure that we're listening to them? Again, working with AWS to understand how can we evolve together and really ultimately their journeys. As you heard, even with those 3 examples they're all very different, right? And that's the point, is that everybody's at a different point in the journey. They're at a different place from a modernization perspective. So we're helping them evolve, as they're helping us evolve as well, and transform with AWS. >> So very mature COMMVAULT stack, the S3 bucket and all the other capabilities. Paul, you just talked about coming together- >> Right. >> Dave: for your customers. >> Yeah, yeah, absolutely. And just, you know, we were talking the other day, Paul and I were talking the other day, it's been, you know, we've worked with AWS, with integration since 2009, right? So a long time, right? I mean, for some that may not seem like a long time ago, but it is, right? It's, you know, over a decade of time and we've really advanced that integration considerably as well. >> What are some of the things that, I don't know if you had a chance to see the keynote this morning? >> Yeah, a little bit. >> What are some of the things that there was, and in fact this is funny, funny data point for you on data. One of my previous guests told me that Adam Selipsky spent exactly 52 minutes talking about data this morning. 52 minutes. >> Okay. >> That there's a data point. But talk about some of the things that he talked about, the direction AWS is going in, obviously new era in the last year. Talk about what you heard and how you think that will evolve the COMMVAULT-AWS relationship. >> Yeah, I think part of that is about flexibility, as Paul mentioned too, architecture matters, right? So as we evolve and some of the things that we pride ourselves on is that we developed our systems and our software and everything else to not worry about what do I have to build to today but how do I continue to evolve with my customer base? And that's what AWS does, right? And continues to do. So that's really how we would see the data environment. It's really about that integration. As they grow, as they add more features we're going to add more features as well. And we're right there with them, right? So there's a lot of things that we also talk about, Paul and I talk about, around, you know, how do we, like Graviton3 was brought up today around some of the innovations around that. We're supporting that with Auto Scale right now, right? So we're right there releasing, right when AWS releasing, co-developing things when necessary as well. >> So let's talk about security a little bit. First of all, what is COMMVAULT, right? You're not a security company but you're an adjacency to security. It's sort of, we're rethinking security. >> Kevin: Yep. >> including data protection, not a bolt-on anymore. You guys both have a background in that world and I'm sure that resonates. >> Yeah. >> So what is the security play here? What role does COMMVAULT play? I think we know pretty well what role AWS plays, but love to hear, Paul, your thoughts as well on security. >> Yeah, I'll start I guess. >> Go on Paul. >> Okay. Yeah, so on the security side of things, there's a quite a few things. So again, on the development side of things, we do things like file anomaly detection, so seeing patterns in data. We talked a lot about analytics as well in the keynote this morning. We look at what is happening in the customer environment, if there's something odd or out of place that's happening, we can detect that and we'll notify people. And we've seen that, we have case studies about that. Other things we do are simple, simple but elegant. Is with our security dashboard. So we'll use our security dashboard to show best practices. Are they using Multi-Factor Authentication? Are you viewing password complexity? You know, things like that. And allows people to understand from a security landscape perspective, how do we layer in protection with their other systems around security. We don't profess to be the security company, or a security company, but we help, you know, obviously add in those additional layers. >> And obviously you're securing, you know, the S3 piece of it. >> Mmmhmm. >> You know, from your standpoint because building it in. >> That's right. And we can tell you that for us, security is job zero. And anyone at AWS will tell you that, and not only that but it will always be our top priority. Right from the infrastructure on down. We're very focused on our shared responsibility model where we handle security from the hypervisor, or host operating system level, down to the physical security of the facilities in which our services run and then it's our customer's responsibility to build secure applications, right. >> Yeah. And you talk about Graviton earlier, Nitro comes into play and how you're, sort of, fencing off, you know, the various components of the system from the operating system, the VMs, and then that is designed in and that's a new evolution that it comes as part of the package. >> Yeah, absolutely. >> Absolutely. >> Paul, talk a little bit about, you know, security, talking about that we had so many conversations this year alone about the threat landscape and how it's dramatically changing, it's top of mind for everybody. Huge rise in ransomware attacks. Ransomware is now, when are we going to get hit? How often? What's the damage going to be? Rather than, are we going to get hit? It's, unfortunately it's progressed in that direction. How does ensuring data security impact how you're planning the roadmap at AWS and how are partners involved in shaping that? >> Right, so like I said, you know, 90% of our roadmap comes from what customers tell us matters, right? And clearly this is an issue that matters very much to customers right now, right? And so, you know, we're certainly hearing that from customers, and COMMVAULT, and partners like COMMVAULT have a big role to play in helping customers to secure and protect their applications, right? And that's why it's so critical that we come together here at re:Invent and we have a bunch of time here at the show with the COMMVAULT technical folks to talk through what they're hearing from customers and what we're hearing. And we have a number of regular touch points throughout the year as well, right? And so what COMMVAULT gets from the relationship is, sort of, early access and feedback into our features and roadmap. And what we get out of it really is that feedback from that large number of customers who interface with Amazon S3 through COMMVAULT. Who are using S3 as a backup target behind COMMVAULT, right? And so, you know, that partnership really allows us to get close to those customers and understand what really matters to them. >> Are you doing joint engineering, or is it more just, hey here you go COMMVAULT, here's the tools available, go, go build. Can you address that? >> Yeah, no, absolutely. There's definitely joint engineering like even things around, you know, data migration and movement of data, we integrate really well and we talk a lot about, hey, what are you, like as Paul mentioned, what are you seeing out there? We actually, I just left a conversation about an hour ago where we're talking about, you know, where are we seeing placement of data and how does that matter to, do you put it on, you know, instant access, or do you put it on Glacier, you know, what should be the best practices? And we tell them, again, some of the telemetry data that we have around what do we see customers doing, what's the patterns of data? And then we feed that back in and we use that to create joint solutions as well. >> You know, I wonder if we could talk about cloud, you know, optimization of cloud costs for a minute. That's obviously a big discussion point in the hallways with customers. And on your earnings call you guys talked about specifically some customers and they specifically mentioned, for example, pushing storage to lower cost tiers. So you brought up Glacier just then. What are you seeing in the field in that regard? How are customers taking advantage of that? And where does COMMVAULT play in, sort of, helping make that decision? >> You want to take part one or you want me to take it? >> I can take part one. I can tell you that, you know, we're very focused on helping customers optimize costs, however necessary, right? And, you know, we introduced intelligent hearing here at the show in 2019 and since launch it's helped customers to reduce costs by over $750 million, right? So that's a real commitment to optimizing costs on behalf of customers. We also launched, you know, later in 2020, Glacier Deep Archive, which is the lowest cost storage in the cloud. So it's an important piece of the puzzle, is to provide those storage options that can allow customers to match the workloads that are, that need to be on folder storage to the appropriate store. >> Yeah, and so, you know, S3 is not this, you know, backup and recovery system, not an archiving system and, you know, in terms of, but you have that intelligence in your platform. 'Cause when I heard that from the earnings call I was like, okay, how do customers then go about deciding what they can, you know, when it's all good times, like yeah, who cares? You know, just go, go, go. But when you got to tighten the belt, how do you guys? >> Yeah, and that goes back to understanding the data pattern. So some of that is we have intelligence and artificial intelligence and everything else and machine learning within our, so we can detect those patterns, right? We understand the patterns, we learn from that and we help customers right size, right. So ultimately we do see a blend, right? As Paul mentioned, we see, you know, hey I'm not going to put everything on Glacier necessarily upfront. Maybe they are, it all depends on their workloads and patterns. So we use the data that we collect from the different customers that we have to share those best practices out and create, you know, the right templates, so to speak, in ways for people to apply it. >> Guys, great joint, you talked about the joint engineering, joint go to market, obviously a very strong synergistic partnership between the two. A lot of excitement. This is only day one, I can only imagine what's going to be coming the next couple of days. But I have one final question for you, but I have same question for both of you. You had the chance to create your own bumper sticker, so you get a shiny new car and for some reason you want to put a bumper sticker on it. About COMMVAULT, what would it say? >> Yeah, so for me I would say comprehensive, yet simple, right? So ultimately about giving you all the bells and whistles but if you want to be very simple we can help you in every shape and form. >> Paul, what's your bumper sticker say about AWS? >> I would say that AWS starts with the customer and works backwards from there. >> Great one. >> Excellent. Guys- >> Kevin: Well done. >> it's been a pleasure to have you on the program. Thank you- >> Kevin: Thank you. >> for sharing what's going on, the updates on the AWS-COMMVAULT partnership and what's in it for customers. We appreciate it. >> Dave: Thanks you guys. >> Thanks a lot. >> Thank you. >> All right. For our guests and Dave Vellante, I'm Lisa Martin. You're watching theCUBE, the leader in live enterprise and emerging tech coverage. (upbeat music)

(upbeat music) >> Good evening, guys. Welcome back to Las Vegas, theCUBE is here live at AWS re:Invent 2021. I'm Lisa Martin. We have two live sets, two remote sets, over 100 guests on theCUBE talking with AWS, and its massive ecosystem of partners bringing you this hybrid tech event, probably the biggest of the year, and I'm pleased to welcome Stephen Kovac next, the Chief Compliance Officer at Zscaler. Stephen, how's it going? >> Well, it's going well, Lisa. Thank you for asking, enjoying Vegas, loving the conference, unbelievable. >> Isn't it great to be back in person? >> Oh, it's so great, I've seen people. >> Conversations you can't replicate on video conferencing, you just can't. >> Can't, and you see people you haven't seen in two years, and it's like all of a sudden you're best buddies again. It's just wonderful, it's so great to back. >> It is, and AWS in typical fashion has done a great job of getting everybody in here safely. I'm not at all surprised, that's what I expected, but it's been great. And I hope that this can demonstrate to other companies, you can do this safely. >> You can, I think so. I mean, there's a lot of effort going into this, but as usual AWS does it right. So, you expect that. >> They do. Talk to me about the Zscaler-AWS partnership. What's going on? >> Well, it's a great partnership. So AWS and Zscaler have been partners since the beginning of Zscaler. We are the largest security cloud in the world. We're born and bred in the cloud security company. So literally we wrote one application that does global security, everything from firewall to proxy, secure web gateway, to DLP, to all this in one piece of software. So, in the past where people would buy appliances for all these devices and put them in their own data center, we wrote a software that allows us to put that in the cloud, run it on the cloud globally around the world. And our partnership with AWS is, we originally built that on AWS, and today still AWS is our prime partner, especially in the zero trust side of our business. So, great relationship, long-term and great I think for both of us, it's been a very, very... >> Fruitful partnership, synergistic? >> Synergistic, love that, so yes. >> You mentioned zero trust, and we have seen such massive changes to the security and the threat landscape the last 20, 22 months. Talk to me about the recent executive order calling for zero trust, how does Zscaler's partnership with AWS help you enable organizations, fed, SLED, DoD, to be able to actually bring in and apply zero trust? >> Yeah, great question. Five years ago I was tasked to bring Zscaler into the government side of the business. So I was employee one to do that. It was a great honor to do it. And the first thing we did is we partnered with AWS because we needed to get FedRAMP compliant. We knew we were going to go into DoD. So we needed to go to the Impact Level five. And eventually we'll be able to go up level six with AWS. And so it was our partnership started there. And as you've seen in five years with all the change that's happened, that obviously the breaches like SolarWinds, and the people up here talking about them all week with you I'm sure. The executive order came down from the Biden Administration, who I completely salute for being just tremendous leaders in the cybersecurity space. And the executive order, one of the big pieces of the executive order was every agency must produce a plan for zero trust. So our cloud platform that is on AWS is a zero trust platform. It is the first and only zero trust platform to get authorized by the federal government at the FedRAMP level, and now the IL five level. So, together we are literally capturing and taking over the, being the leader in the zero trust space for the federal government. And I'm going to get a sip of water, so forgive me, I've been here all week talking to a lot of people, so forgive me for that. >> That's one thing that we don't have to deal with when we're on Zoom, right, is you don't really have the risk of losing your voice. >> Stephen: There you go. >> But in terms of the executive order, something that you mentioned, SolarWinds, Colonial Pipeline, we only hear about some of the big ones. The fact that ransomware happens one attack every 10, 11 seconds, it's a matter of when we get hit, not if. >> As you know, the story coming up from me, coming up on stage with you today, I just got myself breached just this morning, just individually. So yes, it's going to get all of us. And especially, I think when you look at zero trust and ransomware and how they worked out how zero trust can prevent it, you look at the SLED market, you know, state, local governments, they don't have the dollars to go spend like DHS does, or say, some of the DoD does. So, our partnership with AWS allows us to produce a product that is very cost-effective on a per user basis, consumption model, which is what AWS has been famous for since day one, right, the consumption model, use it when you need it, don't use it when you don't. We built our software the same way. So, at some point in a year, in a school year, we'll ramp up with some schools up to a hundred thousand users in the district, and over the summer we'll ramp down to a thousand, and we just bill them for that. So it's a beautiful relationship that we partner in not just the executive order, but being a partner in SLED, fed in the sense that matches making our business together, match the government's business. And that makes us a true leader and makes us a cost-effective solution. And if you think about it just for a moment, yesterday, I told you I was testifying in front of the Senate. And one of the questions I got asked was, oh, how many security updates do you guys see a year? I said, a year, well, we do over 200,000 a day. 200,000 security updates from potential hackers every single day. And we're doing that over 200 billion transactions a day run on AWS. So it's tremendous partnership, and to be able to work like that, and at that kind of volume, and be able to go up and down with the, and you got AWS able to scope up and down, and us to be able to ride that wave with them. It's been great. >> One of the things that we always talk about when we talk AWS is they're customer focused or customer obsession that, hey, we start backwards, we work backwards from the customer. Same thing, synergistic from a cultural perspective? >> Absolutely, I mean, one of the things I always love about AWS and I've been a customer of AWS for many years, even prior to my Zscaler days, I love the way they approach things, right? If they're not trying to go out and sell it, they're trying to meet with the customer and find out what the customer needs, and then build a solution. We're the same way. I always tell, you know, when you think of our solutions, Zscaler, I always tell my sales teams, I say it takes four sales calls for people to really understand what we do. And AWS, in the beginning of AWS, it was kind of the same thing. In the old days, you know, we all just built data centers and we had all these racks, and all this expense and mesh is what you did. It was unusual back in the day, 10 years ago, and I've been to every single re:Invent. I mean, the first one there was like, you're actually going to put all your stuff in this unknown cloud thing, and it will be available when you need it? So yes, you know, the way that they did it is the same way we do it together today. And we do it together today. We partner on many deals today where we're both, our teams are in there together, selling together, whether it's the DoD, federal agencies, SLED agencies, and commercial, you know, selling it hand-in-hand because it's that same philosophy is we're going to build what a customer needs. We're not going to tell the customer what they need. We're going to hear what they need, and that's the same relationship. So I'm going to get another sip real quick. >> Go for it. One of the things that has been a theme that we've heard the last couple of days is every company needs to be a data company or private sector, public sector, and if they're not, they're probably not going to be around much longer. How do you help customers get their handle around that? Because the security threats are only increasing. I mean, it's ransomware as a service. The fact that these criminals are getting much more brazen, you just had this happen to yourself, but enabling them to become data-driven organizations and use the data, extract the value from it securely, that's hard. >> It is, I mean, if you think back in the day, I mean, companies didn't have chief compliance officers that worked in the space that we do. Their chief compliance officer back in the day was the guy that was writing your HR issues and what OSHA issues, and of course, I still deal with some of that stuff, but my true job is really around the data, right? You know, how do we build our platforms, what decisions we make on our platforms, how we're going to certify them to support that, and I mean, chief data officers, chief security officers, I mean, you go into companies today, even car dealerships today. I mean, I'm picking one, you never thought of them having a security officer, but they do, they have to, they have to. And I mean, basic school districts, I mean, I don't about you, when I was a kid and went to school, they didn't have computers, but when my kid went to school, they did, but they didn't have a security officer. Now today, every single school district has security officers. I mean, I love how you said it, that data-driven, that data thought is there. It has to be, it's a real threat. And the sad thing is of these ransomware attacks, how many don't get reported. >> Oh, right, we're only hearing about a select few. >> The numbers are something like 88% don't get reported. It's that big. So that just tells you, we hear the big ones, right, Colonial Pipeline, things like that. We don't hear about West Texas or Middle Illinois school district that paid five grand because somebody had something on the school. That's how, as you said, this ransomware as a service security, we call it a security as a service, there's SaaS, which is software as a service, we're security software as a service, and AWS is the infrastructure as a service that we run on. And that's how it works well together. >> Do you guys go into accounts together from a go-to-market perspective? >> We, do, we can always do a better job. And my good friend here at AWS, who's probably listening, we can always do better. But yeah, so it is become something that, especially in the government space we do, in federal, DoD, because the certifications are really important, certifications are important everywhere, and we have many, we talked about all the certifications we have in federal, FedRAMP and IL five, and we have a plethora of those certifications in the commercial space. But they mean in a federal space, they're really the ticket. They call them the ENERGY STAR of approval, good housekeeping piece. So, you know, having that, teaming up with AWS who we partner together and because AWS has the same certs, we can sell at the same levels. And we do a really great job of co-selling in that space together. And I think when they look at us and they say, well, you're AWS, they've got their FedRAMP high, IL five, and you're Zscaler, you got your FedRAMP high, IL five. Yes, we can do business with these guys, and that's important. >> So you guys both open doors for each other. >> We do, we do in many cases, yeah. As a matter of fact, re:Invent five years ago, a buddy of mine here opened a big, big account for us, which is today our largest account in federal came from re:Invent, where came up to me and said, hey, my customer wants to, he's looking to do something, they're an agency that has global footprint, and they're like, we want to do something as a security as a service. They don't want to ship boxes all over the place. And we just met the customer for a coffee, and next thing you know, became our, still today, our probably largest customer in federal. >> Wow, well, this is the 10th re:Invent, you said you've been to all of them. >> Stephen: I have been to all of them. I can't lie, but I can't say I did all the virtual ones. I mean, I was logged in. (laughs) >> That's okay, we'll wink on that one. But, one of the things then, we've just got about a minute left here, is in new leadership, Andy Jassy being promoted to the CEO of Amazon, we've got Adam Selipsky, heard lot of announcements and news from Adam yesterday, but some of the things that we've been talking about on theCUBE is the first 15 years of innovation at AWS, that's going to accelerate. Do you see that also, like if you look forward to the next decade, do you see things moving much faster than they did the past decade? >> I don't think they can't. I mean, I shouldn't say they have to. And the change of the guard as you might call it here, is it's always good to have a change of the guard I think. You know, the question is when's Andy going to go to space? I mean, that's the next. (Lisa laughs) I think you have the guys who got AWS to the dance, and now the dance, who's going to become the belle of the ball. And this next generation of leadership coming in is fabulous. I think they've made great decisions, and I think they're going to do really well. And we're behind them, we support it. I got a chance to meet with most of them, love a chance to meet with Andy, I haven't met with him yet. So Andy, I'd love to meet you sometime soon. But I'm very impressed with what they've done. And yes, I think it's going to be, the last 10 years of growth is going to be a year next year. I think literally, you take 10 years be compressed to a year, and then next year it will be compressed to a day. So it's moving that fast. >> Yep, get your neck brace on, prepare for that whiplash. >> Yeah, right? That's what I said to Jeff when Jeff went to space, that's how fast we're about to travel, right? But it's really relative. >> It is, there is no limit. Well, Stephen, thank you for joining me, talking about Zscaler, AWS, what you guys are doing, how you're helping to revolutionize the public sector, fed, SLED, a lot of great stuff there. Security is an ever-evolving topic, and we appreciate all of your insights. >> Well, it was wonderful to be here. Great to see you again. And great to be back with all our friends at re:Invent. >> All of our friends, exactly. >> Stephen: Thank you so much for the time today. >> My pleasure. For Stephen Kovac, I'm Lisa Martin. You're watching theCUBE, the global leader in live tech coverage. (pleasant music)

>>Mhm >>Welcome to the cube where we're celebrating the EC 2/15 birthday anniversary. My name is Dave Volonte and we're joined right now by Sandy carter, Vice President of AWS. Welcome Sandy, it's great to see you again, >>David. So great to see you too. Thanks for having me on the show today. >>Very welcome. We were last physically together. I think it was reinvent 2019. Hopefully I'll see you before 2022. But first happy birthday to EC two. I mean, it's hard to imagine back in 2006, the degree to which EC two would impact our industry. Sandy, >>I totally agree. You know, I joined a W S about 4.5 years ago in EC two and it's, it's even amazing to see what's just happened in the last 4.5 years. So I'm with you. Nobody really expected the momentum, but EC two has really shone brightly in value to our customers. >>You know, we've done the public sector summit, you know, many times. It's a great event. Things are a little different in public sector as you well know. So talk about the public sector momentum with EC two and that journey. What have you seen? >>Yeah, so it's a great question day. So I had to go back in the time vault. You know, public sector was founded in 2010 and we were actually founded by the amazon process writing a paper setting up a two pizza team, which happened to be six people. And that journey really started with a lot of our public sector customers thinking that we don't know about the cloud. So we might want to do a pilot or just look at non mission critical workloads now public sector and I know you know this day but public sector is more than just government, it has education, not for profit healthcare and now space. But everybody at that time was very skeptical. So we had to really work hard to migrate some workloads over. And one of our very first non mission critical workloads was the U. S. Navy. Um and what they did was the Navy Media Services actually moved images over to EC two. Now today that seems like oh that's pretty easy. But back then that was a big monumental reference. Um and we had to spend a lot of time on training and education to win the hearts and souls of our customers. So back then we had half of the floor and Herndon Washington, we just had a few people and that room really became a training room. We trained our reps, we trained our customers um research drive. A lot of our early adopters accounts like Nasa and jpl. And um then when cloud first came out and governments that started with the U. S. A. And we announced Govcloud, you know, things really picked up, we had migration of significant workloads. So if you think back to that S. A. P. And just moving media over um with the Navy, the Navy and S. A. P. Migrated their largest S A P E R P solution to the cloud in that time as well. Um, then we started international. Our journey continued with the UK International was UK and us was us. Then we added a P. J. And latin America and Canada. And then of course the partner team which you know, is very close to my heart. Partners today are about 73% of our overall public sector business. And it started out with some interesting small pro program SVS being very crucial to that, accelerating adoption. And then of course now the journey has continued with Covid. That has really accelerated that movement to the cloud. And we're seeing, you know, use of ec two to really help us drive by the cute power needed for A I N. M. L. And taking all that data in from IOT and computing that data. And are they are. Um, and we're really seeing that journey just continue and we see no end in sight. >>So if we can stay in the infancy and sort of the adolescent years of public sector, I mean, remember, I mean as analysts, we were really excited about, you know, the the the introduction of of of of EC two. But but there was a lot of skepticism in whatever industry, financial services, healthcare concerns about security, I presume it was similar in public sector, but I'm interested in how you you dealt with those challenges, how you you listen to folks, you know, how did you drive that leadership to where it is today? >>Yeah, you're right. The the first questions were what is the cloud? Doesn't amazon sell books? What is this clown thing? Um, what is easy to, what is easy to stand for and then what the heck is an instance? You know, way back when there was one instance, it didn't even have a name. And today of course we have over 400 instant types with different names for each one. Um and the big challenges you asked about challenges, the big challenges that we had to face. Dave were first and foremost, how do we educate? Um we had to educate our employees and then we had to educate our customers. So we created these really innovative hands on training programmes, white boarding um, sessions that we needed. They were wildly popular. So we really have to do that and then also prove security as you know. So you asked how we listen to our customers and of course we followed the amazon way we work backwards from where we were. So at that time, customers needed education. And so we started there um, data was really important. We needed to make customer or data for government more available as well. So for instance, we first started hosting the Census Bureau for instance. Um and that was all on EC two. So we had lots of early adopters and I think the early adopters around EC two really helped us to remember. I said that the UK was our international office for a while. So we had NIH we had a genomes project and the UK Ministry of Justice as well. And we had to prove security out. We had to prove how this drove a structured GovCloud and then we had to also prove it out with our partners with things like helping them get fed ramped or other certifications. I'll for that sort of thing as well. And so we really lead in those early days through that education and training. Um we lead with pilots to show the potential of the possible and we lead with that security setting those security standards and those compliance certifications, always listening to the customer, always listening to the partner, knowing how important the partners we're going to be. So for example, recovery dot gov was the first government wide system that moved to the cloud. Um the recovery transparency board was first overseeing that Recovery act spending, which included stimulus tracking website. I don't know if you remember that, but they hosted the recovery dot gov On amazon.com using EC two. And that site quickly made information available to a million visitors per hour and at that time, that was amazing. And the cost savings were significant. We also launched Govcloud. You'd asked about GovCloud earlier and that federal cloud computing strategy when the U. S. Government came out with cloud first and they had to consider what is really going to compel these federal agencies to consider cloud. They had Public-sector customers had 70 requirements for security and safety of the data that we came out with Govcloud to open up all those great opportunities. And I think Dave we continue to leave because we are customer obsessed uh you know, still supporting more security standards and compliance sort than any other provider. Um You know, now we lead with data not just data for census or images for the US Navy, but we've got now data in space and ground station and data at scale with customers like Finra who's now doing 100 billion financial transactions. Not just that one million from the early days. So it has been a heck of a ride for public sector and I love the way that the public sector team really used and leveraged the leadership principles. Re invent and simplify dive deep. Be obsessed with the customers start where they are. Um and make sure that you're always always always listening to what they need. >>You know, it's interesting just observing public sector. It's not uncommon, especially because of the certifications that some of the services, you know come out after they come out for the commercial sector. And I remember years ago when I was at I. D. C. I was kind of the steward of the public sector business. And that was a time when everybody was trying to focus in public sector on commercial off the shelf software. That was the big thing. And they want to understand, they wanted to look at commercial use cases and how they could apply them to government. And when I dug in a little bit and met with generals and like eight different agencies, I was struck by how many really smart people and the things that they were doing. And I said at the time, you know, a lot of my commercial clients could learn a lot from you. And so the reason I bring that up is because I saw the same thing with Govcloud because there was a lot of skepticism in various industries, particularly regulated industries, financial services, healthcare. And then when Govcloud hit and the CIA deal hit, people said, whoa CIA, they're like the most security conscious industry or organization in the world. And so I feel as though in a way public sector led that that breakthrough. So I'm wondering when you think about EC two today and the momentum that it has in the government, Are there similar things that you see? Where's the momentum today in public sector? >>You are right on target day? I mean that CIA was a monumental moment and that momentum with ever increasing adoption to the cloud has continued in public sector. In fact today, public sector is one of our fastest growing areas. So we've got um, you know, thousands of startups or multiple countries that were helping out today to really ignite that innovation. We have over 4000 government agencies, 9000 education agencies. Um 2000 public sector partners from all over the globe. 