(light upbeat music) >> Hey, everyone. Welcome back to theCUBE's day long coverage of Women in Data Science 2023. Live from Stanford University, I'm Lisa Martin. We've had some amazing conversations today with my wonderful co-host, as you've seen. Tracy Zhang joins me next for a very interesting and inspiring conversation. I know we've been bringing them to you, we're bringing you another one here. Dr. Irene Dankwa-Mullan joins us, the Chief Medical Officer at Marti Health, and a speaker at WIDS. Welcome, Irene, it's great to have you. >> Thank you. I'm delighted to be here. Thank you so much for this opportunity. >> So you have an MD and a Master of Public Health. Covid must have been an interesting time for you, with an MPH? >> Very much so. >> Yeah, talk a little bit about you, your background, and Marti Health? This is interesting. This is a brand new startup. This is a digital health equity startup. >> Yes, yes. So, I'll start with my story a little bit about myself. So I was actually born in Ghana. I finished high school there and came here for college. What would I say? After I finished my undergraduate, I went to medical school at Dartmouth and I always knew I wanted to go into public health as well as medicine. So my medical education was actually five years. I did the MPH and my medical degree, at the same time, I got my MPH from Yale School of Public Health. And after I finished, I trained in internal medicine, Johns Hopkins, and after that I went into public health. I am currently living in Maryland, so I'm in Bethesda, Maryland, and that's where I've been. And really enjoyed public health, community health, combining that aspect of sort of prevention and wellness and also working in making sure that we have community health clinics and safety net clinics. So a great experience there. I also had the privilege, after eight years in public health, I went to the National Institute of Health. >> Oh, wow. >> Where I basically worked in clinical research, basically on minority health and health disparities. So, I was in various leadership roles and helped to advance the science of health equity, working in collaboration with a lot of scientists and researchers at the NIH, really to advance the science. >> Where did your interest in health equity come from? Was there a defining moment when you were younger and you thought "There's a lot of inequities here, we have to do something about this." Where did that interest start? >> That's a great question. I think this influence was basically maybe from my upbringing as well as my family and also what I saw around me in Ghana, a lot of preventable diseases. I always say that my grandfather on my father's side was a great influence, inspired me and influenced my career because he was the only sibling, really, that went to school. And as a result, he was able to earn enough money and built, you know, a hospital. >> Oh wow. >> In their hometown. >> Oh my gosh! >> It started as a 20 bed hospital and now it's a 350 bed hospital. >> Oh, wow, that's amazing! >> In our hometown. And he knew that education was important and vital as well for wellbeing. And so he really inspired, you know, his work inspired me. And I remember in residency I went with a group of residents to this hospital in Ghana just to help over a summer break. So during a summer where we went and helped take care of the sick patients and actually learned, right? What it is like to care for so many patients and- >> Yeah. >> It was really a humbling experience. But that really inspired me. I think also being in this country. And when I came to the U.S. and really saw firsthand how patients are treated differently, based on their background or socioeconomic status. I did see firsthand, you know, that kind of unconscious bias. And, you know, drew me to the field of health disparities research and wanted to learn more and do more and contribute. >> Yeah. >> Yeah. So, I was curious. Just when did the data science aspect tap in? Like when did you decide that, okay, data science is going to be a problem solving tool to like all the problems you just said? >> Yeah, that's a good question. So while I was at the NIH, I spent eight years there, and precision medicine was launched at that time and there was a lot of heightened interest in big data and how big data could help really revolutionize medicine and healthcare. And I got the opportunity to go, you know, there was an opportunity where they were looking for physicians or deputy chief health officer at IBM. And so I went to IBM, Watson Health was being formed as a new business unit, and I was one of the first deputy chief health officers really to lead the data and the science evidence. And that's where I realized, you know, we could really, you know, the technology in healthcare, there's been a lot of data that I think we are not really using or optimizing to make sure that we're taking care of our patients. >> Yeah. >> And so that's how I got into data science and making sure that we are building technologies using the right data to advance health equity. >> Right, so talk a little bit about health equity? We mentioned you're with Marti Health. You've been there for a short time, but Marti Health is also quite new, just a few months old. Digital health equity, talk about what Marti's vision is, what its mission is to really help start dialing down a lot of the disparities that you talked about that you see every day? >> Yeah, so, I've been so privileged. I recently joined Marti Health as their Chief Medical Officer, Chief Health Officer. It's a startup that is actually trying to promote a value-based care, also promote patient-centered care for patients that are experiencing a social disadvantage as a result of their race, ethnicity. And were starting to look at and focused on patients that have sickle cell disease. >> Okay. >> Because we realize that that's a population, you know, we know sickle cell disease is a genetic disorder. It impacts a lot of patients that are from areas that are endemic malaria. >> Yeah. >> Yeah. >> And most of our patients here are African American, and when, you know, they suffer so much stigma and discrimination in the healthcare system and complications from their sickle cell disease. And so what we want to do that we feel like sickle cell is a litmus test for disparities. And we want to make sure that they get in patient-centered care. We want to make sure that we are leveraging data and the research that we've done in sickle cell disease, especially on the continent of Africa. >> Okay. >> And provide, promote better quality care for the patients. >> That's so inspiring. You know, we've heard so many great stories today. Were you able to watch the keynote this morning? >> Yes. >> I loved how it always inspires me. This conference is always, we were talking about this all day, how you walk in the Arrillaga Alumni Center here where this event is held every year, the vibe is powerful, it's positive, it's encouraging. >> Inspiring, yeah. >> Absolutely. >> Inspiring. >> Yeah, yeah. >> It's a movement, WIDS is a movement. They've created this community where you feel, I don't know, kind of superhuman. "Why can't I do this? Why not me?" We heard some great stories this morning about data science in terms of applications. You have a great application in terms of health equity. We heard about it in police violence. >> Yes. >> Which is an epidemic in this country for sure, as we know. This happens too often. How can we use data and data science as a facilitator of learning more about that, so that that can stop? I think that's so important for more people to understand all of the broad applications of data science, whether it's police violence or climate change or drug discovery or health inequities. >> Irene: Yeah. >> The potential, I think we're scratching the surface. But the potential is massive. >> Tracy: It is. >> And this is an event that really helps women and underrepresented minorities think, "Why not me? Why can't I get involved in that?" >> Yeah, and I always say we use data to make an make a lot of decisions. And especially in healthcare, we want to be careful about how we are using data because this is impacting the health and outcomes of our patients. And so science evidence is really critical, you know? We want to make sure that data is inclusive and we have quality data. >> Yes. >> And it's transparent. Our clinical trials, I always say are not always diverse and inclusive. And if that's going to form the evidence base or data points then we're doing more harm than good for our patients. And so data science, it's huge. I mean, we need a robust, responsible, trustworthy data science agenda. >> "Trust" you just brought up "trust." >> Yeah. >> I did. >> When we talk about data, we can't not talk about security and privacy and ethics but trust is table stakes. We have to be able to evaluate the data and trust in it. >> Exactly. >> And what it says and the story that can be told from it. So that trust factor is, I think, foundational to data science. >> We all see what happened with Covid, right? I mean, when the pandemic came out- >> Absolutely. >> Everyone wanted information. We wanted data, we wanted data we could trust. There was a lot of hesitancy even with the vaccine. >> Yeah. >> Right? And so public health, I mean, like you said, we had to do a lot of work making sure that the right information from the right data was being translated or conveyed to the communities. And so you are totally right. I mean, data and good information, relevant data is always key. >> Well- >> Is there any- Oh, sorry. >> Go ahead. >> Is there anything Marti Health is doing in like ensuring that you guys get the right data that you can put trust in it? >> Yes, absolutely. And so this is where we are, you know, part of it would be getting data, real world evidence data for patients who are being seen in the healthcare system with sickle cell disease, so that we can personalize the data to those patients and provide them with the right treatment, the right intervention that they need. And so part of it would be doing predictive modeling on some of the data, risk, stratifying risk, who in the sickle cell patient population is at risk of progressing. Or getting, you know, they all often get crisis, vaso-occlusive crisis because the cells, you know, the blood cell sickles and you want to avoid those chest crisis. And so part of what we'll be doing is, you know, using predictive modeling to target those at risk of the disease progressing, so that we can put in preventive measures. It's all about prevention. It's all about making sure that they're not being, you know, going to the hospital or the emergency room where sometimes they end up, you know, in pain and wanting pain medicine. And so. >> Do you see AI as being a critical piece in the transformation of healthcare, especially where inequities are concerned? >> Absolutely, and and when you say AI, I think it's responsible AI. >> Yes. >> And making sure that it's- >> Tracy: That's such a good point. >> Yeah. >> Very. >> With the right data, with relevant data, it's definitely key. I think there is so much data points that healthcare has, you know, in the healthcare space there's fiscal data, biological data, there's environmental data and we are not using it to the full capacity and full potential. >> Tracy: Yeah. >> And I think AI can do that if we do it carefully, and like I said, responsibly. >> That's a key word. You talked about trust, responsibility. Where data science, AI is concerned- >> Yeah. >> It has to be not an afterthought, it has to be intentional. >> Tracy: Exactly. >> And there needs to be a lot of education around it. Most people think, "Oh, AI is just for the technology," you know? >> Yeah, right. >> Goop. >> Yes. >> But I think we're all part, I mean everyone needs to make sure that we are collecting the right amount of data. I mean, I think we all play a part, right? >> We do. >> We do. >> In making sure that we have responsible AI, we have, you know, good data, quality data. And the data sciences is a multi-disciplinary field, I think. >> It is, which is one of the things that's exciting about it is it is multi-disciplinary. >> Tracy: Exactly. >> And so many of the people that we've talked to in data science have these very non-linear paths to get there, and so I think they bring such diversity of thought and backgrounds and experiences and thoughts and voices. That helps train the AI models with data that's more inclusive. >> Irene: Yes. >> Dropping down the volume on the bias that we know is there. To be successful, it has to. >> Definitely, I totally agree. >> What are some of the things, as we wrap up here, that you're looking forward to accomplishing as part of Marti Health? Like, maybe what's on the roadmap that you can share with us for Marti as it approaches the the second half of its first year? >> Yes, it's all about promoting health equity. It's all about, I mean, there's so much, well, I would start with, you know, part of the healthcare transformation is making sure that we are promoting care that's based on value and not volume, care that's based on good health outcomes, quality health outcomes, and not just on, you know, the quantity. And so Marti Health is trying to promote that value-based care. We are envisioning a world in which everyone can live their full life potential. Have the best health outcomes, and provide that patient-centered precision care. >> And we all want that. We all want that. We expect that precision and that personalized experience in our consumer lives, why not in healthcare? Well, thank you, Irene, for joining us on the program today. >> Thank you. >> Talking about what you're doing to really help drive the volume up on health equity, and raise awareness for the fact that there's a lot of inequities in there we have to fix. We have a long way to go. >> We have, yes. >> Lisa: But people like you are making an impact and we appreciate you joining theCUBE today and sharing what you're doing, thank you. >> Thank you. >> Thank you- >> Thank you for having me here. >> Oh, our pleasure. For our guest and Tracy Zhang, this is Lisa Martin from WIDS 2023, the eighth Annual Women in Data Science Conference brought to you by theCUBE. Stick around, our show wrap will be in just a minute. Thanks for watching. (light upbeat music)

(gentle music) (upbeat music) (crowd chattering) >> Welcome back to The City That Never Sleeps. Lisa Martin and John Furrier in New York City for AWS Summit '22 with about 10 to 12,000 of our friends. And we've got two more friends joining us here today. We're going to be talking with Haseeb Budhani, one of our alumni, co-founder and CEO of Rafay Systems, and Kevin Coleman, senior manager for Go-to Market for EKS at AWS. Guys, thank you so much for joining us today. >> Thank you very much for having us. Excited to be here. >> Isn't it great to be back at an in-person event with 10, 12,000 people? >> Yes. There are a lot of people here. This is packed. >> A lot of energy here. So, Haseeb, we've got to start with you. Your T-shirt says it all. Don't hate k8s. (Kevin giggles) Talk to us about some of the trends, from a Kubernetes perspective, that you're seeing, and then Kevin will give your follow-up. >> Yeah. >> Yeah, absolutely. So, I think the biggest trend I'm seeing on the enterprise side is that enterprises are forming platform organizations to make Kubernetes a practice across the enterprise. So it used to be that a BU would say, "I need Kubernetes. I have some DevOps engineers, let me just do this myself." And the next one would do the same, and then next one would do the same. And that's not practical, long term, for an enterprise. And this is now becoming a consolidated effort, which is, I think it's great. It speaks to the power of Kubernetes, because it's becoming so important to the enterprise. But that also puts a pressure because what the platform team has to solve for now is they have to find this fine line between automation and governance, right? I mean, the developers, you know, they don't really care about governance. Just give me stuff, I need to compute, I'm going to go. But then the platform organization has to think about, how is this going to play for the enterprise across the board? So that combination of automation and governance is where we are finding, frankly, a lot of success in making enterprise platform team successful. I think, that's a really new thing to me. It's something that's changed in the last six months, I would say, in the industry. I don't know if, Kevin, if you agree with that or not, but that's what I'm seeing. >> Yeah, definitely agree with that. We see a ton of customers in EKS who are building these new platforms using Kubernetes. The term that we hear a lot of customers use is standardization. So they've got various ways that they're deploying applications, whether it's on-prem or in the cloud and region. And they're really trying to standardize the way they deploy applications. And Kubernetes is really that compute substrate that they're standardizing on. >> Kevin, talk about the relationship with Rafay Systems that you have and why you're here together. And two, second part of that question, why is EKS kicking ass so much? (Haseeb and Kevin laughing) All right, go ahead. First one, your relationship. Second one, EKS is doing pretty well. >> Yep, yep, yep. (Lisa laughing) So yeah, we work closely with Rafay, Rafay, excuse me. A lot of joint customer wins with Haseeb and Co, so they're doing great work with EKS customers and, yeah, love the partnership there. In terms of why EKS is doing so well, a number of reasons, I think. Number one, EKS is vanilla, upstream, open-source Kubernetes. So customers want to use that open-source technology, that open-source Kubernetes, and they come to AWS to get it in a managed offering, right? Kubernetes isn't the easiest thing to self-manage. And so customers, you know, back before EKS launched, they were banging down the door at AWS for us to have a managed Kubernetes offering. And, you know, we launched EKS and there's been a ton of customer adoption since then. >> You know, Lisa, when we, theCUBE 12 years, now everyone knows we started in 2010, we used to cover a show called OpenStack. >> I remember that. >> OpenStack Summit. >> What's that now? >> And at the time, at that time, Kubernetes wasn't there. So theCUBE was present at creation. We've been to every KubeCon ever, CNCF then took it over. So we've been watching it from the beginning. >> Right. And it reminds me of the same trend we saw with MapReduce and Hadoop. Very big promise, everyone loved it, but it was hard, very difficult. And Hadoop's case, big data, it ended up becoming a data lake. Now you got Spark, or Snowflake, and Databricks, and Redshift. Here, Kubernetes has not yet been taken over. But, instead, it's being abstracted away and or managed services are emerging. 'Cause general enterprises can't hire enough Kubernetes people. >> Yep. >> They're not that many out there yet. So there's the training issue. But there's been the rise of managed services. >> Yep. >> Can you guys comment on what your thoughts are relative to that trend of hard to use, abstracting away the complexity, and, specifically, the managed services? >> Yeah, absolutely. You want to go? >> Yeah, absolutely. I think, look, it's important to not kid ourselves. It is hard. (Johns laughs) But that doesn't mean it's not practical, right. When Kubernetes is done well, it's a thing of beauty. I mean, we have enough customer to scale, like, you know, it's like a, forget a hockey stick, it's a straight line up, because they just are moving so fast when they have the right platform in place. I think that the mistake that many of us make, and I've made this mistake when we started this company, was trivializing the platform aspect of Kubernetes, right. And a lot of my customers, you know, when they start, they kind of feel like, well, this is not that hard. I can bring this up and running. I just need two people. It'll be fine. And it's hard to hire, but then, I need two, then I need two more, then I need two, it's a lot, right. I think, the one thing I keep telling, like, when I talk to analysts, I say, "Look, somebody needs to write a book that says, 'Yes, it's hard, but, yes, it can be done, and here's how.'" Let's just be open about what it takes to get there, right. And, I mean, you mentioned OpenStack. I think the beauty of Kubernetes is that because it's such an open system, right, even with the managed offering, companies like Rafay can build really productive businesses on top of this Kubernetes platform because it's an open system. I think that is something that was not true with OpenStack. I've spent time with OpenStack also, I remember how it is. >> Well, Amazon had a lot to do with stalling the momentum of OpenStack, but your point about difficulty. Hadoop was always difficult to maintain and hiring against. There were no managed services and no one yet saw that value of big data yet. Here at Kubernetes, people are living a problem called, I'm scaling up. >> Yep. And so it sounds like it's a foundational challenge. The ongoing stuff sounds easier or manageable. >> Once you have the right tooling. >> Is that true? >> Yeah, no, I mean, once you have the right tooling, it's great. I think, look, I mean, you and I have talked about this before, I mean, the thesis behind Rafay is that, you know, there's like 8, 12 things that need to be done right for Kubernetes to work well, right. And my whole thesis was, I don't want my customer to buy 10, 12, 15 products. I want them to buy one platform, right. And I truly believe that, in our market, similar to what vCenter, like what VMware's vCenter did for VMs, I want to do that for Kubernetes, right. And that the reason why I say that is because, see, vCenter is not about hypervisors, right? vCenter is about hypervisor, access, networking, storage, all of the things, like multitenancy, all the things that you need to run an enterprise-grade VM environment. What is that equivalent for the Kubernetes world, right? So what we are doing at Rafay is truly building a vCenter, but for Kubernetes, like a kCenter. I've tried getting the domain. I couldn't get it. (Kevin laughs) >> Well, after the Broadcom view, you don't know what's going to happen. >> Ehh. (John laughs) >> I won't go there! >> Yeah. Yeah, let's not go there today. >> Kevin, EKS, I've heard people say to me, "Love EKS. Just add serverless, that's a home run." There's been a relationship with EKS and some of the other Amazon tools. Can you comment on what you're seeing as the most popular interactions among the services at AWS? >> Yeah, and was your comment there, add serverless? >> Add serverless with AKS at the edge- >> Yeah. >> and things are kind of interesting. >> I mean, so, one of the serverless offerings we have today is actually Fargate. So you can use Fargate, which is our serverless compute offering, or one of our serverless compute offerings with EKS. And so customers love that. Effectively, they get the beauty of EKS and the Kubernetes API but they don't have to manage nodes. So that's, you know, a good amount of adoption with Fargate as well. But then, we also have other ways that they can manage their nodes. We have managed node groups as well, in addition to self-managed nodes also. So there's a variety of options that customers can use from a compute perspective with EKS. And you'll continue to see us evolve the portfolio as well. >> Can you share, Haseeb, can you share a customer example, a joint customer example that you think really articulates the value of what Rafay and AWS are doing together? >> Yeah, absolutely. In fact, we announced a customer very recently on this very show, which is MoneyGram, which is a joint AWS and Rafay customer. Look, we have enough, you know, the thing about these massive customers is that, you know, not everybody's going to give us their logo to use. >> Right. >> But MoneyGram has been a Rafay plus EKS customer for a very, very long time. You know, at this point, I think we've earned their trust, and they've allowed us to, kind of say this publicly. But there's enough of these financial services companies who have, you know, standardized on EKS. So it's EKS first, Rafay second, right. They standardized on EKS. And then they looked around and said, "Who can help me platform EKS across my enterprise?" And we've been very lucky. We have some very large financial services, some very large healthcare companies now, who, A, EKS, B, Rafay. I'm not just saying that because my friend Kevin's here, (Lisa laughs) it's actually true. Look, EKS is a brilliant platform. It scales so well, right. I mean, people try it out, relative to other platforms, and it's just a no-brainer, it just scales. You want to build a big enterprise on the backs of a Kubernetes platform. And I'm not saying that's because I'm biased. Like EKS is really, really good. There's a reason why so many companies are choosing it over many other options in the market. >> You're doing a great job of articulating why the theme (Kevin laughs) of the New York City Summit is scale anything. >> Oh, yeah. >> There you go. >> Oh, yeah. >> I did not even know that but I'm speaking the language, right? >> You are. (John laughs) >> Yeah, absolutely. >> One of the things that we're seeing, also, I want to get your thoughts on, guys, is the app modernization trend, right? >> Yep. >> Because unlike other standards that were hard, that didn't have any benefit downstream 'cause they were too hard to get to, here, Kubernetes is feeding into real app for app developer pressure. They got to get cloud-native apps out. It's fairly new in the mainstream enterprise and a lot of hyperscalers have experience. So I'm going to ask you guys, what is the key thing that you're enabling with Kubernetes in the cloud-native apps? What is the key value? >> Yeah. >> I think, there's a bifurcation happening in the market. One is the Kubernetes Engine market, which is like EKS, AKS, GKE, right. And then there's the, you know, what, back in the day, we used to call operations and management, right. So the OAM layer for Kubernetes is where there's need, right. People are learning, right. Because, as you said before, the skill isn't there, you know, there's not enough talent available to the market. And that's the opportunity we're seeing. Because to solve for the standardization, the governance, and automation that we talked about earlier, you know, you have to solve for, okay, how do I manage my network? How do I manage my service mesh? How do I do chargebacks? What's my, you know, policy around actual Kubernetes policies? What's my blueprinting strategy? How do I do add-on management? How do I do pipelines for updates of add-ons? How do I upgrade my clusters? And we're not done yet, there's a longer list, right? This is a lot, right? >> Yeah. >> And this is what happens, right. It's just a lot. And really, the companies who understand that plethora of problems that need to be solved and build easy-to-use solutions that enterprises can consume with the right governance automation, I think they're going to be very, very successful here. >> Yeah. >> Because this is a train, right? I mean, this is happening whether, it's not us, it's happening, right? Enterprises are going to keep doing this. >> And open-source is a big driver in all of this. >> Absolutely. >> Absolutely. >> And I'll tag onto that. I mean, you talked about platform engineering earlier. Part of the point of building these platforms on top of Kubernetes is giving developers an easier way to get applications into the cloud. So building unique developer experiences that really make it easy for you, as a software developer, to take the code from your laptop, get it out of production as quickly as possible. The question is- >> So is that what you mean, does that tie your point earlier about that vertical, straight-up value once you've set up it, right? >> Yep. >> Because it's taking the burden off the developers for stopping their productivity. >> Absolutely. >> To go check in, is it configured properly? Is the supply chain software going to be there? Who's managing the services? Who's orchestrating the nodes? >> Yep. >> Is that automated, is that where you guys see the value? >> That's a lot of what we see, yeah. In terms of how these companies are building these platforms, is taking all the component pieces that Haseeb was talking about and really putting it into a cohesive whole. And then, you, as a software developer, you don't have to worry about configuring all of those things. You don't have to worry about security policy, governance, how your app is going to be exposed to the internet. >> It sounds like infrastructure is code. >> (laughs) Yeah. >> Come on, like. >> (laughs) Infrastructure's code is a big piece of it, for sure, for sure. >> Yeah, look, infrastructure's code actually- >> Infrastructure's sec is code too, the security. >> Yeah. >> Huge. >> Well, it all goes together. Like, we talk about developer self-service, right? The way we enable developer self-service is by teaching developers, here's a snippet of code that you write and you check it in and your infrastructure will just magically be created. >> Yep. >> But not automatically. It's going to go through a check, like a check through the platform team. These are the workflows that if you get them right, developers don't care, right. All developers want is I want to compute. But then all these 20 things need to happen in the back. That's what, if you nail it, right, I mean, I keep trying to kind of pitch the company, I don't want to do that today. But if you nail that, >> I'll give you a plug at the end. >> you have a good story. >> But I got to, I just have a tangent question 'cause you reminded me. There's two types of developers that have emerged, right. You have the software developer that wants infrastructures code. I just want to write my code, I don't want to stop. I want to build in shift-left for security, shift-right for data. All that's in there. >> Right. >> I'm coding away, I love coding. Then you've got the under-the-hood person. >> Yes. >> I've been to the engines. >> Certainly. >> So that's more of an SRE, data engineer, I'm wiring services together. >> Yeah. >> A lot of people are like, they don't know who they are yet. They're in college or they're transforming from an IT job. They're trying to figure out who they are. So question is, how do you tell a person that's watching, like, who am I? Like, should I be just coding? But I love the tech. Would you guys have any advice there? >> You know, I don't know if I have any guidance in terms of telling people who they are. (all laughing) I mean, I think about it in terms of a spectrum and this is what we hear from customers, is some customers want to shift as much responsibility onto the software teams to manage their infrastructure as well. And then some want to shift it all the way over to the very centralized model. And, you know, we see everything in between as well with our EKS customer base. But, yeah, I'm not sure if I have any direct guidance for people. >> Let's see, any wisdom? >> Aside from experiment. >> If you're coding more, you're a coder. If you like to play with the hardware, >> Yeah. >> or the gears. >> Look, I think it's really important for managers to understand that developers, yes, they have a job, you have to write code, right. But they also want to learn new things. It's only fair, right. >> Oh, yeah. >> So what we see is, developers want to learn. And we enable for them to understand Kubernetes in small pieces, like small steps, right. And that is really, really important because if we completely abstract things away, like Kubernetes, from them, it's not good for them, right. It's good for their careers also, right. It's good for them to learn these things. This is going to be with us for the next 15, 20 years. Everybody should learn it. But I want to learn it because I want to learn, not because this is part of my job, and that's the distinction, right. I don't want this to become my job because I want, I want to write my code. >> Do what you love. If you're more attracted to understanding how automation works, and robotics, or making things scale, you might be under-the-hood. >> Yeah. >> Yeah, look under the hood all day long. But then, in terms of, like, who keeps the lights on for the cluster, for example. >> All right, see- >> That's the job. >> He makes a lot of value. Now you know who you are. Ask these guys. (Lisa laughing) Congratulations on your success on EKS 2. >> Yeah, thank you. >> Quick, give a plug for the company. I know you guys are growing. I want to give you a minute to share to the audience a plug that's going to be, what are you guys doing? You're hiring? How many employees? Funding? Customer new wins? Take a minute to give a plug. >> Absolutely. And look, I come see, John, I think, every show you guys are doing a summit or a KubeCon, I'm here. (John laughing) And every time we come, we talk about new customers. Look, platform teams at enterprises seem to love Rafay because it helps them build that, well, Kubernetes platform that we've talked about on the show today. I think, many large enterprises on the financial service side, healthcare side, digital native side seem to have recognized that running Kubernetes at scale, or even starting with Kubernetes in the early days, getting it right with the right standards, that takes time, that takes effort. And that's where Rafay is a great partner. We provide a great SaaS offering, which you can have up and running very, very quickly. Of course, we love EKS. We work with our friends at AWS. But also works with Azure, we have enough customers in Azure. It also runs in Google. We have enough customers at Google. And it runs on-premises with OpenShift or with EKS A, right, whichever option you want to take. But in terms of that standardization and governance and automation for your developers to move fast, there's no better product in the market right now when it comes to Kubernetes platforms than Rafay. >> Kevin, while we're here, why don't you plug EKS too, come on. >> Yeah, absolutely, why not? (group laughing) So yes, of course. EKS is AWS's managed Kubernetes offering. It's the largest managed Kubernetes service in the world. We help customers who want to adopt Kubernetes and adopt it wherever they want to run Kubernetes, whether it's in region or whether it's on the edge with EKS A or running Kubernetes on Outposts and the evolving portfolio of EKS services as well. We see customers running extremely high-scale Kubernetes clusters, excuse me, and we're here to support them as well. So yeah, that's the managed Kubernetes offering. >> And I'll give the plug for theCUBE, we'll be at KubeCon in Detroit this year. (Lisa laughing) Lisa, look, we're giving a plug to everybody. Come on. >> We're plugging everybody. Well, as we get to plugs, I think, Haseeb, you have a book to write, I think, on Kubernetes. And I think you're wearing the title. >> Well, I do have a book to write, but I'm one of those people who does everything at the very end, so I will never get it right. (group laughing) So if you want to work on it with me, I have some great ideas. >> Ghostwriter. >> Sure! >> But I'm lazy. (Kevin chuckles) >> Ooh. >> So we got to figure something out. >> Somehow I doubt you're lazy. (group laughs) >> No entrepreneur's lazy, I know that. >> Right? >> You're being humble. >> He is. So Haseeb, Kevin, thank you so much for joining John and me today, >> Thank you. >> talking about what you guys are doing at Rafay with EKS, the power, why you shouldn't hate k8s. We appreciate your insights and your time. >> Thank you as well. >> Yeah, thank you very much for having us. >> Our pleasure. >> Thank you. >> We appreciate it. With John Furrier, I'm Lisa Martin. You're watching theCUBE live from New York City at the AWS NYC Summit. John and I will be right back with our next guest, so stick around. (upbeat music) (gentle music)

>>The cube presents, Dell technologies world brought to you by Dell. >>Hey everyone. Welcome back to the cubes coverage of day. One of Dell technologies world 2022. Live from the Venetian in Las Vegas. They're excited. I dunno if you heard that a group behind me, very excited to be here. Lisa Martin, Dave ante. We're very pleased to welcome Jules Johns SVP of channel from McQuin. Jill, welcome to the program. >>Thank you for having me. I appreciate it. >>And those people back there are very excited. If you heard that big applause >>That >>Went live <laugh> so the, the vibe here is fantastic for the first live Dell technologies world since 2019. A lot of people here, this expo hall is packed a lot of, of momentum here, but there's also a lot of momentum critics. Talk to us about what's going on. >>Well, and you know, so, so many exciting things for Equinex and, you know, in this partnership of Dell, it gives us a chance to, to share that, uh, with partners here throughout the conference. So we are very excited, as you said about, and we just, we named to the fortune 500 this year, 77 quarters of growth consecutively, but underpinning that is having made huge investments in what is the world's largest footprint of global data centers, 240 of them on six continent in 66 markets, but then interconnecting them. So they have the connections that Dell customers need to the clouds. They have the connections that they need to all of the future SaaS providers, so that foresight to put together that interconnection network across our footprint has set us on the path we're on today, which we're very grateful, um, to be at in. And, and really this, the things that are happening with Equinex and Dell together can, couldn't be more of the moment. >>Talk to me about that. The, the last two years, the moments of the last two years have been very challenging. They have for everyone. How has the partnership evolved in that time? >>Well, you know, we at together, Dell and Equinix, what we're doing is really helping, helping our shared interface, customers navigate the complexities of their digital transformation and, and digital transformation is hard and it's not a one and done, and it's not an overnight solution. And so what we are doing is partnering with Dell to think about putting a dedicated Dell it stack in an Equinex data center to give customers that sovereign adjacency so that they can have that security proximate to our, all the clouds and, and, and all, everything else. They need to participate in the ecosystem. And then pairing that with, you know, these interconnected enterprises. So Dell and we are helping customers then be able to have some of their solution on Preem some of their solution in the cloud access, public clouds, and use that collectively to diff fine. We're calling the intelligent edge together. And that intelligent edge means so many different things to customers, but it is really our honor to work together with Dell to help each customer define that for themselves. >>E's amazing company, like you said, it's, it's, you know, I didn't realize it was that many consecutive quarters, but it's a 60 billion plus market cap. If you look at the stock chart, blow your mind, really incredibly successful. And part of the reason it's funny, you know, 10, 15 years ago, people thought, well, oh, 10 years ago, anyway, the cloud is gonna hurt companies like equity. It was exact opposite it. And, and that's because, you know, Charles Phillips used to joke friends. Don't let friends build data centers. Yes. Right. And, and it's not a good use of capital for most companies, unless you're in the data center business. Now, of course you have some of your own as a service offerings. We do. What's the overlap with, with Dell? How do they compliment each other? It, >>It's a good question because, you know, and we get that, are you and Dell in fact competitors, and no, we see them as who complimentary. And in fact, we're working with Dell to bring to market things like something we call power edge, which involves their servers and power store, which involves their storage. And, and then V RIL, which is really the hyperconverged infrastructure. And those are just few first of a series of offerings we expect to bring to market with Dell. And if you think about metal and, and it's Equinex metal that people sometimes think is a competitor, but what metal does for customers is it really allows them to advance, have the equipment placed in our data centers so that they can access that capacity. And according to spikes or needs that they have that equipment in our data centers, that's there for them to avail themselves of that capacity is most often Dell equipment. So we are really doing and executing that bare metal is a service together. >>What are some of the, the things that you're hearing from, from your partner community, in terms of the partnership with Dell, what are partners supposed be excited, the momentum there what's going on in the partner community? >>So, you know, that is that's, that's what near and dear to my heart, since that's what I'm responsible for. Equinex is global partnerships, and they are very excited about what we're doing with Dell. And to be honest with you, all of our top partners are also top partners of Dell. So it makes that we bring it together. So, you know, big categories of partners like the world's largest global network service providers, some of whom are here and who will meet with the at T orange business services. Those folks, in addition to the world's largest global systems integrators, Kendra, Deloitte, Accenture, we pro, uh, all DXC. All of these are partners that Dell and we will meet with together to further our, what we call power three, that together we're better because as much as Dell and Equinex are delivering the customers, most often don't have the experience. They need to execute it without a partner. So they are relying on those partners to take what we are doing and make it their own. And so, so if they're excited about it, it is a, it's a big opportunity for them from a, a revenue services, a and an opportunity for them to step into a next level, trusted advisor status. So partners are excited and, and we're gonna be spending a lot of time with them the next few days. Do you >>See Equinix? You know, these cuz these partnerships are not bespoke partnerships, it's an ecosystem that's organic and evolving and, and growing. Can it be, are you a dot connector in a way, can it be a flywheel effect in your ecosystem? >>Well, I mean our, so our E ecosystems that, um, that we provide wide range of those from high frequency trading to connected cars, um, to the internet things, many and content providers that we are, we do see it as our role to, you know, the 10,000 and growing customers that are in our 240 data centers and six continents that provide those ecosystems. It's, it is our mission to continue to grow that and enrich it because that does differentiate us greatly from another data center provider. And it's the combination of the ecosystem that you find and the people you can connect to at Equinex, and then also the leverage of our fabric in order to be able to access your future needs. >>And it's a lot of technology underneath these, you know, it's that first layer one, I guess, if you will, of the data center, right. And so a lot of your, your customers or your cus your partner's customers, they just don't want to be in that business. As we were saying before, I mean, it's just too expensive. The, the power requirements are going through the roof, so you gotta be really good at managing power. >>You do. In fact, you know, so first of all, you're right, it's extremely difficult for them to also be able to make that kind of commitment, to keep a data center. They would ran, they would manage themselves at the level that Equinex is able to invest. So it's very difficult for people to do it themselves, but even show another, you mentioned actually about the power is near and dear to our hearts because is super committed to sustainability. And so we've made a commitment to holy renewable energy. And it's something that we talk a lot about how we also help partners like Dell meet their initiatives, so, or partners like at T meet their connected climate goals. So we, we are actually using that and coming together with Dell on that story, so that, and, and then helping to amplify that with our partners. And, >>And that's, that's how do you do that? That's putting data centers where you can cool with ambient air. Is it being near the Columbia river? How what's, what's your strategy in that regard, >>Uh, and sustainable. I have to be honest to you. I, uh, I would be out of my depth if I didn't say >>This is the high level. Yeah. >>So, um, we are deploying some of the latest technologies about that, and then experts people who, you know, who all they do is really help us to, um, to reduce the carbon footprint and be able to offset that, be able to use solar, be able to use wind, be able to take advantage of that. And then also to, um, to navigate what's available when you're in 240 locations on six cotton, it's not the same options to reduce your power consumption. And your burden are different in Africa, as you just discovered with our main one acquisition than they are in India, or then they are in, in other parts of the world. So it is for us a journey, and we've been assembling a lot of the talent to do that, but >>You're so large now, even a small percentage improvement can really move the needle. >>And I think because we are the largest, it is incumbent upon us to really set the standard and be committed to it. And, um, and we do see other people following, which is, is a good thing for all of us. Well, >>How important is that in your partnership conversations that partners have that same focus and commitment on ESG that Equinix has >>Partners care a lot about it, but, uh, customers ask us both all the time. I mean, we increasingly see a portion of an RFP or a scope of work asking before I decide to go with Equinex and Dell, tell me how you're going to impact the environment. Tell me about your commitment. And so, um, so we are committed to it, but customers are demanding it to >>Where >>Do you go ahead please? >>Oh, I was just gonna say, it's, it's coming from the, from the voice of a customer, which Equinox is listening to, we know Dell is listening to it as well. >>I'm so >>Sorry. One more time that, that the, the sustainability of the ESG demand is coming from the customers. You were saying, it, >>It both like, I mean, we wanna do the right thing and we've made commitments to it, but our customers are holding us accountable to it. And, you know, sustainability is now a board level priority. It is for us. And it is for companies like Dell and it is for partners and customers. >>It really is. It's it's, I mean, it's up there with security in terms of the board level conversation, where do you want to see the partner ecosystem in the, the, the next let's call it three to five years in your business? You can look out that far. >>Well, you know, I, I think that, um, they, our partners, um, and I, that, I mean, Dells and our mutual partners, you know, are, we've been listening to customers with Dell to deliver a flexible set of options for how customers would consume Equinex and Dell. So our partners are gonna be integrating a variety of those in order to meet the customer where they are in that journey, whether they wanna buy apex as a service, whether they wanna buy Equinex metal, whether they wanna have car some, uh, a partner put together, bespoke, do it yourself, combination with other services. Uh, I, I mean, the customers are going to demand a choice of options. I think partners are gonna embrace multiple versions of that so that they can, you know, to meet the customer where they are and take them >>Well, that's, that's incredibly important these days to meet customer where they are, the customers have a lot of choice. It is, but everything that we're all doing is for the customer, ultimately at the end of the day, <laugh> >>Yes, it, it, it, it is. And, and, you know, the customers are getting Savier, but we are all still early in this journey, as far as the edge, you know, I mean, I think we are all still, um, we're all still grappling at the, at for right now. We like to say that as customers are looking to define that the, the footprint that we offer together with Dell gives them an, an awfully robust set of choices for now. And then we wanna continue to invest and expand to be wherever they need us. >>Well, that's the thing about your business? It's it's optionality. I mean, you can't, I mean, the cloud has a lot of stuff, but you can't get everything you want in the cloud. You can, and you can put anything in your data center. That's, that's, you know, it, >>You can, but you may not know what you need yet. And so that's one of the things we spend a lot of time having our solutions, architects and our sales people together, but they'll talk about future proofing, their strategy. So future proofing, that combination of OnPrem and in an Equinex data center, and maybe some public and future proofing leveraging our fabric so that they might elect different SaaS space services or cloud based services a year to five years from now than the year, even thinking about today. And, and they may expand their edge over time, because they may, they may sort of see that as a, at the customer end point today, most businesses are still sort of using a footprint like ours as their edge, but that could change. And so we wanna be there when it does. >>Yeah. That's a great point because you don't wanna necessarily have to rip it out every cup of years. If you, if you, if you can have a, an architecture that can grow. Yeah, sure. You might want to upgrade it >>Well, and it's one, that's one of the most appealing things about services like metal, where they also, uh, they do sort of prevent that sort of rip and replace, but they also help people navigate the supply chain shortages that are going on right now. So this that's been, this has been a trying two years for supply chain shortages, and being able to take advantage of Dell equipment already staged at an Equinex data center and partners can then bring their customers a quicker immediate response. Have >>You also seen this? You mentioned the supply chain shortages, some of the many challenges that we've experienced in a last few years, how much of a factor has the great resignation been? The labor shortages, the cybersecurity skills gap on, on folks coming, Tolin saying help. We don't have the resources here to do this ourselves. >>We have been fortunate to, to not, to, to be, um, if you're asking about how the reservation has affected us as a company, no, >>Your customers >>Or customers that has oh, okay. Yes. So it is, it is a challenge for them, but it's an opportunity for our partners. So what I see there is it's been challenging for customers to hold onto that talent, but partners are filling that gap and we've access Aon fortunate to hold onto a lot of our best and brightest. And so we put them together with our partner and we try to help customers fill those gaps. >>Well, that's most important thing, filling those gaps. >>You, you ever been one in inside one of these ultra modern data centers? I have not, >>Not yet. >>It's pretty cool. Isn't it? I mean, >>Have you, have you ever had a tour of one? >>I I've never had a tour of an Equinix data center, but I've seen some modern data centers that will blow your mind. Well, >>I mean, they, they come with all the requisite, uh, bio and man traps and all of the bells and, and, and whistles that are actually the first slay of physical security. But then once you get into the data center, then we have sort, we get into the virtual and the digital security that you would expect. So it's, >>Yeah, it's good. And you know, it's not like you drive by the data center, it's a big sign. Here's the data center. It is kind of, you know, they're trying to stay a little hidden and then like, it's get in. It's like getting into fork knots. It's probably harder. And then, but then the it's, it's like this giant clean room, right? It's amazingly clean and just huge. >>There are all >>Your >>Mind. And inside this data centers, all the world's networks come together and peer, and then we have inside their, the, the most direct rom reps to the cloud. So you would expect there, there's a, there's a lot of wires and pipes running very neatly through a very secure, >>Clean systems and power system >>Environment. For sure. >>Amazing engineering. >>It is really >>A >>Tour. You should, you, if they do, you let people tour >>Your, I, I will bring both of you on a tour. Awesome. >>I, my guess >>Would love to. >>Yeah. Great. Sounds fantastic >>On that. So >>Last >>Couple, we'll bring a camera. <laugh> Oh, no, we're not allowed. Not today. >>No phones, no phones sequester. So what, what are some of the things that you're excited about seeing and hearing the next couple of days as this is the first time we've all gotten to be together in so long? >>So, um, well, you know, we are excited about the conversations that we're gonna have power of three that I was talking about. So, you know, we really pride ourselves on sort of having that combination add up to more, to benefit the customer. And so this will be sort of a coming out party of sorts for Equinex and Dell will meet with you almost 20 different global partners that are really important to both of us. So I am most excited about those conversations and about, uh, the education I'm gonna get on the ways they're thinking about integrating it differently, because that is good choice for the market. That is good choice for the customer set. So for the enterprises out there, so that I'm most excited about. Awesome. >>Sounds like tremendous opportunity, lots going on this week, but thank you for coming on, just talking An hour of Equinix and Dell better together, the way that your channel partner program is growing. And of course the momentum of the company will can't wait to see what happens next year. Thank >>You. Thank you. Well, we aim to deliver and thank you again for having us. Thanks, >>Jules. Our pleasure for Dave Volante. I'm Lisa Martin, and you're watching the cubes live coverage day one, Dell technologies world live from Las Vegas, stick around. We'll be right back with our next guest.