24,000 not for profit organizations. And what I see is the way that they're using EC two um is is leading the pack now, especially after Covid, you know, many of these folks accelerated their journey because of Covid. They got to the cloud faster and now they are doing some really things that no one else is doing like sending an outpost postbox into space or leveraging, you know robots and health care for sure. So that momentum continues today and I love that you were the champion of that you know way back when even when you were with I. D. C. >>So I want to ask you, you sort of touched on some interesting use cases, what are some of the more unusual ones and maybe breakthrough use cases that you see? >>Oh so yeah we have a couple. So one is um I mentioned it earlier but there is a robot now that is powered by IOT and EC two and the robot helps to take temperature and and readings for folks that are entering the hospital in latin America really helped during Covid, one of my favorites. It actually blew the socks off of verne or two and you know that's hard to do is a space startup called lunar outpost and they are synthesizing oxygen on mars now that's, that's driven by Ec two. That's crazy. Right? Um, we see state governments like new york, they've got this vision zero traffic and they're leveraging that to prevent accidents all through new york city. I used to live in new york city. So this is really needed. Um, and it continues like with education, we see university of Illinois and Splunk one of our partners, they created a boarding pass for students to get back to school. So I have a daughter in college. Um, and you know, it's really hard for her to prove that she's had the vaccine or that she's tested negative on the covid test. They came out with a past of this little boarding pass, just like you used to get on an airplane to get into different classes and labs and then a couple of my favorites and you guys actually filmed the Cherokee nation. So the Cherokee nation, the chief of the Cherokee nation was on our silicon um show and silicon angles show and the cube featured them And as the chief talked about how he preserves the Cherokee language. And if you remember the Cherokee language has been used to help out the US in many different ways and Presidio. One of our partners helped to create a game, a super cool game that links in with unity To help teach that next generation the language while they're playing a game and then last but not least axle three d out of the UK. Um, they're using easy to, to save lives. They've created a three D imaging process for people getting ready to get kidney transplants and they have just enhanced that taken the time frame down for months. Now today's that they can actually articulate whether the kidney transplant will work. And when I talked to roger their Ceo, they're doing R. O. L return on life's not return on investment. So those are just some of the unusual and breakthrough use cases that we see powered by E. C. To >>Sandy. I'll give you the last word. Your final closing comments. >>Well, my final closing comments are happy birthday to ec two celebrating 15 years. What a game changer and value added. It has been the early days of Ec two. Of course we're about education like what is the cloud? Why is a bookseller doing it. But um, easy to really help to create a new hub of value Now. We've got customers moving so fast with modernization using a I. M and M. L. Containers survivalists. Um, and all of these things are really changing the game and leveling it up as we increased that business connection. So I think the future is really bright. We've only just begun. We've only just begun with EC two and we've only just begun with public sector. You know, our next great moments are still left to come. >>Well, Sandy, thanks so much. Always Great to see you. Really appreciate your time. >>Thank you so much. Dave. I really appreciate it. And happy birthday again to E. C. To keep >>It right there were celebrating Ec 2's 15th birthday right back. >>Mhm.

>> Narrator: From around the globe, it's theCube. With digital coverage of AWS re:Invent 2020. Special coverage sponsored by AWS worldwide public sector. >> Hello and welcome to theCube virtual, and our coverage of AWS re:Invent 2020 with special coverage of public sector. We are theCube virtual and I'm your host, Justin Warren, and today I'm joined by two people. We have Jim Richberg the CISO for Public Sector from Fortinet who comes to us from Washington DC. Jim, welcome. >> Thank you. Thank you, Justin. >> And we also have Kenny Holmes. Who's the head of worldwide Public Sector Go-to-market from Fortinet as well. And he comes to us from Chicago in Illinois. Kenny, thanks. >> Yes, thank you. Thank you, Justin. >> Gentlemen, welcome to theCube. Now this year has been pretty dramatic and for a lot of us as I'm sure you're very well aware and it's been a bit of an accelerator for people's interest in public cloud in particular for the public sector. So what have you seen, Kenny? Sorry, Jim, we'll start with you around the federal government's interest in cloud. What have you noticed in their adoption of public cloud and AWS in this year? >> So, we used to joke in the federal government in my 34 years, they'll never let a good crisis go to waste. That you can make an upside out of any situation. And as you noted, Justin this has been a dramatic accelerator to federal government's adoption of cloud. Three quarters of the agencies were already moving in the direction of the cloud and planning to spend roughly $8 billion on it this year. And that was pre COVID. And the pace certainly picked up. We had the guidance that came out of DHS, the interim guidance that facilitated abilities to let these now as of mid-March remote teleworkers connect directly to the cloud without having to connect back through their agency infrastructure. So they issued very quick guidance to say, look you got to get the job done. You got to get it done in the cloud. So they did that as a way to accelerate it in the short term. And then they put out the guidance later this year for a trusted internet connection access which had a use case that was built around again facilitating the ability to say you can connect directly to the cloud with security in that direct line stack. You no longer have to haul your data back to the enterprise edge, to the data center on-premise to then go straight out to the cloud. So the federal government said we will give you the ability to move in the direction of cloud and the agencies have been using this at scale. And that's why roughly half of the federal workforce is now working from home. And many of them are using cloud-based applications and services. So the dramatic impact on the federal government. >> Yeah, we've seen it here in Nate in my home of Australia. The federal government is very keen on that but there's other levels of government as I'm sure we're all aware. Particularly as state and even local governments. So Kenny, maybe you could give us a bit of a flavor for how does local and that more regional government have they been doing it basically the same as federal government or is there something unique to the way that they've had to adapt? >> Well, state and local governments are certainly facing the really the perfect storm of the rising demand and declining resources. The pandemic has certainly driven, a lower tax base and lower revenues. And as a result of that, we've seen adjustments in budgets, et cetera but we're also in a position uniquely where it's also driving digital innovation at the same time. So we're seeing the two of those and they don't necessarily have kind of diabolically opposed if you think about it. So, the two of those are coming together but so they're doing more with less and they're using digital transformation to get there where in the commercial world a lot of folks who've been doing digital transformation for a long time. Now, government is being more forced into doing it. And they're really embracing that from our perspective. So we've seen traditionally security be at the top of their demands from a CIO perspective and their most important initiatives. The now we're seeing digital transformation and more specifically we're seeing cloud, right be a key part of that. So, they've done things initially, obviously moving email and some of those things but today we're seeing an increasing amount of workloads that we're seeing them, move from maybe a previous provider, over to AWS et cetera. So, those are some of the things that we're seeing from our state and local perspective >> To build on Kenny's point. I think the key differentiator Justin, between the federal and the state and local experience has been the resources, the federal government with COVID. The federal government runs a deficit. We've seen the deficit balloon, federal spending is up 17 to 20%, not what it's passed out of the stimulus money but simply what government is spending at the federal level. So we are using cloud at the federal level to do more as Kenny noted, state governments and local governments because they're funded exclusively by taxes they can't run a deficit. They have had to say we need to spend smarter because we can't spend more. We can't even spend as much and oh my goodness we have to deliver more digital services at the same time. So for them it has been a matter of having to eke greater efficiencies out of every dollar which has pointed them in the direction of AWS and the cloud in a different sense. And the federal government that said there's greater efficiencies because we need our remote telework people to get the job done, state government, it's the perfect storm. And if they don't do this they're literally going to have to curtail vital services. >> Yeah and as we've seen the security challenge pretty much is the same everywhere. I mean, there's some variations in exactly one sort of threat you might have as a federal government compared to local but broadly speaking, the malware and ransomware and things of that nature is pretty much just a miasma that we have to wade through. So what does, Fortinet helping with these customers, particularly as they move to as you mentioned, they're moving a lot of things into AWS. So what is Fortinet's role there in helping customers make better use of public cloud? >> So I think one of the things that Fortinet really has brought to this equation is they really are a very broad based cybersecurity provider. The biggest problem that organizations typically have, of course, you know in the cloud, it's misconfiguration by the customer. It's not AWS that's making the mistake 99% plus of the time it's misconfiguration by the customer. So having the ability to say if you know how to do your security in an on-premise environment, and you've got controls, capabilities and settings that you're comfortable with you can migrate those intact if they work for you into your cloud environment. So the fact that we are soup to nuts, that we have things at the edge and offer that same suite of capabilities in AWS allows us to be able to tell, help the users if they've configured it right, not have to go back and start from scratch and say, well, now that I'm in AWS I need to reconfigure other than as you have to do it because it's a different platform, but if you've got the policies in place that are managing security managing risk well for your enterprise carry them forward to a different environment. >> I think Kenny is that a particular opportunity there for local government? As you mentioned that restrained resources means that it's much more difficult for them to correctly configure their environments but also to make this level of change, they have a lot of other responsibilities it's difficult to become cybersecurity experts. Is that where you see Fortinet helping a great deal in more local government. >> Yes it is one of the key areas. The best way you can think of it is the ability to do what Jim was saying in a single pane of glass. And the fact that we can do that. That's something you don't hear a lot about anymore, but Fortinet actually is one of the largest security providers in the world. Has it single pane of glass across, being able to manage your on-prem infrastructure being able to manage whether if someone's migrating away from another cloud over to AWS and being able to look at these holistically it's just a fantastic way for them to be efficient as well as around training and certifications and helping our customers to be able to take advantage of the products without additional costs or other things that I've been throwing down the gauntlet for other providers to say, hey, security shouldn't be something else that they have to invest. They're going to invest in your technology. You should provide them with the training, provide them with security awareness, sobriety with certifications around your product that should be table stakes. >> And we do see a lot of that structure of how to do this and provide that training tends to be the same regardless of where you are. Is that something that we see say to getting defined at federal government level with some of the standards and then that then sort of trickles down into more local government. Kenny, is that something that you see happening at all? Or are we seeing things defined at local government that are actually going back the other way? >> Yeah, well, compliance runs across both. I mean, there's probably more compliance on the federal side that Jim could speak to but there's certainly compliance is always a major factor. And it can't be that just we need to do one-off solutions for a particular compliance issue. It needs to be holistic as we're talking about it. If I have to pick solutions based on what and where they're protecting. And now I have to think about the compliance for those as well. That's yet another thing to think about, I don't see our customers thinking that way. They don't have the skillsets to continue to evolve that way. That's an expanded, use of what they're doing and they just don't have those resources. So they have to be able to do more with less we've talking about, and to be able to take a platform like the fabric that Fortinet it offers it really offers that to them. >> At the federal level I'm not even sure that I would characterize it as compliance and regulatory things that state local government have to do, but the National Institute of Standards and Technology NIST tends to promulgate what are considered best practices. Then your cybersecurity framework has basically been adopted globally modified by certain places. And I did too in different ways, but when NIST comes up with something like zero trust architecture, new standards are understood, the 800 Series. I'm surprised people in local government where we'll talk about 800-53 or 800-207, just like we fed geeks too. So it's really setting best practices and standards that are different from compliance but to build on Kenny's point about resources where I think Kenny has flown the other way from local government up has been in the direction of saying state and local government had been the Canary in the coal mine on saying, you have to migrate to the cloud as a way of doing more with less. So the federal government has been turning the printing press, turning the crank faster and faster that will change, and this is one where can say you're spending smarter by moving in the direction of AWS and in accelerating that growth into the cloud, because my prediction as a former intelligence analyst is probably this time next year, a lot of federal agencies will be having the discussion about how to live in a much tightened budgetary environment because we went through something called sequestration 10 years ago that made for very tight zero sum budgeting. That's going to be a coming attraction and that's going to push federal government even more, so with the saying, I got to get the data off of Graham. I've got to continue to telework, Hey, and look we can follow the best practices of state and local government in this case. >> Well, it certainly sounds like we'll be able to learn from each other and adapt it. It's not going away. We're certainly going to have cybersecurity issues for the foreseeable future, but it sounds like there's a lot of work happening and there is room for happiness about how things are generally going. So, gentlemen, thank you so much for joining us here and please thank you to my guest Jim Richberg and Kenny Holmes from Fortinet. You've been watching theCube virtual and our coverage of AWS re:Invent 2020 with special coverage of the public sector. Make sure you check out all the rest of our coverage on your desktop laptop or phone wherever you might be. I've been your host, Justin Warren. I look forward to seeing you again soon. (soft upbeat music)

>> So nice to meet you. And I'm Tetsuhiko Teshima from German branch of MEI Laboratories. I'm working at the Technische Universitat Munchen to conduct wet experiment like using chemical and biological samples. So it's great honor and pleasure for me to have a chance to share with you some topics about miniaturized biointerfaces that I have been working on over the last six or seven years, I guess. So before starting, please let me introduce myself and my background. So I started to work in this company since this March, but until the last year, I was working in NTT Basic Research Laboratories that is located in Kanagawa, Japan. And I have work on basic nanoscience research. But when going back to the further, I was originally a student studying biology especially infectious microbiology. And then I learned about the miniaturize fluidic system to manipulate single cells and MEMS technologies that is kind of a fabrication process for semiconductor devices. So, this background motivate me to start interdisciplinary work, especially about biomedical engineering at NTT Corporation. So in recent year, wearable electrodes have been developed to continuously monitor the vital data, including the heart rate, ECG, or EMG waveforms for rapid diagnosis and early stage treatment of disease. So conventionally, rigid metals or metal-plated fibers have been widely used as the electrodes but they lack flexibility and biocompatibilities, which results in the noise in obtaining data and the patient allergic reaction during the long time years. So at NTT, we are working on the research and development of the conductive composite materials. So, due to its high flexibility and hydrophilicity and biocompatibilities, so this electrodes can successfully record ECG without any rashes and itches to the skin. So now these wearable electrodes cores toy are commercially available and funds are applied for not only the medical care and rehabilitation for the patients, but also for example, remote monitoring system of the workers, integration with these sportswear and entertainment show. But this product is originated from the basic scientific findings especially on the conductive polymers, PEDOT:PSS and silk fibers. So there was some mainly conducted by two key scientists clinician doctor Tsukada, and chemist doctor, Nakashima. In order to realize this product, they try so many prototypes. And make so many effort to obtain the pharmaceutical probables for medical usage. So through this experience, we are going back to the original material science and research and making non-toxic interfaces with cells and tissues in order to seek new kind of development. So, as a next challenge, I have focused on the electrodes that work inside the bodies. So we have the tissues and organs with electrical signals like heart and brain. So if implanted electrodes can work on these tissues, this help us to increase the variety of the vital data like EEG. And also it can directly treat the targeted tissues as a surgical, too, like CRT pacing. So in this case, these biointerfaces should be populated in very humid environment and in non-toxic manner. They also should be transformed into soft, three dimensional structures, in order to fit the shape of cells and tissues because they have very complicated 3D structures. So I decided to develop the basic electrode component that meets all of these requirements that is biocompatible for example, like 3D film-electrodes. So what I tried at first is to create a non-toxic, very soft and flexible film-electrodes using the materials that are using the heatable electrodes that is silk bundles and PEDOT:PSS. So, firstly, I dissolve the silk bundle to extract a specific protein and process into a palette shape using MEMS technologies, one of my main skill. So by adding the conductive polymers, >> PEDOT: PSS little by little, the palettes will gradually become blue but maintain the high optical transparency. Through this experiment, I discover a very unique materials scientific aspect of silk fibroin. So when PEDOT:PSS got added, the molecular structure and the confirmation of silk protein dramatically change from alpha helix to the beta sheet, and I focused this structure change, leads to the increase in conductivity compared with the PEDOT:PSS pristine films. By using the lithographic fabrication process, the films can be process into very tiny shape, with same deviation as single cell Lego. So this electrode is made of the silk fibroin, the, are very cell friendly protein. So the suspender cells prefer to adhere to their surface. So after attaching the cells on a surface, I can manipulate the cells while maintain the adhesive properties and electrically simulate the cells for the cool, very weak electrical signals from the cells. So in this step we created a non-toxic, transparent, and very flexible films and film-based electrodes. But please note that the, they are 2D and they're not 3D. So in the next step, I try to investigated how to transform these same 2D film to 3D shape. So here, among two polymers I used, so I replace the PEDOT:PSS with different type of polymers, there is parylene, like this. So when the parylene is adhering to the silk fibroin layers so, the gradient of the mechanical stiffness is formed in the synchronous directions as shown here. And this gradient causes the driving force of same film folding, like this. So this is a, this is a movie of the self-folding bilayer films. And you can see these rectangular patterns spontaneously transform into the cylindrical shapes. So just before folding, I suspended the cells on top of the films that is derived from the heart muscles. So the folding films, so here can gently rub the cells inside the tubes and you can incubate them safely more than for two weeks in order to reconstitute the self-beating, fiber-shaped muscle tissues, as shown here. So also this reconstituted tissues can be manipulated like building blocks by picking up and dissolving using glass capillaries. So I believe this techniques has a potential to facilitate high-order self-assembly like artificial neural networks or tissue engineering. So I realized to transform the two different film to 3D shape. So I use this method to transform into 3D electrodes. So in the final step, instead of the silk fibroin, I focus on using extremely thin electrodes materials that is called graphene. So as I explained as extremely thin, so it consist of the only single layer of carbon atom. So since they has just a single atom thickness, it has very high optical transparency and flexibility. So when the graphene was transform to the parylene surface I found this bilayer was tightly bonded due to the strong molecular interactions and the graphene itself straight on the parylene surface and this cell film becomes three dimensional electrodes, like tubeless structures. So as you can see in this movie, like this. So just after releasing them from the service lead, I instantly undergoes a phase transition and collapse. So since, this hexagonal molecular structure of graphene is distorted due to the folding process, so electrical characteristics dramatically change from firstly metallic to the semiconductor like non-linear shape, shown here. Or interestingly, the curvature and direction of the cell folding can be well controls with number of graphene, this and it's crystalline directions. So when a merged layers graphene were transfer, the curvature radius become smaller and smaller. And when the crystal, crystal, sorry, single crystalline graphene was loaded on the surface of parylene, this bilayer was folded in one fixed same direction, especially along the arms here siding. So by simply transferring the single carbon atom layer to the parylene surface, so we achieved the self-assembly of 3D transparent electrodes. In order to demonstrate biocompatibility of this graphene electrodes, we apply for the interface with neurons. So as there was a self-folding of silk fibroin, so we suspended the neurons are encapsulated in the self-folded graphene tubes, like this. So I made it a very tiny holes on the films. So the encapsulated neurons can uptake the nutrition and oxygen through this pore. So I culture the neurons for, without any damage, to the cells, and they exhibit cell-cell contact for tissue-like structures and they elongate their nuclei and axon to the outside through this pore. Therefore, the embedded neurons properly exhibit cell-cell interaction and drive intrinsic morphologies and function, which shows achievement of biocompatibility of the graphene electrodes. So in summary, we have been working on producing tiny 3D electrodes, step-by-step, using only four materials. For example, by mixing conductive polymer, >> PEDOT: PSS with silk fibroin, I made transparent and flexible 2D electrodes. By making a bilayer with silk fibroin with parylene, I demonstrated the self-assembly from 2D film to 3D shape. Finally, by transferring the graphene to paralyene, we could assembly tiny 3D electrodes. So in the future, we will continue to work on making bioelectrodes from the material science and biological viewpoints. However, these two approaches are not sufficient for the research or the bioelectronics. And we especially needed the technology of electrochemical assessment of fabricated electrodes and the method to lead up of obtain vital data and manipulation and analysis of obtain data. Therefore, I belong to both of the TUM and NTT research, in order to achieve the four system. So when I look over the world R&D of the bioelectronics, especially implantable electronics are very active, regardless of the university and industry. So firstly, John Rogers' group in University of Illinois, in United States, started to advocate about the implantable, flexible bioelectronics, more than 10 years ago. So now the research on, about it, is rapidly growing all over the world, not only US, but the Asia and Europe. So, the industrial community also tend to participate in this field. So I really hope to contributed to the scientific achievement and the creation of industry from the German basis, by making the most of my experience and cooperation with Japan and American side. So finally, I like to introduce my colleagues in TUM. So they are loved members and he, he is supervisor, Professor Bernhard Wolfrum, especially of the electrochemistry and electrochemical engineering process for biomedical application. So I'm so happy to work with this wonderful team and also appreciated the daily support of the members in NTT research in United States. Finally, let me just conclude by acknowledging my supervisor, mentors, Professor Wolfrum, Director Tomoike, and Dr. Alexander. And also the member from NTT who always support me, especially Mr. Kikuchi, Dr. Nakashima, Tsukada fellow, Director Goto, Dr. Yamamoto, and Director Sogawa. Finally, let me thanks Professor Offenhausser from Julich, for his kind assistance and introduction to this wonderful collaboration schemes. So, that's all. And I hope this presentation was useful to you. Thank you very much.