>>Hi everyone. Welcome to the cubes coverage of eight of his public sector summit live in Washington D. C, where it's a face to face real event. I'm johN for a year host but virtual events. Hybrid events were hybrid event as well. We've got a great remote interview. Got a guest here in person, Jon Stankovic, president of cloud solutions. Smartronix and Britain was the VP of eight of his managed services, also known as A M. S with amazon web services, jOHN and jOHN and three johns here. Welcome to the cube remote >>in person. >>Hybrid. >>Thanks. Thank you. Great to be on the cube longtime viewer and I really appreciate what you >>do for fun to be here remotely but I feel like it right there. >>Yeah, I love the hybrid if it's only gonna get better next time will be in the metaverse soon. But uh, jOHn on the line there, I want to ask you with AWS managed services, take us through what you guys are doing with Smart Trust because this is an interesting service you guys are working together. How's that relates at the table for us. >>Yeah, well, you know, we're really excited about this announcement, We've been working with Smartronix since we launched A. M S 4.5 years ago. So we've been able to build up working with them, you know, a huge library of automation capabilities and this really just formalised as that in an offer for our joint customers where we can bring the expertise from AWS and Smartronix and offer a full solution that's highly integrated to help help our customers jointly accelerate their cloud adoption as well as their operating model transformation as they start to move to a more devops motion and they need help. We're there together to provide our expertise and make that simple for them. >>Well I appreciate the call. You john b john s over here. Js john Stankevich. Um tell me about Smart trust because you heard what's going on with devoPS to point a whole revolutions going on in devops, you're starting to see a highly accelerated modern application development environment which means that the software developers are setting the pace there, the pace car of the innovation, right? And so other teams like security or I. T. Become blockers. Blockers a drag and anchor. So the shift left on security for instance is causing a lot of problems on the security team. So all this is going on like right now so still the speed is the game. What's your take? >>Sure so absolutely. I think that's where this partnership really really excels. You know, we want customers to focus on their mission, you know, national security, health care outcomes. Um we want them to kind of take the rest off their plate. So when you say some of the quote unquote blockers around security uh Smartronix has invested heavily in a federally authorized platform that sits on top of what a WS has done from a Fed ramp and so right off the bat speed agility. We don't want our customers spending time replicating things that we've done at scale and leveraging what AWS has and so by kind of utilizing this, this joint offer all of a sudden a big part of that compliance is taken care of. Uh, and then things like devoPS, things like SRE models that you hear a lot about, we fold all that into this uh, combined service offering. >>I know a little about what you guys are doing. You mentioned SRE is very cool, but let's take a minute to explain what you guys are doing because you guys are on the cutting edge of solving a lot of problems from infrastructure fools around the deVOPS stack. What are you guys doing in the cloud services? >>Sure. So I think jOHN hit a little bit on it. But you know, we look at AMS as best in breed at scale managing core parts of the U. S. Infrastructure. What Smartronix does is many times customers have some unique requirements and we take that core kind of powered by aims and we try and fill in those kind of complementary skill sets and complementary requirements. And so something like the devops, which is basically making sure that those people developing that software, they have also the ability to manage it and on an ongoing basis. Kind of run it. We develop all the frameworks and that's part of this offering to enable that. >>What's the solution jOHN B because I think you guys don't, this is people have challenges. I want to understand those challenges. And then when they go to the external managed service, what's involved, you walk us through that? Because I think that's important. >>Yeah, sure. You know, it turns out jOHN nailed this one. That moving to the cloud can be, can be a big transformation for many, many enterprises and government teams. Right. They worked for many years and have an ecosystem in their traditional data center. But when they move to the cloud, there's a lot of moving pieces and so what we like to focus on is helping them with the undifferentiated aspects of safely and automating cloud operations. So working with, with Smartronix allows us to take what we're doing across the infrastructure services, around security, around automation, around patching instance management, container management, all of those uh, undifferentiated, heavy lifting passed by now with Smartronix and expertise across the application layer across customers, unique environments across federal and moderate the various government standards and compliance is, and we think we're able to get, take a customer um, from kind of really early stage cloud experience and rapidly deploy configure and get them into a very stable scalable posture operationally on the cloud so that they can start to invest in their people, their skills and their differentiated application on the cloud that really drive the differentiation in their business and not have to worry about best practice configurations and operational run books and, and and automation is and and and the latest dep sec ops capabilities that will pick up for them while they're training and getting, they're getting their emotions in place, >>jOHn is on the Smartronix side. Talk about the difference between scale okay. Which is a big issue with cloud these customers want to have with AMS but then you also have some scale, maybe some scale to but highly compliant environments, regulated industries, for instance, this is the hot areas because scale is unwieldy, but if you don't want get rain it in, it can be chaotic. Right? So also regulations and compliance is a huge issue. >>Yeah. What what we found is um, at times customers look at it and they just get frustrated because it can be kind of intimidating and we as a combined team really have spent a lot of time we have accelerators to walk customers through that process and a really flexible model. If they feel that they have a lot of domain expertise in it, then we'll just kind of be almost a supporter other customers look at it and say, you know, we'd like you to take the entire patch of that compliance and so highly regulated environments. Both commercial D. O. D. National Security, um federal civilian agencies, state and local, they're all looking to this and saying we really want someone that's been through things like the U. S. Audited managed service provider, things like they're managed security service provider, things like fed ramp or D. O. D. Ill four and five. And I think to be honest Smartronix has just invested heavily in that with the goal of reducing all that complexity and it's it's really been taken off and we really appreciate the partnership specifically with jOHn and uh the A. W. S. A. M. S. Team. >>All right so you guys were going together, what's the ultimate benefit to the customer? >>I can I'll give my thing right off the bat all this innovation coming out of A. W. S. Um It's fantastic but only if you have the ability to take advantage of it. And so thousands of new services being rolled out. We really want customers to be able to take advantage of that and let at times us do what we do best and let them focus on their mission. And I think that's what really AWS is all about and we just feel very fortunate to be an enabler of that >>john be talking about talking about the staffing issues too because one of the problems that we have been reporting and this has come up at every reinvest on the max. Peterson about this as well. He's promised last year was gonna train 29 million people. See how that comes out of reinvent when the report card comes back. I was kinda busting his chops a little bit there but he had a smile on his face I think is gonna hit the numbers a lot of times, Maybe people don't have an SRE they don't have a devout person or they have some staff that they're in transition or transforming this is a huge factor. What's your take on this, >>you know, that that is so important, you know, as john mentioned, it's all about helping the customers focused and and their their cloud talent is scarce and it's a scarce resource and you you want to make sure that your cloud talent is working on the cool stuff or they're going to leave and and as you train and skill, these folks, they want to focus on what really impacts the business, what's really differentiating doing, you know, doing the cloud and the necessities on operations and operational tasks and sec ops and things like that, sometimes, that's not the sexiest part of the work that the customer really wants to focus their team on. So again, I think together we're able to help drive high levels of automation and really do that day in and day out work that is not necessarily the differentiator of their business and that's going to attract and keep the best and brightest minds in these in these customers um which allows us to help them with the undifferentiated aspects of of the heavy lifting. >>Not only is availability of people, it's keeping the people, I love that great call out there, Okay, where does this go? Where's the relationship. So you guys are partnering, you have the M. S. Is going on? Strong managed services not gonna go away mormon people were using managed services. It's part of the ecosystem within the ecosystem. What's next in the relationship? >>Well, I think, you know, I'll speak first, john, I'm sure you've got some thoughts to, but you know, we've got so many things on our plate around predictive operations and the predictive capabilities that we're excited about tackling together. Obviously there's all sorts of unique applications that require even deeper capabilities and working with Smartronix to help us, you know, provide even greater insight into the application layer. So I kind of see us expanding um both horizontally as well as well as vertically and horizontally. We've got customers looking at the edge with the outpost solutions and we can snap into those capabilities as well. So there's a tremendous amount of kind of, I'd say vertical and horizontal opportunity that we can continue to expand it together, >>john your reaction, That's >>pretty right on Absolutely. I think john Berger really hit it and I think really machine learning, you know, that's a big area of focus, if you look at all this data is being collected, predictive modeling and so we have this kind of transition from a model where people were basically watching screens reacting and what the AWS MSP offer and what you know, AmS offers is really predicting, so you you're not doing that, you're not reacting, you're proactively ahead of things. And that's the honest truth is AWS is such a well run service. It just doesn't break, you know, it doesn't break like what you see in the traditional kind of legacy infrastructure. And so at times we're just continuing to climb that stack. As, as john mentioned, >>it's really interesting as you guys are, as you're talking, I'm thinking myself just go back a couple of years ago, eight years ago or so. DevoPS is a bad word. Dev's dominate up. So I was through them now, operational leverage is a huge part of this ai operations, um, the entire I. T service management being disrupted heavily by cloud operations that also facilitate rapid development models. Right? So, again, this is like under reported, but it's a really nuanced point hardened operations for security and not holding back the developers is the cloud scale. What's your guys reaction to that? >>Yeah, I completely agree. I think, you know, the automation piece of things and I think customers are still going through transitions. You know, traditionally managed services means a big staff and it's like I said, sitting there watching screens and you flip that model where you have developers actually deploying code and infrastructure to support it. It's, you know, it's very transitional and very transformative and I think that's where an offering, like what we've really partnered on really, really helps because at times it can be overwhelming for customers and we just want to simplify that. And as I've said, let them focus on their mission. >>Amen one last question before we break, because I was talking to another partner, a big part of AWS. Um, and we're talking about SAS versus solutions and sometimes if you're too Sassy, you're not really building a custom solution, but you can have the best of both worlds. A little professional services, maybe some headroom on the stack, if you will your building solutions. So the next question is, as you guys put this cutting edge innovative innovative solution together, how are your customers consuming it? Like what's the consumption? I'm assuming there must be happy because a lot of heavy lifting being taken away, they don't have to deal with house the contract process. >>Well, you know, I think, you know, we have the opportunity, we support customers and kind of all modes of their application stack. So, you know, a full stacks solution. You know, even a legacy architecture moving to the cloud requires a high degree of automation to support it. And then as those applications become modernized over time, they become much more cloud native at some point, they might even become a full stack Starzz offer. So many of our customers actually run their SAAS platform leveraging our capability as well. So, you know, I think it gives the customer a lot of optionality uh, and future kind of growth as they modernize their application stack. >>Yeah, john your reaction. Absolutely. >>I think one of the greatest benefits is it's freeing up funds to do mission work. And so instead of spending time procuring hardware and managing it and leasing data center space, they literally have more funding. And so we've seen customers literally transform their business because this piece of it's done more efficiently and they have really excess and really additional funding to do their mission. >>We love the business model innovation, faster um, higher quality, easy and inexpensive. That's the flywheel gentlemen, Thank you for coming on and get the three. John john thank you. Vice President Cloud Solutions. That Smartronix, thank you for coming on. John Barrington BP of amazon websites managed. There is a also known as AWS and A M. S. A W. S got upside down. W. M. Looks the same. Thank you guys for coming. I appreciate it. Thank you. We appreciate great great Cube covers here. eight of us summit we're live on the ground and were remote. It's a hybrid event. I'm John for your host. Thanks for watching. Mhm

>>Mhm Hello and welcome to the cubes coverage of AWS amazon web services, Global public Sector partner awards program. I'm john for your host of the cube here we're gonna talk about the best covid solution to great guests. Benham or with healthcare and life sciences lead at palantir Ben welcome to the cube SAm Michaels, Director of automation and compound management and Cats. National Center for advancing translational sciences and Cats. Part of the NIH National sort of health Gentlemen, thank you for coming on and and congratulations on the best covid solution. >>Thank you so much john >>so I gotta, I gotta ask you the best solution is when can I get the vaccine? How fast how long it's gonna last but I really appreciate you guys coming on. I >>hope you're vaccinated. I would say john that's outside of our hands. I would say if you've not got vaccinated, go get vaccinated right now, have someone stab you in the arm, you know, do not wait and and go for it. That's not on us. But you got that >>opportunity that we have that done. I got to get on a plane and all kinds of hoops to jump through. We need a better solution anyway. You guys have a great technical so I wanna I wanna dig in all seriousness aside getting inside. Um you guys have put together a killer solution that really requires a lot of data can let's step back and and talk about first. What was the solution that won the award? You guys have a quick second set the table for what we're talking about. Then we'll start with you. >>So the national covered cohort collaborative is a secure data enclave putting together the HR records from more than 60 different academic medical centers across the country and they're making it available to researchers to, you know, ask many and varied questions to try and understand this disease better. >>See and take us through the challenges here. What was going on? What was the hard problem? I'll see everyone had a situation with Covid where people broke through and cloud as he drove it amazon is part of the awards, but you guys are solving something. What was the problem statement that you guys are going after? What happened? >>I I think the problem statement is essentially that, you know, the nation has the electronic health records, but it's very fragmented, right. You know, it's been is highlighted is there's there's multiple systems around the country, you know, thousands of folks that have E H. R. S. But there is no way from a research perspective to actually have access in any unified location. And so really what we were looking for is how can we essentially provide a centralized location to study electronic health records. But in a Federated sense because we recognize that the data exist in other locations and so we had to figure out for a vast quantity of data, how can we get data from those 60 sites, 60 plus that Ben is referencing from their respective locations and then into one central repository, but also in a common format. Because that's another huge aspect of the technical challenge was there's multiple formats for electronic health records, there's different standards, there's different versions. And how do you actually have all of this data harmonised into something which is usable again for research? >>Just so many things that are jumping in my head right now, I want to unpack one at the time Covid hit the scramble and the imperative for getting answers quickly was huge. So it's a data problem at a massive scale public health impact. Again, we were talking before we came on camera, public health records are dirty, they're not clean. A lot of things are weird. I mean, just just massive amount of weird problems. How did you guys pull together take me through how this gets done? What what happened? Take us through the the steps He just got together and said, let's do this. How does it all happen? >>Yeah, it's a great and so john, I would say so. Part of this started actually several years ago. I explain this when people talk about in three C is that and Cats has actually established what we like to call, We support a program which is called the Clinical translation Science Award program is the largest single grant program in all of NIH. And it constitutes the bulk of the Cats budget. So this is extra metal grants which goes all over the country. And we wanted this group to essentially have a common research environment. So we try to create what we call the secure scientific collaborative platforms. Another example of this is when we call the rare disease clinical research network, which again is a consortium of 20 different sites around the nation. And so really we started working this several years ago that if we want to Build an environment that's collaborative for researchers around the country around the world, the natural place to do that is really with a cloud first strategy and we recognize this as and cats were about 600 people now. But if you look at the size of our actual research community with our grantees were in the thousands. And so from the perspective that we took several years ago was we have to really take a step back. And if we want to have a comprehensive and cohesive package or solution to treat this is really a mid sized business, you know, and so that means we have to treat this as a cloud based enterprise. And so in cats several years ago had really gone on this strategy to bring in different commercial partners, of which one of them is Palin tear. It actually started with our intramural research program and obviously very heavy cloud use with AWS. We use your we use google workspace, essentially use different cloud tools to enable our collaborative researchers. The next step is we also had a project. If we want to have an environment, we have to have access. And this is something that we took early steps on years prior that there is no good building environment if people can't get in the front door. So we invested heavily and create an application which we call our Federated authentication system. We call it unified and cats off. So we call it, you know, for short and and this is the open source in house project that we built it and cats. And we wanted to actually use this for all sorts of implementation, acting as the front door to this collaborative environment being one of them. And then also by by really this this this interest in electronic health records that had existed prior to the Covid pandemic. And so we've done some prior work via mixture of internal investments in grants with collaborative partners to really look at what it would take to harmonize this data at scale. And so like you mentioned, Covid hit it. Hit really hard. Everyone was scrambling for answers. And I think we had a bit of these pieces um, in play. And then that's I think when we turned to ban and the team at volunteer and we said we have these components, we have these pieces what we really need. Something independent that we can stand up quickly to really address some of these problems. One of the biggest one being that data ingestion and the harmonization step. And so I can let Ben really speak to that one. >>Yeah. Ben Library because you're solving a lot of collaboration problems, not just the technical problem but ingestion and harmonization ingestion. Most people can understand is that the data warehousing or in the database know that what that means? Take us through harmonization because not to put a little bit of shade on this, but most people think about, you know, these kinds of research or non profits as a slow moving, you know, standing stuff up sandwich saying it takes time you break it down. By the time you you didn't think things are over. This was agile. So take us through what made it an agile because that's not normal. I mean that's not what you see normally. It's like, hey we'll see you next year. We stand that up. Yeah. At the data center. >>Yeah, I mean so as as Sam described this sort of the question of data on interoperability is a really essential problem for working with this kind of data. And I think, you know, we have data coming from more than 60 different sites and one of the reasons were able to move quickly was because rather than saying oh well you have to provide the data in a certain format, a certain standard. Um and three C. was able to say actually just give us the data how you have it in whatever format is easiest for you and we will take care of that process of actually transforming it into a single standard data model, converting all of the medical vocabularies, doing all of the data quality assessment that's needed to ensure that data is actually ready for research and that was very much a collaborative endeavor. It was run out of a team based at johns Hopkins University, but in collaboration with a broad range of researchers who are all adding their expertise and what we were able to do was to provide the sort of the technical infrastructure for taking the transformation pipelines that are being developed, that the actual logic and the code and developing these very robust kind of centralist templates for that. Um, that could be deployed just like software is deployed, have changed management, have upgrades and downgrades and version control and change logs so that we can roll that out across a large number of sites in a very robust way very quickly. So that's sort of that, that that's one aspect of it. And then there was a bunch of really interesting challenges along the way that again, a very broad collaborative team of researchers worked on and an example of that would be unit harmonization and inference. So really simple things like when a lab result arrives, we talked about data quality, um, you were expected to have a unit right? Like if you're reporting somebody's weight, you probably want to know if it's in kilograms or pounds, but we found that a very significant proportion of the time the unit was actually missing in the HR record. And so unless you can actually get that back, that becomes useless. And so an approach was developed because we had data across 60 or more different sites, you have a large number of lab tests that do have the correct units and you can look at the data distributions and decide how likely is it that this missing unit is actually kilograms or pounds and save a huge portion of these labs. So that's just an example of something that has enabled research to happen that would not otherwise have been able >>just not to dig in and rat hole on that one point. But what time saving do you think that saves? I mean, I can imagine it's on the data cleaning side. That's just a massive time savings just in for Okay. Based on the data sampling, this is kilograms or pounds. >>Exactly. So we're talking there's more than 3.5 billion lab records in this data base now. So if you were trying to do this manually, I mean, it would take, it would take to thousands of years, you know, it just wouldn't be a black, it would >>be a black hole in the dataset, essentially because there's no way it would get done. Ok. Ok. Sam take me through like from a research standpoint, this normalization, harmonization the process. What does that enable for the, for the research and who decides what's the standard format? So, because again, I'm just in my mind thinking how hard this is. And then what was the, what was decided? Was it just on the base records what standards were happening? What's the impact of researchers >>now? It's a great quite well, a couple things I'll say. And Ben has touched on this is the other real core piece of N three C is the community, right? You know, And so I think there's a couple of things you mentioned with this, johN is the way we execute this is, it was very nimble, it was very agile and there's something to be said on that piece from a procurement perspective, the government had many covid authorities that were granted to make very fast decisions to get things procured quickly. And we were able to turn this around with our acquisition shop, which we would otherwise, you know, be dead in the water like you said, wait a year ago through a normal acquisition process, which can take time, but that's only one half the other half. And really, you're touching on this and Ben is touching on this is when he mentions the research as we have this entire courts entire, you know, research community numbering in the thousands from a volunteer perspective. I think it's really fascinating. This is a really a great example to me of this public private partnership between the companies we use, but also the academic participants that are actually make up the community. Um again, who the amount of time they have dedicated on this is just incredible. So, so really, what's also been established with this is core governance. And so, you know, you think from assistance perspective is, you know, the Palin tear this environment, the N three C environment belongs to the government, but the N 33 the entire actually, you know, program, I would say, belongs to the community. We have co governance on this. So who decides really is just a mixture between the folks on End Cats, but not just end cast as folks at End Cats, folks that, you know, and I proper, but also folks and other government agencies, but also the, the academic communities and entire these mixed governance teams that actually set the stage for all of this. And again, you know, who's gonna decide the standard, We decide we're gonna do this in Oman 5.3 point one um is the standard we're going to utilize. And then once the data is there, this is what gets exciting is then they have the different domain teams where they can ask different research questions depending upon what has interest scientifically to them. Um and so really, you know, we viewed this from the government's perspective is how do we build again the secure platform where we can enable the research, but we don't really want to dictate the research. I mean, the one criteria we did put your research has to be covid focused because very clearly in response to covid, so you have to have a Covid focus and then we have data use agreements, data use request. You know, we have entire governance committees that decide is this research in scope, but we don't want to dictate the research types that the domain teams are bringing to the table. >>And I think the National Institutes of Health, you think about just that their mission is to serve the public health. And I think this is a great example of when you enable data to be surfaced and available that you can really allow people to be empowered and not to use the cliche citizen analysts. But in a way this is what the community is doing. You're doing research and allowing people from volunteers to academics to students to just be part of it. That is citizen analysis that you got citizen journalism. You've got citizen and uh, research, you've got a lot of democratization happening here. Is that part of it was a result of >>this? Uh, it's both. It's a great question. I think it's both. And it's it's really by design because again, we want to enable and there's a couple of things that I really, you know, we we clamor with at end cats. I think NIH is going with this direction to is we believe firmly in open science, we believe firmly in open standards and how we can actually enable these standards to promote this open science because it's actually nontrivial. We've had, you know, the citizen scientists actually on the tricky problem from a governance perspective or we have the case where we actually had to have students that wanted access to the environment. Well, we actually had to have someone because, you know, they have to have an institution that they come in with, but we've actually across some of those bridges to actually get students and researchers into this environment very much by design, but also the spirit which was held enabled by the community, which, again, so I think they go they go hand in hand. I planned for >>open science as a huge wave, I'm a big fan, I think that's got a lot of headroom because open source, what that's done to software, the software industry, it's amazing. And I think your Federated idea comes in here and Ben if you guys can just talk through the Federated, because I think that might enable and remove some of the structural blockers that might be out there in terms of, oh, you gotta be affiliate with this or that our friends got to invite you, but then you got privacy access and this Federated ID not an easy thing, it's easy to say. But how do you tie that together? Because you want to enable frictionless ability to come in and contribute same time you want to have some policies around who's in and who's not. >>Yes, totally, I mean so Sam sort of already described the the UNa system which is the authentication system that encounters has developed. And obviously you know from our perspective, you know we integrate with that is using all of the standard kind of authentication protocols and it's very easy to integrate that into the family platform um and make it so that we can authenticate people correctly. But then if you go beyond authentication you also then to actually you need to have the access controls in place to say yes I know who this person is, but now what should they actually be able to see? Um And I think one of the really great things in Free C has done is to be very rigorous about that. They have their governance rules that says you should be using the data for a certain purpose. You must go through a procedure so that the access committee approves that purpose. And then we need to make sure that you're actually doing the work that you said you were going to. And so before you can get your data back out of the system where your results out, you actually have to prove that those results are in line with the original stated purpose and the infrastructure around that and having the access controls and the governance processes, all working together in a seamless way so that it doesn't, as you say, increase the friction on the researcher and they can get access to the data for that appropriate purpose. That was a big component of what we've been building out with them three C. Absolutely. >>And really in line john with what NIH is doing with the research, all service, they call this raz. And I think things that we believe in their standards that were starting to follow and work with them closely. Multifactor authentication because of the point Ben is making and you raised as well, you know, one you need to authenticate, okay. This you are who you say you are. And and we're recognizing that and you're, you know, the author and peace within the authors. E what do you authorized to see? What do you have authorization to? And they go hand in hand and again, non trivial problems. And especially, you know, when we basis typically a lot of what we're using is is we'll do direct integrations with our package. We using commons for Federated access were also even using login dot gov. Um, you know, again because we need to make sure that people had a means, you know, and login dot gov is essentially a runoff right? If they don't have, you know an organization which we have in common or a Federated access to generate a login dot gov account but they still are whole, you know beholden to the multi factor authentication step and then they still have to get the same authorizations because we really do believe access to these environment seamlessly is absolutely critical, you know, who are users are but again not make it restrictive and not make it this this friction filled process. That's very that's very >>different. I mean you think about nontrivial, totally agree with you and if you think about like if you were in a classic enterprise, I thought about an I. T. Problem like bring your own device to work and that's basically what the whole world does these days. So like you're thinking about access, you don't know who's coming in, you don't know where they're coming in from, um when the churn is so high, you don't know, I mean all this is happening, right? So you have to be prepared two Provisions and provide resource to a very lightweight access edge. >>That's right. And that's why it gets back to what we mentioned is we were taking a step back and thinking about this problem, you know, an M three C became the use case was this is an enterprise I. T. Problem. Right. You know, we have users from around the world that want to access this environment and again we try to hit a really difficult mark, which is secure but collaborative, Right? That's that's not easy, you know? But but again, the only place this environment could take place isn't a cloud based environment, right? Let's be real. You know, 10 years ago. Forget it. You know, Again, maybe it would have been difficult, but now it's just incredible how much they advanced that these real virtual research organizations can start to exist and they become the real partnerships. >>Well, I want to Well, that's a great point. I want to highlight and call out because I've done a lot of these interviews with awards programs over the years and certainly in public sector and open source over many, many years. One of the things open source allows us the code re use and also when you start getting in these situations where, okay, you have a crisis covid other things happen, nonprofits go, that's the same thing. They, they lose their funding and all the code disappears. Saying with these covid when it becomes over, you don't want to lose the momentum. So this whole idea of re use this platform is aged deplatforming of and re factoring if you will, these are two concepts with a cloud enables SAM, I'd love to get your thoughts on this because it doesn't go away when Covid's >>over, research still >>continues. So this whole idea of re platform NG and then re factoring is very much a new concept versus the old days of okay, projects over, move on to the next one. >>No, you're absolutely right. And I think what first drove us is we're taking a step back and and cats, you know, how do we ensure that sustainability? Right, Because my background is actually engineering. So I think about, you know, you want to build things to last and what you just described, johN is that, you know, that, that funding, it peaks, it goes up and then it wanes away and it goes and what you're left with essentially is nothing, you know, it's okay you did this investment in a body of work and it goes away. And really, I think what we're really building are these sustainable platforms that we will actually grow and evolve based upon the research needs over time. And I think that was really a huge investment that both, you know, again and and Cats is made. But NIH is going in a very similar direction. There's a substantial investment, um, you know, made in these, these these these really impressive environments. How do we make sure the sustainable for the long term? You know, again, we just went through this with Covid, but what's gonna come next? You know, one of the research questions that we need to answer, but also open source is an incredibly important piece of this. I think Ben can speak this in a second, all the harmonization work, all that effort, you know, essentially this massive, complex GTL process Is in the N three Seagate hub. So we believe, you know, completely and the open source model a little bit of a flavor on it too though, because, you know, again, back to the sustainability, john, I believe, you know, there's a room for this, this marriage between commercial platforms and open source software and we need both. You know, as we're strong proponents of N cats are both, but especially with sustainability, especially I think Enterprise I. T. You know, you have to have professional grade products that was part of, I would say an experiment we ran out and cast our thought was we can fund academic groups and we can have them do open source projects and you'll get some decent results. But I think the nature of it and the nature of these environments become so complex. The experiment we're taking is we're going to provide commercial grade tools For the academic community and the researchers and let them use them and see how they can be enabled and actually focus on research questions. And I think, you know, N3C, which we've been very successful with that model while still really adhering to the open source spirit and >>principles as an amazing story, congratulated, you know what? That's so awesome because that's the future. And I think you're onto something huge. Great point, Ben, you want to chime in on this whole sustainability because the public private partnership idea is the now the new model innovation formula is about open and collaborative. What's your thoughts? >>Absolutely. And I mean, we uh, volunteer have been huge proponents of reproducibility and openness, um in analyses and in science. And so everything done within the family platform is done in open source languages like python and R. And sequel, um and is exposed via open A. P. I. S and through get repository. So that as SaM says, we've we've pushed all of that E. T. L. Code that was developed within the platform out to the cats get hub. Um and the analysis code itself being written in those various different languages can also sort of easily be pulled out um and made available for other researchers in the future. And I think what we've also seen is that within the data enclave there's been an enormous amount of re use across the different research projects. And so actually having that security in place and making it secure so that people can actually start to share with each other securely as well. And and and be very clear that although I'm sharing this, it's still within the range of the government's requirements has meant that the, the research has really been accelerated because people have been able to build and stand on the shoulders of what earlier projects have done. >>Okay. Ben. Great stuff. 1000 researchers. Open source code and get a job. Where do I sign up? I want to get involved. This is amazing. Like it sounds like a great party. >>We'll send you a link if you do a search on on N three C, you know, do do a search on that and you'll actually will come up with a website hosted by the academic side and I'll show you all the information of how you can actually connect and john you're welcome to come in. Billion by all means >>billions of rows of data being solved. Great tech he's working on again. This is a great example of large scale the modern era of solving problems is here. It's out in the open, Open Science. Sam. Congratulations on your great success. Ben Award winners. You guys doing a great job. Great story. Thanks for sharing here with us in the queue. Appreciate it. >>Thank you, john. >>Thanks for having us. >>Okay. It is. Global public sector partner rewards best Covid solution palantir and and cats. Great solution. Great story. I'm john Kerry with the cube. Thanks for watching. Mm mm. >>Mhm

>>Hello, and welcome. Very excited to see everybody here. DockerCon is going fantastic. Everybody's uh, engaging in the chat. It's awesome to see. My name is Peter McKee. I'm the head of developer relations here at Docker and Taber. Today. We're going to be talking about container first development now and in the future. But before we do that, a couple little housekeeping items, first of all, yes, we are live. So if you're in our session, you can go ahead and chat, ask us questions. We'd love to get all your questions and answer them. Um, if you come to the main page on the website and you do not see the chat, go ahead and click on the blue button and that'll die. Uh, deep dive you into our session and you can interact with the chat there. Okay. Without further ado, let's just jump right into it. Katie, how are you? Welcome. Do you mind telling everybody who you are and a little bit about yourself? >>Absolutely. Hello everyone. My name is Katie and currently I am the eco-system advocate at cloud native computing foundation or CNCF. My responsibility is to lead and represent the end-user community. So these are all the practitioners within the cloud native space that are vendor neutral. So they use cloud native technologies to build their services, but they don't sell it. So this is quite an important characteristic as well. My responsibility is to make sure to close the gap between these practitioners and the project maintainers, to make sure that there is a feedback loop around. Um, I have many roles within the community. I am on the advisory board for KIPP finishes, a sandbox project. I'm working with open UK to make sure that Elton standards are used fairly across data, hardware, and software. And I have been, uh, affiliated way if you'd asked me to make sure that, um, I'm distributing a cloud native fundamental scores to make cloud and they do a few bigger despite everyone. So looking forward to this panel and checking with everyone. >>Awesome. Yeah. Welcome. Glad to have you here. Johanna's how are you? Can you, uh, tell everybody a little bit about yourself and who you are? Yeah, sure. >>So hi everybody. My name is Johannes I'm one of the co-founders at get pot, which in case you don't know is an open-source and container based development platform, which is probably also the reason why you Peter reached out and invited me here. So pleasure to be here, looking forward to the discussion. Um, yeah, though it is already a bit later in Munich. Um, and actually my girlfriend had a remote cocktail class with her colleagues tonight and it took me some stamina to really say no to all the Moscow mules that were prepared just over there in my living room. Oh wow. >>You're way better than me. Yeah. Well welcome. Thanks for joining us. Jerome. How are you? Good to see you. Can you tell everybody who you are and a little bit about yourself? Hi, >>Sure. Yeah, so I'm, I, I used to work at Docker and some, for me would say I'm a container hipster because I was running containers in production before it for hype. Um, I worked at Docker before it was even called Docker. And then since 2018, I'm now a freelancer and doing training and consulting around Docker containers, Kubernetes, all these things. So I used to help folks do stuff with Docker when I was there and now I still have them with containers more generally speaking. So kind of, uh, how do we say same, same team, different company or something like that? Yeah. >>Yeah. Perfect. Yeah. Good to see you. I'm glad you're on. Uh, Jacob, how are you? Good to see you. Thanks for joining us. Good. Yeah. Thanks for having me tell, tell everybody a little bit about yourself who you are. >>Yeah. So, uh, I'm the creator of a tool called mutagen, which is an open source, uh, development tool for doing high performance file synchronization and, uh, network forwarding, uh, to enable remote development. And so I come from like a physics background where I was sort of always doing, uh, remote developments, you know, whether that was on a big central clusters or just like some sort of local machine that was a bit more powerful. And so I, after I graduated, I built this tool called mutagen, uh, for doing remote development. And then to my surprise, people just started using it to use, uh, with Docker containers. And, uh, that's kind of grown into its primary use case now. So I'm, yeah, I've gotten really involved with the Docker community and, uh, talked with a lot of great people and now I'm one of the Docker captains. So I get to talk with even more and, and join these events and yeah, but I'm, I'm kind of focused on doing remote development. Uh, cause I, you know, I like, I like having all my tools available on my local machine, but I also like being able to pull in a little bit more powerful hardware or uh, you know, maybe a software that I can't run locally. And so, uh, that's sort of my interest in, in Docker container. Yeah. Awesome. >>Awesome. We're going to come back to that for sure. But yeah. Thank you again. I really appreciate you all joining me and yeah. So, um, I've been thinking about container first development for a while and you know, what does that actually mean? So maybe, maybe we can define it in our own little way. So I, I just throw it out to the panel. When you think about container first development, what comes to mind? What w what, what are you kind of thinking about? Don't be shy. Go ahead. Jerome. You're never a loss of words >>To me. Like if I go back to the, kind of the first, uh, you know, training engagements we did back at Docker and kind of helping folks, uh, writing Dockerfiles to stop developing in containers. Um, often we were replacing, um, uh, set up with a bunch of Vagrant boxes and another, like the VMs and combinations of local things. And very often they liked it a lot and they were very soon, they wanted to really like develop in containers, like run this microservice. This piece of code is whatever, like run that in containers because that means they didn't have to maintain that thing on their own machine. So that's like five years ago. That's what it meant to me back then. However, today, if you, if you say, okay, you know, developing in containers, um, I'm thinking of course about things like get bought and, uh, I think it's called PR or something like that. >>Like this theme, maybe that thing with the ESCO, that's going to run in a container. And you, you have this vs code thing running in your browser. Well, obviously not in your browser, but in a container that you control from your browser and, and many other things like that, that I, I think that's what we, where we want to go today. Uh, and that's really interesting, um, from all kinds of perspectives, like Chevy pair pairing when we will not next to each other, but actually thousands of miles away, um, or having this little environment that they can put aside and come back to it later, without it having using resource in my machine. Um, I don't know, having this dev service running somewhere in the cloud without needing something like, it's at the rights that are like the, the possibilities are really endless. >>Yeah. Yeah. Perfect. Yeah. I'm, you know, a little while ago I was, I was torn, right. W do I spin up containers? Do I develop inside of my containers? Right. There's foul sinking issues. Um, you know, that we've been working on at Docker for a while, and Jacob is very, very familiar with those, right? Sometimes it, it becomes hard, but, and I, and I love developing in the cloud, but I also have this screaming, you know, fast machine sitting on my desktop that I think I should take advantage of. So I guess another question is, you know, should we be developing inside of containers? Is that a smart thing to do? Uh, I'd love to hear you guys' thoughts around that. >>You know, I think it's one of those things where it's, you know, for me container first development is really about, um, considering containers as sort of a first class citizen in, in terms of your development toolkit, right. I mean, there's not always that silver bullet, that's like the one thing you should use for everything. You know, you shouldn't, you shouldn't use containers if they're not fitting in or adding value to your workflow, but I think there's a lot of scenarios that are like, you know, super on super early on in the development process. Like as soon as you get the server kind of running and working and, you know, you're able to access it, you know, running on your local system. Uh that's I think that's when the value comes in to it to add containers to, you know, what you're doing or to your project. Right. I mean, for me, they're, um, they're more of a orchestrational tool, right? So if I don't have to have six different browser tabs open with like, you know, an API server running at one tab and a web server running in another tab and a database running in another tab, I can just kind of encapsulate those and, and use them as an automation thing. So I think, you know, even if you have a super powerful computer, I think there's still value in, um, using containers as, as a orchestrational mechanism. Yeah. Yeah, >>For sure. I think, I think one of the, one of my original aha moments with Docker was, oh, I can spin up different versions of a database locally and not have to install it and not have to configure it and everything, but, you know, it just ran inside of a container. And that, that was it. Although it's might seem simple to some people that's very, very powerful. Right. So I think being able to spin things up and containers very quickly is one of the super benefits. But yeah, I think, uh, developing in containers is, is hard right now, right. With, um, you know, and how do you do that? Right. Does anybody have any thoughts around, how do you go about that? Right. Should you use a container as just a development environment, so, you know, creating an image and then running it just with your dev tools in it, or do you just, uh, and maybe with an editor all inside of it, and it's just this process, that's almost like a VM. Um, yeah. So I'll just kick it back to the panel. I'd love to hear your thoughts on, you know, how do you set up and configure, uh, containers to develop in any thoughts around that? >>Maybe one step back again, to answer your question, what kind of container first development mean? I think it doesn't mean, um, by default that it has to be in the cloud, right? As you said, um, there are obvious benefits when it comes to the developer experience of containers, such as, I dunno, consistency, we have standardized tools dependencies for the dev side of things, but it also makes their dev environment more similar to all the pipeline that is somehow happening to the right, right. So CIC D all the way to production, it is security, right? Which also somehow comes with standardization. Um, but vulnerability scanning tools like sneak are doing a great job there. And, um, for us, it gets pod. One of the key reasons why we created get pod was literally creating this peace of mind for deaths. So from a developer's point of view, you do not need to take care anymore about all the hassle around setups and things that you will need to install. >>And locally, based on some outdated, REIT me on three operating systems in your company, everybody has something different and leading to these verbs in my machine situations, um, that really slow professional software developers down. Right. Um, back to your point, I mean, with good pod, we obviously have to package everything together in one container because otherwise, exactly the situation happens that you need to have five browser tabs open. So we try and leverage that. And I think a dev environment is not just the editor, right? So a dev environment includes your source code. It includes like a powerful shell. It includes file systems. It includes essentially all the tools you need in order to be productive databases and so on. And, um, yeah, we believe that should be encapsulated, um, um, in a container. >>Yeah. Awesome. Katie, you talked to a lot of end users, right. And you're talking to a lot of developers. What, what's your thoughts around container first development, right? Or, or what's the community out there screaming or screaming. It might be too to, uh, har you know, to, to two grand of the word. Right. But yeah, I love it. I love to hear what your, your thoughts. >>Absolutely. So I think when you're talking about continuing driven development, uh, the first thing that crosses my mind is the awareness of the infrastructure or the platform you're going to run your application on top of, because usually when you develop your application, you'd like to replicate as much as possible the production or even the staging environment to make sure that when you deploy your application, you have us little inconsistencies as possible, but at the same time, you minimize the risk for something to go wrong as well. So when it talking about the, the community, um, again, when you deploy applications and containers and Kubernetes, you have to use, you have awareness about, and probably apply some of the best practices, like introducing liveliness and readiness probes, to make sure that your application can restart in, in case it actually goes down or there's like a you're starving going CPU or something like that. >>So, uh, I think when it comes to deployment and development of an application, the main thing is to actually improve the end developer experience. I think there has been a lot of focus in the community to develop the tool, to actually give you the right tool to run application and production, but that doesn't necessarily, um, go back to how the end developer is actually enabling that application to run into that production system. So I think there has been, uh, this focus for the community identified now, and it's more, more, um, or trying to build momentum on enhancing the developer experience. And we've seen this going through many, uh, where we think production of many tools did what has been one of them, which actually we can have this portable, um, development environment if you choose so, and you can actually replicate them across different teams in different machines, which is actually quite handy. >>But at the same time, we had tools such as local composts has been a great tool to run locally. We have tool such as carefully, which is absolutely great to automatically dynamically upload any changes to how within your code. So I think all of these kinds of tools, they getting more matured. And again, this is going back to again, we need to enhance our developer experience coming back to what is the right way to do so. Um, I think it really depends on the environment you have in production, because there's going to define some of the structures with the tool and you're going to have internally, but at the same time, um, I'd like to say that, uh, it really depends on, on what trucks are developing. Uh, so it's, it's, I would like to personally, I would like to see a bit more diversification in this area because we might have this competitive solutions that is going to push us to towards a new edge. So this is like, what definitely developer experience. If we're talking about development, that's what we need to enhance. And that's what I see the momentum building at the moment. >>Yeah. Yeah. Awesome. Jerome, I saw you shaking your head there in agreement, or maybe not, but what's your thoughts? >>I was, uh, I was just reacting until 82. Uh, it depends thinking that when I, when I do training, that's probably the answer that I gave the most, uh, each time somebody asks, oh, should we do diesel? And I was also looking at some of the questions in the chat about, Hey, the, should we like have a negatory in the, in the container or something like that. And folks can have pretty strong opinions one way or the other, but as a ways, it kind of depends what we do. It also depends of the team that we're working with. Um, you, you could have teams, you know, with like small teams with folks with lots of experience and they all come with their own Feb tools and editorials and plugins. So you know that like you're gonna have PRI iMacs out of my cold dead hands or something like that. >>So of course, if you give them something else, they're going to be extremely unhappy or sad. On the other hand, you can have team with folks who, um, will be less opinionated on that. And even, I don't know, let's say suddenly you start working on some project with maybe a new programming language, or maybe you're targeting some embedded system or whatever, like something really new and different. And you come up with all the tools, even the ADE, the extensions, et cetera, folks will often be extremely happy in that case that you're kind of giving them a Dettol and an ADE, even if that's not what they usually would, uh, would use, um, because it will come with all of the, the, the nice stage, you know, the compression, the, um, the, the, the bigger, the, whatever, all these things. And I think there is also something interesting to do here with development in containers. >>Like, Hey, you're going to start working on this extremely complex target based on whatever. And this is a container that has everything to get started. Okay. Maybe it's not your favorites editor, but it has all the customization and the conserver and whatever. Um, so you can start working right away. And then maybe later you, we want to, you know, do that from the container in a way, and have your own Emacs, atom, sublime, vs code, et cetera, et cetera. Um, but I think it's great for containers here, as well as they reserve or particularly the opportunity. And I think like the, that, that's one thing where I see stuff like get blood being potentially super interesting. Um, it's hard for me to gauge because I confess I was never a huge ID kind of person had some time that gives me this weird feeling, like when I help someone to book some, some code and you know, that like with their super nice IDE and everything is set up, but they feel kind of lost. >>And then at some point I'm like, okay, let's, let's get VI and grep and let's navigate this code base. And that makes me feel a little bit, you know, as this kind of old code for movies where you have the old, like colorful guy who knows going food, but at the end ends up still being obsolete because, um, it's only a going for movies that whole good for masters and the winning right. In real life, we don't have conformance there's anymore mentioned. So, um, but part of me is like, yeah, I like having my old style of editor, but when, when the modern editorial modern ID comes with everything set up and configured, that's just awesome. That's I, um, it's one thing that I'm not very good at sitting up all these little things, but when somebody does it and I can use it, it's, it's just amazing. >>Yeah. Yeah. I agree. I'm I feel the same way too. Right. I like, I like the way I've I have my environment. I like the tools that I use. I like the way they're set up. And, but it's a big issue, right? If you're switching machines, like you said, if you're helping someone else out there, they're not there, your key bindings aren't there, you can't, you can't navigate their system. Right? Yeah. So I think, you know, talking about, uh, dev environments that, that Docker's coming out with, and we're, you know, there's a lot, there, there's a, it's super complex, all these things we're talking about. And I think we're taking the approach of let's do something, uh, well, first, right. And then we can add on to that. Right. Because I think, you know, setting up full, full developed environments is hard, right. Especially in the, the, um, cloud native world nowadays with microservices, do you run them on a repo? >>Do you not have a monitor repo? Maybe that would be interesting to talk about. I think, um, you know, I always start out with the mono repos, right. And you have all your services in there and maybe you're using one Docker file. And then, because that works fine. Cause everything is JavaScript and node. And then you throw a little Python in there and then you throw a little go and now you start breaking things out and then things get too complex there, you know, and you start pulling everything out into different, get repos and now, right. Not everything just fits into these little buckets. Right. So how do you guys think maybe moving forward, how do we attack that night? How do we attack these? Does separate programming languages and environments and kind of bring them all together. You know, we, we, I hesitate, we solve that with compose around about running, right about executing, uh, running your, your containers. But, uh, developing with containers is different than running containers. Right. It's a, it's a different way to think about it. So anyway, sorry, I'm rattling on a little bit, but yeah. Be interesting to look at a more complex, uh, setup right. Of, uh, of, you know, even just 10 microservices that are in different get repos and different languages. Right. Just some thoughts. And, um, I'm not sure we all have this flushed out yet, but I'd love to hear your, your, you guys' thoughts around that. >>Jacob, you, you, you, you look like you're getting ready to jump there. >>I didn't wanna interrupt, but, uh, I mean, I think for me the issue isn't even really like the language boundary or, or, um, you know, a sub repo boundary. I think it's really about, you know, the infrastructure, right? Because you have, you're moving to an era where you have these cloud services, which, you know, some of them like S3, you can, you can mock up locally, uh, or run something locally in a container. But at some point you're going to have like, you know, cloud specific hardware, right? Like you got TPS or something that maybe are forming some critical function in your, in your application. And you just can't really replicate that locally, but you still want to be able to develop against that in some capacity. So, you know, my, my feeling about where it's going to go is you'll end up having parts of your application running locally, but then you also have, uh, you know, containers or some other, uh, element that's sort of cohabitating with, uh, you know, either staging or, or testing or production services that you're, uh, that you're working with. >>So you can actually, um, you know, test against a really or realistic simulation or the actual, uh, surface that you're running against in production. Because I think it's just going to become untenable to keep emulating all of that stuff locally, or to have to like duplicate these, you know, and, you know, I guess you can argue about whether or not it's a good thing that, that everything's moving to these kind of more closed off cloud services, but, you know, the reality of situation is that's where it's going to go. And there's certain hardware that you're going to want in the cloud, especially if you're doing, you know, machine learning oriented stuff that there's just no way you're going to be able to run locally. Right. I mean, if you're, even if you're in a dev team where you have, um, maybe like a central machine where you've got like 10 or 20 GPU's in it, that's not something that you're going to be able to, to, to replicate locally. And so that's how I kind of see that, um, you know, containers easing that boundary between different application components is actually maybe more about co-location, um, or having different parts of your application run in different locations, on different hardware, you know, maybe someone on your laptop, maybe it's someone, you know, AWS or Azure or somewhere. Yeah. It'd be interesting >>To start seeing those boundaries blur right. Working local and working in the cloud. Um, and you might even, you might not even know where something is exactly is running right until you need to, you know, that's when you really care, but yeah. Uh, Johanas, what's your thoughts around that? I mean, I think we've, we've talked previously of, of, um, you know, hybrid kind of environments. Uh, but yeah. What, what's your thoughts around that? >>Um, so essentially, yeah, I think, I mean, we believe that the lines between cloud and local will also potentially blur, and it's actually not really about that distinction. It's just packaging your dev environment in a way and provisioning your dev environment in a way that you are what we call always ready to coat. So that literally, um, you, you have that for the, you described as, um, peace of mind that you can just start to be creative and start to be productive. And if that is a container potentially running locally and containers are at the moment. I think, you know, the vehicle that we use, um, two weeks ago, or one week ago actually stack blitz announced the web containers. So potentially some things, well, it's run in the browser at some point, but currently, you know, Docker, um, is the standard that enables you to do that. And what we think will happen is that these cloud-based or local, um, dev environments will be what we call a femoral. So it will be similar to CIS, um, that we are using right now. And it doesn't literally matter, um, where they are running at the end. It's just, um, to reduce friction as much as possible and decrease and yeah, yeah. Essentially, um, avoid or the hustle that is currently involved in setting up and also managing dev environments, um, going forward, which really slows down specifically larger teams. >>Yeah. Yeah. Um, I'm going to shift gears a little bit here. We have a question from the audience in chat, uh, and it's, I think it's a little bit two parts, but so far as I can see container first, uh, development, have the challenges of where to get safe images. Um, and I was going to answer it, but let me keep it, let me keep going, where to get safe images and instrumentation, um, and knowing where exactly the problem is happening, how do we provide instrument instrumentation to see exactly where a problem might be happening and why? So I think the gist of it is kind of, of everything is in a container and I'm sitting outside, you know, the general thought around containers is isolation, right. Um, so how do I get views into that? Um, whether debugging or, or, or just general problems going on. I think that's maybe a broader question around the, how you, you know, you have your local hosts and then you're running everything containers, and what's the interplay there. W what's your thoughts there? >>I tend to think that containers are underused interactively. I mean, I think in production, you have this mindset that there's sort of this isolated environment, but it's very, actually simple to drop into a shell inside of a container and use it like you would, you know, your terminal. Um, so if you want to install software that way, you know, through, through an image rather than through like Homebrew or something, uh, you can kind of treat containers in that way and you can get a very, um, you know, direct access to the, to the space in which those are running in. So I think, I think that's maybe the step one is just like getting rid of that mindset, that, that these are all, um, you know, these completely encapsulated environments that you can't interact with because it's actually quite easy to just Docker exec into a container and then use it interactively >>Yeah. A hundred percent. And maybe I'll pass, I'm going to pass this question. You drone, but maybe demystify containers a little bit when I talked about this on the last, uh, panel, um, because we have a question in the, in the chat around, what's the, you know, why, why containers now I have VMs, right? And I think there's a misunderstanding in the industry, uh, about what, what containers are, we think they're fair, packaged stuff. And I think Jacob was hitting on that of what's underneath the hood. So maybe drown, sorry, for a long way to set up a question of what, what, what makes up a container, what is a container >>Is a container? Well, I, I think, um, the sharpest and most accurate and most articulate definition, I was from Alice gold first, and I will probably misquote her, but she said something like containers are a bunch of capsulated processes, maybe running on a cookie on welfare system. I'm not sure about the exact definition, but I'm going to try and, uh, reconstitute that like containers are just processes that run on a Unix machine. And we just happen to put a bunch of, um, red tape or whatever around them so that they are kind of contained. Um, but then the beauty of it is that we can contend them as much, or as little as we want. We can go kind of only in and put some actual VM or something like firecracker around that to give some pretty strong angulation, uh, all we can also kind of decontam theorize some aspects, you know, you can have a container that's actually using the, um, the, um, the network namespace of the host. >>So that gives it an entire, you know, wire speed access to the, to the network of the host. Um, and so to me, that's what really interesting, of course there is all the thing about, oh, containers are lightweight and I can pack more of them and they start fast and the images can be small, yada yada, yada. But to me, um, with my background in infrastructure and building resilient, things like that, but I find really exciting is the ability to, you know, put the slider wherever I need it. Um, the, the, the ability to have these very light containers, all very heavily, very secure, very anything, and even the ability to have containers in containers. Uh, even if that sounds a little bit, a little bit gimmicky at first, like, oh, you know, like you, you did the Mimi, like, oh, I heard you like container. >>So I put Docker when you're on Docker. So you can run container for you, run containers. Um, but that's actually extremely convenient because, um, as soon as you stop building, especially something infrastructure related. So you challenge is how do you test that? Like, when we were doing.cloud, we're like, okay, uh, how do we provision? Um, you know, we've been, if you're Amazon, how do you provision the staging for us installed? How do you provision the whole region, Jen, which is actually staging? It kind of makes things complicated. And the fact that we have that we can have containers within containers. Uh, that's actually pretty powerful. Um, we're also moving to things where we have secure containers in containers now. So that's super interesting, like stuff like a SIS box, for instance. Um, when I saw that, that was really excited because, uh, one of the horrible things I did back in the days as Docker was privileged containers, precisely because we wanted to have Docker in Docker. >>And that was kind of opening Pandora's box. That's the right, uh, with the four, because privileged containers can do literally anything. They can completely wreck up the machine. Um, and so, but at the same time, they give you the ability to run VPNs and run Docker in Docker and all these cool things. You can run VM in containers, and then you can list things. So, um, but so when I saw that you could actually have kind of secure containers within containers, like, okay, there is something really powerful and interesting there. And I think for folks, well, precisely when you want to do development in containers, especially when you move that to the cloud, that kind of stuff becomes a really important and interesting because it's one thing to have my little dev thing on my local machine. It's another thing when I want to move that to a swarm or Kubernetes cluster, and then suddenly even like very quickly, I hit the wall, which is, oh, I need to have containers in my containers. Um, and then having a runtime, like that gets really intense. >>Interesting. Yeah, yeah, yeah. And I, and jumping back a bit, um, yeah, uh, like you said, drum at the, at the base of it, it containers just a, a process with, with some, uh, Abra, pardon me, operating constructs wrapped around it and see groups, namespaces those types of things. But I think it's very important to, for our discussion right. Of, uh, developers really understanding that, that this is just the process, just like a normal process when I spin up my local bash in my term. Uh, and I'm just interacting with that. And a lot of the things we talk about are more for production runtimes for securing containers for isolating them locally. I don't, I don't know. I'll throw the question out to the panel. Is that really relevant to us locally? Right. Do we want to pull out all of those restrictions? What are the benefits of containers for development, right. And maybe that's a soft question, but I'd still love to hear your thoughts. Maybe I'll kick it over to you, Katie, would you, would you kick us off a little bit with that? >>I'll try. Um, so I think when, again, I was actually thinking of the previous answers because maybe, maybe I could do a transition here. So, interesting, interesting about containers, a piece of trivia, um, the secrets and namespaces have been within the Linux kernel since 2008, I think, which just like more than 10 years ago, hover containers become popular in the last years. So I think it's, it's the technology, but it's about the organization adopting this technology. So I think why it got more popular now is because it became the business differentiator organizations started to think, how can I deliver value to my customers as quickly as possible? So I think that there should be this kind of two lane, um, kind of progress is the technology, but it's at the same time organization and cultural now are actually essential for us to develop, uh, our applications locally. >>Again, I think when it's a single application, if you have just one component, maybe it's easier for you to kind of run it locally, have a very simple testing environment. Sufficient is a container necessary, probably not. However, I think it's more important when you're thinking to the bigger picture. When we have an architecture that has myriads of microservices at the basis, when it's something that you have to expose, for example, an API, or you have to consume an API, these are kind of things where you might need to think about a lightweight set up within the containers, only local environment to make sure that you have at least a similar, um, environment or a configuration to make sure that you test some of the expected behavior. Um, I think the, the real kind of test you start from the, the dev cluster will like the dev environment. >>And then like for, for you to go to staging and production, you will get more clear into what exactly that, um, um, configuration should be in the end. However, at the same time, again, it's, it's more about, um, kind of understanding why you continue to see this, the thing, like, I don't say that you definitely need containers at all times, but there are situations when you have like, again, multiple services and you need to replicate them. It's just the place to, to, to work with these kind of, um, setups. So, um, yeah, really depends on what you're trying to develop here. Nothing very specific, unfortunately, but get your product and your requirements are going to define what you're going to work with. >>Yeah, no, I think that's a great answer, right. I think one of the best answers in, in software engineering and engineering in general as well, it depends. Right. It's things are very specific when we start getting down to the details, but yeah, generally speaking, you know, um, I think containers are good for development, but yeah, it depends, right. It really depends. Is it helping you then? Great. If it's hindering you then, okay. Maybe think what's, what's the hindrance, right. And are containers the right solution. I agree. 