from the cube studios in Palo Alto in Boston connecting with thought leaders all around the world this is a cube conversation hi Bri welcome back this is Dave Volante and welcome to this special presentation made possible by IBM we're talking about data op data ops in Acton Steve Lucas here he's the senior vice president and director of data management at Associated Bank be great to see how are things going and in Wisconsin all safe we're doing well we're staying safe staying healthy thanks for having me Dave yeah you're very welcome so Associated Bank and regional bank Midwest to cover a lot of the territories not just Wisconsin but another number of other states around there retail commercial lending real estate offices stuff I think the largest bank in in Wisconsin but tell us a little bit about your business in your specific role sure yeah no it's a good intro we're definitely largest bank at Corvis concen and then we have branches in the in the Upper Midwest area so Minnesota Illinois Wisconsin our primary locations my role at associated I'm director data management so been with the bank a couple of years now and really just focused on defining our data strategy as an overall everything from data ingestion through consumption of data and analytics all the way through and then I'm also the data governance components and keeping the controls and the rails in place around all of our data in its usage so financial services obviously one of the more cutting-edge industries in terms of their use of technology not only are you good negotiators but you you often are early adopters you guys were on the Big Data bandwagon early a lot of financial services firms we're kind of early on in Hadoop but I wonder if you could tell us a little bit about sort of the business drivers and and where's the poor the pressure point that are informing your digital strategy your your data and data op strategy sure yeah I think that one of the key areas for us is that we're trying to shift from more of a reactive mode into more of a predictive prescriptive mode from a data and analytics perspective and using our data to infuse and drive more business decisions but also to infuse it in actual applications and customer experience etc so we have a wealth of data at our fingertips we're really focused on starting to build out that data link style strategy make sure that we're kind of ahead of the curve as far as trying to predict what our end users are going to need and some of the advanced use cases we're going to have before we even know that they actually exist right so it's really trying to prepare us for the future and what's next and and then abling and empowering the business to be able to pivot when we need to without having everything perfect that they prescribed and and ready for what if we could talk about a little bit about the data journey I know it's kind of a buzzword but in my career as a independent observer and analyst I've kind of watched the promise of whether it was decision support systems or enterprise data warehouse you know give that 360 degree view of the business the the real-time nature the the customer intimacy all that in and up until sort of the recent digital you know meme I feel as though the industry hasn't lived up to that promise so I wonder if you could take us through the journey and tell us sort of where you came from and where you are today and I really want to sort of understand some of the successes they've had sure no that's a that's a great point nice I feel like as an industry I think we're at a point now where the the people process technology have sort of all caught up to each other right I feel that that real-time streaming analytics the data service mentality just leveraging web services and API is more throughout our organization in our industry as a whole I feel like that's really starting to take shape right now and and all the pieces of that puzzle have come together so kind of where we started from a journey perspective it was it was very much if your your legacy reporting data warehouse mindset of tell me tell me the data elements that you think you're going to need we'll figure out how do we map those in and form them we'll figure out how to get those prepared for you and that whole lifecycle that waterfall mentality of how do we get this through the funnel and get it to users quality was usually there the the enablement was still there but it was missing that that rapid turnaround it was also missing the the what's next right than what you haven't thought of and almost to a point of just discouraging people from asking for too many things because it got too expensive it got too hard to maintain there was some difficulty in that space so some of the things that we're trying to do now is build that that enablement mentality of encouraging people to ask for everything so when we bring out new systems - the bank is no longer an option as far as how much data they're going to send to us right we're getting all of the data we're going to we're going to bring that all together for people and then really starting to figure out how can this data now be used and and we almost have to push that out and infuse it within our organization as opposed to waiting for it to be asked for so I think that all of the the concepts so that bringing that people process and then now the tools and capabilities together has really started to make a move for us and in the industry I mean it's really not an uncommon story right you had a traditional data warehouse system you had you know some experts that you had to go through to get the data the business kind of felt like it didn't own the data you know it felt like it was imposing every time it made a request or maybe it was frustrated because it took so long and then by the time they got the data perhaps you know the market had shifted so it create a lot of frustration and then to your point but but it became very useful as a reporting tool and that was kind of this the sweet spot so so how did you overcome that and you know get to where you are today and you know kind of where are you today I was gonna say I think we're still overcoming that we'll see it'll see how this all goes right I think there's there's a couple of things that you know we've started to enable first off is just having that a concept of scale and enablement mentality and everything that we do so when we bring systems on we bring on everything we're starting to have those those components and pieces in place and we're starting to build more framework base reusable processes and procedures so that every ask is not brand new it's not this reinvent the wheel and resolve for for all that work so I think that's helped if expedite our time to market and really get some of the buy-in and support from around the organization and it's really just finding the right use cases and finding the different business partners to work with and partner with so that you help them through their journey as well is there I'm there on a similar roadmap and journey for for their own life cycles as well in their product element or whatever business line there so from a process standpoint that you kind of have to jettison the you mentioned waterfall before and move to a more being an agile approach did it require different different skill sets talk about the process and the people side of yeah it's been a it's been a shift we've tried to shift more towards I wouldn't call us more formal agile I would say we're a little bit more lean from a an iterative backlog type of approach right so what are you putting that work together in queues and having the queue of B reprioritized working with the business owners to help through those things has been a key success criteria for us and how we start to manage that work as opposed to opening formal project requests and and having all that work have to funnel through some of the old channels that like you mentioned earlier kind of distracted a little bit from from the way things had been done in the past and added some layers that people felt potentially wouldn't be necessary if they thought it was a small ask in their eyes you know I think it also led to a lot of some of the data silos and and components that we have in place today in the industry and I don't think our company is alone and having data silos and components of data in different locations but those are there for a reason though those were there because they're they're filling a need that has been missing or a gap in the solution so what we're trying to do is really take that to heart and evaluate what can we do to enable those mindsets and those mentalities and find out what was the gap and why did they have to go get a siloed solution or work around operations and technology and the channels that had been in place what would you say well your biggest challenges in getting from point A to point B point B being where you are today there were challenges on each of the components of the pillar right so people process technology people are hard to change right men behavioral type changes has been difficult that there's components of that that definitely has been in place same with the process side right so so changing it into that backlog style mentality and working with the users and having more that be sort of that maintenance type support work is is a different call culture for our organization and traditional project management and then the tool sets right the the tools and capabilities we had to look in and evaluate what tools do we need to Mabel this behavior in this mentality how do we enable more self-service the exploration how do we get people the data that they need when they need it and empower them to use so maybe you could share with us some of the outcomes and I know it's yeah we're never done in this business but but thinking about you know the investments that you've made in intact people in reprocessing you know the time it takes to get leadership involved what has been so far anyway the business outcome and you share any any metrics or it is sort of subjective a guidance I yeah I think from a subjective perspective the some of the biggest things for us has just been our ability to to truly start to have that very 60 degree view of the customer which we're probably never going to get they're officially right there's there everyone's striving for that but the ability to have you know all of that data available kind of at our fingertips and have that all consolidated now into one one location one platform and start to be that hub that starts to redistribute that data to our applications and infusing that out has been a key component for us I think some of the other big kind of components are differentiators for us and value that we can show from an organizational perspective we're in an M&A mode right so we're always looking from a merger and acquisition perspective our the model that we've built out from a data strategy perspective has proven itself useful over and over now in that M&A mentality of how do you rapidly ingest new data sets it had understood get it distributed to the right consumers it's fit our model exactly and and it hasn't been an exception it's been just part of our overall framework for how we get that data and it wasn't anything new that we had to do different because it was M&A just timelines were probably a little bit more expedited the other thing that's been interesting in some of the world that were in now right from a a Kovach perspective and having a pivot and start to change some of the way we do business and some of the PPP loans and and our business models sort of had to change overnight and our ability to work with our different lines of business and get them the data they need to help drive those decisions was another scenario where had we not had the foundational components there in the platform there to do some of this if we would have spun a little bit longer so your data ops approach I'm gonna use that term helped you in this in this kovat situation I mean you had the PPE you had you know of slew of businesses looking to get access to that money you had uncertainty with regard to kind of what the rules of the game were what you was the bank you had a Judah cape but you it was really kind of opaque in terms of what you had to do the volume of loans had to go through the roof in the time frame it was like within days or weeks that you had to provide these so I wonder if we could talk about that a little bit and how you're sort of approach the data helped you be prepared for that yeah no it was a race I mean the bottom line was it felt like a race right from from industry perspective as far as how how could we get this out there soon enough fast enough provide the most value to our customers our applications teams did a phenomenal job on enabling the applications to help streamline some of the application process for the loans themselves but from a data and reporting perspective behind the scenes we were there and we had some tools and capabilities and readiness to say we have the data now in our in our lake we can start to do some business driven decisions around all all of the different components of what's being processed on a daily basis from an application perspective versus what's been funded and how do those start to funnel all the way through doing some data quality checks and operational reporting checks to make sure that that data move properly and got booked in in the proper ways because of the rapid nature of how that was was all being done other covent type use cases as well we had some some different scenarios around different feed reporting and and other capabilities that the business wasn't necessarily prepared for we wouldn't have planned to have some of these types of things and reporting in place that we were able to give it because we had access to all the data because of these frameworks that we had put into place that we could pretty rapidly start to turn around some of those data some of those data points and analytics for us to make some some better decisions so given the propensity in the pace of M&A there has to be a challenge fundamentally in just in terms of data quality consistency governance give us the before and after you know before kind of before being the before the data ops mindset and after being kind of where you are today I think that's still a journey we're always trying to get better on that as well but the data ops mindset for us really has has shifted us to start to think about automation right pipelines that enablement a constant improvement and and how do we deploy faster deploy more consistently and and have the right capabilities in place when we need it so you know where some of that has come into place from an M&A perspective is it's really been around the building scale into everything that we do dezq real-time nature this scalability the rapid deployment models that we have in place is really where that starts to join forces and really become become powerful having having the ability to rapidly ingesting new data sources whether we know about it or not and then exposing that and having the tools and platforms be able to expose that to our users and enable our business lines whether it's covent whether it's M&A the use cases keep coming up right they we keep running into the same same concept which is how rapidly get people the data they need when they need it but still provide the rails and controls and make sure that it's governed and controllable on the way as well [Music] about the tech though wonder if we could spend some time on that I mean can you paint a picture of us so I thought what what what we're looking at here you've got you know some traditional IDI w's involved I'm sure you've got lots of data sources you you may be one of the zookeepers from the the Hadoop days with a lot of you know experimentation there may be some machine intelligence and they are painting a pic before us but sure no so we're kind of evolving some of the tool sets and capabilities as well we have some some generic kind of custom in-house build ingestion frameworks that we've started to build out for how to rapidly ingest and kind of script out the nature of of how we bring those data sources into play what we're what we've now started as well as is a journey down IBM compact product which is really gonna it's providing us that ability to govern and control all of our data sources and then start to enable some of that real-time ad hoc analytics and data preparation data shaping so some of the components that we're doing in there is just around that data discovery pointing that data sources rapidly running data profiles exposing that data to our users obviously very handy in the emanating space and and anytime you get new data sources in but then the concept of publishing that and leveraging some of the AI capabilities of assigning business terms in the data glossary and those components is another key component for us on the on the consumption side of the house for for data we have a couple of tools in place where Cognos shop we do a tableau from a data visualization perspective as well that what that were we're leveraging but that's where cloud pack is now starting to come into play as well from a data refinement perspective and giving the ability for users to actually go start to shape and prep their data sets all within that governed concept and then we've actually now started down the enablement path from an AI perspective with Python and R and we're using compact to be our orchestration tool to keep all that governed and controlled as well enable some some new AI models and some new technologies in that space we're actually starting to convert all of our custom-built frameworks into python now as well so we start to have some of that embedded within cloud pack and we can start to use some of the rails of those frameworks with it within them okay so you've got the ingest and ingestion side you've done a lot of automation it sounds like called the data profiling that's maybe what classification and automating that piece and then you've got the data quality piece the governance you got visualization with with tableau and and this kind of all fits together in a in an open quote unquote open framework is that right yeah I exactly I mean the the framework itself from our perspective where we're trying to keep the tools as as consistent as we can we really want to enable our users to have the tools that they need in the toolbox and and keep all that open what we're trying to focus on is making sure that they get the same data the same experience through whatever tool and mechanism that they're consuming from so that's where that platform mentality comes into place having compact in the middle to help govern all that and and reprovision some of those data sources out for us has it has been a key component for us well see if it sounds like you're you know making a lot of progress or you know so the days of the data temple or the high priest of data or the sort of keepers of that data really to more of a data culture where the businesses kind of feel ownership for their own data you believe self-service I think you've got confidence much more confident than the in the compliance and governance piece but bring us home just in terms of that notion of data culture and where you are and where you're headed no definitely I think that's that's been a key for us too as as part of our strategy is really helping we put in a strategy that helps define and dictate some of those structures and ownership and make that more clear some of the of the failures of the past if you will from an overall my monster data warehouse was around nobody ever owned it there was there wasn't you always ran that that risk of either the loudest consumer actually owned it or no one actually owned it what we've started to do with this is that Lake mentality and and having all that data ingested into our our frameworks the data owners are clear-cut it's who sends that data in what is the book record system for that source data we don't want a ability we don't touch it we don't transform it as we load it it sits there and available you own it we're doing the same mentality on the consumer side so we have we have a series of structures from a consumption perspective that all of our users are consuming our data if it's represented exactly how they want to consume it so again that ownership we're trying to take out a lot of that gray area and I'm enabling them to say yeah I own this I understand what I'm what I'm going after and and I can put the the ownership and the rule and rules and the stewardship around that as opposed to having that gray model in the middle that that that we never we never get but I guess to kind of close it out really the the concept for us is enabling people and end-users right giving them the data that they need when they need it and it's it's really about providing the framework and then the rails around around doing that and it's not about building out a formal bill warehouse model or a formal lessor like you mentioned before some of the you know the ivory tower type concepts right it's really about purpose-built data sets getting the giving our users empowered with the data they need when they need it all the way through and fusing that into our applications so that the applications and provide the best user experiences and and use the data to our advantage all about enabling the business I got a shove all I have you how's that IBM doing you know as a as a partner what do you like what could they be doing better to make your life easier sure I think I think they've been a great partner for us as far as that that enablement mentality the cloud pack platform has been a key for us we wouldn't be where we are without that tool said I our journey originally when we started looking at tools and modernization of our staff was around data quality data governance type components and tools we now because of the platform have released our first Python I models into the environment we have our studio capabilities natively because of the way that that's all container is now within cloud back so we've been able to enable new use cases and really advance us where we would have a time or a lot a lot more technologies and capabilities and then integrate those ourselves so the ability to have that all done has or and be able to leverage that platform has been a key to helping us get some of these roles out of this as quickly as we have as far as a partnership perspective they've been great as far as listening to what what the next steps are for us where we're headed what can we what do we need more of what can they do to help us get there so it's it's really been an encouraging encouraging environment I think they as far as what can they do better I think it's just keep keep delivering write it delivery is ping so keep keep releasing the new functionality and features and keeping the quality of the product intact well see it was great having you on the cube we always love to get the practitioner angle sounds like you've made a lot of progress and as I said when we're never finished in this industry so best of luck to you stay safe then and thanks so much for for sharing appreciate it thank you all right and thank you for watching everybody this is Dave Volante for the cube data ops in action we got the crowd chat a little bit later get right there but right back right of this short break [Music] [Music]

>>Ly from San Diego, California. It's the cube covering to clock in cloud native con brought to you by red hat, the cloud native computing foundation and its ecosystem Marsh. >>Welcome back to San Diego. It's CubeCon cloud native con 2019. You're watching the cube. I'm streaming in my cohost for three days of live coverage is John Troyer and happened at welcome fresh off the keynote stage to my right is as hers as har who's the chief architect for telco at red hat and the man that was behind the scenes for a lot of it, hunting Garcia, telco solutions manager at red hat. A gentlemen, thanks so much for joining us and a very interesting keynote. So you know 5g uh, you know, my background's networking, we all watch it. Um, uh, let's say my telco provider already says that I have something related to five G on my phone that we grumble a little bit about, but we're not going to talk about that where we are going to talk about his keynote. Uh, we had a China mobile up on stage. Uh, maybe a, I love a little bit behind the scenes as you were saying. Uh, you know, the cloud native enabled not just uh, you know, the keynote and what it's living, but it gets a little bit of what >>well, sure. Um, look, when we took on this particular project to build a cloud native environment, uh, for five genes, we spent a lot of time planning and in fact this is a guy who actually did, you know, most of that work, um, to do a lot of planning in terms of picking different components and getting that together. Um, one of the things that cloud native environment allows us to do is bring things up quickly. The resilience part of it and the scale bar, right? Those are the two important components and attributes of cloud native. In fact, what happened last night was obviously one of the circuit breakers trapped and we actually lost power to that particular entire part that is onstage. I mean, nobody knows about this. I didn't talk about it as part of the keynote, but guess what? Through because it was cloud native because it was built in an automated fashion. People were able to work. Yes, they spent about three hours or so to actually get that back up. But we got it back up and running and we showed it live today. But what, I'm not trying to stress on how it failed a white fail. I'm trying to stress on how quickly things came back up and more important. The only cloud native way of doing things could have done that. Otherwise it wouldn't have been possible. All right. >>as, as the man behind the scenes there. Uh, it's great when we have, you know, here's actually the largest telco provider in the world. Uh, you know, showing what it, it's happened. So the title Kubernetes everywhere that telco edge gets a little bit of a hind, the scenes as to kind of the, the, the mission of building the solution and how you got it, you know, your, your, your customers, your partners, uh, engaged and excited to participate in. >> This is what's that very thirsting enterprise through realize. Actually, we took four months around, uh, 15 partners. And, uh, I would say partners >>because in that case, I'm taking, uh, uh, bell Canada and China mobile is a partners. They are part of the project. They were giving us a requirement, helping us all the way to it and together other, uh, more, uh, commercial partners. And of course, uh, as whatsover Allianz, like the team in the and the open interface, Allianz is, we're working with us is, was about 8,200 people working behind the scenes to get this work, uh, to have a lab, uh, directly, completely set up with a full, uh, Fuji containerized MoMA and network in France, uh, have the same in Montreal. Fuji and fogey called directly Montiel as well, uh, in one of our partners, uh, Calum labs and then bringing here the fudgey pop, uh, and have everything connected to the public cloud. So we have everything in there. So all the technology, all the mobile technology was there. >>We have enterprise technology that we're using to connect all the, all the labs and the, and the pop here with the public cloud to. Uh, um, technology and we have of course deployed as, as a, as our, uh, was mentioning. We deployed Kubernete is on the public cloud and we have as