110% and, >>And everything. I would like absurd this too as well. When we, again, we're talking about the development team and now we have this culture where we have the platform and infrastructure team, and then you have your engineering team separately, especially when the regulations are going to be segregated. So, um, it's quite important to understand that there might be a, uh, a level of up-skilling required. So pushing for someone to use containers, because this is the right way for you to develop your application might be not, uh, might not be the most efficient way to actually develop a product because you need to spend some time to make sure that the, the engineering team has the skills to do so. So I think it's, it's, again, going back to my answers here is like, truly be aware of how you're trying to develop how you actually collaborate and having that awareness of your platform can be quite helpful in developing your, uh, your publication, the more importantly, having less, um, maybe blockers pushing it to a production system. >>Yeah, yeah. A hundred percent. Yeah. The, uh, the cultural issue is, is, um, within the organization, right. Is a very interesting thing. And it, and I would submit that it's very hard from top down, right. Pushing down tools and processes down to the dev team, man, we'll just, we'll just rebel. It usually comes from the bottom up. Right. What's working for us, we're going to do right. And whether we do it in the shadows and don't let it know, or, or we've conformed, right. Yeah. A hundred percent. Um, interesting. I would like to think a little bit in the future, right? Like, let's say, I don't know, two, three years from now, if, if y'all could wave a and I'm from Texas. So I say y'all, uh, if you all could wave a magic wand, what, what, what would that bring about right. What, what would, what would be the best scenario? And, and we just don't have to say containers. Right. But, you know, what's the best development environment and I'm going to kick it over to you, Jacob. Cause I think you hinted at some of that with some hybrid type of stuff, but, uh, yeah. Implies, they need to keep you awake. You're, you're, you're, uh, almost on the other side of the world for me, but yeah, please. >>Um, I think, you know, it's, it's interesting because you have this technology that you've been, that's been brought from production, so it's not, um, necessarily like the right or the normal basis for development. So I think there's going to be some sort of realignment or renormalization in terms of, uh, you know, what the, what the basis and the abstractions that we're using on a daily basis are right. Like images and containers as they exist now are really designed for, um, for production use cases. And, and in terms of like, even even the ergonomics of opening a shell inside a container, I think is something that's, um, you know, not as polished or not as smooth as it could be because they've come from production. And so I think it's important, like not to, not to have people look at, look at the technology as it exists now and say like, okay, this is slightly rough around the edges, or it wasn't designed for this use case and think, oh, there's, you know, there's never any way I could use this for, for my development of workflows. >>I think it's, you know, it's something Docker's exploring now with, uh, with the, uh, dev containers, you know, it's, it's a new, and it's an experimental paradigm and it may not be what the final picture looks like. As, you know, you were saying, there's going to be kind of a baseline and you'll add features to that or iterate on that. Um, but I think that's, what's interesting about it, right? Cause it's, there's not a lot of things as developers that you get to play with that, um, that are sort of the new technology. Like if you're talking about things you're building to ship, you want to kind of use tried and true components that, you know, are gonna, that are going to be reliable. But I think containers are that interesting point where it's like, this is an established technology, but it's also being used in a way now that's completely different than what it was designed for. And, and, you know, as hackers, I think that's kind of an interesting opportunity to play with it, but I think, I think that's, what's going to happen is you're just going to see kind of those production, um, designed, uh, knobs kind of sanded down or redesigned for, for development. So that's kind of where I see it going. >>Yeah. Yeah. And I think that's what I was trying to hint out earlier is like, um, yeah, just because all these things are there, does it actually mean we need them locally? Right. Do they make sense? I, I agree. A hundred percent, uh, anybody else drawn? What are your thoughts around that? And then, and then, uh, I'll probably just ask all of you. I'd love to hear each of your thoughts of the future. >>I had a thought was maybe unrelated, but I was kind of wondering if we would see something on the side of like energy efficiency in some way. Um, and maybe it's just because I've been thinking a lot about like climate change and things like that recently, and trying to reduce like the, uh, the energy use energy use and things like that. Perhaps it's also because I recently got a new laptop, which on paper is super awesome, but in practice, as soon as you try to have like two slack tabs and a zoom call, you know, it's super fast, both for 30 seconds. And after 30 seconds, it blows its thermal budget and it's like slows down to a crawl. And I started to think, Hmm, maybe, you know, like before we, we, we were thinking about, okay, I don't have that much CPU available. So you have to be kind of mindful about that. >>And now I wonder how are we going to get in something similar to that, but where you try to save CPU cycles, not just because you don't have that many CPU cycles, but more because you know, that you can't go super fast for super long when you are on one of these like small laptops or tablets or phones, like you have this demo budget to take into account. And, um, I wonder if, and how like, is there something where goaltenders can do some things here? I guess it can be really interesting if they can do some the equivalent of like Docker top and Docker stats. And if I could see, like how much what's are these containers using, I can already do that with power top on Linux, for instance, like process by process. So I'm thinking I could see what's the power usage of, of some containers. Um, and I wonder if down the line, is this going to be something useful or is this just silly because we can just masquerade CPU usage for, for Watson and forget about it. >>Yeah. Yeah. It was super, super interesting, uh, perspective for sure. I'm going to shut up because I want to, I want to give, make sure I give Johannes and Katie time. W w what are your thoughts of the future around, let's just say, you know, container development in general, right? You want, you want to start absolutely. Oh, honest, Nate. Johns wants more time. I say, I'll try not to. Beneficiate >>Expensive here, but, um, so one of the things that we've we've touched upon earlier in the panel was multicloud strategy. And I was reading one of the data reports from it was about the concept of Kubernetes from gamer Townsville. But what is working for you to see there is that more and more organizations are thinking about multicloud strategy, which means that you need to develop an application or need an infrastructure or a component, which will allow you to run this application bead on a public cloud bead, like locally in a data center and so forth. And here, when it comes to this kind of, uh, maybe problems we come across open standards, this is where we require something, which will allow us to execute our application or to run our platform in different environments. So when you're thinking about the application or development of the application, one of the things that, um, came out in 2019 at was the Oakland. >>Um, I wish it was Kybella, which is a, um, um, an open application model based application, which allows you to describe the way you would like your service to be executed in different environments. It doesn't need to be well developed specifically for communities. However, the open application model is specialized. So specialized tries to cover multiple platforms. You will be able to execute your application anywhere you want it to. So I think that that's actually quite important because it completely obstructs what is happening underneath it, completely obstructs notions, such as containers, uh, or processes is just, I want this application and I want to have this kind of behavior is so example of, to scale in this conditions or to, um, to be exposed for these, uh, end points and so forth. And everything that I would like to mention here is that maybe this transcends again, the, uh, the logistics of the application development, but it definitely will impact the way we run our applications. >>So one of the biggest, well, one of the new trends that is kind of gaining momentum now has been around Plaza. And this is again, something which is trying to present what we have the on containers. Again, it's focusing on the, it's kind of a cyclical, um, uh, action movement that we have here. When we moved from the VMs to containers, it was smaller footprint. We want like better execution, one, this agnosticism of the platforms. We have the same thing happening here with Watson, but again, it consents a new, um, uh, kind of, well, it teaches in you, uh, in new climax here, where again, we shrink the footprint of the cluster. We have a better isolation of all the services. We have a better trend, like portability of how services and so forth. So there is a great potential out there. And again, like why I'm saying this is some of these technologies are gonna define the way we're gonna do our development of the application on our local environment. >>That's why it's important to kind of maybe have an eye there and maybe see if some of those principles of some of those technologies we can bring internally as well. And just this, like a, a final thought here, um, security has been mentioned as well. Um, I think it's something which has been, uh, at the forefront, especially when it comes to containers, uh, especially when it comes to enterprise organizations and those who are regulated, which I feel come very comfortable to run their application within a VM where you have the full isolation, you can do what we have complete control of what's happening inside that compute. So, um, again, security has been at the forefront at the moment. So I know it has mentioned in the panel before. I'd like to mention that we have the security white paper, which has been published. We have the software supply chain, white paper as well, which twice to figure out or define some of these good practices as well, again, which you can already apply from your development environment and then propagate them to production. So I'm just going to leave, uh, all of these. That's all. >>That's awesome. And yeah, well, while is very, very interesting. I saw the other day that, um, and I forget who it was, maybe, maybe all can remember, um, you know, running, running the node, um, engine inside of, you know, in Walzem inside of a browser. Right. And, uh, at first glance I said, well, we already have a JavaScript execution engine. Right. And it's kind of like Docker and Docker. So you have, uh, you know, you have the browser, then, then you have blossom and then you have a node, you know, a JavaScript runtime. And, and I didn't understand was while I was, um, you know, actually executing is JavaScript and it's not, but yeah, it's super interesting, super powerful. I always felt that the browser was, uh, Java's what write once run anywhere kind of solution, right. That never came about, they were thinking of set top, uh, TV boxes and stuff like that, which is interesting. >>I don't know, you'll some of the history of Java, but yeah. Wasm is, is very, I'm not sure how to correctly pronounce it, but yeah, it's extremely interesting because of the isolation in that boxing. Right. And running powerful languages that were used to inside of a more isolated environment. Right. And it's almost, um, yeah, it's kind of, I think I've mentioned it before that the containers inside of containers, right. Um, yeah. So Johannes, hopefully I gave you enough time. I delayed, I delayed as much as I can. My friend, you better, you better just kidding. I'm just kidding, please, please. >>It was by the way, stack let's and they worked together with Google and with Russell, um, developing the web containers, it's called there's, it's quite interesting. The research they're doing there. Yeah. Yeah. I mean, what we believe and I, I also believe is that, um, yeah, probably somebody is doing to death environments, what Docker did to servers and at least that good part. We hope that somebody will be us. Um, so what we mean by that is that, um, we think today we are still somehow emotionally attached to our dev environments. Right. We give them names, we massage them over time, which can also have its benefits, but it's, they're still pets in some way. Right. And, um, we believe that, um, environments in the future, um, will be treated similar like servers today as automated resources that you can just spin up and close down whenever you need them. >>Right. And, um, this trend essentially that you also see in serverless, if you look at what kind of Netlify is doing a bit with preview environments, what were sellers doing? Um, there, um, we believe will also arrive at, um, at Steph environments. It probably won't be there tomorrow. So it will take some time because if there's also, you know, emotion involved into, in that, in that transition, but ultimately really believe that, um, provisioning dev environments also in the cloud allows you to leverage the power of the cloud and to essentially build all that stuff that you need in order to work in advance. Right? So that's literally either command or a button. So either, I don't know, a command that spins up your local views code and SSH into, into a container, or you do it in a browser, um, will be the way that professional development teams will develop in the future. Probably let's see in our direction of document, we say it's 2000 to 23. Let's see if that holds true. >>Okay. Can we, can, we let's know. Okay. Let's just say let's have a friendly bet. I don't know that's going to be closed now, but, um, yeah, I agree. I, you know, it's my thought around is it, it's hard, right? Th these are hard. And what problems do you tackle first, right? Do you tackle the day, one of, uh, you know, of development, right. I joined a team, Hey, here's your machine? And you have Docker installed and there you go, pull, pull down your environment. Right. Is that necessarily just an image? You know, what, what exactly is that sure. Containers are involved. Right. But that's, I mean, you, you've probably all gone through it. You joined a team, new project, even open-source project, right there. There's a huge hurdle just to get everything configured, to get everything installed, to get it up and running, um, you know, set aside all understanding the code base. >>Cause that's a different issue. Right. But just getting everything running locally and to your point earlier, Jacob of around, uh, recreating, local production cues and environments and, you know, GPS or anything like that, right. Is extremely hard. You can't do a lot of that locally. Right. So I think that's one of the things I'd love to see tackled. And I think that's where we're tackling in dev environments, uh, with Docker, but then now how do you become productive? Right. And where do we go from there? And, uh, and I would love to see this kind of hybrid and you guys have been all been talking about it where I can, yes. I have it configured everything locally on my nice, you know, apple notebook. Right. And then, you know, I go with the family and we go on vacation. I don't want to drag this 16 inch, you know, Mac laptop with me. >>And I want to take my nice iPad with the magic keyboard and all the bang stuff. Right. And I just want to fire up and I pick up where I left off. Right. And I keep coding and environment feels, you know, as much as it can that I'm still working at backup my desktop. I think those, those are very interesting to me. And I think reproducing, uh, the production running runtime environments as close as possible, uh, when I develop my, I think that's extremely powerful, extremely powerful. I think that's one of the hardest things, right. It's it's, uh, you know, we used to say, we, you debug in production. Right. We would launch, right. We would do, uh, as much performance testing as possible. But until you flip that switch on a big, on a big site, that's where you really understand what is going to break. >>Right. Well, awesome. I think we're just about at time. I really, really appreciate everybody joining me. Um, it's been a pleasure talking to all of you. We have to do this again. If I, uh, hopefully, you know, I I'm in here in America and we seem to be doing okay with COVID, but I know around the world, others are not. So my heart goes out to them, but I would love to be able to get out of here and come see all of you and meet you in person, maybe break some bread together. But, um, again, it was a pleasure talking to you all, and I really appreciate you taking the time. Have a good evening. Cool. >>Thanks for having us. Thanks for joining us. Yes.

>> Narrator: From theCUBE studios in Palo Alto in Boston connecting with our leaders all around the world. This is theCUBE conversation. >> Welcome to theCUBE and the special IBM Brocade panel. I'm Lisa Martin. And I'm having a great opportunity here to sit down for the next 20 minutes with three gentlemen please welcome Brian Sherman a distinguished engineer from IBM, Brian, great to have you joining us. >> Thanks for having me. >> And Matt key here. Flash systems SME from IBM, Matt, happy Friday. >> Happy Friday, Lisa. Thanks for having us. >> Our pleasure. And AIG Customer solution here from Brocade is here. AJ welcome. >> Thanks for having me along. >> AJ we're going to stick with you, IBM and Brocade have had a very long you said about 22 year strategic partnership. There's some new news. And in terms of the evolution of that talk to us about what's going on with with Brocade IBM and what is new in the storage industry? >> Yeah, so the the newest thing for us at the moment is that IBM just in mid-October launched our Gen seven platforms. So this is think about the stresses that are going on in the IT environments. This is our attempt to keep pace with with the performance levels that the IBM teams are now putting into their storage environments the All-Flash Data Centers and the new technologies around non-volatile memory express. So that's really, what's driving this along with the desire to say, "You know what people aren't allowed "to be in the data center." And so if they can't be in the data center then the fabrics actually have to be able to figure out what's going on and basically provide a lot of the automation pieces. So something we're referring to as the autonomous SAM. >> And we're going to dig into NBME of our fabrics in a second but I do want to AJ continue with you in terms of industries, financial services, healthcare airlines there's the biggest users, biggest need. >> Pretty much across the board. So if you look at the global 2000 as an example, something on the order of about 96, 97% of the global 2000 make use of fiber channel environments and in portions of their world generally tends to be a lot of the high end financial guys, a lot of the pharmaceutical guys, the automotive, the telcos, pretty much if the data matters, and it's something that's critical whether we talk about payment card information or healthcare environments, data that absolutely has to be retained, has to get there, has to perform then it's this combination that we're bringing together today around the new storage elements and the functionalities they have there. And then our ability in the fabric. So the concept of a 64 gig environment to help basically not be the bottleneck in the application demands, 'cause one thing I can promise you after 40 years in this industry is the software guys always figure out how to all the performance that the hardware guys put on the shelf, right? Every single time. >> Well there's gauntlet thrown down there. Matt, let's go to you. I want to get IBM's perspective on this. Again, as we said, a 22 year strategic partnership, as we look at things like not being able to get into the data center during these unprecedented times and also the need to be able to remove some of those bottlenecks how does IBM view this? >> Yeah, totally. It's certainly a case of raising the bar, right? So we have to as a vendor continue to evolve in terms of performance, in terms of capacity, cost density, escalating simplicity, because it's not just a case of not be able to touch the rates, but there's fewer people not being able to adjust the rates, right? It's a case where our operational density continues to have to evolve being able to raise the bar on the network and be able to still saturate those line rates and be able to provide that simply a cost efficiency that gets us to a utilization that raises the bar from our per capita ratio from not just talking about 200, 300 terabytes per admin but going beyond the petabyte scale per admin. And we can't do that unless people have access to the data. And we have to provide the resiliency. We have to provide the simplicity of presentation and automation from our side. And then this collaboration that we do with our network brother like Brocade here continued to stay out of the discussion when it comes to talking about networks and who threw the ball next. So we truly appreciate this Gen seven launch that they're doing we're happy to come in and fill that pipe on the flash side for them. >> Excellent and Brian as a distinguished engineer and let me get your perspectives on the evolution of the technology over this 22 year partnership. >> Thanks Lisa. It certainly has been a longstanding, a great relationship, great partnership all the way from inventing joint things, to developing, to testing and deploying to different technologies through the course of time. And it's been one of those that where we are today, like AJ had talked about being able to sustain what the applications require today in this always on time type of environment. And as Matt said, bringing together the density and operational simplicity to make that happen 'cause we have to make it easier from the storage side for operations to be able to manage this volume of data that we have coming out and our due diligence is to be able to serve the data up as fast as we can and as resilient as we can. >> And so sticking with you, Brian that simplicity is key because as we know as we get more and more advances in technology the IT environment is only becoming more complex. So really truly enabling organizations in any industry to simplify is absolute table stakes. >> Yeah, it definitely is. And that's core to what we're focused on and how do we make the storage environment simple. It's been one those through the years and historically, we've had entry-level us and the industry as a whole, is that an entry-level product mid range level products, high-end level products. And earlier this year, we said enough, enough of that it's one product portfolio. So it's the same software stack it's just, okay. Small, medium and large in terms of the appliances that get delivered. Again, building on what Matt said, from a density perspective where we can have a petabyte of uncompressed and data reduced storage in a two Enclosure. So it becomes from a overall administration perspective, again, one software stake, one automation stack, one way to do point in time copies, replication. So in focusing on how to make that as simple for the operations as we possibly can. >> I think we'd all take a little bit of that right now. Matt, let's go to you and then AJ view, let's talk a little bit more, dig into the IBM storage arrays. I mean, we're talking about advances in flash, we're talking about NBME as a forcing function for applications to change and evolve with the storage. Matt, give us your thoughts on that. >> We saw a monumental leap in where we take some simplicity pieces from how we deliver our arrays but also the technology within the arrays. About nine months ago, in February we launched into the latest generation of non technology and with that born the story of simplicity one of the pieces that we've been happily essentially negating of value prop is storage level tiering and be able to say, "Hey, well we still support the idea of going down "to near line SaaS and enterprise disc in different flavors "of solid state whether it's tier one short usage "the tier zero high performance, high usage, "all the way up to storage class memory." While we support those technologies and the automated tiering, this elegance of what we've done as latest generation technology that we launched nine months ago has been able to essentially homogenize the environments to we're able to deliver that petabyte per rack unit ratio that Brian was mentioning be able to deliver over into all tier zero solution that doesn't have to go through woes of software managed data reduction or any kind of software managed hearing just to be always fast, always essentially available from a 100% data availability guaranteed that we offer through a technology called hyper swap, but it's really kind of highlighting what we take in from that simplicity story, by going into that extra mile and meeting the market in technology refresh. I mean, if you say the words IBM over the Thanksgiving table, you're kind of thinking, how big blue, big mainframe, old iron stuff but it's very happy to say over in distributed systems that we are in fact leading this pack by multiple months not just the fact that, "Hey, we announced sooner." But actually coming to delivering on-prem the actual solution itself nine, 10 months prior to anybody else and when that gets us into new density flavors gets us into new efficiency offerings. Not just talk about, "Hey, I can do this petabyte scale "a couple of rack units but with the likes of Brocade." That actually equates to a terabyte per second and a floor tile, what's that do for your analytics story? And the fact that we're now leveraging NBME to undercut the value prop of spinning disc in your HBC analytics environments by five X, that's huge. So now let's take near line SaaS off the table for anything that's actually per data of an angle of value to us. So in simplicity elements, what we're doing now will be able to make our own flash we've been deriving from the tech memory systems acquisition eight years ago and then integrating that into some essentially industry proven software solutions that we do with the bird flies. That appliance form factor has been absolutely monumental for us in the distributed systems. >> And thanks for giving us a topic to discuss at our socially distant Thanksgiving table. We'll talk about IBM. I know now I have great, great conversation. AJ over to you lot of advances here also in such a dynamic times, I want to get Brocade's perspective on how you're taking advantage of these latest technologies with IBM and also from a customer's perspective, what are they feeling and really being able to embrace and utilize that simplicity that Matt talked about. >> So there's a couple of things that fall into that to be honest, one of which is that similar to what you heard Brian described across the IBM portfolio for storage in our SaaS infrastructure. It's a single operating system up and down the line. So from the most entry-level platform we have to the largest platform we have it's a single software up and down. It's a single management environment up and down and it's also intended to be extremely reliable and extremely performance because here's part of the challenge when Matt's talking about multiple petabytes in a two U rack height, but the conversation you want to flip on its head there a little bit is "Okay exactly how many virtual machines "and how many applications are you going to be driving "out of that?" Because it's going to be thousands like between six and 10,000 potentially out of that, right? So imagine then if you have some sort of little hiccup in the connectivity to the data store for 6,000 to 10,000 applications, that's not the kind of thing that people get forgiving about. When we're all home like this. When your healthcare, when your finance, when your entertainment, when everything is coming to you across the network and remotely in this version and it's all application driven, the one thing that you want to make sure of is that network doesn't hiccup because humans have a lot of really good characteristics. Patience would not be one of those. And so you want to make sure that everything is in fact in play and running. And that's as one of the things that we work very hard with our friends at IBM to make sure of is that the kinds of analytics that Matt was just describing are things that you can readily get done. Speed is the new currency of business is a phrase you hear from... A quote you hear from Marc Benioff at Salesforce, right. And he's right if you can get data out of intelligence out of the data you've been collecting, that's really cool. But one of the other sort of flip sides on the people not being able to be in the data center and then to Matt's point, not as many people around either is how are humans fast enough when you look... Honestly when you look at the performance of the platforms, these folks are putting up how is human response time going to be good enough? And we all sort of have this headset of a network operations center where you've got a couple dozen people in a half lit room staring at massive screens on the thing to pop. Okay, if the first time a red light pops the human begins the investigation at what point is that going to be good enough? And so our argument for the autonomy piece of of what we're doing in the fabrics is you can't wait on the humans. You need to augment it. I get that people still want to be in charge and that's good. Humans are still smarter than the Silicon. We're not as repeatable, but we're still so far smarter about it. And so we needed to be able to do that measurement. We need to be able to figure out what normal looks like. We need to be able to highlight to the storage platform and to the application admins, when things go sideways because the demand from the applications isn't going to slow down. The demands from your environment whether you want to think about take the next steps with not just your home entertainment home entertainment systems but learning augmented reality, right. Virtual reality environments for kids, right? How do you make them feel like they're part and parcel of the classroom, for as long as we have to continue living a modified world and perhaps past it, right? If you can take a grade school from your local area and give them a virtual walkthrough of the loop where everybody's got a perfect view and it all looks incredibly real to them those are cool things, right? Those are cool applications, right? If you can figure out a new vaccine faster, right. Not a bad thing, right. If we can model better, not a bad thing. So we need to enable those things we need to not be the bottleneck, which is you get Matt and Brian over an adult beverage at some point and ask them about the cycle time for the Silicon they're playing with. We've never had Moore's law applied to external storage before never in the history of external storage. Has that been true until now. And so their cycle times, Matt, right? >> Yeah you struck a nerve there AJ, cause it's pretty simple for us to follow the linear increase in capacity and computational horsepower, right. We just ride the X86 bandwagon, ride the Silicon bandwagon. But what we have to do in order to maintain But what we have to do in order to maintain the simplicity story is followed more important one is the resiliency factor, right? 