well Kubernete is open, rehabbed, open stack, uh, sorry. They had OpenShift container platform running on the, on all the premise in the lab in France and Davi, Marcia and they pop here. Uh, as I say, it was kind of an interesting enterprise. We have some hiccups last night, but uh, we were able to put that out the world telco, >>very specialized, very high service level agreements. I always want by phone to work and so a little bit, uh, uses different terminology than the rest of it sometimes. Right. And MP and VNF and VCO. But so maybe let's real to tell people a little bit like what are we actually talking about here? I mean, people also may not be following edge and, and teleco and what's actually sitting in their home town or, or it used to be embedded chips and none, it was a like Linux, but we're actually talking about installing Kubernetes clusters in a lot of different, really interesting typologies. That's absolutely true actually with the way how, and described it as perfect in the sense that we actually had Kubernetes clusters sitting in a data center environment in France, in Montreal and a remote pop that's sitting here on stage. So it was not just independent clusters but also stretch clusters where we actually had some worker nodes here that will attach back to the Montreal cluster. >>So the flexibility that it gave us was just awesome. We can't achieve that. Uh, you know, in general. But you brought up an interesting topic around, uh, you know, Getty or, uh, or, or the Teleco's operating environment, which is different and cloud native principles has, are a little bit different where they weren't very high availability, they weren't very high reliability with good amount of redundancy. Well, cloud native and actually those attributes to you. But the operational model is very different. You have to almost use codas throwaway hardware as throwaway and do a horizontal scale model to be able to build that. Whereas in the older environment, hardware was a premium switches and routers with a premium and you couldn't have a failure. So you needed all of those, you know, compliance of high availability and upgradability and so on. Here I'm upgrading processes in Linux, I'm upgrading applications. I can go deploy anytime, tear them down. Anytime I'm monitoring the infrastructure, using metrics, using telemetry. That wasn't the case before. So a different operating environment, but it provides actually better residency models than what telcos are actually yesterday. Yeah. >>Um, it's a complicated ecosystem to put all these pieces together. Uh, it gives, gives a little insight as to, uh, you know, red hats, leadership and uh, the, the, the partners that help you put it in. >>I will let him answer that. >>Um, is another, our first rodeo. We have been working on the vitro central office project with the, with the leaner foundation, uh, networking and Hopi NFV community for three last years. Uh, let's say, and the interesting part of this one is that even though we typically get with working with what the technology that they are using now, uh, we decided it's time to go with the technologies that we'll be using from now on. Um, but of course, uh, there is a set of partners that we need. We need to build the infrastructure from scratch. So for example, we have a Lenovo that was bringing all the, all the servers, uh, for the, for the set up in, uh, and here in San Diego, which actually the San Diego pub was built originally in Raleigh, Illinois, facilities and cheap all over the country to here for the show. Uh, and uh, then we have the fabric part. >>So the networking part, that's his cologne. Uh, this was working and bringing us the software defined fabric, uh, to connect all the different future. And then, then we start building this over layers on top. So we have, they had OpenShift container platform for the to completely deploy over metal servers. And then we start adding all the rest of the components, like the four G core fundamental Tran, like dividing for GFG radio from Altron, uh, together with Intel come Scott. That's his building. He started building the mobile part of it in Montreal, a San Diego. And then we add on top of that. Then we start adding the IMS core in the public cloud and then we connect everything through the by tuning. >>So a couple of things that I'd like to highlight in terms of coordinating partners, getting to know when they're ready, figuring out an onboarding process that gives them a sandbox to play with their configurations first before you connect them back into the main environment. Partitioning that working simultaneously with Malden, we had a Slack board that was full of messages every day. We had a nonstop, you know, every morning we had a scam call, right then it's like a scrum meeting every morning, just a daily stand up from eight 30 to nine 30. And we continue that all over the day. >>So as her, one of the things I really like to China mobile, uh, when they talked about in the keynote, first of all they said, you know, the problem is, you know, 20 by 2026, you know, it's, it's rainbows and unicorns and you know, 5g, uh, you know, will help enable so much around the planet. Seriously. Um, but you know, today she, she talked about major challenge in the rollout and infrastructure and service and capability. So, you know, help us understand a little bit the hype from reality of where we are with five G what we could expect. >>Absolutely. We are going through the hype phase right now, right? We are absolutely all the operators want FFG service to be delivered for sure. The reason why they want it to be delivered as they don't want to be left behind. Now there are some operators when we in more opportunistic and looking at 5g as a way to insert themselves into different conversations, IOT conversation, um, smart city conversation, right? Um, edge compute conversation. So they're being very strategic about how the big, the set of technologies, how they go deploy in that particular infrastructure and strategically offer capabilities and build partnerships. Nobody's going to rip out their existing three G four G network and replace that with 5g by 2026. It's not gonna happen, but what will happen by 2026 is an incremental phase of services that will be continued to offer. As an example, I'll give you, um, cable providers are looking at 5g as a way to get into homes because they can deploy in millimeter wave band a radio closer to the house and get a very high speed multi-gigabit high speed connection into the home without having to worry about what's your copper look like? >>Do I have fiber to the home? Do I have fiber to the business and so on. And so. So that's actually an interesting, >>okay, so you're saying solving the last mile issue in a very targeted use. >>Absolutely. So that's one. The other area might be running a partnership with BMW Toyota in, you know, some of these car companies to provide telemetry back from cars into their own, you know, operating environment so that they know what's going on, what's being used, how is it being used, how can we, how can we do provide diagnosis before the car actually begins to fail? Uh, big, you know, private environments like oil and gas mining, they are going to deploy public safety and security where all of these, you know, policemen on and safety personnel are required to now use body cams. Now you have video feeds coming from hundreds of people. There are deployment and incidents. Now you can take that information you need high speed broadband, you need the ability to analyze data and do analytics and provide feedback immediately so that they can actually act. So do three, this specific targeted use case, even a country like India where they're talking about using 5g for very specific use cases, not replacing your phone calling. >>I love that point. And it kind of ties back into some of the other things you were saying about the a agility and the operational model. And I relate it back to it. You know, my, again, my perception of some telco maybe 20 years old and that they had a tendency to do very monolithic projects. And you know, when you're out, when you're rolling out a infrastructure across the country, there's a certain, uh, monolithic nature to it. But you're talking about rolling out one, rolling out individual projects rolling out. That's also the advice we give to it. Try it with one thing, you know, try open shift with that one application and then also though, but it takes uh, the upskilling and the cultural model. So true with your telco petitioners who are, we're on Slack, they're with you and I, you know, I don't, I don't know if there's any relation, any other kinds of things to pull out about the mirror of, of the it transformation with telco transformation and colon Turner. That's actually a good point that you bring up, >>right? Look, the costs of building, if I have infrastructure from ground up is extremely high. If they want to completely revamp that. You're talking about replacing every single radio, you're talking about adding capacity more adding, you know, backhaul capacity and so on. So that isn't going to happen overnight. It's going to happen. It may take even more 10 years. Right. I mean in the most interesting thing, that stat stack that I saw was even LTE is going to grow. LTE subscriber count is going to grow for the next two years before it flatmates. So we're not going to LTE four G that's been around for a decade almost. Right. And it's going to still grow for the next two years, then it's going to flatten and then you'll start to see more 5g subscribers. Now back to the point that you were bringing up in terms of operational model change and in terms of how things will be I D principles applying it principles to telco. >>Um, there are still some challenges that we need to solve in Coobernetti's environment in particular, uh, to address the teleco side of the house. And in fact through this particular proof of concept, that was one of the things we were really attempting to highlight and shine a light on. Um, but in terms of operational models, what use applicable and it will now be totally applicable on the telco network, the CIC pipeline. There's delivery of applications and software that testing and integration, the, you know, um, operational models. Absolutely. Those, in fact, I actually have a number of service providers and telcos that I talked to who are actually thinking about a common platform for it end telco network. And they are now saying, okay, red hat, can you help us in terms of designing this type of a system. So I think what could speak to you a little bit about, uh, in this context is how the same infrastructure can be used for any kind of application. So you want to talk about how the community's platform can be used to deploy CNS and then to deploy applications and how you've shown that. Yeah. Well this is what, >>what we have been doing, right. So we have, uh, the coordinators platform does, is actually deploy and the services we have, all these partners are bringing their Cloudnative uh, function, uh, applications on top of that, that what we are calling the CNF the quantities and network functions. And basically what we were doing as well during the whole process is that we have, those partners are still developing, still finishing the software. So we were building and deploying at the same time and testing on the same time. So during the last four months, and even I can tell you even just to deny >>even last night, so the full CACD pipeline that we deploy in ID side, here it is in operation on the network side. >>Well yeah. So, so I, I want to give you the final word cause you know, John was talking about it cycles, you know, if you think about enterprises, how long they used to take to deploy things, uh, and what cloud data is doing for them. Uh, it sounds like we're going through a similar trends. >>Absolutely big in a big way. Um, telcos are actually deploying a private cloud environment and they're also leveraging public cloud in mind. In fact, sometimes they using public cloud as sandbox for their development to be completed until they get deployed and private. Claremont, they still need the private time enrollment for their own purposes, like security, data sovereignty and uh, you know, their own operational needs. So, but they want to make it as transparent as possible. And in fact, that was one of the things we want to also attempted to show, which is a public cloud today, a private cloud and bare metal, a private cloud on OpenStack. And it was like, and you know, it came together, it worked, but it is real. That's more important. And, uh, for enterprise and for telcos to be literally going down the same path with respect to their applications, their services and their operational models. I think this is really a dream come true. >>Well, congratulations on the demo. Uh, but even more importantly, congratulations on the progress. Great to see, uh, you know, the global impact that's going to have in the telecommunications market. Definitely look forward to hearing more than. >>Thank you very much. Thank you. The opportunity to >>actually be here. All right. For John Troyer, I'm Stu Miniman back with lots more here from CubeCon Claude, date of con 2019 in San Diego, California. Thanks for watching the queue.

>>from Las Vegas. It's the Q covering. Next work. 2019 America's Do You buy Juniper Networks? Come back already. Jeffrey here with the Cube were in Las Vegas at Caesar's at the Juniper. Next work event. About 1000 people kind of going over a lot of new cool things. 400 gigs. Who knew that was coming out of new information for me? But that's not what we're here today. We're here for the fourth installment of around the Cube unpacking. I were happy to have all the winners of the three previous rounds here at the same place. We don't have to do it over the phone s so we're happy to have him. Let's jump into it. So winner of Round one was Bob Friday. He is the VP and CTO at Missed the Juniper Company. Bob, Great to see you. Good to be back. Absolutely. All the way from Seattle. Sharna Parky. She's a VP applied scientist at Tech CEO could see Sharna and, uh, from Google. We know a lot of a I happen to Google. Rajan's chef. He is the V p ay ay >>product management on Google. Welcome. Thank you, Christy. Here >>All right, so let's jump into it. So just warm everybody up and we'll start with you. Bob, What are some When you're talking to someone at a cocktail party Friday night talking to your mom And they say, What is a I What >>do you >>give him? A Zen examples of where a eyes of packing our lives today? >>Well, I think we all know the examples of the south driving car, you know? Aye, aye. Starting to help our health care industry being diagnosed cancer for me. Personally, I had kind of a weird experience last week at a retail technology event where basically had these new digital mirrors doing facial recognition. Right? And basically, you start to have little mirrors were gonna be a skeevy start guessing. Hey, you have a beard, you have some glasses, and they start calling >>me old. So this is kind >>of very personal. I have a something for >>you, Camille, but eh? I go walking >>down a mall with a bunch of mirrors, calling me old. >>That's a little Illinois. Did it bring you out like a cane or a walker? You know, you start getting some advertising's >>that were like Okay, you guys, this is a little bit over the top. >>Alright, Charlotte, what about you? What's your favorite example? Share with people? >>Yeah, E think one of my favorite examples of a I is, um, kind of accessible in on your phone where the photos you take on an iPhone. The photos you put in Google photos, they're automatically detecting the faces and their labeling them for you. They're like, Here's selfies. Here's your family. Here's your Children. And you know, that's the most successful one of the ones that I think people don't really think about a lot or things like getting loan applications right. We actually have a I deciding whether or not we get loans. And that one is is probably the most interesting one to be right now. >>Roger. So I think the father's example is probably my favorite as well. And what's interesting to me is that really a I is actually not about the Yeah, it's about the user experience that you can create as a result of a I. What's cool about Google photos is that and my entire family uses Google photos and they don't even know actually that the underlying in some of the most powerful a I in the world. But what they know is they confined every picture of our kids on the beach whenever they whenever they want to. Or, you know, we had a great example where we were with our kids. Every time they like something in the store, we take a picture of it, Um, and we can look up toy and actually find everything that they've taken picture. >>It's interesting because I think most people don't even know the power that they have. Because if you search for beach in your Google photos or you search for, uh, I was looking for an old bug picture from my high school there it came right up until you kind of explore. You know, it's pretty tricky, Raja, you know, I think a lot of conversation about A They always focus the general purpose general purpose, general purpose machines and robots and computers. But people don't really talk about the applied A that's happening all around. Why do you think that? >>So it's a good question. There's there's a lot more talk about kind of general purpose, but the reality of where this has an impact right now is, though, are those specific use cases. And so, for example, things like personalizing customer interaction or, ah, spotting trends that did that you wouldn't have spotted for turning unstructured data like documents into structure data. That's where a eyes actually having an impact right now. And I think it really boils down to getting to the right use cases where a I right? >>Sharon, I want ask you. You know, there's a lot of conversation. Always has A I replace people or is it an augmentation for people? And we had Gary Kasparov on a couple years ago, and he talked about, you know, it was the combination if he plus the computer made the best chess player, but that quickly went away. Now the computer is actually better than Garry Kasparov. Plus the computer. How should people think about a I as an augmentation tool versus a replacement tool? And is it just gonna be specific to the application? And how do you kind of think about those? >>Yeah, I would say >>that any application where you're making life and death decisions where you're making financial decisions that disadvantage people anything where you know you've got u A. V s and you're deciding whether or not to actually dropped the bomb like you need a human in the loop. If you're trying to change the words that you are using to get a different group of people to apply for jobs, you need a human in the loop because it turns out that for the example of beach, you type sheep into your phone and you might get just a field, a green field and a I doesn't know that, uh, you know, if it's always seen sheep in a field that when the sheep aren't there, that that isn't a sheep like it doesn't have that kind of recognition to it. So anything were we making decisions about parole or financial? Anything like that needs to have human in the loop because those types of decisions are changing fundamentally the way we live. >>Great. So shift gears. The team are Jeff Saunders. Okay, team, your mind may have been the liquid on my bell, so I'll be more active on the bell. Sorry about that. Everyone's even. We're starting a zero again, so I want to shift gears and talk about data sets. Um Bob, you're up on stage. Demo ing some some of your technology, the Miss Technology and really, you know, it's interesting combination of data sets A I and its current form needs a lot of data again. Kind of the classic Chihuahua on blue buried and photos. You got to run a lot of them through. How do you think about data sets? In terms of having the right data in a complete data set to drive an algorithm >>E. I think we all know data sets with one The tipping points for a I to become more real right along with cloud computing storage. But data is really one of the key points of making a I really write my example on stage was wine, right? Great wine starts a great grape street. Aye, aye. Starts a great data for us personally. L s t M is an example in our networking space where we have data for the last three months from our customers and rule using the last 30 days really trained these l s t m algorithms to really get that tsunami detection the point where we don't have false positives. >>How much of the training is done. Once you once you've gone through the data a couple times in a just versus when you first started, you're not really sure how it's gonna shake out in the algorithm. >>Yeah. So in our case right now, right, training happens every night. So every night, we're basically retraining those models, basically, to be able to predict if there's gonna be an anomaly or network, you know? And this is really an example. Where you looking all these other cat image thinks this is where these neural networks there really were one of the transformational things that really moved a I into the reality calling. And it's starting to impact all our different energy. Whether it's text imaging in the networking world is an example where even a I and deep learnings ruling starting to impact our networking customers. >>Sure, I want to go to you. What do you do if you don't have a big data set? You don't have a lot of pictures of chihuahuas and blackberries, and I want to apply some machine intelligence to the problem. >>I mean, so you need to have the right data set. You know, Big is a relative term on, and it depends on what you're using it for, right? So you can have a massive amount of data that represents solar flares, and then you're trying to detect some anomaly, right? If you train and I what normal is based upon a massive amount of data and you don't have enough examples of that anomaly you're trying to detect, then it's never going to say there's an anomaly there, so you actually need to over sample. You have to create a population of data that allows you to detect images you can't say, Um oh, >>I'm going to reflect in my data set the percentage of black women >>in Seattle, which is something below 6% and say it's fair. It's not right. You have to be able thio over sample things that you need, and in some ways you can get this through surveys. You can get it through, um, actually going to different sources. But you have to boot, strap it in some way, and then you have to refresh it, because if you leave that data set static like Bob mentioned like you, people are changing the way they do attacks and networks all the time, and so you may have been able to find the one yesterday. But today it's a completely different ball game >>project to you, which comes first, the chicken or the egg. You start with the data, and I say this is a ripe opportunity to apply some. Aye, aye. Or do you have some May I objectives that you want to achieve? And I got to go out and find the >>data. So I actually think what starts where it starts is the business problem you're trying to solve. And then from there, you need to have the right data. What's interesting about this is that you can actually have starting points. And so, for example, there's techniques around transfer, learning where you're able to take an an algorithm that's already been trained on a bunch of data and training a little bit further with with your data on DSO, we've seen that such that people that may have, for example, only 100 images of something, but they could use a model that's trained on millions of images and only use those 100 thio create something that's actually quite accurate. >>So that's a great segue. Wait, give me a ring on now. And it's a great Segway into talking about applying on one algorithm that was built around one data set and then applying it to a different data set. Is that appropriate? Is that correct? Is air you risking all kinds of interesting problems by taking that and applying it here, especially in light of when people are gonna go to outweigh the marketplace, is because I've got a date. A scientist. I couldn't go get one in the marketplace and apply to my data. How should people be careful not to make >>a bad decision based on that? So I think it really depends. And it depends on the type of machine learning that you're doing and what type of data you're talking about. So, for example, with images, they're they're they're well known techniques to be able to do this, but with other things, there aren't really and so it really depends. But then the other inter, the other really important thing is that no matter what at the end, you need to test and generate based on your based on your data sets and on based on sample data to see if it's accurate or not, and then that's gonna guide everything. Ultimately, >>Sharon has got to go to you. You brought up something in the preliminary rounds and about open A I and kind of this. We can't have this black box where stuff goes into the algorithm. That stuff comes out and we're not sure what the result was. Sounds really important. Is that Is that even plausible? Is it feasible? This is crazy statistics, Crazy math. You talked about the business objective that someone's trying to achieve. I go to the data scientist. Here's my data. You're telling this is the output. How kind of where's the line between the Lehman and the business person and the hard core data science to bring together the knowledge of Here's what's making the algorithm say this. >>Yeah, there's a lot of names for this, whether it's explainable. Aye, aye. Or interpret a belay. I are opening the black box. Things like that. Um, the algorithms that you use determine whether or not they're inspect herbal. Um, and the deeper your neural network gets, the harder it is to inspect, actually. Right. So, to your point, every time you take an aye aye and you use it in a different scenario than what it was built for. For example, um, there is a police precinct in New York that had a facial recognition software, and, uh, victim said, Oh, it looked like this actor. This person looked like Bill Cosby or something like that, and you were never supposed to take an image of an actor and put it in there to find people that look like them. But that's how people were using it. So the Russians point yes, like it. You can transfer learning to other a eyes, but it's actually the humans that are using it in ways that are unintended that we have to be more careful about, right? Um, even if you're a, I is explainable, and somebody tries to use it in a way that it was never intended to be used. The risk is much higher >>now. I think maybe I had, You know, if you look at Marvis kind of what we're building for the networking community Ah, good examples. When Marvis tries to do estimate your throughput right, your Internet throughput. That's what we usually call decision tree algorithm. And that's a very interpretive algorithm. and we predict low throughput. We know how we got to that answer, right? We know what features God, is there? No. But when we're doing something like a NAMI detection, that's a neural network. That black box it tells us yes, there's a problem. There's some anomaly, but that doesn't know what caused the anomaly. But that's a case where we actually used neural networks, actually find the anomie, and then we're using something else to find the root cause, eh? So it really depends on the use case and where the night you're going to use an interpreter of model or a neural network which is more of a black box model. T tell her you've got a cat or you've got a problem >>somewhere. So, Bob, that's really interested. So can you not unpacking? Neural network is just the nature of the way that the communication and the data flows and the inferences are made that you can't go in and unpack it, that you have to have the >>separate kind of process too. Get to the root cause. >>Yeah, assigned is always hard to say. Never. But inherently s neural networks are very complicated. Saito set of weights, right? It's basically usually a supervised training model, and we're feeding a bunch of data and trying to train it to detect a certain features, sir, an output. But that is where they're powerful, right? And that's why they basically doing such good, Because they are mimicking the brain, right? That neural network is a very complex thing. Can't like your brain, right? We really don't understand how your brain works right now when you have a problem, it's really trialling there. We try to figure out >>right going right. So I want to stay with you, bought for a minute. So what about when you change what you're optimizing? Four? So you just said you're optimizing for throughput of the network. You're looking for problems. Now, let's just say it's, uh, into the end of the quarter. Some other reason we're not. You're changing your changing what you're optimizing for, Can you? You have to write separate algorithm. Can you have dynamic movement inside that algorithm? How do you approach a problem? Because you're not always optimizing for the same things, depending on the market conditions. >>Yeah, I mean, I think a good example, you know, again, with Marvis is really with what we call reinforcement. Learning right in reinforcement. Learning is a model we use for, like, radio resource management. And there were really trying to optimize for the user experience in trying to balance the reward, the models trying to reward whether or not we have a good balance between the network and the user. Right, that reward could be changed. So that algorithm is basically reinforcement. You can finally change hell that Algren works by changing the reward you give the algorithm >>great. Um, Rajan back to you. A couple of huge things that have come into into play in the marketplace and get your take one is open source, you know, kind of. What's the impact of open source generally on the availability, desire and more applications and then to cloud and soon to be edge? You know, the current next stop. How do you guys incorporate that opportunity? How does it change what you can do? How does it open up the lens of >>a I Yeah, I think open source is really important because I think one thing that's interesting about a I is that it's a very nascent field and the more that there's open source, the more that people could build on top of each other and be able to utilize what what others others have done. And it's similar to how we've seen open source impact operating systems, the Internet, things like things like that with Cloud. I think one of the big things with cloud is now you have the processing power and the ability to access lots of data to be able to t create these thes networks. And so the capacity for data and the capacity for compute is much higher. Edge is gonna be a very important thing, especially going into next few years. You're seeing Maur things incorporated on the edge and one exciting development is around Federated learning where you can train on the edge and then combine some of those aspects into a cloud side model. And so that I think will actually make EJ even more powerful. >>But it's got to be so dynamic, right? Because the fundamental problem used to always be the move, the computer, the data or the date of the computer. Well, now you've got on these edge devices. You've got Tanya data right sensor data all kinds of machining data. You've got potentially nasty hostile conditions. You're not in a nice, pristine data center where the environmental conditions are in the connective ity issues. So when you think about that problem yet, there's still great information. There you got latent issues. Some I might have to be processed close to home. How do you incorporate that age old thing of the speed of light to still break the break up? The problem to give you a step up? Well, we see a lot >>of customers do is they do a lot of training on the cloud, but then inference on the on the edge. And so that way they're able to create the model that they want. But then they get fast response time by moving the model to the edge. The other thing is that, like you said, lots of data is coming into the edge. So one way to do it is to efficiently move that to the cloud. But the other way to do is filter. And to try to figure out what data you want to send to the clouds that you can create the next days. >>Shawna, back to you let's shift gears into ethics. This pesky, pesky issue that's not not a technological issue at all, but right. We see it often, especially in tech. Just cause you should just cause you can doesn't mean that you should. Um so and this is not a stem issue, right? There's a lot of different things that happened. So how should people be thinking about ethics? How should they incorporate ethics? Um, how should they make sure that they've got kind of a, you know, a standard kind of overlooking kind of what they're doing? The decisions are being made. >>Yeah, One of the more approachable ways that I have found to explain this is with behavioral science methodologies. So ethics is a massive field of study, and not everyone shares the same ethics. However, if you try and bring it closer to behavior change because every product that we're building is seeking to change of behavior. We need to ask questions like, What is the gap between the person's intention and the goal we have for them? Would they choose that goal for themselves or not? If they wouldn't, then you have an ethical problem, right? And this this can be true of the intention, goal gap or the intention action up. We can see when we regulated for cigarettes. What? We can't just make it look cool without telling them what the cigarettes are doing to them, right so we can apply the same principles moving forward. And they're pretty accessible without having to know. Oh, this philosopher and that philosopher in this ethicist said these things, it can be pretty human. The challenge with this is that most people building these algorithms are not. They're not trained in this way of thinking, and especially when you're working at a start up right, you don't have access to massive teams of people to guide you down this journey, so you need to build it in from the beginning, and you need to be open and based upon principles. Um, and it's going to touch every component. It should touch your data, your algorithm, the people that you're using to build the product. If you only have white men building the product, you have a problem you need to pull in other people. Otherwise, there are just blind spots that you are not going to think of in order to still that product for a wider audience, but it seems like >>they were on such a razor sharp edge. Right with Coca Cola wants you to buy Coca Cola and they show ads for Coca Cola, and they appeal to your let's all sing together on the hillside and be one right. But it feels like with a I that that is now you can cheat. Right now you can use behavioral biases that are hardwired into my brain is a biological creature against me. And so where is where is the fine line between just trying to get you to buy Coke? Which somewhat argues Probably Justus Bad is Jule cause you get diabetes and all these other issues, but that's acceptable. But cigarettes are not. And now we're seeing this stuff on Facebook with, you know, they're coming out. So >>we know that this is that and Coke isn't just selling Coke anymore. They're also selling vitamin water so they're they're play isn't to have a single product that you can purchase, but it is to have a suite of products that if you weren't that coke, you can buy it. But if you want that vitamin water you can have that >>shouldn't get vitamin water and a smile that only comes with the coat. Five. You want to jump in? >>I think we're going to see ethics really break into two different discussions, right? I mean, ethics is already, like human behavior that you're already doing right, doing bad behavior, like discriminatory hiring, training, that behavior. And today I is gonna be wrong. It's wrong in the human world is gonna be wrong in the eye world. I think the other component to this ethics discussion is really round privacy and data. It's like that mirror example, right? No. Who gave that mirror the right to basically tell me I'm old and actually do something with that data right now. Is that my data? Or is that the mirrors data that basically recognized me and basically did something with it? Right. You know, that's the Facebook. For example. When I get the email, tell me, look at that picture and someone's take me in the pictures Like, where was that? Where did that come from? Right? >>What? I'm curious about to fall upon that as social norms change. We talked about it a little bit for we turn the cameras on, right? It used to be okay. Toe have no black people drinking out of a fountain or coming in the side door of a restaurant. Not that long ago, right in the 60. So if someone had built an algorithm, then that would have incorporated probably that social norm. But social norms change. So how should we, you know, kind of try to stay ahead of that or at least go back reflectively after the fact and say kind of back to the black box, That's no longer acceptable. We need to tweak this. I >>would have said in that example, that was wrong. 50 years ago. >>Okay, it was wrong. But if you ask somebody in Alabama, you know, at the University of Alabama, Matt Department who have been born Red born, bred in that culture as well, they probably would have not necessarily agreed. But so generally, though, again, assuming things change, how should we make sure to go back and make sure that we're not again carrying four things that are no longer the right thing to do? >>Well, I think I mean, as I said, I think you know what? What we know is wrong, you know is gonna be wrong in the eye world. I think the more subtle thing is when we start relying on these Aye. Aye. To make decisions like no shit in my car, hit the pedestrian or save my life. You know, those are tough decisions to let a machine take off or your balls decision. Right when we start letting the machines Or is it okay for Marvis to give this D I ps preference over other people, right? You know, those type of decisions are kind of the ethical decision, you know, whether right or wrong, the human world, I think the same thing will apply in the eye world. I do think it will start to see more regulation. Just like we see regulation happen in our hiring. No, that regulation is going to be applied into our A I >>right solutions. We're gonna come back to regulation a minute. But, Roger, I want to follow up with you in your earlier session. You you made an interesting comment. You said, you know, 10% is clearly, you know, good. 10% is clearly bad, but it's a soft, squishy middle at 80% that aren't necessarily super clear, good or bad. So how should people, you know, kind of make judgments in this this big gray area in the middle? >>Yeah, and I think that is the toughest part. And so the approach that we've taken is to set us set out a set of AI ai principles on DDE. What we did is actually wrote down seven things that we will that we think I should do and four things that we should not do that we will not do. And we now have to actually look at everything that we're doing against those Aye aye principles. And so part of that is coming up with that governance process because ultimately it boils down to doing this over and over, seeing lots of cases and figuring out what what you should do and so that governments process is something we're doing. But I think it's something that every company is going to need to do. >>Sharon, I want to come back to you, so we'll shift gears to talk a little bit about about law. We've all seen Zuckerberg, unfortunately for him has been, you know, stuck in these congressional hearings over and over and over again. A little bit of a deer in a headlight. You made an interesting comment on your prior show that he's almost like he's asking for regulation. You know, he stumbled into some really big Harry nasty areas that were never necessarily intended when they launched Facebook out of his dorm room many, many moons ago. So what is the role of the law? Because the other thing that we've seen, unfortunately, a lot of those hearings is a lot of our elected officials are way, way, way behind there, still printing their e mails, right? So what is the role of the law? How should we think about it? What shall we What should we invite from fromthe law to help sort some of this stuff out? >>I think as an individual, right, I would like for each company not to make up their own set of principles. I would like to have a shared set of principles that were following the challenge. Right, is that with between governments, that's impossible. China is never gonna come up with same regulations that we will. They have a different privacy standards than we D'oh. Um, but we are seeing locally like the state of Washington has created a future of work task force. And they're coming into the private sector and asking companies like text you and like Google and Microsoft to actually advise them on what should we be regulating? We don't know. We're not the technologists, but they know how to regulate. And they know how to move policies through the government. What will find us if we don't advise regulators on what we should be regulating? They're going to regulate it in some way, just like they regulated the tobacco industry. Just like they regulated. Sort of, um, monopolies that tech is big enough. Now there is enough money in it now that it will be regularly. So we need to start advising them on what we should regulate because just like Mark, he said. While everyone else was doing it, my competitors were doing it. So if you >>don't want me to do it, make us all stop. What >>can I do? A negative bell and that would not for you, but for Mark's responsibly. That's crazy. So So bob old man at the mall. It's actually a little bit more codified right, There's GDP are which came through May of last year and now the newness to California Extra Gatorade, California Consumer Protection Act, which goes into effect January 1. And you know it's interesting is that the hardest part of the implementation of that I think I haven't implemented it is the right to be for gotten because, as we all know, computers, air, really good recording information and cloud. It's recorded everywhere. There's no there there. So when these types of regulations, how does that impact? Aye, aye, because if I've got an algorithm built on a data set in in person, you know, item number 472 decides they want to be forgotten How that too I deal with that. >>Well, I mean, I think with Facebook, I can see that as I think. I suspect Mark knows what's right and wrong. He's just kicking ball down tires like >>I want you guys. >>It's your problem, you know. Please tell me what to do. I see a ice kind of like any other new technology, you know, it could be abused and used in the wrong waste. I think legally we have a constitution that protects our rights. And I think we're going to see the lawyers treat a I just like any other constitutional things and people who are building products using a I just like me build medical products or other products and actually harmful people. You're gonna have to make sure that you're a I product does not harm people. You're a product does not include no promote discriminatory results. So I >>think we're going >>to see our constitutional thing is going applied A I just like we've seen other technologies work. >>And it's gonna create jobs because of that, right? Because >>it will be a whole new set of lawyers >>the holdings of lawyers and testers, even because otherwise of an individual company is saying. But we tested. It >>works. Trust us. Like, how are you gonna get the independent third party verification of that? So we're gonna start to see a whole terrorist proliferation of that type of fields that never had to exist before. >>Yeah, one of my favorite doctor room. A child. Grief from a center. If you don't follow her on Twitter Follower. She's fantastic and a great lady. So I want to stick with you for a minute, Bob, because the next topic is autonomous. And Rahman up on the keynote this morning, talked about missed and and really, this kind of shifting workload of fixing things into an autonomous set up where the system now is, is finding problems, diagnosing problems, fixing problems up to, I think, he said, even generating return authorizations for broken gear, which is amazing. But autonomy opens up all kinds of crazy, scary things. Robert Gates, we interviewed said, You know, the only guns that are that are autonomous in the entire U. S. Military are the ones on the border of North Korea. Every single other one has to run through a person when you think about autonomy and when you can actually grant this this a I the autonomy of the agency toe act. What are some of the things to think about in the word of the things to keep from just doing something bad, really, really fast and efficiently? >>Yeah. I mean, I think that what we discussed, right? I mean, I think Pakal purposes we're far, you know, there is a tipping point. I think eventually we will get to the CP 30 Terminator day where we actually build something is on par with the human. But for the purposes right now, we're really looking at tools that we're going to help businesses, doctors, self driving cars and those tools are gonna be used by our customers to basically allow them to do more productive things with their time. You know, whether it's doctor that's using a tool to actually use a I to predict help bank better predictions. They're still gonna be a human involved, you know, And what Romney talked about this morning and networking is really allowing our I T customers focus more on their business problems where they don't have to spend their time finding bad hard were bad software and making better experiences for the people. They're actually trying to serve >>right, trying to get your take on on autonomy because because it's a different level of trust that we're giving to the machine when we actually let it do things based on its own. But >>there's there's a lot that goes into this decision of whether or not to allow autonomy. There's an example I read. There's a book that just came out. Oh, what's the title? You look like a thing. And I love you. It was a book named by an A I, um if you want to learn a lot about a I, um and you don't know much about it, Get it? It's really funny. Um, so in there there is in China. Ah, factory where the Aye Aye. Is optimizing um, output of cockroaches now they just They want more cockroaches now. Why do they want that? They want to grind them up and put them in a lotion. It's one of their secret ingredients now. It depends on what parameters you allow that I to change, right? If you decide Thio let the way I flood the container, and then the cockroaches get out through the vents and then they get to the kitchen to get food, and then they reproduce the parameters in which you let them be autonomous. Over is the challenge. So when we're working with very narrow Ai ai, when use hell the Aye. Aye. You can change these three things and you can't just change anything. Then it's a lot easier to make that autonomous decision. Um and then the last part of it is that you want to know what is the results of a negative outcome, right? There was the result of a positive outcome. And are those results something that we can take actually? >>Right, Right. Roger, don't give you the last word on the time. Because kind of the next order of step is where that machines actually write their own algorithms, right? They start to write their own code, so they kind of take this next order of thought and agency, if you will. How do you guys think about that? You guys are way out ahead in the space, you have huge data set. You got great technology. Got tensorflow. When will the machines start writing their own A their own out rhythms? Well, and actually >>it's already starting there that, you know, for example, we have we have a product called Google Cloud. Ottawa. Mel Village basically takes in a data set, and then we find the best model to be able to match that data set. And so things like that that that are there already, but it's still very nascent. There's a lot more than that that can happen. And I think ultimately with with how it's used I think part of it is you have to start. Always look at the downside of automation. And what is what is the downside of a bad decision, whether it's the wrong algorithm that you create or a bad decision in that model? And so if the downside is really big, that's where you need to start to apply Human in the loop. And so, for example, in medicine. Hey, I could do amazing things to detect diseases, but you would want a doctor in the loop to be able to actually diagnose. And so you need tohave have that place in many situations to make sure that it's being applied well. >>But is that just today? Or is that tomorrow? Because, you know, with with exponential growth and and as fast as these things are growing, will there be a day where you don't necessarily need maybe need the doctor to communicate the news? Maybe there's some second order impacts in terms of how you deal with the family and, you know, kind of pros and cons of treatment options that are more emotional than necessarily mechanical, because it seems like eventually that the doctor has a role. But it isn't necessarily in accurately diagnosing a problem. >>I think >>I think for some things, absolutely over time the algorithms will get better and better, and you can rely on them and trust them more and more. But again, I think you have to look at the downside consequence that if there's a bad decision, what happens and how is that compared to what happens today? And so that's really where, where that is. So, for example, self driving cars, we will get to the point where cars are driving by themselves. There will be accidents, but the accident rate is gonna be much lower than what's there with humans today, and so that will get there. But it will take time. >>And there was a day when will be illegal for you to drive. You have manslaughter, right? >>I I believe absolutely there will be in and and I don't think it's that far off. Actually, >>wait for the day when I have my car take me up to Northern California with me. Sleepy. I've only lived that long. >>That's right. And work while you're while you're sleeping, right? Well, I want to thank everybody Aton for being on this panel. This has been super fun and these air really big issues. So I want to give you the final word will just give everyone kind of a final say and I just want to throw out their Mars law. People talk about Moore's law all the time. But tomorrow's law, which Gardner stolen made into the hype cycle, you know, is that we tend to overestimate in the short term, which is why you get the hype cycle and we turn. Tend to underestimate, in the long term the impacts of technology. So I just want it is you look forward in the future won't put a year number on it, you know, kind of. How do you see this rolling out? What do you excited about? What are you scared about? What should we be thinking about? We'll start with you, Bob. >>Yeah, you know, for me and, you know, the day of the terminus Heathrow. I don't know if it's 100 years or 1000 years. That day is coming. We will eventually build something that's in part of the human. I think the mission about the book, you know, you look like a thing and I love >>you. >>Type of thing that was written by someone who tried to train a I to basically pick up lines. Right? Cheesy pickup lines. Yeah, I'm not for sure. I'm gonna trust a I to help me in my pickup lines yet. You know I love you. Look at your thing. I love you. I don't know if they work. >>Yeah, but who would? Who would have guessed online dating is is what it is if you had asked, you know, 15 years ago. But I >>think yes, I think overall, yes, we will see the Terminator Cp through It was probably not in our lifetime, but it is in the future somewhere. A. I is definitely gonna be on par with the Internet cell phone, radio. It's gonna be a technology that's gonna be accelerating if you look where technology's been over last. Is this amazing to watch how fast things have changed in our lifetime alone, right? Yeah, we're just on this curve of technology accelerations. This in the >>exponential curves China. >>Yeah, I think the thing I'm most excited about for a I right now is the addition of creativity to a lot of our jobs. So ah, lot of we build an augmented writing product. And what we do is we look at the words that have happened in the world and their outcomes. And we tell you what words have impacted people in the past. Now, with that information, when you augment humans in that way, they get to be more creative. They get to use language that have never been used before. To communicate an idea. You can do this with any field you can do with composition of music. You can if you can have access as an individual, thio the data of a bunch of cultures the way that we evolved can change. So I'm most excited about that. I think I'm most concerned currently about the products that we're building Thio Give a I to people that don't understand how to use it or how to make sure they're making an ethical decision. So it is extremely easy right now to go on the Internet to build a model on a data set. And I'm not a specialist in data, right? And so I have no idea if I'm adding bias in or not, um and so it's It's an interesting time because we're in that middle area. Um, and >>it's getting loud, all right, Roger will throw with you before we have to cut out, or we're not gonna be able to hear anything. So I actually start every presentation out with a picture of the Mosaic browser, because what's interesting is I think that's where >>a eyes today compared to kind of weather when the Internet was around 1994 >>were just starting to see how a I can actually impact the average person. As a result, there's a lot of hype, but what I'm actually finding is that 70% of the company's I talked to the first question is, Why should I be using this? And what benefit does it give me? Why 70% ask you why? Yeah, and and what's interesting with that is that I think people are still trying to figure out what is this stuff good for? But to your point about the long >>run, and we underestimate the longer I think that every company out there and every product will be fundamentally transformed by eye over the course of the next decade, and it's actually gonna have a bigger impact on the Internet itself. And so that's really what we have to look forward to. >>All right again. Thank you everybody for participating. There was a ton of fun. Hope you had fun. And I look at the score sheet here. We've got Bob coming in and the bronze at 15 points. Rajan, it's 17 in our gold medal winner for the silver Bell. Is Sharna at 20 points. Again. Thank you. Uh, thank you so much and look forward to our next conversation. Thank Jeffrey Ake signing out from Caesar's Juniper. Next word unpacking. I Thanks for watching.