'Cause as we increased the capacity as we increased the essentially the amount of data responsible for each admin we have to literally log rhythmically increase the resiliency of these boxes because we're going to talk about petabyte scale systems and hosting them really 10,000 virtual machines in the two U form factor. I need to be able to accommodate that to make sure things don't blip. I need resilient networks, right. Have redundancy and access. I need to have protection schemes at every single layer of the stack. And so we're quite happy to be able to provide that as we leapfrog the industry and go in literally situations that are three times the competitive density that we you see out there and other distributed systems that are still bound by the commercial offerings, then, hey we also have to own that risk from a vendor side we have to make these things is actually rate six protection scheme equivalent from a drive standpoint and act back from controllers everywhere. Be able to supply the performance and consistency of that service throughout even the bad situations. >> And to that point, one of the things that you talked about, that's interesting to me that I'd kind of like you to highlight is your recovery times, because bad things will happen. And so you guys do something very, very different about that. That's critical to a lot of my customers because they know that Murphy will show up one day. So, I mean 'cause it happens, so then what. >> Well, speaking of that, then what Brian I want to go over to you. You mentioned Matt mentioned resiliency. And if we think of the situation that we're in in 2020 many companies are used to DR and BC plans for natural disasters, pandemics. So as we look at the shift and then the the volume of ransomware, that's going up one ransomware attack every 11 seconds this year, right now. How Brian what's that change that businesses need to make from from cyber security to cyber resiliency? >> Yeah, it's a good point in, and I try to hammer that home with our clients that, you're used to having your business continuity disaster recovery this whole cyber resiliency thing is a completely separate practice that we have to set up and think about and go through the same thought process that you did for your DR What are you going to do? What are you going to pretest? How are you going to test it? How are you going to detect whether or not you've got ransomware? So I spent a lot of time with our clients on that theme of you have to think about and build your cyber resiliency plan 'cause it's going to happen. It's not like a DR plan where it's a pure insurance policy and went and like you said, every 11 seconds there's an event that takes place. It's going to be a win not then. Yeah and then we have to work with our customers to put in a place for cyber resiliency and then we spent a lot of discussion on, okay what does that mean for my critical applications, from a restore time of backup and mutability. What do we need for those types of services, right? In terms of quick restore, which are my tier zero applications that I need to get back as fast as possible, what other ones can I they'll stick out on tape or virtual tape in and do things like that. So again, there's a wide range of technology that we have available in the in the portfolio for helping our clients from cyber resiliency. And then we try to distinguish that cyber resiliency versus cyber security. So how do we help to keep every, everybody out from a cybersecurity view? And then what can we do from the cyber resiliency, from a storage perspective to help them once once it gets to us, that's a bad thing. So how can we help? How help our folks recover? Well, and that's the point that you're making Brian is that now it's not a matter of, could this happen to us? It's going to, how much can we tolerate? But ultimately we have to be able to recover. We can't restore that data and one of those things when you talk about ransomware and things, we go to that people as the weakest link insecurity AJ talked about that, there's the people. Yeah there's probably quite a bit of lack of patients going on right now. But as we look as I want to go back over to you to kind of look at, from a data center perspective and these storage solutions, being able to utilize things to help the people, AI and Machine Learning. You talked about AR VR. Talk to me a little bit more about that as you see, say in the next 12 months or so as moving forward, these trends these new solutions that are simplified. >> Yeah, so a couple of things around that one of which is iteration of technology the storage platforms the Silicon they're making use of Matt I think you told me 14 months is the roughly the Silicon cycle that you guys are seeing, right? So performance levels are going to continue to go up the speeds. The speeds are going to continue to go up. The scale is going to is going to continue to shift. And one of the things that does for a lot of the application owners is it lets them think broader. It lets them think bigger. And I wish I could tell you that I knew what the next big application was going to be but then we'd be having a conversation about which Island in the Pacific I was going to be retiring too. But they're going to come and they're going to consume this performance because if you look at the applications that you're dealing with in your everyday life, right. They continue to get broader. The scope of them continues to scale out, right. There's things that we do. I saw I think it was an MIT development recently where they're talking about being able to and they were originally doing it for Alzheimer's and dementia, but they're talking about being able to use the microphones in your smartphone to listen to the way you cough and use that as a predictor for people who have COVID that are not symptomatic yet. So asymptomatic COVID people, right? So when we start talking about where this, where this kind of technology can go and where it can lead us, right. There's sort of this unending possibility for it. But what that on, in part is that the infrastructure has to be extremely sound, right? The foundation has to be there. We have to have the resilience, the reliability and one of the points that Brian was just making is extremely key. We talk about disaster tolerance business continuous, so business continuance is how do you recover? Cyber resilience is the same conversation, right? So you have the protection side of it. Here's my defenses. Now what happens when they actually get in. And let's be honest, right? Humans are frequently that weak link, right. For a variety of behaviors that the humans that humans have. And so when that happens, where's the software in the storage that tells you, "Hey, wait there's an odd traffic behavior here "where data is being copied "at rates and to locations that that are not normal." And so that's part of when we talk about what we're doing in our side of the automation is how do you know what normal looks like? And once you know what normal looks like you can figure out where the outliers are. And that's one of the things that people use a lot for trying to determine whether or not ransomware is going on is, "Hey, this is a traffic pattern, that's new. "This is a traffic pattern. "That's different." Are they doing this because they're copying the dataset from here to here and encrypting it as they go, right? 'Cause that's one of the challenges you got to, you got to watch for. So I think you're going to see a lot of advancement in the application space. And not just the MIT stuff, which is great. The fact that people are actually able to or I may have misspoken, maybe Johns Hopkins. And I apologize to the Johns Hopkins folks that kind of scenario, right. There's no knowing what they can make use of here in terms of the data sets, right. Because we're gathering so much data, the internet of things is an overused phrase but the sheer volume of data that's being generated outside of the data center, but manipulated analyzed and stored internally. 'Cause you got to have it someplace secure. Right and that's one of the things that we look at from our side is we've got to be that as close to unbreakable as we can be. And then when things do break able to figure out exactly what happened as rapidly as possible and then the recovery cycle as well. >> Excellent and I want to finish with you. We just have a few seconds left, but as AJ was talking about this massive evolution and applications, for example when we talk about simplicity and we talk about resiliency and being able to recover when something happens, how did these new technologies that we've been unpacking today? How did these help the admin folks deal with all of the dynamics that are happening today? >> Yeah so I think the biggest the drop, the mic thing we can say right now is that we're delivering 100% tier zero in Vme without data reduction value props on top of it at a cost that undercuts off-prem S3 storage. So if you look at what you can do from an off-prem solution for air gap and from cyber resiliency you can put your data somewhere else. And it's going to take whatever long time to transfer that data back on prem, to read get back to your recover point. But when you work at economics that we're doing right now in the distributed systems, hey, you're DR side, your copies of data do not have to wait for that. Off-prem bandwidth to restore. You can actually literally restore it in place. And you couple that with all of the the technology on the software side that integrates with it I get incremental point in time. Recovery is either it's on the primary side of DRS side, wherever, but the fact that we get to approach this thing from a cost value then by all means I can naturally absorb a lot of the cyber resiliency value in that too. And because it's all getting all the same orchestrated capabilities, regardless of the big, small, medium, all that stuff, it's the same skillsets. And so I don't need to really learn new platforms or new solutions to providing cyber resiliency. It's just part of my day-to-day activity because fundamentally all of us have to wear that cyber resiliency hat. But as, as our job, as a vendor is to make that simple make it cost elegance, and be able to provide a essentially a homogenous solutions overall. So, hey, as your business grows, your risk gets averted on your recovery means also get the thwarted essentially by your incumbent solutions and architecture. So it's pretty cool stuff that we're doing, right. >> It is pretty cool. And I'd say a lot of folks would say, that's the Nirvana but I think the message that the three of you have given in the last 20 minutes or so is that IBM and Brocade together. This is a reality. You guys are a cornucopia of knowledge. Brian, Matt, AJ, thank you so much for joining me on this panel I really enjoyed our conversation. >> Thank you. >> Thank you again Lisa. >> My pleasure. From my guests I'm Lisa Martin. You've been watching this IBM Brocade panel on theCUBE.

>>Hello, everyone. And welcome back to our wall to wall coverage of the data Cloud Summit. This is Dave a lot. And we're seeing the emergence of a next generation workload in the cloud were more facile access and governed. Sharing of data is accelerating. Time to insights and action. All right, allow me to introduce our next guest. Amy Irwin is here. She's the vice president of strategy for experience. And Matt Glickman is VP customer product strategy it snowflake with an emphasis on financial services. Folks, welcome to the Cube. Thanks so much for coming on. >>Thanks for >>having us >>nice to be here. Hey, >>So, Amy, I mean, obviously 2020 has been pretty unique and crazy and challenging time for a lot of people. I don't know why I've been checking my credit score a lot more for some reason. On the app I love the app I got hacked. I had a lock it the other day I locked my credit. Somebody tried to dio on and it worked. I was so happy. So thank you for that. But so we know experience, but there's a ton of data behind what you do. I wonder if you could share kind of where you sit in the data space and how you've seen organizations leverage data up to this point. And really, if you could address maybe some of the changes that you're seeing as a result of the pandemic, that would be great. >>Sure, sure. Well, Azaz, you mentioned experience Eyes best known as a credit bureau. Uh, I work in our marketing services business unit, and what we do is we really help brands leverage the power of data and technology to make the right marketing decisions and better understand and connect with consumers. Eso we offer markers products around data identity activation measurement. We have a consumer view data file that's based on off line P I and contains demographic interest, transaction data and other attributes on about 300 million people in the U. S. Uh, and on the identity side, we've always been known for our safe haven or privacy friendly matching that allows marketers to connect their first party data to experience or other third parties. Uh, but in today's world, with the growth and importance of digital advertising and consumer behavior shifting to digital, uh, experience also is working to connect that offline data to the digital world for a complete view of the customer you mentioned co vid, um, we actually we serve many different verticals. And what we're seeing from our clients during co vid is that there's a bearing impact of the pandemic. The common theme is that those that have successfully pivoted their businesses to digital are doing much better. Uh, as we all know, Kobe accelerated very strong trends to digital both in the commerce and immediate viewing habits. We work with a lot of retailers. Retail is a tale of two cities with big box and grocery growing and apparel retail really struggling. We've helped our clients leveraging our data to better understand the shifts in these consumer behaviors and better segment their customers during this really challenging time. Eso think about there's there's a group of customers that is still staying home that is sheltered in place. There's a group of customers starting that significantly varied their consumer behavior, but it's starting to venture out a little. And then there's a group of customers that's doing largely what they did before and a somewhat modified fashion. So we're helping our clients segment those customers into groups to try and understand the right messaging and right offers for each of those groups. And we're also helping them with at risk audiences. Eso That's more on the financial side. Which of your customers air really struggling? Do the endemic And how do you respond? >>It's awesome, thank you. You know, it's it's funny. I mean somebody I saw Twitter poll today asking if we measure our screen time and I said, Oh my no eso Matt, let me ask you. You spend a ton of time in financial services. You really kind of cut your teeth there, and it's always been very data oriented. You've seen a lot of changes tell us about how your customers are bringing together data, the skills that people obviously a big part of the equation and applications to really put data at the center of their universe. What's new and different that these companies were getting out of the investments in data and skills. >>That's a great question. Um, the acceleration that Amy mentioned Israel, Um, we're seeing it particularly this year, but I think even in the past few years, the reluctance of customers to embrace the cloud is behind us. And now there's this massive acceleration to be able to go faster on, and in some ways the new entrance into this category. Have an advantage versus, you know, the companies that have been in the space within its financial services or beyond. Um, and in a lot of ways they are are seeing the cloud and services like snowflake as a way toe not only catch up but leapfrog your competitors and really deliver a differentiated experience to your customers to your business, internally or externally. Um, and this past, you know, however long this crisis has been going on, has really only accelerated that, because now there's a new demand. Understand your customer better your your business better with with your traditional data sources and also new alternative data sources, Um, and also be able to take a pulse. One of things that we learned which was you know, I opening experience was as the crisis unfolded, one of our data partners decided to take the data sets about where the cases where were happening from the Johns Hopkins and World Health Organization and put that on our platform, and it became a runaway hit where now with thousands of our customers overnight, we're using this data to understand how their business was doing versus how the crisis was unfolding in real time. On this has been a game changer, and I think it's only it's only scratching the surface of what now the world will be able to do when data is really at their fingertips. You're not hindered by your legacy platforms. >>I wrote about that back in the early days of the pandemic when you guys did that and talked about some of the changes that you guys enabled and and, you know you're right about Cloud. I mean, financial services. Cloud used to be an evil word, and now it's almost become a mandate. Amy, I >>wonder if you >>could tell us a little bit more about what? What, you know your customers they're having to work through in order to achieve some of these outcomes. I mean, I'm interested in the starting point. I've been talking a lot and writing a lot on talking to practitioners about what I call the data lifecycle. Sometimes people call it the data pipeline. It za complicated matter, but those customers and companies that can put data at the center and really treat that pipeline is the heart of their organization, If you will, really succeeding. What are you seeing and what really is the starting point there? >>Yes, yes, that's a good question. And as you mentioned, first party, I mean, we start with first party data. Right? First party data is critical to understanding consumers on been in different verticals, different companies. Different brands have varying levels of first party data. So retailers gonna have a lot more first party data financial services company, then say an auto manufacturer. Uh, while many marketers have that first party data to really have a 3 60 view of the customer, they need third party data as well. And that's where experience comes in. We help brands connect those disparate data sets both 1st and 3rd party baked data to better understand consumers and create a single customer view, which has a number of applications. I think the last that I heard was that there's about eight devices on average per person. I always joke that we're gonna have these enormous. I mean, that that number is growing. We're gonna have these enormous charging stations in our house, and I think we're because all the different devices and way seamlessly move from device to device along our customer journey. And, um, if the brand doesn't understand who we are, it's much harder for the brand to connect with consumers and create a positive customer experience and way site that about 95% of companies are actually that they are looking to achieve that single customer view. They recognize, um, that they need that. And they've aligned various teams from e commerce to marketing to sales toe at a minimum in just their first party data and then connect that data to better understand, uh, consumers so consumers can interact with the brand through website and mobile app in store visits, um, by the phone, TV ads, etcetera. And a brand needs to use all of those touchpoints often collected by different parts of the organization and then adding that third party data to really understand the consumers in terms of specific use cases, Um, there's there's about three that come to mind, so there's first. There's relevant advertising and reaching the right customer. There's measurement s or being able to evaluate your advertising efforts. Uh, if you see an ad on the if I see it out of my mobile and then I by by visiting a desktop website understanding or get a direct mail piece, understanding that those connect those interactions are all connected to the same person is critical for measurement. And then there's, uh, there's personalization, um, which includes encourage customer experience amongst your own, um, touch points with that consumer personalized marketing communication and then, of course, um, analytics. So those are the use cases we're seeing? Great. >>Thank you, Amy. I'm out. You can't really talk about data without talking about, >>you know, >>governance and and and compliance. And I remember back in 2006, when the Federal Rules of Civil Procedure went in, it was easy. The lawyers just said, No, nobody can have access, but that's changed. One of things I like about what snowflakes doing with the data cloud is it's really about democratizing access, but doing so in a way that gives people confidence that they only have access to the right data. So maybe you could talk a little bit about how you're thinking about this topic, what you're doing to help customers navigate, which has traditionally been such a really challenging problem. >>No, it's another great question. Um, this is where I think the major disruption is happening. Um, and what Amy described being able to join together 1st and 3rd party data sets. Um, being able to do this was always a challenge because data had to be moved around, had a ship, my first party data to the other side. The third party data had to be shipped to me on being able to join those data sets together, um was problematic at best. And now, with the focus on privacy and protecting P, I, um, this is this is something that has to change. And the good news is with the data cloud data does not have to move. Data can stay where it belongs. Experiencing keep its data experience. Customers can hold on to their data. Yet the data can be joined together on this universal global platform that we call the data cloud. On top of that, and particularly with the regulations that are coming out that are gonna prevent data from being collected on either a mobile device or in wet warren as cookies and Web browsers, new approaches. And we're seeing this a lot in our space, both in financials and in media is to set up these data clean rooms where both sides can give access to one another, but not have to reveal any P i i to do that joint. Um, this is gonna be huge right now. You actually can protect your your customers, private your consumers, private identities, but still accomplish that. Join that Amy mentioned to be able to thio relate the cause and effect of these campaigns and really understand the signals. Um, that these data sets are trying to say about one another again without having to move data without having to reveal P. I We're seeing this happening now. This is this is the next big thing that we're gonna see explode over the next months and years to come. >>I totally agree. Massive changes coming in public policy in this area, and I wanted we only have a few minutes left. I wonder if for our audience members that you know, looking for some advice, what's the what's the one thing you'd recommend? They start doing differently or consider putting in place. That's going to set them up for success over the next decade. >>Yeah, that's a good question. Um, you know, I think e always say, you know, first harness all of your first party data across all touchpoints. Get that first party data in one place and working together Second back that data with trusted third parties and in mats, just in some ways to do that and then third, always with the customer first speak their language. Uh, where and when they want to be, uh, reached out thio on and use the information. You have to really create a better a better customer experience for your customers. >>Matt. What would you add to that? Bring us home if you would >>applications. Um, the idea that data can now be your data can now be pulled into your own business applications the same way that Netflix and Spotify are pulled into your consumer and lifestyle applications again without data moving these personalized applications experiences is what I encourage everyone to be thinking about from first principles. What would you do in your next app that you're gonna build? If you had all of your consumers, consumers had access to their data in the app and not having to think about things you know from scratch. Leverage the data cloud leverage these, you know, service providers like experience and build the applications of tomorrow. >>I'm super excited when I talked to practitioners like yourselves about the future of data Guys, Thanks so much for coming on. The Cube was really a pleasure having you and hope we can continue this conversation in the future. >>Thank you. >>All right. Thank you for watching. Keep it right there. We've got great content. Tons of content coming at the Snowflake Data Cloud Summit. This is Dave Volonte for the Cube. Keep it right there.

>> Hello everyone, and welcome back to our wall-to-wall coverage of the Datacloud summit, this is Dave Vellante, and we're seeing the emergence of a next generation workload in the cloud, more facile access, and governed sharing of data is accelerating time to insights and action. Alright, allow me to introduce our next guest. Aimee Irwin is here, she's the vice president of strategy for Experian, and Matt Glickman is VP of customer product strategy at Snowflake, with an emphasis on financial services, folks, welcome to theCUBE, thanks so much for coming on. >> Thanks Dave, nice to be here. >> Hey so Aimee, obviously 2020's been pretty unique and crazy and challenging time for a lot of people, I don't know why, I've been checking my credit score a lot more for some reason on the app, I love the app, I had to lock it the other day, I locked my credit, somebody tried to do, and it worked, I was so happy, so thank you for that. So, we know Experian, but there's a ton of data behind what you do, I wonder if you could share kind of where you sit in the data space, and how you've seen organizations leverage data up to this point, and really if you could address some of the changes you're seeing as a result of the pandemic, that would be great. >> Sure, sure. Well, as you mentioned, Experian is best known as a credit bureau. I work in our marketing services business unit, and what we do is we really help brands leverage the power of data and technology to make the right marketing decisions, and better understand and connect with consumers. So we offer marketers products around data, identity, activation, measurement, we have a consumer-view data file that's based on offline PII and contains demographic interest, transaction data, and other attributes on about 300 million people in the US. And on the identity side we've always been known for our safe haven, or privacy-friendly matching, that allows marketers to connect their first party data to Experian or other third parties, but in today's world, with the growth in importance of digital advertising, and consumer behavior shifting to digital, Experian also is working to connect that offline data to the digital world, for a complete view of the customer. You mentioned COVID, we actually, we serve many different verticals, and what we're seeing from our clients during COVID is that there's a varying impact of the pandemic. The common theme is that those who have successfully pivoted their businesses to digital are doing much better, as we all know, COVID accelerated very strong trends to digital, both in e-commerce and in media-viewing habits. We work with a lot of retailers, retail is a tale of two cities, with big box and grocery growing, and apparel retail really struggling. We've helped our clients, leveraging our data to better understand the shifts in these consumer behaviors, and better psych-map their customers during this really challenging time. So think about, there's a group of customers that is still staying home, that is sheltered in place, there's a group of customers starting to significantly vary their consumer behavior, but is starting to venture out a little, and then there's a group of customers that's doing largely what they did before, in a somewhat modified fashion, so we're helping our clients segment those customers into groups to try and understand the right messaging and right offers for each of those groups, and we're also helping them with at-risk audiences. So that's more on the financial side, which of your customers are really struggling due to the pandemic, and how do you respond. >> That's awesome, thank you. You know, it's funny, I saw a twitter poll today asking if we measure our screen time, and I said, "oh my, no." So, Matt, let me ask you, you spent a ton of time in financial services, you really kind of cut your teeth there, and it's always been very data-oriented, you're seeing a lot of changes, tell us about how your customers are bringing it together, data, the skills, the people, obviously a big part of the equation, and applications to really put data at the center of the universe, what's new and different that these companies are getting out of the investments in data and skills? >> That's a great question, the acceleration that Aimee mentioned is real. We're seeing, particularly this year, but I think even in the past few years, the reluctance of customers to embrace the cloud is behind us, and now there's this massive acceleration to be able to go faster, and in some ways, the new entrants into this category have an advantage versus the companies that have been in this space, whether it's financial services or beyond, and in a lot of ways, they all are seeing the cloud and services like Snowflake as a way to not only catch up, but leapfrog your competitors, and really deliver a differentiated experience to your customers, to your business, internally or externally. And this past, however long this crisis has been going on, has really only accelerated that, because now there's a new demand to understand your customer better, your business better, with your traditional data sources, and also new, alternative data sources, and also being able to take a pulse. One of the things that we learned, which was an eye-opening experience, was as the crisis unfolded, one of our data partners decided to take the datasets about where the cases were happening from the Johns Hopkins, and World Health Organization, and put that on our platform, and it became a runaway hit. Thousands of our customers overnight were using this data to understand how their business was doing, versus how the crisis was unfolding in real time. And this has been a game-changer, and it's only scratching the surface of what now the world will be able to do when data is really at their fingertips, and you're not hindered by your legacy platforms. >> I wrote about that back in the early days of the pandemic when you guys did that, and talked about some of the changes that you guys enabled, and you know, you're right about cloud, in financial services cloud used to be an evil word, and now it's almost, it's become a mandate. Aimee, I wonder if you could tell us a little bit more about what your customers are having to work through in order to achieve some of these outcomes. I mean, you know, I'm interested in the starting point, I've been talking a lot, and writing a lot, and talking to practitioners about what I call the data life cycle, sometimes people call it the data pipeline, it's a complicated matter, but those customers and companies that can put data at the center and really treat that pipeline as the heart of their organization, if you will, are really succeeding. What are you seeing, and what really is the starting point, there? >> Yes, yeah, that's a good question, and as you mentioned, first party, I mean we start with first party data, right? First party data is critical to understanding consumers. And different verticals, different companies, different brands have varying levels of first party data. So a retailers going to have a lot more first party data, a financial services company, than say, an auto manufacturer. And while many marketers have that first party data, to really have a 360 view of the customer, they need third party data as well, and that's where Experian comes in, we help brands connect those disparate datasets, both first and third party data to better understand consumers, and create a single customer view, which has a number of applications. I think the last stat I heard was that there's about eight devices, on average, per person. I always joke that we're going to have these enormous, and that number's growing, we're going to have these enormous charging stations in our house, and I think we already do, because of all the different devices. And we seamlessly move from device to device, along our customer journey, and, if the brand doesn't understand who we are, it's much harder for the brand to connect with consumers and create a positive customer experience. And we cite that about 95 percent of companies, they are looking to achieve that single customer view, they recognize that they need that, and they've aligned various teams from e-commerce, to marketing, to sales, to at a minimum adjust their first party data, and then connect that data to better understand consumers. So, consumers can interact with a brand through a website, a mobile app, in-store visits, you know, by the phone, TV ads, et cetera, and a brand needs to use all of those touchpoints, often collected by different parts of the organization, and then add in that third party data to really understand the consumers. In terms of specific use cases, there's about three that come to mind. So first there's relevant advertising, and reaching the right customer, there's measurement, so being able to evaluate your advertising efforts, if you see an ad on, if I see an ad on my mobile, and then I buy by visiting a desktop website, understanding, or I get a direct mail piece, understanding that those interactions are all connected to the same person is critical for measurement. And then there's personalization, which includes improved customer experience amongst your own touchpoints with that consumer, personalized marketing communication, and then of course analytics, so those are the use cases we're seeing. >> Great, thank you Aimee. Now Matt, you can't really talk about data without talking about governance and compliance, and I remember back in 2006, when the federal rules of civil procedure went in, it was easy, the lawyers just said, "no, nobody can have access," but that's changed, and one of the things I like about what Snowflake's doing with the data cloud is it's really about democratizing access, but doing so in a way that gives people confidence that they only have access to the right data. So maybe you could talk a little bit about how you're thinking about this topic, what you're doing to help customers navigate, which has traditionally been such a really challenging problem. >> Another great question, this is where I think the major disruption is happening. And what Aimee described, being able to join together first and third party datasets, being able to do this was always a challenge, because data had to be moved around, I had to ship my first party data to the other side, and the third party data had to be shipped to me, and being able to join those datasets together was problematic at best, and now with the focus on privacy and protecting PII, this is something that has to change, and the good news is, with the data cloud, data does not have to move. Data can stay where it belongs, Experian can keep its data, Experian's customers can hold onto their data, yet the data can be joined together on this universal, global platform that we call the data cloud. On top of that, and particularly with the regulations that are coming out that are going to prevent data from being collected on either a mobile device or as cookies on web browsers, new approaches, and we're seeing this a lot in our space, both in financials and media, is to set up these data clean rooms, where both sides can give access to one another, but not have to reveal any PII to do that join. This is going to be huge, now you actually can protect your customers' and your consumers' private identities, but still accomplish that join that Aimee mentioned, to be able to relate the cause and effect of these campaigns, and really understand the signals that these datasets are trying to say about one another, again without having to move data, without having to reveal PII, we're seeing this happening now, this is the next big thing, that we're going to see explode over the months and years to come. >> I totally agree, massive changes coming in public policy in this area, and we only have a few minutes left, and I wonder if for our audience members that are looking for some advice, what's the, Aimee, what's the one thing you'd recommend they start doing differently, or consider putting in place that's going to set them up for success over the next decade? >> Yeah, that's a good question. You know, I think, I always say, first, harness all of your first party data across all touchpoints, get that first party data in one place and working together, second, connect that data with trusted third parties, and Matt suggested some ways to do that, and then third, always put the customer first, speak their language, where and when they want to be reached out to, and use the information you have to really create a better customer experience for your customers. >> Matt, what would you add to that? Bring us home, if you would. >> Applications. The idea that data, your data can now be pulled into your own business applications the same way that Netflix and Spotify are pulled into your consumer and lifestyle applications, again, without data moving, these personalized application experiences is what I encourage everyone to be thinking about from first principles. What would you do in your next app that you're going to build, if you had all your consumers, if the consumers had access to their data in the app, and not having to think about things from scratch, leverage the data cloud, leverage these service providers like Experian, and build the applications of tomorrow. >> I'm super excited when I talk to practitioners like yourselves, about the future of data, guys, thanks so much for coming on theCUBE, it was a really a pleasure having you, and I hope we can continue this conversation in the future. >> Thank you. >> Thanks. >> Alright, thank you for watching, keep it right there, we got great content, and tons of content coming at the Snowflake data cloud summit, this is Dave Vellante for theCUBE, keep it right there.