>>Live from Orlando, Florida. It's the cube covering Microsoft ignite brought to you by Cohesity. >>Good afternoon everyone. You are watching the cubes live coverage of Microsoft ignite. I am your host, Rebecca Knight, along with my cohost Stu Miniman. We are joined by Sean Gifford. He is the senior infrastructure administrator, administrator and infrastructure team lead at Illinois mutual. Thank you so much for coming on the cube. Thanks for having me. This is really fun. Yeah. So tell us a little bit about Illinois mutual. >>Sure. So Alou Mutual's a a life insurance company. We sell life insurance Dai and several other insurance products. We've been around for a little over a hundred years now. So, uh, not myself, but uh, you know, the company. Um, and uh, we are based in Peoria, Illinois, uh, about 200 employees. And uh, we're uh, mostly uh, based on one headquarters there with a couple of their uh, uh, one of their, uh, co located dead center. >>And you are a senior infrastructure administrator. Tell us, tell our viewers a little about what you do. >>Sure. So basically a infrastructure admin means you do just about everything now. Just seems that way sometimes. Um, so, uh, my team, uh, handles everything from windows system, ministration, um, individual systems like a, your exchange, SharePoint, you know, things like that that we would use on prem. Um, too. Also outside of the on prem side, any of our cloud management, et cetera. All right, so, so Sean, you know, this shows decades old and started out at the windows administrator and you know, what's now office or O three 65, uh, at its core. Uh, so have you been to the show before or is this your first time? Uh, on one time, watch. Never on before. Okay. So, but you know, I, I'd love just your viewpoint on Microsoft before we get into some of the environments. Cause of that, you know, Microsoft, you know, started out as people knew kind of windows and some of their apps, but now, you know, the sprawling company with, you know, apps everywhere in the cloud, the edge and the data center, uh, you know, such a big footprint is what they do. >>How you personally in Illinois mutual look at Microsoft? Well, Microsoft is definitely a major partner for Illinois mutual. Right. I mean, we are a very big Microsoft shop. Does that mean that everyone, uh, you know, thinks that Microsoft is the best that every product? Of course not, but, uh, they do a lot of things and they do them really well. So I mean, we obviously rely on them not only for our on prem active directory, but then replicating that out to, to as your, um, you know, I mean our email much just people like might not like to admit it is still one of the most essential pieces of the infrastructure. Um, and that's around on exchange. So I mean, honestly, uh, as much as a, you know, people might want to say Cisco networking is like the backbone of the network. Uh, my Microsoft technologies really are kind of the backbone as far as I look at it. >>Okay. So you still have exchange, you know, in your own shop. You haven't made the move. DOE Microsoft pressure in there. >> Yeah, I know, right? Um, so, uh, no. Yeah, we're, we're still on prem. Um, we have our O three 65 account and we're, um, full disclosure. So, you know, I've been in it for 20 some years, but, uh, uh, been into Eleni mutual for about four. When I was in consulting before only mutual. I did a lot of, uh, in a cloud consulting and getting people on. So it felt really weird to me, but that's, uh, you know, coming into Eleanor mutual where, uh, at the time they came on, uh, it was, the cloud in general was like a bad word. Um, so, and getting past that culture-wise has been a little bit of a struggle. >> Oh yeah. I would, I'd love you to just step back for a second. >>You know, you work for a company that's over a hundred years old, uh, so, you know, exchange in cloud and everything like that is, you know, been around for a very short piece of the overall company. So tell us some of the, you know, what are some of the changes, the pressures going on? Oftentimes there's M and a involved in pulling all those things together. So, uh, you know, Illinois mutual as a company, what are the, what are the drivers and stressors on, you know, your, your, your, your organization? >> Yeah, well first and foremost, data security, right? Um, getting it, uh, any data so that it's fully encrypted at rest in transit and all that sort of thing so that, uh, you know, and, and you don't have to worry about it, uh, leaving anywhere once it's on someone else's prem. Right. Um, it has always been a big part of it. >>Um, trust I mean in is really what it just comes down to. Uh, when you, when you're selling life insurance policies that, you know, go for the life of a human being, you know, that's a pretty longterm relationship. And, uh, going with something, uh, especially a technology like that, that is considered as you say, you know, new to the game, uh, has, has been a struggle for sure. I mean, we're, uh, just to give you an idea, we're a still on mainframe and, uh, we have now to be, to be fair, we have a sizable, uh, uh, project for getting, uh, things moved off of the mainframe, but that, you know, is 40 plus years old. Getting, getting that moving, uh, to, you know, try and hop just into the end of the 20th century, let alone the 21st is always a little bit hard. >>So talk about some of the specific challenges of managing legacy infrastructure, managing tape and, and sort of what, what you do as more of a on the Vanguard of technology in terms of how you're leading your organization to make changes that are, that are much needed. >>Yeah. Uh, so yeah, when, when I came in on, in fact until just a few months ago, you bring up the example of tape. I mean, uh, we had been doing tape off to a, on off-prem, a site that, uh, had been just the way they did it, right. And, uh, um, as a joke, when some people an earlier, um, as the new crew came in, uh, one of the things that we instituted is a, uh, that's how we always done it. Jar. Um, and, uh, instead of people having a swear jar, right, they'd have to throw money in a anytime. They didn't say, I can't do it cause that's how we've always done it. And that's always been just that struggle, you know, with tape, you know, why is it that we're sending our tapes, why are we sending tapes at all? But why are we sending them to this place that's a, you know, three miles away from our place and calling that disaster recovery. >>Um, so I, I, that has been one of the major struggles for sure. Um, getting through that. But, uh, I've been really impressed, uh, culture-wise with the fact that, uh, people are really starting to, to get in line with it. You know, they're seeing the, the advantages that we're bringing. Um, w when you have a cloud strategy that's well thought out and, uh, isn't, uh, at least inherently a, you know, tied to a given vendor as your AWS or whoever it might be. Um, and, and you're not making decisions for cloud just for the sake of calling it cloud. It makes a big difference. I think. So, uh, as you, as you started to embrace cloud, uh, how did things like data protection and security, you know, what stayed the same? You know, what, what things did you need to rethink as you roll those out? >>Data protection changes completely, right? Um, first of all, uh, you know, everyone had that, uh, idea that if it's in cloud, of course it's completely protected, right? It's not right. And so getting people to understand that, uh, as they say, Oh yeah, we're going to, you know, do this new sass offering. It's totally, you know, they take care of everything, the applications on them. You don't have to touch it. Right? Well, no, that's not really the case. You know, that they can lose a data just like anybody else. So getting through pieces like that on the, on the cloud side is, has been a struggle. But, uh, getting into just even normal or excuse me, newer, um, on-prem technologies has, has meant changing completely the way we're doing a lot of things. Um, the, uh, it was becoming harder and harder, especially as we moved data sets off of the, uh, uh, mainframe side to keep up with a lot of those replication timeframes and things like that because, uh, it, as you push more data through what is still a small pipe and it's never big enough, um, it, uh, it became everyday nightmares. >>So it's been a struggle. >>So when you are, when you, when you come to the conclusion that you need to make a change and you need to look for other kinds of solutions, how do you go about finding the right vendor for the problem that you're trying to solve? How do you find the best in class? Right. And that's, >>that's been an interesting piece with w with alimony mutual and, and, uh, having spent time at VARs for the first part of my career, I was used to, you know, answering things like RFPs and whatnot. Right. Um, and we don't necessarily do it within an RFP process, but, uh, honestly conventions like this one and stuff is how I like to do it. Um, you know, we get really stuck in the day to day doldrums and stuff like that too, right? As much as you're trying. And your goal might always be to, you know, get things to at least the cutting edge if not the bleeding edge. Uh, you really need to, you know, be at a places where you can learn about new new technologies now. So when it comes to us, we end up finding a lot of our vendors like that. And, uh, you know, cause we don't really want her to necessarily rely on, you know, the sales people or, or even really our, our, you know, sales people from a VAR or anything like that. >>It's about trying to find, uh, that, that third party knowledge to, to really understand what's the best thing for the needs and the, uh, pain points that you're having. And that's Sean, can you bring us in through, can you tell us, you know, which solutions you were, uh, you were deciding between and how you ultimately came to your final decision? Yeah. So, uh, so we looked at, uh, several different vendors. Um, when it came to our, uh, data protection, uh, analysis, we had looked at a beam for awhile. We had looked at rubric. Um, we had, we had looked at, uh, uh, of course, uh, you know, trying to continue things along with our current vendor at the time we should have been con ball. Um, and we did, uh, we did an M U a you right. a utility attribute analysis. Yeah. Uh, and we, uh, set that up and, uh, just tried to really compare and, uh, uh, you know, what are the actual things we really wanted, what were the selection criteria we have and grading each vendor on those things. >>Um, and ultimately that's what it took to be able to get it through to, you know, to our executives and, and whatnot, uh, building an algorithm that, uh, that, that looked at all those pieces and then, you know, as really address the pain points we were having, you know, uh, not just as a Jeep cause yes, as always a big thing. Right. But is it gonna replicate in time? Is it, is it going to, uh, reduce our overhead, uh, that we're in, that we're experiencing right now? Am I going to have to keep on a full time contractor just to, you know, do my data protection. So, all right, so you ended up choosing Cohesity. So what was it about Cohesity that separated it from, uh, from, from all the others? Yeah, so Cohesity, um, I had pretty given up, uh, when I did the analysis I was talking to you about a couple of years ago. >>Um, I looked around and nobody could quite fit the square peg into the round hole that I was trying to make it work. Right? I wanted a lot of things and nobody had exactly what I was looking for. Can we sit? He was the first one that could really do most of what I wanted to do. Uh, as an example. Um, being able to replicate your data, but while keeping it encrypted on both ends and but still having dedupe and compression and all those things built in, into the platform and, and weight, it's actually searchable wallets in those States, right? I can do like a Google type search and be able to find exactly what I'm looking for. Made a huge difference and it cut it down. Uh, you know, time wise, not only on the administrative effort but also when I had to do a restore and we had a major project just a, a month or so ago where, uh, I had my DBA doing a backup, uh, during a rollout. He accidentally set at the backup to go with the wrong side at the wrong data center. Everyone was kind of freaking out, right? What are we gonna do? We restored it across data centers, across the handling, kept within our timeframes. I was, that's the type of thing, type of thing that really makes it different stuff. So, >>so, so talk about some of the results that you've seen since implementing this. >>Yeah, so replication, um, that I brought up a couple of times, but, uh, it was a really big problem that we would take. For instance, um, I'll take SQL as an example, right? Our SQL data, we would do a data mirroring, right? So it replicated across our wind line for that. We would, uh, we would do a, uh, primary storage replication. So in this case, a nimble Sans that would replicate across with snapshots and then our actual data protection. Uh, so the same exact data would have to replicate across one tiny land line three times for every a replication. Um, since putting in Cohesity, we have experienced an actual, I was blown away when we actually calculated the results, but it was actually a four times increase in replication efficiency. Uh, it just allowed us to do a whole lot more without buying more land bandwidth. So this is a big deal for us. >>So, in terms of this show, as you said this, this is really helpful for you to go and meet different kinds of companies that you might not even know exists. There are new entrance all the time. So what are you going to bring back with you when you go back to Illinois mutual next week? What are some of the things that have stuck out to you, resonated most with you? >>Yeah, so I'm, I'm really encouraged and even with just Cohesity, for instance, I've talked to a, I'm actually met up with a couple of the engineers that I've talked with them, um, who had one of them and even put out a, uh, a new, uh, feature request for us. And he was telling me before lunchtime about some new features available that I can start to change up some of my jobs. I've, I'm really excited. I was texting my, my, uh, data protection, uh, you know, secondary admin, uh, uh, you know, texting furiously to them, we can do this. And, you know, I'm really excited about that. But, uh, honestly on the other side, is these your side? I'm, uh, really, uh, excited to learn about some of the things that we can actually implement, uh, even with older infrastructure, uh, in trying to pull some of those things, uh, into a cloud platform in ways that actually make sense and aren't gonna lose us money in the longterm. So I'm happy with that. Thank you so much for coming on the cube. Thank you very much. It's been fun. I'm Rebecca aid for Stu Miniman. Stay tuned for more of the cube.

(techno music) >> Live, from Washington DC, it's theCUBE. Covering AWS Public Sector Summit, 2018. Brought to you by Amazon Web Services and its ecosystem partners. >> Okay, welcome back, everyone, this is the live CUBE coverage here in Washington DC for AWS Public Sector Summit 2018. This is the, kind of like the reinvent for Public Sector. I'm John Furrier, f my co-host Stu Miniman, our next guest is Hardik Bhatt, Smart Cities Vertical Lead for Amazon Web Services, been a former CIO, knows the state and local governments cold. This is a very key area around Internet of Things and technology with cloud, because smart cities have to do not only technology roll outs for some of the new capabilities, but all manage some of the societal changes, like self-driving cars and a variety of other things, from instrumenting sensors and traffic lights and video cam ... I mean, this is a little, just a little ... Welcome to theCUBE. >> Thank you very much, John. Good to see you, Stu, good morning. Looking forward to having a great conversation. >> So, smart cities obviously is really hot, but we love it, because it brings life, and work, life, and play together, because we all live in towns, and we live in cities, and the cities provide services to the residents, transportation, sidewalks, and things that we take for granted in the analog world. Now there's a whole digital set of services coming big time. So, are they prepared? (laughs) It used to be buy a mainframe, then move it to a minicomputer, get a Local Area Network, buy some PCs, buy some network tablets, now the cloud's here. What's your assessment of the smart cities landscape for state and local governments? Because it really is something that's on the front burner, in terms of figuring it out. What's the architecture? Lot of questions. What's your, what's the state of the union, if you will, for-- >> You know it has been, like, how the governments have been for many years, right? Governments exist so that they can provide better services, they can provide better quality of life, they can create an environment where businesses thrive, jobs can be created, education can be given, and you can build a workforce and talent, et cetera. And smart cities is just, I'd say, a trend where, you know, you're using multitudes of technology to kind of help the government get its mission accomplished in a smoother, faster, better, cheaper manner. And a lot of times, I've seen, because how smart cities movement started a decade ago, we kind of compare smart cities with the Internet of Things or the sensors, but smart cities is much more than just the IoT, or the Internet of Things, I mean if you're talking about creating a new stream of data that is real-time, whether coming in from sensors, coming from video, you already as a government, I used to be a CIO for the City of Chicago, we used petabytes of data that was already sitting in my data center, and then there's also this whole third-party data. So smart cities is a lot about how do you as a city are aggregating this different sources of data and then making some action from it, so that ultimately, going back to the city's priorities, you are giving better public safety, or you're providing better public health, or you're providing better education or you're providing, better providing government services. So that's what we are seeing. Our customers are, when we say smart cities, they jump right into, "What problems are you solving?" And that, to me, is the core for Amazon, core for Amazon Web Services. We want to know our customers' problems and then work backwards to solve them. >> What are some of the problems right now that are low-hanging fruit? Because obviously it's an evolution. You set the architecture up, but ultimately governments would love to have some revenue coming in from businesses. You mention that. Education is certainly there. What are some of the challenges there? Is it pre-existing stuff, or is it new opportunities? What are some of the trends you're seeing for use cases? It is actually both pre-existing stuff that they are trying to solve, as well the new stuff, the new opportunities that are getting created, because the technology is much different than what it used to be 10 years ago. The cloud, especially, is creating a lot more new opportunities, because of the nimbleness it brings, the agility it brings. So, in transportation side, we are seeing on one hand, multiple departments, multi-jurisdictional, so state transportation department, as well as a local transportation department, working together to create kind of a virtual information sharing environment or a virtual command center, so that they can detect an accident, a traffic incident, much quicker and respond to that, because now they can aggregate this data. And they're also now adding to that some public safety information. So whether it is a police department, fire department, EMS, so that they can address that incident quickly and then not only clear the traffic and clear the congestion, or reduce the congestion time, but they can also address the, any public safety issue that may have arisen out of that incident that has happened. So, the Department of Transportation, the USDOT, through the Federal Highway Administration, has been giving out $60 million worth of grants to six to ten recipients. The grant, this year's grant period, just closed on Monday, and we worked with multiple customers who are looking to kind of respond to that. So on one hand, it is that. So this is an age-old problem, but new technology can help you solve that. On the other hand, another customer that we worked with is looking for on-demand micro-transit solutions. As you can see, all the ride-sharing applications are making easier to jump in a car and move to one place to the other. It is causing a dip in transit ridership. So the public transit agents, they are looking for solutions to that. So they are looking at, "Can we build an on-demand microtransit "so you can pool your friends and jump into a transit van, as opposed to a private car?" And then you can go from point A to point B in a much more affordable manner. So they are looking at that. On the public health side, you know, we have the DC Benefits Exchange, Health Benefits Exchange, is on AWS, and they have seen significant savings. They have seen $1.8 million of annual savings because they are using cloud and cloud services. On the other hand, you have State of Georgia, which is using Alexa. So they have built Alexa Skills where you can ask, as a resident of State of Georgia getting SNAP benefit, the Supplemental Nutritional Assistance, the food-stamp program, you can say, "Alexa, what's my SNAP balance?" So based on the answer then, based on the balance you know, you can plan your, you know, where you're going to use that money. So we are seeing large volume of data now coming on the cloud where the governments are looking to move kind of the needle. We are also seeing this nimble, quick solutions that can start going out. And we are seeing a lot of driver behind the innovation is our City on a Cloud challenge. So we have seen the City on a Cloud winners, since last so many years, are kind of the ones who are driving innovation and they're also driving a lot of collaboration. So I can, there are three trends that I can jump into as we kind of talk more. >> Yeah, it's interesting. I think back a decade ago, when you talk smarter cities, you'd see this video, and it would look like something out of a science fiction. It's like, you know, "Oh, the flying taxi'll come, "and it will get you and everything." But what I, the stories I have when I talk to CIOs in cities and the like, it's usually more about, it's about data. It's about the underlying data, and maybe it's a mobile app, maybe it's a thing like Alexa Skills. So help us understand a little bit, what does the average citizen, what do they see? How does their, you know, greater transparency and sharing of information and collaboration between what the agencies are doing and, you know, the citizenship. >> I think that's a great question. I mean that is what, as a former CIO, I always had to balance between, what I do creates internal government efficiency, but the citizens don't feel it, don't see it, they don't, it doesn't get in the news media. And on the other hand, I also have to, to my governor, to my mayor, to the agency directors, have to give them visible wins. So, I'll give you an example, so City of Chicago, back in the day, in 2010 when I was the CIO. We did a contract with our AWS, currently AWS Partner Socrata, to open up the data. So that was kind of the beginning of the Open Data Movement, and eventually, I left the city, I went work for Cisco, and the city government continued to kind of build on top of Socrata. And they build what they called the Windy Grid, which is basically bringing all of their various sets of data, so 311, code violations, inspections, crime, traffic, and they built an internal data analytics engine. So now, agencies can use that data. And now, what they did, two years ago, they were one of the City on a Cloud Challenge winners, and they, Uturn Data Solutions is our partner that was the winner of that, and they built Chicago Open Grid. So they basically opened that up on a map-based platform. So now as a citizen of Chicago, I can go on Chicago Open Grid, and I can see which restaurants in, surrounding my area, have failed inspections. Have they failed inspection because of a mice infestation, or was it something very minor, so I can decide whether I want to go to that restaurant or not. I can also look at the crime patterns in my area, I can look at the property values, I can look at the education kind of quality in the schools in my neighborhood. So, we have seen kind of now, and it's all on AWS cloud. >> This open data is interesting to me. Let's take that to another level. That's just the user side of it, there's also a delivery value. I saw use cases in Chicago around Health and Human Services, around being more efficient with either vaccines, or delivery of services based on demographics and other profile, all because of open data. So this brings up a question that comes up a lot, and we're seeing here is a trend, is Amazon Web Services public sector has been really good. Teresa Carlson has done an amazing job leaning on partners to be successful. Meaning it's a collaboration. What's that like in the state and local government? What's the partner landscape look like? What are the benefits for partners to work with AWS? Because it seems obvious to me, it might not be obvious to them. But if they have an innovative idea, whether it's to innovate something on the edge of the network in their business, they can do it, and they can scale with Amazon. What is the real benefits of partnering with AWS? >> You hit a key point on there. Teresa has done a fantastic job in customer management as well as building our partners. Similarly, we have a great leader within the state and local government, Kim Majerus. She leads all of our state and local government business. And her focus is exactly like Teresa: How can we help the customers, and also how can we enable partners to help customers? So I'll give you and example. The City of Louisville in Kentucky. They were a City on a Cloud winner, and they, basically what they're building with a partner of ours, Slingshot, they (laughs) get, I was, I used to be in Traffic Management Authority, back in my days, and we used to do traffic studies. So, basically, they send an intern out with clicker or have those black strips to count the number of cars, and based on that, we can plan whether we want to increase the signal timing on this approach, or we can plan the detours if we close the street, what's the, and it's all manual. It used to take, cost us anywhere from 10 to 50 thousand dollars, every traffic study. So what Louisville did with Slingshot is they got the free Waze data that they get gives all of the raw traffic information. Slingshot brought that on to a AWS platform, and now they are building a traffic analysis tool, which now you can do like a snap of a finger, get the analysis and you can manage the signal-approach timing. The cool thing about this is, they're building it in open source code. And the code's available on GitHub, and I was talking to the Chief Data Officer of Louisville, who's actually going to be speaking at this event later today. 12 other cities have already looked into this. They've started to download the code, and they are starting to use it. So, collaboration through partners also enables collaboration amongst all of our customers. >> And also, I'd just point out, that's a great example, love that, and that's new for me to hear that. But also, to me the observation is, it's new data. So being able to be responsive, to look at that opportunity. Now, it used to be in the old world, and I'm sure you can attest to this, being a CIO back in the day, is okay, just say there's new data available, you have to provision IT. >> Oh my God, yeah. >> I mean, what, old way, new way. I mean, compare and contrast the time it would take to do that with what you can do today. >> It's a big, huge difference. I'll tell you as the CIO for the State of Illinois, when I started in early 2015, in my first performance management session, I asked my Infrastructure Management Team to give me the average days it takes to build a server, 49 days. I mean, you're talking seven weeks or maybe, if you talk, 10 business weeks. It's not acceptable. I mean the way the pace of innovation is going, with AWS on cloud, you are talking about minutes you can spin up that server. And that's what we are seeing, a significant change, and that's why Louisville-- >> And I think you got to think it's even worse when you think about integration, personnel requirements, the meetings that have to get involved. It's a nightmare. Okay, so obviously cloud, we know cloud, we love cloud, we use cloud ourselves. So I got to ask you this could, City in a Cloud program, which we've covered in the past, so last year had some really powerful winners. This has been a very successful program. You're involved in it, you have unique insights, you've been on both sides of the table. How is that going? How is it inspiring other cities? What's the camaraderie like? What's the peer review? Is there a peer, is there a network building? How is that spreading? >> That is actually enabling collaboration in a significant manner. Because, you know, you are openly telling what you want to do, and then you are doing that. Everybody is watching you. Like Louisville is a perfect example where they built this, they're building this, and they're going to share it through open source code to all the cities. 12 is just the beginning. I'd not be surprised if there are 120 cities that are going to do this. Because who doesn't want to save two hundred, three hundred thousand dollars a year? And also lots of time to do the traffic studies. Same thing we have seen with, as Virginia Beach is building their Early Flood Warning System. There are other cities who are looking into, like how do we, New Orleans? And others are looking at, "How do we take what Virginia Beach has built? "And how can we use it for us?" And yesterday, they announced this year of the winners that includes Las Vegas, that includes LA Information Technology Department, that includes the City of Philadelphia, and I've been in conversations with all of the CIOs, CDOs, and the leaders of these agencies. The other thing, John, I have seen is, there's a phenomenal leadership that's out there right now in the cities and states that they want to innovate, they want to collaborate, and they want to kind of make a big difference. >> Hold on, hold on, so one more question, this is a really good question, want to get, follow-up on that. But this, what you're talking about to me signifies really the big trend going on right now in this modern era. You've got large cloud scale. You have open source, open sharing, and collaboration happening. This is the new network effect. This is the flywheel. This is uniquely different. This kind of categorizes cloud. And this wasn't available when IT systems and processes were built, 20, 30 years ago. I mean, this is the big shift, you, I mean do you agree? >> Absolutely, this is the big shift, the availability of the cloud, the ubiquitous nature of mobile platform that people have. The newer way of, like, the natural language processing, use of Alexa is becoming so prevalent in government. I mean, in City of Chicago, 50% of the 311 calls that we used to get in 2010, 3 1/2 million of those were informational in nature. If I could offload that on to my Alexa Skills, I can free up my workforce, the 311 call-takers, to do much better, higher-level, you know, call-taking, as opposed to this. So you're absolutely right. I've seen the trends we are seeing is, there is lots of collaboration going on between the governments and partners. I'm also seeing the governments are going at modernization from different points based on their pain points. And I'm also seeing a definite acceleration in modernization. Government, because the technology, AWS, the cloud, our services that we are seeing. And the pace of innovation that AWS brings is also enabling the acceleration in governments. >> Yeah, to help put a point on the, on the conversation here, there's been for years discussion about, "Well, what is the changing role of the CIO?" You've sat on that side of the table, you know, worked with lots of COs, what do you see is the role of the future for the CIO when, specifically when you talk state and local governments? >> I would say CIO is the kind of has to be an enabler of government services. Because if I go back to my city days and working with a mayor, or my state days, working with a governor, at the end of the day, the governor or the mayor is looking at creating better quality of life, providing better health, better education, better safety, et cetera. And CIO is kind of the key partner in that metrics to enable what the governor, what the mayor, the agency directors want to do. And because now data enables the CIO to kind of quickly give solutions, or AI services, Alexa and Polly and Rekog ... All of these things give you, give me as a CIO, ability to provide quick wins to the mayor, to the governor, and also very visible wins. We are seeing that, you know, CIO is becoming a uniquely positioned individual and leader to kind of enable the government. >> All right, thanks so much for comin' on theCUBE. Love the insight, love to follow up. You bring a great perspective and great insight and Amazon's lucky to have you on the team. Lot of great stuff goin' on in the cities and local governments. It's a good opportunity for you guys. Thanks for coming on, appreciate it. >> Thank you very much. >> It's theCUBE live here in Washington DC for AWS, Amazon Web Services Public Sector Summit, I'm John Furrier, Stu Miniman, again second year of live coverage. It's a packed house, a lot of great cloud action. Again, the game has changed. It's a whole new world, cloud scale, open source, collaboration, mobile, all this new data's here. This is the opportunity, this is what theCUBE's doing. We're doin' our part, sharing the data with you. Stay with us, more coverage from day two, here in Washington, after this short break. (techno music)

>> Live, from Washington, D.C. It's theCUBE, covering the AWS Public Sector Summit 2018. Brought to you by Amazon Web Services, and its ecosystem partners. (futuristic music) >> Hey, welcome back everyone. We're live in Washington, D.C. for Amazon Web Services Public Sector Summit. This is their big show for the public sector. It's like a mini reinvent for specifically the public sector. I'm John Furrier, your host, with Stu Miniman, my co-host this segment, and Stewart Mclaurin, president of the White House Historic Association, is our guest. I heard him speak last night at a private dinner with Teresa Carlson and their top customers. Great story here, Amazon success story, but I think something more we can all relate to. Stewart, thank you for joining us and taking the time, appreciate it. >> Thanks John, it's just great to be with you. >> Okay, so let's jump into it; what's your story? You work for the White House Historical Association, which means you preserve stuff? Or, you provide access? Tell the story. >> Well, we have a great and largely untold story, and a part of our partnership with Amazon Web Services is to blow that open so more people know who we are and what we do, and have access to the White House, because it's the people's house. It doesn't belong to any one particular president; it's your house. We were founded in 1961 by First Lady Jacqueline Kennedy, who realized that the White House needed a nonprofit, nonpartisan partner. We have no government funding whatsoever, completely private. So we fund the acquisition of art, furnishings, decorative arts for the White House, if a new rug is needed, or new draperies are needed on the State Floor, or a frame needs to be regilded. We also acquire the china, the presidential and first lady portraits that are done; we fund those. But more importantly, in my view, is our education mission that Mrs. Kennedy also started, to teach and tell the stories of White House history going back to 1792, when George Washington selected that plot of land and the architect to build that house that we know today. So we unpack those stories through publications, programs, lectures, symposia, and now this new multifaceted partnership with AWS. >> Let's talk about, first of all, a great mission. This is the people's house; I love that. But it's always the secret cloak and dagger, kind of what's going on in there? The tours are not always, they're probably packed when people go through there, but the average person on the street doesn't have access. >> Sure, well, your cable news channels handle the politics and the policy of the place. We handle the building and the history, and all that's taken place there, including innovation and technology. If you think of Thomas Edison and Alexander Graham Bell, and others that evolved their early technologies through the White House, about 500,000 people get a chance to go through the White House every year. And when you think about in that small space, the president and his family lives, the president and his staff work, it's the ceremonial stage upon which our most important visitors are received, and then about 500,000 people schlep through, so you imagine 500,000 people that are going through your house, and all of that takes place. But it's very important to us for people to be able to see up close and personal, and walk through these spaces where Lincoln walked, and Roosevelt worked. >> Is that what the book you have, and share the book 'cause it's really historic, and the app that you have with Amazon, I think this is a great-- >> Sure, this is a real prize from our office. Mrs. Kennedy wanted us to teach and tell the stories of White House history, and so the first thing she wanted was a guide book, because the White House never had one. So in 1962, she published this guide book with us, and this is her actual copy. Her hands held this book. This was her copy of the book. Now, we continue to update this. It's now in its 24th edition, and each new edition has the latest renovations and updates that the latest president has added. But it's now 2018. So books are great, but we want to be able to impart this information and experience to people not only around Washington, who are going through the White House, but across the country and around the world. So this app that we've developed, you get through WHExperience at the App Store, you have three different tours. If you're walking through the White House, tours are self-guided, so unless you know what you're looking at, you don't know what you're looking at. So you can hold up an image, you can see, it brings to life for you everything that you're looking at in every room. Two other types of tours; if you're outside the White House in President's Park, it will unpack and open the doors of these rooms for you virtually, so you can see the Oval Office, and the Cabinet Room, and the Blue Room, and the Green Room. If you're around the world, there's a third tour experience, but the best part of it is, empowered by Amazon recognition technology, and it allows people to take a selfie, and it analyzes that selfie against all presidential portraits and first lady portraits, and the spatial features of your face, and it will tell you you're 47% Ronald Reagan, or 27% Jackie Kennedy, and people have a lot of fun with that part of the app. >> (laughs) That's awesome. >> Stewart, fascinating stuff. You know, when I go to a museum a lot of times, it's like, oh, the book was something you get on the way home, because maybe you couldn't take photos, or the book has beautiful photos. Can you speak a little bit about how the technology's making the tours a little bit more interactive? >> Sure, well we love books, and we'll publish six hardbound books this year on the history of the White House, and those are all available at our website, whitehousehistory.org. But the three facets of technology that we're adapting with Amazon, it's the app that I've spoken about, and that has the fun gamification element of portrait analysis, but it also takes you in a deeper depth in each room, even more so than the book does. And we can update it for seasons, like we'll update it for the Fall Garden Tour, we'll update it for the Christmas decorations, we'll update it for the Easter Egg Roll. But another part of the partnership is our digital library. We have tens of thousands of images of the White House that have literally been in a domestic freezer, frozen for decades, and with AWS, we're unpacking those and digitizing them, and it's like bringing history to life for the first time. We're seeing photographs of Kennedy, Johnson, other presidents, that haven't been seen by anybody in decades, and those are becoming available through our digital library. And then third, we're launching here a chatbot, so that through a Lex and Polly technology, AWS technology, you'll be able to go to Alexa and ask questions about White House history and the spaces in the White House, or keyboard to our website and ask those questions as well. >> It's going to open up a lot of windows to the young folks in education too. >> It is. >> It's like you're one command away; Hey, Alexa! >> It takes a one-dimensional picture off of a page, or off of a website, and it gives the user an experience of touring the White House. >> Talk about your vision around modernization. We just had a conversation with the CEO of Tellus, when we're talking about government has a modernization approach, and I think Obama really put the stake in the ground on that; former President Obama. And that means something to a lot of people, for you guys it's extending it forward. But your digital strategy is about bringing the experience digitally online from historical documents, and then going forward. So is there plans in the future, for virtual reality and augmented reality, where I can pop in and-- >> That's right. We're looking to evolve the app, and to do other things that are AR and VR focused, and keep it cool and fun, but we're here in a space that's all about the future. I was talking at this wonderful talk last night, about hundreds of thousands of people living and working on Mars, and that's really great. But we all need to remember our history and our roots. History applies to no matter what field you're in, medicine, law, technology; knowing your history, knowing the history of this house, and what it means to our country. There are billions of people around the world that know what this symbol means, this White House. And those are billions of people who will never come to our country, and certainly never visit the White House. Most of them won't even meet an American, but through this app, they'll be able to go into the doors of the White House and understand it more fully. >> Build a community around it too; is there any online social component? You guys looking around that at all? >> All of this is just launched, and so we do want to build some interactive, because it's important for us to know who these people are. One simple thing we're doing with that now, is we're asking people to socially post and tag us on these comparative pictures they take with presidents and first ladies. So there's been some fun from that. >> So Stewart, one of the things I've found interesting is your association, about 50 people, and what you were telling me off-camera, there's not a single really IT person inside there, so walk us through a little bit about how this partnership began, who helps you through all of these technical decisions, and how you do some pretty fun tech on your space. >> Unfortunately, a lot of historical organizations are a little dusty, or at least perceived to be that way. And so we want to be a first mover in this space, and an influencer of our peer institutions. Later this summer, we're convening 200 presidential sites from around the country, libraries, birthplaces, childhood homes, and we're going to share with them the experience that we've had with AWS. We'll partner or collaborate with them like we're already doing with some, like the Lincoln Library in Illinois, where we have a digitization partnership with them. So with us, it's about collaboration and partnership. We are content rich, but we are reach-challenged, and a way to extend our reach and influence is through wonderful partnerships like AWS, and so that's what we're doing. Now another thing we get with AWS is we're not just hiring an IT vendor of some type. They know our mission, they appreciate our mission, and they support our mission. Teresa Carlson was at the White House with us last Friday, and she had the app, and she was going through and looking at things, and it came to life for her in a new real and fresh way, and she'd been to the White House many times on business. >> That's great; great story. And the thing is, it's very inspirational on getting these other historic sites online. It's interesting. It's a digital library, it's a digital version. So, super good. Content rich, reach-challenged; I love that line. What else is going on? Who funds you guys? How do you make it all work? Who pays the bills? Do you guys do donations, is it philanthropy, is it-- >> We do traditional philanthropy, and we'd love for anybody to engage us in that. During the Reagan Administration in 1981, someone had the brilliant idea, now if I'd been in the room when this happened, I probably would have said, "Okay, fine, do that." But thank goodness we did, because it has funded our organization all these years. And that's the creation of the annual, official White House Christmas ornament, and we feature a different president each year sequentially so we don't have to make a political decision. This year, it's Harry Truman, and that ornament comes with a booklet, and it has elements of that ornament that talk about those years in the White House. So with Truman, it depicts the south balcony, the Truman Balcony on the south portico. The Truman seal that eventually evolved into being the Presidential Seal. On the reverse is the Truman Blue Room of the White House. So these are teaching tools, and we sell a lot of those ornaments. People collect them; once you start, you can't stop. A very traditional thing, but it's an important thing, and that's been a lifeblood. Actually, Teresa Carlson chairs our National Council on White House History. John Wood, that you just had on before me, is on our National Council on White House History. These are some of our strong financial supporters who believe in our mission, and who are collaborating it with us on innovative ways, and it's great to have them involved with us because it brings life in new ways, rather than just paper books. >> Stewart, I had a non-technical question for you. According to your mission, you also obtained pieces. I'm curious; what's the mission these days? What sort of things are you pulling in? >> Well, there's a curator in the White House. It's a government employee that actually manages the White House collection. Before President and Mrs. Kennedy came into the White House, a new president could come in and get rid of anything they wanted to, and they did. That's how they funded the new, by selling the old. That's not the case anymore. With the Kennedys, there's a White House collection, like a museum, and so we'll work with the White House and take their requests. For example, a recent acquisition was an Alma Thomas painting. Alma Thomas is the first African American female artist to have a work in the White House collection; a very important addition. And to have a work in the White House collection, the artist should be deceased and the work over 25 years old, so we're getting more of the 21st century. The great artists of the American 20th century are becoming eligible to have their works in the collection. >> Stewart, thanks so much for coming on theCUBE and sharing your story. It's good to see you speak, and thanks for the ornament we got last night. >> Sure. Well, you've teased this ornament. Everybody's going to want and need one now, so go to whitehousehistory.org. >> John, come on, you have to tell the audience who you got face matched recognition with on the app. >> So who did you get face matched with? >> I think I'm 20% James Buchanan, but you got the Gipper. >> I'm Ronald Reagan. Supply-side economics, trickle-down, what do they call it? Voodoo economics, was his famous thing? >> That's right. >> He had good hair, John. >> Well, you know, our job is to be story tellers, and thank you for letting us share a little bit of our story here today. We love to make good friends through our social channels, and I hope everyone will download this app and enjoy visiting the White House. >> We will help with the reach side and promote your mission. Love the mission, love history, love the digital convergence while preserving and maintaining the great history of the United States. And a great, good tool. It's going to open up-- >> Amazon gave us these stickers for everybody who had downloaded the app, so I'm officially giving you your downloaded app sticker to wear. Stu, this is yours. >> Thank you so much. >> Thanks guys, really appreciate it. >> Thank so much, great mission. Check out the White House-- >> Historical Association. >> Historicalassociation.org, and get the White House app, which is WHExperience on the App Store. >> That's right. >> Okay, thanks so much. Be back with more, stay with us. Live coverage here at AWS, Amazon Web Services Public Sector Summit. We'll be right back. (futuristic music)

(uptempo techno music) >> Announcer: Live from Chicago, Illinois. It's theCube, covering VeeamOn 2018. Brought to you by Veeam. >> Welcome back, here in the windy city. This is theCube's coverage of VeeamOn 2018. I'm your host Stu Miniman, and they're breaking down the show, but we always have room for bringing some diversity to the show. Both, we've got Charu Madan, who is the director of strategic alliances with Nutanix. Always want more women in technology on our program. >> Thank you. >> And also, we can't go without getting in to talk to more users. So also happy to welcome to the program Chris Hippensteel, who's network and system administrator with New Resources Consulting. Right over the border in Milwaukee, Wisconsin. Thank you both for joining us. >> Thank you for having me. >> Thank you, it's great to be here. >> So Charu, I saw you last week. You're following me around at all these shows. Of course I was at your show Nutanix. NEXT in New Orleans. Just give our audience your role at Nutanix. What brings you to the Veeam show? >> Absolutely Stu, thank you for having us here, and it looks like we'll be forklifted out of here as being the last Cube event of the day. But yes we had an amazing event last weekend in New Orleans and as you saw the customers were stoked, they were pumped. I just got a chance to talk to so many customers about our direction, about what they heard at the keynote, and I think they were absolutely excited. Our direction in software being a cloud company. All those things resonated so well. And I think the fact that we launched our freedom campaign, you probably heard that freedom to build, freedom to run any application, freedom to invent, freedom to really focus on multi-cloud, and not be bogged down by which cloud. And hybrid cloud is a complex journey, and finally freedom to play. And I think that would resonate very well with Chris out here. So I think that was a very powerful message we sent out that we are giving our customers choice, and ability to run Nutanix anywhere and any workload. >> Yeah absolutely, I had a great conversation with your new CMO, Ben at the show as a customer. So Chris is this your first VeeamOn? >> Yes, this is my first VeeamOn Conference. >> All right, tell us a little bit about your role and your organization. >> Yes, so I'm the network and systems engineer and administrator at New Resources Consulting. And so I pretty much take care of the whole show. Anywhere from simple help desk questions to rebuilding an SAN environment. I came into the company, and there's a lot of legacy equipment, and things were breaking. It wasn't good so-- >> So Chris before we get into the tech, and the company itself. Give us a thumbnail what the operation is. >> Yeah, so New Resources Consulting is a consulting firm out of Milwaukee, Wisconsin. We have users based all over the U.S. and in Canada. We focus a lot on managed services, Oracle solutions, PeopleSoft. We do a lot with the water and waste management out in L.A., in Boston and Denver. We focus on that part of IT. >> It sounds very much as changing dynamic happening there. What are some of the stresses on the organization? What's your role in connection with the business? >> Some of the stresses that I was having was we're sitting there trying to get development servers spun up and with the legacy equipment. It going down a lot. I just wasn't able to do that. So now I'm happy that with Nutanix, I'm able to keep everything running smoothly. It's almost like the company doesn't even know I'm there sometimes. >> It's interesting. Last week, we've been talking a lot about invisible. This week, it's about availability. So maybe you could speak to what that means for your operation. Give us the before and journey that you went through. >> Yes, so before as I mentioned, I had a lot of legacy equipment. I was bidding on things on eBay. They didn't even have the option to buy some things that I needed to replace, and my availability wasn't really there. Both at work and in my home life. I was constantly putting out fires instead of working on growing the company, getting new equipment in, doing new processes. That was before, now after my wife is quite happy that I'm home at reasonable times, and not leaving the house at 9 or 10 p.m. or four o'clock in the morning to go switch out controller cards or drives in my SAN. It's allowed me to work on other projects doing Office 365 roll out. As well as a lot of documentation that wasn't there before me, and helping out my users. Where I wasn't able to do so much because I was putting out all those fires. All right Chris, I've heard from Nutanix customers forgive me my weekend back. Lots of new opportunities. As the first one I think, it helped me in my home relationship. >> Chris: Yes. >> So families are happy to see, a happy wife, a happy life. >> Chris: Yes, exactly. >> Charu give us a little bit of color on what you're seeing and maybe some of the Nutanix Veeam partnership. >> Yeah, and I'll replay what I heard and what I saw actually from customers last week in New Orleans and this week here in Chicago. In New Orleans, Veeam folks had a break out session where they were going to talk about the partnership, and what we are doing together. And it was a full house, people had to be turned back, and could not be accommodated in that room. So that's just a testament to show how much interest there is in Nutanix, in Veeam and the joint solution. Then I talked to customers like Chris. Got talking to him in details on Monday, and Chris is talking about how Veeam and Nutanix has simplified his operations, reduced costs, tremendously for his company. And really helped in focus on driving business value to his internal clients verses like he said, "Keeping the lights on." Just talking to customers about this and hearing the excitement, the elation from our customers. That is really empowering, so I think the two companies have very similar principles. We both love simplicity for our clients. We are both extremely customer-centric, so that makes us very well positioned as companies who work very well together having that common DNA. So we are very excited to have a great partnership with Veeam and I would say now amping up our partnership, and doing even better, bigger stuff. >> Chris, one of the things I hear through both companies. Multi-hypervisors, all good. How the cloud story is maturing. Any commentaries? What you're using from the hypervisor space and what does cloud mean to your organization? >> Yeah, so we don't do too much of the cloud. We keep everything in-house but we are a VMware shop currently, but we're looking forward to Veeam and Nutanix to roll out their hypervisor. Get that solution ready for us. VMware is what we currently use and it's working great, but moving to Nutanix, it allowed me to save a lot of money on cost with the licensing I currently had to the licensing I have now. And Nutanix is going to help me out even further when I move over to their hypervisor, saving me even more money for my company, which is always good for everybody. >> All right, well Charu. Chris is a good set up there. We're talking about age V. I talked to Peter McKay a little bit about it at Veeam, but give us the update on bringing those solutions together. >> Yeah, great question, and yes, I guess some of the rumors are true. We are working on it. The teams are actively working on bringing that delight to customers like Chris because Chris you're not the first one who's asked for it. We've had thousands of customers asking us for that capability of Veeam being able to back up, not just with VMware but also now with our Acropolis Hypervisor. It's imminent. We already have hundreds of customers running the beta. We launched the beta a couple of months back, and the GA is right around the corner. It's not years, it's not months. What the Veeam folks tell me, it's a matter of a few weeks and we are very excited about getting that out. And really like Chris just said it so well. Helping them save costs and helping our thousands of customers do the same. >> It's really nice to see both companies working together, and know that they actually listen to their customers. They listen to what we want and then they go and they find the solutions and work together to actually make it a reality. >> All right Chris, I want to give you the final word. We're getting towards the end of the show. They got the closing keynote. They've got the big Veeam party. >> Chris: All right. >> Nutanix had a great party in New Orleans last week. Veeam actually had a great party too. >> Charu: That's true. >> New Orleans last year. So just for your peers, tell them some of the key take aways. One of the main things that you got out of coming to the show. >> Yeah, the big things I really liked. A lot of the break out sessions, I was able to actually sit down face-to-face with technicians that I had talked to over the phone that I looked up and I've learned so much from. And actually dig deeper into conversations with them 'cause coming to something like this, it's different than just being on the phone with somebody for support or asking questions, or reading knowledge-based articles. So a lot of the break out sessions, getting to meet more of the faces from Nutanix and Veeam, and talking to them about new things that I'm looking forward to. And just brainstorming how I can better run my business with their advice. >> All right, well Chris and Charu. I appreciate you helping bring us to a close of our coverage. Here in Chicago has been a deep dish of all of the technology for the culture. A little bit of sports discussion. So thank you so much for watching. Of course, always go to theCube.net for all the replays of this show. See where we're going to be at. Come say hi to us. Hit us up on any of the social media. For Stu Miniman, my co-host for the week Dave Vellante. The whole crew here from SiliconANGLE Media. Thank you so much for watching theCube. (uptempo techno music)