>>Hello, everyone. And welcome back to our wall to wall coverage of the data Cloud Summit. This is Dave a lot. And we're seeing the emergence of a next generation workload in the cloud were more facile access and governed. Sharing of data is accelerating. Time to insights and action. All right, allow me to introduce our next guest. Amy Irwin is here. She's the vice president of strategy for experience. And Matt Glickman is VP customer product strategy it snowflake with an emphasis on financial services. Folks, welcome to the Cube. Thanks so much for coming on. >>Thanks for >>having us >>nice to be here. Hey, >>So, Amy, I mean, obviously 2020 has been pretty unique and crazy and challenging time for a lot of people. I don't know why I've been checking my credit score a lot more for some reason. On the app I love the app I got hacked. I had a lock it the other day I locked my credit. Somebody tried to dio on and it worked. I was so happy. So thank you for that. But so we know experience, but there's a ton of data behind what you do. I wonder if you could share kind of where you sit in the data space and how you've seen organizations leverage data up to this point. And really, if you could address maybe some of the changes that you're seeing as a result of the pandemic, that would be great. >>Sure, sure. Well, Azaz, you mentioned experience Eyes best known as a credit bureau. Uh, I work in our marketing services business unit, and what we do is we really help brands leverage the power of data and technology to make the right marketing decisions and better understand and connect with consumers. Eso We offer marketers products around data identity activation measurement. We have a consumer view data file that's based on offline P I and contains demographic interest, transaction data and other attributes on about 300 million people in the U. S. Uh, and on the identity side, we've always been known for our safe haven or privacy friendly matching that allows marketers to connect their first party data to experience or other third parties. Uh, but in today's world, with the growth and importance of digital advertising and consumer behavior shifting to digital, uh, experience also is working to connect that offline data to the digital world for a complete view of the customer you mentioned co vid, um, we actually, we start of many different verticals. And what we're seeing from our clients during co vid is that there's a bearing impact of the pandemic. The common theme is that those that have successfully pivoted their businesses to digital are doing much better. Uh, as we all know, Kobe accelerated very strong trends to digital both in the commerce and immediately eating habits. We work with a lot of retailers. Retail is a tale of two cities with big box and grocery growing and apparel retail really struggling. We've helped our clients leveraging our data to better understand the shifts in these consumer behaviors and better segment their customers during this really challenging time. Eso think about there's there's a group of customers that it's still staying home that is sheltered in place. There's a group of customers starting that significantly varied their consumer behavior, but it's starting to venture out a little. And then there's a group of customers that's doing largely what they did before in a somewhat modified fashion. So we're helping our clients segment those customers into groups to try and understand the right messaging and right offers for each of those groups. And we're also helping them with at risk. Audi's is S O. That's more on the financial side. Which of your customers are really struggling due to the pandemic. And how do you respond? >>So it's awesome. Thank you. You know it Zafon e I mean somebody. I saw Twitter poll today asking if we measure our screen time and I said, Oh my no eso Matt, let me ask you. You spend a ton of time and financial services. You really kind of cut your teeth there, and it's always been very data oriented. You've seen a lot of changes tell us about how your customers are bringing together data, the skills that people obviously a big part of the equation and applications to really put data at the center of their universe. What's new and different that these companies are getting out of the investments in data and skills. >>That's a great question. Um, the acceleration that Amy mentioned Israel, Um, we're seeing a particularly this year, but I think even in the past few years, the reluctance of customers to embrace. The cloud is behind us. And now there's this massive acceleration to be able to go faster on, and in some ways the new entrance into this category have an advantage versus, you know, the companies that have been in the space, whether it's financial services or beyond. Um, and in a lot of ways they are are seeing the cloud and services like snowflakes as a way toe not only catch up but leapfrog your competitors and really deliver a differentiated experience to your customers to your business, internally or externally. Um, and this past, you know, however long this crisis has been going on, has really only accelerated that, because now there's a new demand. Understand your customer better your your business better with with your traditional data sources and also new alternative data sources, Um, and also be able to take a pulse. One of things that we learned which was you know, I opening experience was as the crisis unfolded, one of our data partners decided to take the data sets about where the cases where were happening from the Johns Hopkins and World Health Organization and put that on our platform and it became a runaway hit. Where now, with thousands of our customers overnight, we're using this data to understand how their business was doing versus how the crisis was unfolding in real time. On this has been a game changer, and I think it's only it's only scratching the surface of what now the world will be able to do when data is really at their fingertips. You're not hindered by your legacy platforms. >>I wrote about that back in the early days of the pandemic when you guys did that and talked about some of the changes that you guys enabled. And you know you're right about Cloud. I mean, financial services. Cloud used to be an evil word, and now it's almost become a mandate. Amy, I >>wonder if you >>could tell us a little bit more about what? What you know your customers they're having to work through in order to achieve some of these outcomes. I mean, I'm interested in the starting point. I've been talking a lot and writing a lot on talking to practitioners about what I call the data lifecycle. Sometimes people call it the data pipeline. It's it's a complicated matter, but those customers and companies that can put data at the center and really treat that pipeline is, you know, the heart of their organization, if you will, Really succeeding. What are you seeing and what really is the starting point there? >>Yes, yes, that's a good question. And as you mentioned, first party, I mean, we start with first party data. Right? First party data is critical to understanding consumers on been in different verticals, different companies. Different brands have varying levels of first party data. So retailers gonna have a lot more first party data financial services company, then say an auto manufacturer. Uh, while many marketers have that first party data to really have a 3 60 view of the customer, they need third party data as well. And that's where experience comes in. We help brands connect those disparate data sets both 1st and 3rd party baked data to better understand consumers and create a single customer view, which has a number of applications. I think the last that I heard was that there's about eight devices on average per person. I always joke that we're gonna have these enormous. I mean, that that number is growing we're gonna have these enormous charging stations in our house, and I think we're because all the different devices and way seamlessly move from device to device along our customer journey. And, um, if the brand doesn't understand who we are, it's much harder for the brand to connect with consumers and create a positive customer experience and way site that about 95% of companies are actually that they are looking to achieve that single customer view. They recognize, um, that they need that. And they've aligned various teams from e commerce to marketing to sales so at a minimum in just their first party data, and then connect that data to better understand, uh, consumers. So consumers can interact with the brand through website and mobile app in store visits, um, by the phone TV ad, etcetera. And a brand needs to use all of those touchpoints often collected by different parts of the organization and then adding that third party data to really understand the consumers in terms of specific use cases, Um, there's there's about three that come to mind. So there's first. There's relevant advertising and reaching the right customer. There's measurement s or being able to evaluate your advertising efforts. Uh, if you see an ad on if I see it out of my mobile and then I by by visiting a desktop website, understanding or I get a direct mail piece understanding that those connect those interactions are all connected to the same person is critical for measurement. And then there's, uh, there's personalization, um, which includes improved customer experience amongst your own, um, touch points with that consumer Parsons marketing communication and then, of course, um, analytics. So those are the use cases we're seeing? Great. >>Thank you, Amy. I'm at you Can't really talk about data without talking about, >>you know, >>governance and and and compliance. And I remember back in 2006 when the Federal Rules of Civil Procedure went in, it was easy. The lawyers just said, No, nobody can have access, but that's changed. One of things I like about what snowflakes doing with the data cloud is it's really about democratizing access, but doing so in a way that gives people confidence that they only have access to the right data. So maybe you could talk a little bit about how you're thinking about this topic what you're doing to help customers navigate, which has traditionally been such a really challenging problem. >>No, it's another great question. Um, this is where I think the major disruption is happening. Um, and what Amy described being able to join together 1st and 3rd party data sets. Um, being able to do this was always a challenge because data had to be moved around, had to ship my first party data to the other side. The third party data had to be shipped to me. And being able to join those data sets together, um was problematic at best. And now, with the focus on privacy and protecting P, I, um, this is this is something that has to change. And the good news is with the data cloud data does not have to move. Data can stay where it belongs experience and keep its data experience. Customers can hold on to their data. Yet the data can be joined together on this universal global platform that we call the data cloud. On top of that, and particularly with the regulations that are coming out that are going to prevent data from being collected on either a mobile device or in wet warn as cookies and Web browsers. New approaches and we're seeing this a lot in our space, both in financials and in media is to set up these data clean rooms where both sides can give access to one another but not have to reveal any P i i to do that joint. Um, this is gonna be huge right now. You actually can protect your your customers, private your consumers, private identities, but still accomplish that. Join that Amy mentioned to be able to thio, relate the cause and effect of these campaigns and really understand the signals that these data sets are trying to say about one another again without having to move data without having to reveal P. I We're seeing this happening now. This is this is the next big thing that we're gonna see explode over the next months and years to come. >>I totally agree massive changes coming in public policy in this area, and I wanted we only have a few minutes left. I wonder if for our audience members that you know, looking for some advice, what's the what's the one thing you'd recommend? They start doing differently or consider putting in place That's going to set them up for success over the next decade. >>Yeah, that's a good question. Um, you know, I think e always say, you know, first harness all of your first party data across all touchpoints. Get that first party data in one place and working together psychic back that data with trusted third parties and mats, just in some ways to do that and then third, always with the customer first speak their language, uh, where and when they want to be, uh, reached out thio on and use the information. You have to really create a better a better customer experience for your customers. >>Matt. What would you add to that? Bring us home if you would >>applications. Um, the idea that data can now be your data can now be pulled into your own business applications the same way that Netflix and Spotify are pulled into your consumer and lifestyle applications again without data moving these personalized applications experiences is what I encourage everyone to be thinking about from first principles. What would you do in your next app that you're going to build? If you had all of your consumers. Consumers had access to their data in the APP and not having to think about things, you know, from scratch. Leverage the data cloud leverage these, you know, service providers like experience and build the applications of tomorrow. >>I'm super excited when I talked to practitioners like yourselves about the future of data Guys. Thanks so much for coming on. The Cube was really a pleasure having you and hope we can continue this conversation in the future. >>Thank you. >>Anything. >>All right. Thank you for watching. Keep it right there. We've got great content. Tons of content coming at the Snowflake Data Cloud Summit. This is Dave Volonte for the Cube. Keep it right there.

>> Hello, welcome to the final day of the NTT Research Summit Upgrade 2020. My name is Joe Alexander and I belong to the Medical and Health Informatics lab, so-called MEI lab, and I lead the development of the bio digital twin. I'd like to give you a high level overview of what we mean by bio digital twin, what some of our immediate research targets are, and a description of our overall approach. You will note that my title is not simply bio digital twin, but more specifically a cardiovascular bio digital twin and you'll soon understand why. What do we mean by digital twin? For our project, we're taking the definition on approach used in commercial aviation, mostly for predictive maintenance of jet engines. A digital twin is an up-to-date virtual representation, an electronic replica if you will. Now, if anything which gives you real-time insight into the status of the real-world asset to enable better management and to inform decision-making. It aims to merge the real and the virtual world. It enables one to design, simulate, and verify products digitally, including mechanics and multi-physics. It allows integration of complex systems. It allows for predictive maintenance through direct real-time monitoring of the health and structure of the plane parts, mitigating danger. It enables monitoring of all machines anywhere at all times. This allows feeding back insights to continuously optimize the digital twin of the product, which in turn leads to continuous improvement of the product in the real world. A robust platform is needed for digital twins to live, learn and run. Because we aim to apply these concepts to biological systems for predictive maintenance of health, we use the term bio digital twin. We're aiming for a precision medicine and predictive health maintenance. And while ultimately we intend to represent multiple organ systems and the diseases affecting them, we will start with the cardiovascular system. When we revisit concepts from the last slide, there's the one-to-one mapping as you can see on this slide. A cardiovascular bio digital twin is an up-to-date virtual representation as well, but of a cardiovascular system, which gives you real-time insight into the status of the cardiovascular system of a real world patient to enable better care management and to inform clinical decision-making. It does so by merging the real and virtual world. It enables one to design, simulate, and verify drug and device treatments digitally, including cardiovascular mechanics and multi-physics. It allows integration of complex organ systems. It allows for predictive maintenance of health care through direct real-time monitoring of the health and functional integration, or excuse me, functional integrity of body parts, mitigating danger. It enables monitoring of all patients anywhere at all times. This allows feedback to continuously optimize the digital twins of subjects, which in turn leads to continuous improvements to the health of subjects in the real world. Also a robust platform is needed for digital twins to live, learn, and run. One platform under evaluation for us is called embodied bio-sciences. And it is a cloud-based platform leveraging AWS distributed computing database and cuing solutions. There are many cardiovascular diseases that might be targeted by cardiovascular bio digital twin. We have chosen to focus on the two most common forms of heart failure, and those are ischemic heart failure and hypertensive heart failure. Ischemic heart failure is usually due to coronary artery disease and hypertensive heart failure usually is secondary to high blood pressure. By targeting heart failure, number one, it forces us to automatically incorporate biological mechanisms, common to many other cardiovascular diseases. And two, heart failure is an area of significant unmet medical need, especially given the world's aging population. The prevalence of heart failure is estimated to be one to one and a half. I'm sorry, one to 5% in the general population. Heart failure is a common cause of hospitalization. The risk of heart failure increases with age. About a third to a half of the total number of patients diagnosed with heart failure, have a normal ejection fraction. Ischemic heart failure occurs in the setting of an insult to the coronary arteries causing atherosclerosis. The key physiologic mechanisms of ischemic heart failure are increased myocardial oxygen demand in the face of a limited myocardial oxygen supply. And hypertensive heart failure is usually characterized by complex myocardial alterations resulting from the response to stress imposed by the left ventricle by a chronic increase in blood pressure. In order to achieve precision medicine or optimized and individualized therapies for heart failure, we will develop three computational platforms over a five-year period. A neuro-hormonal regulation platform, a mechanical adaptation platform and an energetics platform. The neuro-hormonal platform is critical for characterizing a fundamental feature of chronic heart failure, which is neuro-humoral activation and alterations in regulatory control by the autonomic nervous system. We will also develop a mechanical adaptation and remodeling platform. Progressive changes in the mechanical structure of the heart, such as thickening or thinning a bit muscular walls in response to changes in workloads are directly related to future deterioration in cardiac performance and heart failure. And we'll develop an energetics platform, which includes the model of the coronary circulation, that is the blood vessels that supply the heart organ itself. And will thus provide a mechanism for characterizing the imbalances between the oxygen and metabolic requirements of cardiac tissues and their lack of availability due to neuro-hormonal activation and heart failure progression. We consider it the landscape of other organizations pursuing innovative solutions that may be considered as cardiovascular bio digital twins, according to a similar definition or conceptualization as ours. Some are companies like the UT Heart, Siemens Healthineers, Computational Life. Some are academic institutions like the Johns Hopkins Institute for Computational Medicine, the Washington University Cardiac Bio Electricity and Arrhythmia Center. And then some are consortia such as echos, which stands for enhanced cardiac care through extensive sensing. And that's a consortium of academic and industrial partners. These other organizations have different aims of course, but most are focused on cardiac electrophysiology and disorders of cardiac rhythm. Most use both physiologically based and data driven methods, such as artificial intelligence and deep learning. Most are focused on the heart itself without robust representations of the vascular load, and none implement neuro hormonal regulation or mechanical adaptation and remodeling, nor aim for the ultimate realization of close loop therapeutics. By autonomous closed loop therapeutics, I mean, using the cardiovascular bio digital twin, not only to predict cardiovascular events and determine optimal therapeutic interventions for maintenance of health or for disease management, but also to actually deliver those therapeutic interventions. This means not only the need for smart sensors, but also for smart actuators, smart robotics, and various nanotechnology devices. Going back to my earlier comparisons to commercial aviation, autonomous closed loop therapeutics means not only maintenance of the plane and its parts, but also the actual flying of the plane in autopilot. In the beginning, we'll include the physician pilots in the loop, but the ultimate goal is an autonomous bio digital twin system for the cardiovascular system. The goal of realizing autonomous closed loop therapeutics in humans is obviously a more longterm goal. We're expecting to demonstrate that first in animal models. And our initial thinking was that this demonstration would be possible by the year 2030, that is 10 years. As of this month, we were planning ways of reaching this target even sooner. Finally, I would also like to add that by setting our aims at such a high ambition target, we drive the quality and accuracy of old milestones along the way. Thank you. This concludes my presentation. I appreciate your interest and attention. Please enjoy the remaining sessions, thank you.