>> Announcer: Live from Chicago, Illinois; it's theCUBE. Covering VeeamON 2018. Brought to you by Veeam. >> Welcome back to the Windy City, everybody. You're watching theCUBE, the leader in live tech coverage, where we go out to the events, we extract the signal from the noise. This is our second day at VeeamON 2018, our second year. I'm Dave Vellante with Stu Miniman, my co-host. Phil Goodwin is here, he's a research director at IDC's storage systems and software group. Phil, thanks very much for coming on theCUBE. >> Pleasure to be here today. >> So you've been to more VeeamONs than we have, so you've seen even a greater evolution, although we've been to a lot of VeeamUGs. We saw a lot of green. This company has painted Chicago in green. What's your take on the progression and ascendancy of Veeam beyond just being a virtualization specialist? >> Sure, obviously the most interesting thing about Veeam is how they really have become the high growth leader of this industry, and in many ways, kind of the darling of the industry because they've got a lot of the momentum, a lot of the attention that's going on in the data protection and recovery software space. I think what has really struck me over the years of these VeeamON conferences, and really from the very first one that I attended three years ago, is the degree to which there is an ecosystem that's been built up around the products that they have for things like disaster recovery as a service, backup as a service and so forth. Where people take the Veeam software, build it into their own products and go to market with that, and I think that's totally unique in the way they've done that compared to many of their competitors. >> Let's see, we're talking about 800 plus million dollars in bookings, mid-30% growth rates. I presume the data protection market's not growing that fast. >> No, although it's surprisingly strong. Last year it grew at about 7% rate. We don't expect it to keep going that fast but if you compare that to other stores' software, which is 1% to 2% or in some cases even negative, it's actually an area that's quite bright. >> Yeah it's grown much, much faster than the overall IT business, right? >> Oh yeah, absolutely. >> And so, why? Why is it growing faster? >> Well part of it's driven by capacity. A lot of the vendor models are associated with the capacity and so they charge upgrades every year and as data is growing at about 40% per year on a compound annual growth rate, that does cause customers to upgrade their licenses. But we're also seeing an acceleration in the deployment of applications so we expect IT organizations, according to our research, to add an additional 200 applications over the next 36 months. That's not a lot of new applications. What we find in many cases is what we would call the traditional incumbent vendors, who have their footprint within the enterprise, maintain that footprint in many cases, but those new applications have the opportunity to bring in new products and that's really where the opportunity for Veeam is. >> So part of the growth is somewhat artificial if I understand it in that it's pricing driven, and so that would suggest, given that data protection is largely insurance, that the CFOs are going to look at that line out and say, "Oh, this isn't sustainable." Unless, and I want to run this by you, research indicates that Fortune 1000 companies leave, over a three to four year period, billions of dollars each on the table because of not the most end-to-end or well-thought-out architected data protection solutions. Maybe that expands the TAM a little bit, but is that kind of growth sustainable? You've already sort of indicated it's not, but maybe talk about that a little bit. >> Right. The nature of threats has really changed a lot over the years too, so if you look back on computing, it used to be system failure, human error, and to some degree natural disaster were your biggest threats. Nowadays it's actually ransomware, malware, and other things that are much bigger threats than the traditional types of threats that organizations have dealt with. As the evolution of data protection has come about, what we've found is very much a willingness among IT organizations to not simply try and go with a single product, but to rather buy a best-in-class product for specific platforms. In the case of Veeam, I think they really did a very successful job of riding the virtual infrastructure wave when most of their competitors were architected specifically for second platform types of applications. >> Phil, one of the interesting things to watch in Veeam is their expansion beyond that virtualization. What insight can you give us about data protection and SAS and public cloud and service providers? A lot of those environments you would think that the platform or the provider might have a choice, so how does Veeam get in there? How much do customers really have choice there? >> That's really a great point because what is happening is we're moving data protection from the system level. We've moved it up to the virtualization layer and now it's really moving to the application layer, where it is the application developer whose building that data protection directly into their application. So what we're seeing is those application developers, which as you mentioned many are SAS applications on the web, building the data protection into their specific environment. But the other thing that's happening is IT organizations are suddenly realizing that much of that data that is in the web or with those SAS applications is not being protected according to the SLAs of the organization. They're using third party tools and applications like Veeam to bring that data back on site and to protect it according to what the requirements and government's requirements are. >> Okay, so let's unpack some of this. If I understood it correctly, going back to the developers, as architecting in the data protection approach, is that a result of the DeVops trend, infrastructure as code, or is it something else driving it? >> I think it's more being driven by the fact that these are discrete applications outside the data center. So if I'm inside the data center and I'm trying to protect 100 different applications, I may try and apply the same techniques to all of them, the same policies. But these are applications like Salesforce.com, or Payday, or other applications that are really, for lack of a better term, a single application. That environment really doesn't have to consider the other systems within a data center. >> So it's the SAS guy saying "one size fits all." >> Phil: For them, yes. >> Which, by the way, is an age-old problem inside the data center. Either you were not protected enough or you were paying too much. Do companies like Veeam solve that problem by providing more granularity and maybe aligning better with that? >> Yeah. They go attack the problem in a couple of different ways. First of all, they certainly have their traditional business within the data center, but they're also partnering with many of the cloud-based organizations like Azure and Amazon and others to be able to help organizations protect data they have in the cloud. Plus they're working with specific applications to be able to provide that kind of protection for a SAS app. >> I want to come back to something you were talking about with Stu about best of breeds. We do a lot of these shows. You talk to a lot of customers and a lot of technology companies. You get two ends of the spectrum. You get the best of breed guys like Veeam say, "Hey, we're best of breed, "why would you buy that old, clunky, "outdated backup capability?" And then, without naming names, you get the integrated full stack companies going, "Why would anybody buy from some tiny little company? "Oh yeah, okay they're 800 million, "but they can't do digital transformation and big data "and SAS and blah blah blah! "So why would anybody, who cares about backup?" So you have two completely counterpoised positions. How can you help us parse through that? >> I think a lot of it comes down to who is the actual consumer and buyer of the solution and that's indeed changing. What we're seeing much more is it is the application developer, the application provider, or even the line of business making the decision as to what applications are being deployed, as opposed to the central IT organization. So whereas the central IT organizations say "This is part of digital transformation," the business unit may be buying other applications. >> We talked a little earlier about money being left on the table. I don't know what your research shows but clearly there's opportunities there that's not being harvested today. From a cost-benefit analysis standpoint, I know it's one area that you focus on and spend some time there, is it a reasonable expectation that CFOs will actually look at that lost opportunity, that soft revenue that they're losing, which really is not that soft, and say, "Hey, we actually need "to increase our spending in this area?" >> Some of them, yes. What you really find is a maturity curve, of course, where you have some organizations that really have a very traditional view and have not tried to move forward. But our research is showing that about 60% of organizations have embarked on some kind of digital transformation, and that about 70% have a cloud-first perspective. Those organizations really are looking at those kinds of opportunities, both in terms of cost, opportunity cost or absolute cost, and saying, "How can we optimize this environment entirely?" >> If I were the CFO, and let's say I had the cash so I wasn't capital constrained, I would still say, "Look, this is insurance, "so figure out a way to get more value out of this data. "You got all of this data in the backup repository, "what can we do with that? "What analysis can we do? "Can we maybe be more efficient "with regard to how we do security?" It's like the US government. "Can we have this agency talk to that agency "and figure out a way we can get more leverage?" and really be putting pressure on them to do that. Is that an unreasonable expectation for CFOs? >> No, and in fact what our research has shown is that about 40% of organizations use their backup data sets for analytics. They also, about 30% of them, 33% use it for other purposes such as development and test, staging, others. So organizations really are trying to leverage that vast amount of information that they have for other purposes. One of the challenges that come out though is GDPR, the European regulation to the right to be forgotten and the way organizations have to be able to manage that data. Going into those data repositories, including backup data sets, to say "Okay, this is data "that we have to expunge by regulation." >> Phil, I wonder, we've been talking about the threats of GDPR and you might get sued or everything. The last few years, we've really been talking about how we get insights and data. Insights can transform businesses around data. Is GDPR a threat to this whole wave of getting value out of data? >> I don't think it's a threat to getting the value out of the data, I think it's a threat to how you manage that data. And the threat is much more widespread than many organizations realize. If you're doing business with anyone who is European or has traveled to Europe, and really any kind of footprint in that regard can potentially put your organization at risk if you're capturing any of that data. >> But that stat you just threw out was pretty interesting. The 40% percent of organizations that you surveyed are actually doing some types of analytics with their backup data. I would think that governance and compliance and GDPR related stuff, they're going to take, those 40% are going to take a similar approach to GDPR. Say, "Okay, guys, we got to do this. "Find some more value out of it, "or else get you in a headlock." Right? That's a huge number! >> Right, and one of the ways you do that is, and that Veeam has done is to open up APIs, application programming interfaces, to allow third party organizations to leverage that data repository and do that kind of analytics. Veaam, themselves, or any other backup vendor can't really leverage, or can't really do that, but by opening that up to third parties it increases that ecosystem and increases the value that IT organizations can get from their data and their investment. >> Some of your research. Maybe you can highlight some of the stuff you're proud of, fun stuff you've been working on, things that are current, recent, that you want to highlight to the audience. >> I think some of the interesting things, the trends in the industry really are that the kinds of things like backup and recovery and high availability and disaster recovery, we see really going into a continuum of availability. Where, if I can move data across geographies, and I can recover my application seamlessly regardless of where the data is, why do I ever need to have disaster recovery again? And in fact, that's where we believe availability is going, and in fact the theme for Veeam at this show is hyper-availability. One of the ways you do that is by placing the data in the right locations for that kind of recovery. Watching from the days of backing up once a day onto tape to continuous availability is actually a pretty interesting development. >> So who's doing a good job in this place? Sounds like Veeam is getting it done obviously, and the numbers speak for themselves. You got the startups, Cohesity, Rubrik, Zerto obviously plays in there. You have Veritas is supposedly retooling. You had Bill Coleman in there, former BEA guy who's supposedly put a lot of R and D into that. You got the leader in Dell EMC. Obviously they have a lot of resource, spend a lot of money, they're going through a retooling process. IBM has software defined everything. It seems like it's jump ball right now instead of wide open. >> It really is. You look at, you mentioned Dell EMC, they're focusing on IOT. Well IOT generates a phenomenal amount of data. What data needs to be captured, how does it need to be captured, protected, managed, is going to be a huge issue for organizations so that's a very interesting target. Veritas has been looking at their 360 data management and really taking a holistic view of data management and they're doing some very interesting things there. Commvault has done actually a pretty nice job of getting into some cloud-related kinds of things. And then finally as you mentioned, Rubrik and Cohesity, I would put them along with Veeam as probably the three companies that right now are disrupting this industry the most. There are probably certainly some other ones that are up and coming, but in terms of those that are really providing some disruption, I would probably go with those three. >> Alright, they're breaking down VeeamON 2017. Phil, thanks for coming on theCUBE. Great stuff, really good analysis. Appreciate you having on. >> Pleasure, guys, take care. >> The trains are backing up. We're trying to jam everything in before they shut down our studio, so we'll be right back right after this short break. (upbeat music)

>> Announcer: Live from Chicago, Illinois, it's theCUBE. Covering VeeamOn 2018. Brought to you by VeeamOn. >> We're back. VeeamOn 2018. You're watching theCUBE, the leader in live tech coverage, where we go out to the events and we extract the signal from the noise. Dave Vellante, with my co-host Stu Miniman and Marc Crespi is here. He's the Vice President of Sales Engineering at ExaGrid, another Mass boy. Welcome back to theCUBE. Good to see you again, Marc. >> Thanks, great to be with you guys again. Great to be on another fantastic VeeamOn in the world-class city of Chicago. >> Yeah, it's a great city. What's happening at VeeamOn for ExaGrid this year? >> Quite a few executive meetings, a lot of customer contact, existing customers, prospective customers, meeting with the joint sales teams and so on. We coordinate a lot with VeeamOn in the field and on an engineering level, so great to get off the phone and see each other face to face and really deepen the relationship. >> So, talk a little bit about what the conversation is like with customers, particularly as it relates to data protection. We're hearing a lot on cloud, multi-cloud, intelligent data management. What does that all mean to your customers? >> Sure. So, obviously VeeamOn provides a wealth of different functionality in all of those areas, whether it be the intelligent data management, which includes cloud components, et cetera. We at ExaGrid play a role, mostly on the on-premise side, to be honest, of the equation. And because we typically deal with a quite large customers, the use of the cloud is really, typically relegated for older, more archive oriented data, or long-term retention backup data than it is for primary data, or even primary copy for disaster recovery simply because of the logistics of managing that much data when you may need it. However, the cloud plays a very important role in those types of customers, as many of them have regulatory requirements, compliance requirements to keep data long-term that they may never need to access, or never need to touch. In which case tiering that out to the cloud is a potentially good strategy. >> Marc, one of the things we're watching at this show is how VeeamOn's trying to get deeper and broader into the enterprise. If you can, give us a little color as to how you're seeing, where is VeeamOn being successful, what are customers liking for that kind of solution? >> Sure. We're seeing a significant amount of traction with VeeamOn and enterprise customers. In fact, we met with a large travel agency out here at the show who's looking at both VeeamOn and ExaGrid as a combined solution. So we're working very closely. VeeamOn has a dedicated enterprise team in the field, and they're breaking down doors to a number of the different enterprises. And our solution, the way it scales and its performance profile is very well-suited to the enterprise. We are an enterprise-class company as well, so we're doing cross-introductions for each other and to each other's enterprise customer base as we go. >> Talk a little bit more about your solution, where the sweet spot is. We always talk about horses for courses on theCUBE. >> Marc: Sure. Yeah. >> What's your favorite course? >> So, we define a target customer, the first demographic that we use is typically the amount of data they have under management. Put another way, the amount of primary data they have, or the utilization on their primary storage. And where we typically live, these days is 50 terabyte is kind of the low end, all the way up to multiple petabytes of data being backed up. And we can store many, many weeks, or months, or years of that data because of the data deduplication impact. But that's our sweet spot. And typically that's the most key demographic for us to look at, is how much data they're managing. >> And you're an infrastructure provider, obviously. You have software, but you don't do backup software. That's not your specialty, right? >> That's correct. That's one of the reasons we have such a close relationship with VeeamOn. And, quite honestly, we partner with a number of folks, but VeeamOn is clearly one of our key, if not our key partner because they provide the data protection functionality, the management, et cetera, and we provide the intelligent hyperconverged secondary storage that can store all of that data, deduplicate it, replicate it, and also provide, uniquely, I might add; support for some of VeeamOn's really critical features, like Instant VM Recovery and Virtual Lab and SureBackup. Because of the way our product is architected those features work extremely well with us, where in some cases, in some solutions they don't quite work as well. >> I think back to a number of years ago deduplication was all the talk in the storage industry. How are the latest trends in everything from Flash's adoption, NVMe, and NVMe over fabric coming soon, how's that going to impact what customers are doing in your space? >> Sure, so first I'll tackle the deduplication part of it. There's no question that it's now become an accepted norm. It's rare these days that you're explaining what it is, or what it does. But there still is one left over misconception that I think it's really important for all of us who have deduplication to educate customers. And that is that not every type of deduplication is created equal. Sometimes people conflate it with compression. You know, all compression's kind of the same to a certain extent. The way deduplication is implemented, there are certain characteristics that will either increase the amount of data reduction you get or lessen the amount of data reduction you get. For customers it's really important to know what type of algorithm you're dealing with 'cause that's going to translate to cost over the long term. So that's the first thing. The other trends, the adoption of Flash and so on, really has been more on the primary storage side, where that level of performance is required for high transaction, high performance requiring applications and so on. Because Flash remains quite a bit more expensive than spinning disc is, it's inroads into backup or secondary storage have been somewhat more on a limited basis. >> So, if I understand you correctly, a large part of the data reduction is a function of the algorithm... I don't want to say not so much the workload, but I was always under the impression that the workload determined the sort of data reduction efficacy. >> Marc: Sure. >> Which I'm sure is true, but you're saying the algorithm also has a huge impact. >> It's a combination. So, there's no question that certain data types deduplicate extremely well, other types not as well, and some not at all. You know, pre-compressed, pre-encrypted data tends not to deduplicate well at all. Where the algorithm comes in is there's a couple of elements, not to get to get too much in the weeds, but something called block size, which is basically the size of the objects that you examine when you deduplicate, and then whether or not you do what's called variable-length analysis, which is adjusting to the fact that the data is expanding and shrinking as it's changing. Algorithm's that implement very large block sizes and avoid variable-length technology are going to get much lower deduplication ratios than algorithms that implement both of those elements, smaller object sizes, and variable-length technology. And we're in the latter category of the more aggressive form of deduplication. >> So, you've got greater granularity and the greater ability to drive data reduction ratios, assuming the workload is favorable to that. >> Exactly right. If you were to compare the same workload across the two algorithms, the less aggressive and the more aggressive, the more aggressive is going to do better on that workload than the less aggressive. >> And again, I know it depends on the workload, but are we talking about on a percentage basis 10% better, 20%, 50%, a 100%? >> Marc: Multiples better. Some cases five to 10 times better. >> Even an order of magnitude in some cases. >> Marc: An order of magnitude better, yes, in some cases. >> What about encryption? What's the state of encryption these days? What are you advising customers with regard to encryption? >> Well, for years we've been under the impression that everything's going to have to be encrypted at some point. It's been a slow journey. You know, there's PCI compliance, HIPPA compliance. Obviously, there's been some pretty infamous hacks that have happened and so on. So the way we look at encryption, we have encryption solutions, self-encrypting appliances, and we recommend to customers, even if you don't need encryption today, if there is a slight chance that you'll need it in the future, then go with our encrypting line of appliances. The cost difference is nominal. It's in single-digit, low single-digit percentages, and it's there when you need it. So you don't have to potentially swap after that. We also do encryption any time we move data over the LAN. So we're fully ready for all of these compliances. It's certified encryption, you know, federal level certification, et cetera, so-- >> Yeah, Marc, let us know what companies aren't aware of the need for encryption and I'm going to short those stocks. (laughing) >> Okay, you got it. Yeah, you might want to change your bank. >> All right. Got to ask you. Brady, if you were Robert Kraft, would you have traded Tom Brady? >> Absolutely not. >> That's unanimous, there. Three for three on that. >> Absolutely, no. >> Okay, why not? What would the rationale be? >> I think he's got a lot more to give yet. I think it would have been on par with the Babe Ruth trade. It would have been a historical disaster. You know, he got us to the Super Bowl last year. Granted, Philly inched us out, but I still think he's the GOAT and he's going to stay the GOAT. >> Giselle said Tom Brady can't catch the ball. I would say also, he can't play defense, so-- >> I would agree with that as well. >> All right, what about Garoppolo? Do you think it was the right move to hold onto him, essentially as an insurance policy in case Brady went down before the trade deadline, or should they have been more proactive and gotten more for him? >> I think it probably would have been the right move for the Patriots to hang on to Garoppolo, however, for Garoppolo himself, and for the fact that they needed to get at least something for him, I think it was the right move at the right time. He needs to play. He's a great quarterback. He's already turning that San Francisco franchise around. >> Right. >> So I'm happy to see him play. I actually now start watching 49ers games 'cause I want to root for him. >> Me, too. I'm a fan of Garoppolo. >> Marc: He's a son of the Patriots. >> I agree. I think it was the smart move, Stu to keep him as an insurance policy, just in case. You don't know. I mean, Brady, you know, 40 plus years old. I mean, look what happened last year. >> It's the economics, Dave, though. They weren't going to pay him what he needed to be able to be a backup, and I agree with Marc. He was ready to play, obviously and it is fun to watch him on the 49ers. >> No, we agree. One of 'em had to go, right? Okay, and now we're three for three. So Peter McKay, Patrick Osborne, and now Marc Crespi all say Brady should stay. Right move. We'll see. Hey, they're the favorite to win the Super Bowl next year. Hopefully, they can get there. >> Sounds like I'm in good company. >> Marc, thanks very much for coming back on theCUBE. >> Thank you. It's always a pleasure to see you guys. >> All right, keep it right there, everybody. We'll be back with our next guest right after this short break. You're watching theCUBE, from VeeamOn 2018. (upbeat music)