>> Narrator: From around the globe, it's "theCUBE" with digital coverage of Smart Data Marketplaces brought to you by Io-Tahoe. >> We're back. We're talking about smart data and have been for several weeks now. Really it's all about injecting intelligence and automation into the data life cycle of the data pipeline. And today we're drilling into Smart Data Marketplaces, really trying to get to that self-serve, unified, trusted, secured, and compliant data models. And this is not trivial. And with me to talk about some of the nuances involved in actually getting there with folks that have experienced doing that. They'd send a series of digital evangelist with Tata Consultancy Services, TCS. And Ajay Vohora is back, he's the CEO of Io-Tahoe. Guys, great to see you, thanks so much for coming on. >> Good to see you, Dave. >> Hey Dave. >> Ajay, let's start with you. Let's set up the sort of smart data concept. What's that all about? What's your perspective? >> Yeah, so I mean, our way of thinking about this is you you've got data, it has latent value, and it's really about discovering what the properties of that data. Does it have value? Can you put that data to work? And the way we go about that with algorithms and machine learning, to generate signals in that data identified patterns, that means we can start to discover how can we apply that data to down stream? What value can we unlock for a customer and business? >> Well, so you've been on this, I mean, really like a laser, why? I mean, why this issue? Did you see a gap in the marketplace in terms of talking to customers and maybe you can help us understand the origin? >> Yeah, I think that the gap has always been there. They've been, it's become more apparent over recent times with big data. So the ability to manually work with volumes of data in petabytes is prohibitively complex and expensive. So you need the different routes, you need different set of tools and methods to do that. Metadata are data that you can understand about data. That's what we at Io-Tahoe focus on, discovering and generating that metadata. That ready, that analogy to automate those data ops processes. So the gap David, is being felt by a business owner prizes and all sectors, healthcare, telecoms, and putting that data to work. >> So Ved, Let's talk a little bit about your role. You work with a lot of customers. I see you as an individual in a company who's really trying to transform what is a very challenging industry. That's sort of ripe for transformation, but maybe you could give us your perspective on this, what kind of signals you're looking for from the data pipeline and we'll get into how you are helping transform healthcare? >> Thanks, David. You know I think this year has been one of those years where we've all realized about this idea of unknown unknowns, where something comes around the corner that you're completely not expecting. And that's really hard to plan for obviously. And I think what we need is the ability to find early signals and be able to act on things as soon as you can. Sometimes, and you know, the COVID-19 scenario of course, is hopefully once in a generation thing, but most businesses struggle with the idea that they may have the data there in their systems, but they still don't know which bit of that is really valuable and what are the signals they should be watching for. And I think the interesting thing here is the ability for us to extract from a massive data, the most critical and important signals. And I think that's where we want to focus on. >> And so, talk a little bit about healthcare in particular and sort of your role there, and maybe at a high level. How Tata and your eco-system are helping transform healthcare? >> So if you look at healthcare, you've got the bit where people need active intervention from a medical professional. And then you've got this larger body of people, typically elderly people who aren't unwell, but they have frailties. They have underlying conditions and they're very vulnerable, especially in the world that we're in now in the post-COVID-19 scenario. And what we were trying to look at is how do we keep people who are elderly, frail and vulnerable? How can we keep them safe in their own homes rather than moving to care homes, where there has been an incredibly high level of infection for things like COVID-19. So the world works better if you can keep people safe in their own homes, if you can see the slide we've got. We're also talking about a world where care is expensive. In most Western countries, especially in Western Europe, the number of elderly people is increasing as a percentage of the population, quite significantly, and resources just are not keeping up. We don't have enough people. We don't have enough funding to look after them effectively. And the care industry that used to do that job has been struggling of late. So it's kind of a perfect storm for the need for technology intervention there. And in that space, what we're saying is the data signal that we want to receive are exactly what as a relative, or a son or daughter you might want from a parent to say, "Everything's okay. "We know that today's been just like every other day "there are no anomalies in your daily living." If you could get the signals that might tell us that something's wrong, something not quite right. We don't need very complex diagnostics. We just need to know something's not quite right, that my dad hasn't woken up as has always at seven o'clock, but till nine o'clock there's no movement. Maybe he's a bit unwell. It's that kind of signal that if we can generate, can make a dramatic difference to how we can look out for these people, whether through professional carers or through family members. So what we're looking to do is to sensor-enable homes of vulnerable people so that those data signals can come through to us in a curated manner, in a way that protects privacy and security of the individual, but gives the right people, which is carers or chosen family members the access to the signals, which is alerts that might tell you there was too much movement at night, or the front door was been left open, things like that that would give you a reason to call him and check. Everybody has spoken to in this always has an example of an uncle or a relative or parent that they've looked after. And all they're looking for is a signal. Even stories like my father's neighbor calls me when he doesn't open his curtain by 11 o'clock, that actually, if you think about it is a data signal that something might be all right. And I think what we're trying to do with technology is create those kinds of data signals because ultimately, the healthcare system works much better if you can prevent rather than cure. So every dollar that you put into prevention saves maybe $3 to $5 downstream. The economic summit also are working our favor. >> And those signals give family members the confidence to act. Ajay, it is interesting to hear what Ved was talking about in terms of the unknowns, because when you think about the early days of the computer industry, there were a lot of knowns, the processes were known. It was like the technology was the big mystery. Now, I feel like it's flipped. We've certainly seen that with COVID. The technology is actually quite well understood and quite mature and reliable. One of the examples is automated data discovery, which is something that you guys have been been focused on at Io-Tahoe. Why is automated data discovery such an important component of a smart data life cycle? >> Yeah. I mean, if we look David at the schematic and this one moves from left to right where right at the outset with that latent data, the value is late because you don't know. Does it have? Can it be applied? Can that data be put to work or not? And the objective really is about driving some form of exchange or monetization of data. If you think about it in insurance or healthcare, you've got lots of different parties, providers, payers, patients, everybody's looking to make some kind of an exchange of information. The difficulty is in all of those organizations, that data sits within its own system. So data discovery, if we drill into the focus itself that, it's about understanding which data has value, classifying that data so that it can be applied and being able to tag it so that it can then be put to use it's the real enabler for DataOps. >> So maybe talk a little bit more about this. We're trying to get to self-service. It's something that we hear a lot about. You mentioned putting data to work. It seems to me that if the business can have access to that data and serve themselves, that's the way to put data to work. Do you have thoughts on that? >> Yeah, I mean, thinking back in terms of what IT and the IT function in a business could provide, there have been limitations around infrastructure, around scaling, around compute. Now that we're in an economy that is digital driven by API's your infrastructure, your data, your business rules, your intelligence, your models, all of those on the back of an API. So the options become limitless. How you can drive value and exchange that data. What that allows us to do is to be more creative, if we can understand what data has value for what use case. >> Ved, Let's talk a little bit about the US healthcare system. It's a good use case. I was recently at a chief data officer conference and listening to the CDO of Johns Hopkins, talk about the multiple different formats that they had to ingest to create that COVID map. They even had some PDFs, they had different definitions, and that's sort of underscored to me, the state of the US healthcare industry. I'm not as familiar with the UK and Europe generally, but I am familiar with the US healthcare system and the diversity that's there, the duplication of information and the like, maybe you could sort of summarize your perspectives and give us kind of the before and your vision of the after, if you will? >> The use of course, is particularly large and complex system. We all know that. We also know, I think there is some research that suggests that in the US the per-capita spend on healthcare is among the highest in the world. I think it's like 70%, and that compares to what just under 9%, which is going to be European, typical European figure. So it's almost double of that, but the outcomes are still vastly poor. When Ajay and I were talking earlier, I think we believe that there is a concept of a data friction. When you've got multiple players in an eco-system, trying to provide a single service as a patient, you're receiving a single health care service. There are probably a dozen up to 20 different organizations that have to collaborate to make sure you get that top of the line health care service. That kind of investment deserves. And what prevents it from happening very often is what we would call data friction, which is the ability to effectively share data. Something as simple as a healthcare record, which says, "This is Dave, this is Ved, this is Ajay." And when we go to hospital for anything, whatever happens, that healthcare record can capture all the information and tie to us as an individual. And if you go to a different hospital, then that record will follow you. This is how you would expect that to be implemented, but I think we're still on that journey. There are lots and lots of challenges. I've seen anecdotal data around people who suffered because they weren't carrying a card when they went into hospital, because that card has the critical elements of data, but in today's world, should you need to carry a piece of paper or can the entire thing be a digital data flow that can easily be, can certainly navigate through lack of paper and those kinds of things. So the vision that I think we need to be looking at is an effective data exchange or marketplace back with a kind of a backbone model where people agree and sign off a data standard, where each individual's data is always tied to the individual. So if you were to move States, if you would move providers, change insurance companies, none of that would impact your medical history, your data, and the ability to have the other care and medical professionals to access the data at the point of need and at the point of healthcare delivery. So I think that's the vision we're looking at, but as you rightly you said that there are enormous number of challenges, partly because of the history, of healthcare, I think it was technology enablement of healthcare started early. So there's a lot of legacy as well. So we shouldn't trivialize the challenges that the industry faces, but that I think is the way we want to go. >> Well, privacy is obviously a huge one, and a lot of the processes are built around non-digital processes and what you're describing as a flip for digital first. I mean, as a consumer, as a patient, I want an app for that. So I can see my own data. I can see price, price transparency, give access to people that I think need it. And that is a daunting task, isn't it? >> Absolutely. And I think the implicit idea and what you just said, which is very powerful is also on the app you want to control. >> Yes. >> And sometimes you want to be able to change access on data at that point. Right now, I'm at the hospital. I would like to access my data. And when I walk away or maybe three days later, I want to revoke that access. It's that level of control. And absolutely, it is by no means a trivial problem, but I think that's where you need the data automation tools. If you try to do any of this manually, we'd be here for another decade trying to solve this, but that's where tools like Io-Tahoe come in because to do this, a lot of the heavy lifting behind the scenes has to be automated. There has to be a machine churning that and presenting the simpler options. And I know you were talking about it just a little while ago Ajay. I was reminded of the example of a McDonald's or a Coke, because the sales store idea that you can go in and you can do your own ordering off a menu, or you can go in and select five different flavors from a Coke machine and choose your own particular blend of Coke. It's a very trivial example, but I think that's the word we want to get to with access of data as well. If it was that simple for consumers, for enterprise, business people, for doctors, then that's where we ultimately want to be able to arrive. But of course, to make something very simple for the end-user, somebody has to solve for complexity behind the scenes. >> So Ajay, it seems to me Ajay there're two major outcomes here. One is of course, the most important I guess, is patient outcomes, and the other is cost. I mean, they talked about the cost issues, we all, US especially understand the concerns about rising costs of healthcare. My question is this, how does a Smart Data Marketplace fit into achieving those two very important outcomes? >> When we think about how automation is enabling that, where we've got different data formats, the manual tasks are involved, duplication of information. The administrative overhead of that alone and the work, the rework, and the cycles of work that generates. That's really what we're trying to help with data is to eliminate that wasted effort. And with that wasted effort comes time and money to employ people to work through those siloed systems. So getting to the point where there is an exchange in a marketplace just as they would be for banking or insurance is really about automating the classification of data to make it available to a system that can pick it up through an API and to run a machine learning model and to manage a workflow, a process. >> Right, so you mentioned backing insurance, you're right. I mean, we've actually come a long way and just in terms of, know the customer and applying that to know the patient would be very powerful. I'm interested in what you guys are doing together, just in terms of your vision. Are you going to market together, kind of what you're seeing in terms of promoting or enabling this self-service, self-care. Maybe you could talk a little bit about Io-Tahoe and Tata, the intersection at the customer? >> Sure. I think we've been very impressed with the TCS vision of 4.0, how the re-imagining traditional industries, whether it's insurance, banking, healthcare, and bringing together automation, agile processes, robotics, AI, and once those enablers, technology may have brought together to re-imagine how those services can be delivered digitally. All of those are dependent on data. So we see that there's a really good fit here to enable understanding the legacy, the historic situation that has built up over time in an organization, a business and to help shine a light on what's meaningful in that to migrate to the cloud or to drive a digital twin, data science project. >> Ved, anything you can add to that? >> Sure. I mean, we do take the business 4.0 model quite seriously in terms of a lens with which you look at any industry, and what I talked about in healthcare was an example of that. And for us business 4.0, means a few very specific things. The technology that we use in today's verse should be agile, automated, intelligent, and cloud-based. These have become kind of hygiene factors now. On top of that, the businesses we build should be mass customized. They should be risk embracing. They should engage ecosystems, and they should strive for exponential value, not 10% growth year on year, but doubling, tripling every three, four years, because that's the competition that most businesses are facing today. And within that, the Tata group itself, is an extremely purpose-driven business. We really believe that we exist to serve communities, not just one specific set, i.e. shareholders, but the broader community in which we live and work. And I think this framework also allows us to apply that to things like healthcare, to education and to a whole vast range of areas where, everybody has a vision of using data science or doing really clever stuff at the gradients. But what becomes clear is, to do any of that, the first thing you need is a foundational piece. And as a foundation isn't right, then no matter how much you invest in the data science tools you won't get the answers you want. And the work we're doing with the Io-Tahoe really, for me, is particularly exciting because it sorts out that foundational piece. And at the end of it, to make all of this, again, I will repeat that, to make it simple and easy to use for the end user, whoever that is. And I realized that I'm probably the first person who's used fast food as a shining example for healthcare in this discussion, but you can make a lot of different examples. And today, if you press a button and start a car, that's simplicity, but someone has solved for that. And that's what we want to do with data as well. >> Yeah, that makes a lot of sense to me. We talk a lot about digital transformation and a digital business, and I would observe that a digital business puts data at the core. And you can certainly be the best example. There is, of course, Google is an all digital business, but take a company like Amazon, Who's got obviously a massive physical component to its business. Data is at the core. And that's exactly my takeaway from this discussion. Both of you are talking about putting data at the core, simplifying it, making sure that it's compliant, and healthcare it's taking longer, 'cause it's such a high risk industry, but it's clearly happening, COVID I guess, was an accelerant. Guys, Ajay, I'll start with you. Any final thoughts that you want to leave the audience with? _ Yeah, we're really pleased to be working with TCS. We've been able to explore how we're able to put dates to work in a range of different industries. Ved has mentioned healthcare, telecoms, banking and insurance are others. And the same impact they speak to whenever we see the exciting digital transformations that are being planned, being able to accelerate those, unlock the value from data is where we're having a purpose. And it's good that we can help patients in the healthcare sector, consumers in banking realize a better experience through having a more joined up marketplace with their data. >> Ved, you know what excites me about this conversation is that, as a patient or as a consumer, if I'm helping loved ones, I can go to the web and I can search, and I can find a myriad of possibilities. What you're envisioning here is really personalizing that with real time data. And that to me is a game changer. Your final thoughts? >> Thanks, David. I absolutely agree with you that the idea of data centricity and simplicity are absolutely forefront, but I think if we were to design an organization today, you might design it very differently to how most companies today are structured. And maybe Google and Amazon are probably better examples of that because you almost have to think of a business as having a data engine room at its core. A lot of businesses are trying to get to that stage, whereas what we call digital natives, are people who have started life with that premise. So I absolutely agree with you on that, but extending that a little bit. If you think of most industries as eco-systems that have to collaborate, then you've got multiple organizations who will also have to exchange data to achieve some shared outcomes. Whether you look at supply chains of automobile manufacturers or insurance companies or healthcares we've been talking about. So I think that's the next level of change we want to be able to make, which is to be able to do this at scale across organizations at industry level or in population scheme for healthcare. >> Yeah, Thank you for that. Go ahead Ajay. >> David that's where it comes back to again, the origination where we've come from in big data. The volume of data combined with the specificity of individualizing, personalizing a service around an individual amongst that massive data from different providers is where is exciting, that we're able to have an impact. >> Well, and you know Ajay, I'm glad you brought that up because in the early days of big data, there were only a handful of companies, the biggest financial institutions. Obviously, the internet giants who had all these engineers that were able to take advantage of it. But with companies like Io-Tahoe and others, and the investments that the industry has made in terms of providing the tools and simplifying that, especially with machine intelligence and AI and machine learning, these are becoming embedded into the tooling so that everybody can have access to them, small, medium, and large companies. That's really, to me, the exciting part of this new era that we're entering. >> Yeah, and we have placed those, take it down to the level of not-for-profits and smaller businesses that want to innovate and leapfrog into, to growing their digital delivery of their service. >> And I know a lot of time, but Ved, what you were saying about TCS's responsibility to society, I think is really, really important. Large companies like yours, I believe, and you clearly do as well, have a responsibility to society more than just a profit. And I think, Big Tech it's a better app in a lot of cases, but so thank you for that and thank you gentlemen for this great discussion. I really appreciate it. >> Thanks David. >> Thank you. >> All right, keep it right there. I'll be right back right after this short break. This is Dave Vellante for theCUBE. (calm music)

>> Narrator: From around the globe, it's "theCUBE" with digital coverage of Smart Data Marketplaces brought to you by Io-Tahoe. >> We're back. We're talking about smart data and have been for several weeks now. Really it's all about injecting intelligence and automation into the data life cycle of the data pipeline. And today we're drilling into Smart Data Marketplaces, really trying to get to that self-serve, unified, trusted, secured, and compliant data models. And this is not trivial. And with me to talk about some of the nuances involved in actually getting there with folks that have experienced doing that. They'd send a series of digital evangelist with Tata Consultancy Services, TCS. And Ajay Vohora is back, he's the CEO of Io-Tahoe. Guys, great to see you, thanks so much for coming on. >> Good to see you, Dave. >> Hey Dave. >> Ajay, let's start with you. Let's set up the sort of smart data concept. What's that all about? What's your perspective? >> Yeah, so I mean, our way of thinking about this is you you've got data, it has latent value, and it's really about discovering what the properties of that data. Does it have value? Can you put that data to work? And the way we go about that with algorithms and machine learning, to generate signals in that data identified patterns, that means we can start to discover how can we apply that data to down stream? What value can we unlock for a customer and business? >> Well, so you've been on this, I mean, really like a laser, why? I mean, why this issue? Did you see a gap in the marketplace in terms of talking to customers and maybe you can help us understand the origin? >> Yeah, I think that the gap has always been there. They've been, it's become more apparent over recent times with big data. So the ability to manually work with volumes of data in petabytes is prohibitively complex and expensive. So you need the different routes, you need different set of tools and methods to do that. Metadata are data that you can understand about data. That's what we at Io-Tahoe focus on, discovering and generating that metadata. That ready, that analogy to automate those data ops processes. So the gap David, is being felt by a business owner prizes and all sectors, healthcare, telecoms, and putting that data to work. >> So Ved, Let's talk a little bit about your role. You work with a lot of customers. I see you as an individual in a company who's really trying to transform what is a very challenging industry. That's sort of ripe for transformation, but maybe you could give us your perspective on this, what kind of signals you're looking for from the data pipeline and we'll get into how you are helping transform healthcare? >> Thanks, David. You know I think this year has been one of those years where we've all realized about this idea of unknown unknowns, where something comes around the corner that you're completely not expecting. And that's really hard to plan for obviously. And I think what we need is the ability to find early signals and be able to act on things as soon as you can. Sometimes, and you know, the COVID-19 scenario of course, is hopefully once in a generation thing, but most businesses struggle with the idea that they may have the data there in their systems, but they still don't know which bit of that is really valuable and what are the signals they should be watching for. And I think the interesting thing here is the ability for us to extract from a massive data, the most critical and important signals. And I think that's where we want to focus on. >> And so, talk a little bit about healthcare in particular and sort of your role there, and maybe at a high level. How Tata and your eco-system are helping transform healthcare? >> So if you look at healthcare, you've got the bit where people need active intervention from a medical professional. And then you've got this larger body of people, typically elderly people who aren't unwell, but they have frailties. They have underlying conditions and they're very vulnerable, especially in the world that we're in now in the post-COVID-19 scenario. And what we were trying to look at is how do we keep people who are elderly, frail and vulnerable? How can we keep them safe in their own homes rather than moving to care homes, where there has been an incredibly high level of infection for things like COVID-19. So the world works better if you can keep people safe in their own homes, if you can see the slide we've got. We're also talking about a world where care is expensive. In most Western countries, especially in Western Europe, the number of elderly people is increasing as a percentage of the population, quite significantly, and resources just are not keeping up. We don't have enough people. We don't have enough funding to look after them effectively. And the care industry that used to do that job has been struggling of late. So it's kind of a perfect storm for the need for technology intervention there. And in that space, what we're saying is the data signal that we want to receive are exactly what as a relative, or a son or daughter you might want from a parent to say, "Everything's okay. "We know that today's been just like every other day "there are no anomalies in your daily living." If you could get the signals that might tell us that something's wrong, something not quite right. We don't need very complex diagnostics. We just need to know something's not quite right, that my dad hasn't woken up as has always at seven o'clock, but till nine o'clock there's no movement. Maybe he's a bit unwell. It's that kind of signal that if we can generate, can make a dramatic difference to how we can look out for these people, whether through professional carers or through family members. So what we're looking to do is to sensor-enable homes of vulnerable people so that those data signals can come through to us in a curated manner, in a way that protects privacy and security of the individual, but gives the right people, which is carers or chosen family members the access to the signals, which is alerts that might tell you there was too much movement at night, or the front door was been left open, things like that that would give you a reason to call him and check. Everybody has spoken to in this always has an example of an uncle or a relative or parent that they've looked after. And all they're looking for is a signal. Even stories like my father's neighbor calls me when he doesn't open his curtain by 11 o'clock, that actually, if you think about it is a data signal that something might be all right. And I think what we're trying to do with technology is create those kinds of data signals because ultimately, the healthcare system works much better if you can prevent rather than cure. So every dollar that you put into prevention saves maybe $3 to $5 downstream. The economic summit also are working our favor. >> And those signals give family members the confidence to act. Ajay, it is interesting to hear what Ved was talking about in terms of the unknowns, because when you think about the early days of the computer industry, there were a lot of knowns, the processes were known. It was like the technology was the big mystery. Now, I feel like it's flipped. We've certainly seen that with COVID. The technology is actually quite well understood and quite mature and reliable. One of the examples is automated data discovery, which is something that you guys have been been focused on at Io-Tahoe. Why is automated data discovery such an important component of a smart data life cycle? >> Yeah. I mean, if we look David at the schematic and this one moves from left to right where right at the outset with that latent data, the value is late because you don't know. Does it have? Can it be applied? Can that data be put to work or not? And the objective really is about driving some form of exchange or monetization of data. If you think about it in insurance or healthcare, you've got lots of different parties, providers, payers, patients, everybody's looking to make some kind of an exchange of information. The difficulty is in all of those organizations, that data sits within its own system. So data discovery, if we drill into the focus itself that, it's about understanding which data has value, classifying that data so that it can be applied and being able to tag it so that it can then be put to use it's the real enabler for that per day drops. >> So maybe talk a little bit more about this. We're trying to get to self-service. It's something that we hear a lot about. You mentioned putting data to work. It seems to me that if the business can have access to that data and serve themselves, that's the way to put data to work. Do you have thoughts on that? >> Yeah, I mean, thinking back in terms of what IT and the IT function in a business could provide, there have been limitations around infrastructure, around scaling, around compute. Now that we're in an economy that is digital driven by API's your infrastructure, your data, your business rules, your intelligence, your models, all of those on the back of an API. So the options become limitless. How you can drive value and exchange that data. What that allows us to do is to be more creative, if we can understand what data has value for what use case. >> Ved, Let's talk a little bit about the US healthcare system. It's a good use case. I was recently at a chief data officer conference and listening to the CDO of Johns Hopkins, talk about the multiple different formats that they had to ingest to create that COVID map. They even had some PDFs, they had different definitions, and that's sort of underscored to me, the state of the US healthcare industry. I'm not as familiar with the UK and Europe generally, but I am familiar with the US healthcare system and the diversity that's there, the duplication of information and the like, maybe you could sort of summarize your perspectives and give us kind of the before and your vision of the after, if you will? >> The use of course, is particularly large and complex system. We all know that. We also know, I think there is some research that suggests that in the US the per-capita spend on healthcare is among the highest in the world. I think it's like 70%, and that compares to what just under 9%, which is going to be European, typical European figure. So it's almost double of that, but the outcomes are still vastly poor. When Ajay and I were talking earlier, I think we believe that there is a concept of a data friction. When you've got multiple players in an eco-system, trying to provide a single service as a patient, you're receiving a single health care service. There are probably a dozen up to 20 different organizations that have to collaborate to make sure you get that top of the line health care service. That kind of investment deserves. And what prevents it from happening very often is what we would call data friction, which is the ability to effectively share data. Something as simple as a healthcare record, which says, "This is Dave, this is Ved, this is Ajay." And when we go to hospital for anything, whatever happens, that healthcare record can capture all the information and tie to us as an individual. And if you go to a different hospital, then that record will follow you. This is how you would expect that to be implemented, but I think we're still on that journey. There are lots and lots of challenges. I've seen anecdotal data around people who suffered because they weren't carrying a card when they went into hospital, because that card has the critical elements of data, but in today's world, should you need to carry a piece of paper or can the entire thing be a digital data flow that can easily be, can certainly navigate through lack of paper and those kinds of things. So the vision that I think we need to be looking at is an effective data exchange or marketplace back with a kind of a backbone model where people agree and sign off a data standard, where each individual's data is always tied to the individual. So if you were to move States, if you would move providers, change insurance companies, none of that would impact your medical history, your data, and the ability to have the other care and medical professionals to access the data at the point of need and at the point of healthcare delivery. So I think that's the vision we're looking at, but as you rightly you said that there are enormous number of challenges, partly because of the history, of healthcare, I think it was technology enablement of healthcare started early. So there's a lot of legacy as well. So we shouldn't trivialize the challenges that the industry faces, but that I think is the way we want to go. >> Well, privacy is obviously a huge one, and a lot of the processes are built around non-digital processes and what you're describing as a flip for digital first. I mean, as a consumer, as a patient, I want an app for that. So I can see my own data. I can see price, price transparency, give access to people that I think need it. And that is a daunting task, isn't it? >> Absolutely. And I think the implicit idea and what you just said, which is very powerful is also on the app you want to control. >> Yes. >> And sometimes you want to be able to change access on data at that point. Right now, I'm at the hospital. I would like to access my data. And when I walk away or maybe three days later, I want to revoke that access. It's that level of control. And absolutely, it is by no means a trivial problem, but I think that's where you need the data automation tools. If you try to do any of this manually, we'd be here for another decade trying to solve this, but that's where tools like Io-Tahoe come in because to do this, a lot of the heavy lifting behind the scenes has to be automated. There has to be a machine churning that and presenting the simpler options. And I know you were talking about it just a little while ago Ajay. I was reminded of the example of a McDonald's or a Coke, because the sales store idea that you can go in and you can do your own ordering off a menu, or you can go in and select five different flavors from a Coke machine and choose your own particular blend of Coke. It's a very trivial example, but I think that's the word we want to get to with access of data as well. If it was that simple for consumers, for enterprise, business people, for doctors, then that's where we ultimately want to be able to arrive. But of course, to make something very simple for the end-user, somebody has to solve for complexity behind the scenes. >> So Ajay, it seems to me Ajay there're two major outcomes here. One is of course, the most important I guess, is patient outcomes, and the other is cost. I mean, they talked about the cost issues, we all, US especially understand the concerns about rising costs of healthcare. My question is this, how does a Smart Data Marketplace fit into achieving those two very important outcomes? >> When we think about how automation is enabling that, where we've got different data formats, the manual tasks are involved, duplication of information. The administrative overhead of that alone and the work, the rework, and the cycles of work that generates. That's really what we're trying to help with data is to eliminate that wasted effort. And with that wasted effort comes time and money to employ people to work through those siloed systems. So getting to the point where there is an exchange in a marketplace just as they would be for banking or insurance is really about automating the classification of data to make it available to a system that can pick it up through an API and to run a machine learning model and to manage a workflow, a process. >> Right, so you mentioned backing insurance, you're right. I mean, we've actually come a long way and just in terms of, know the customer and applying that to know the patient would be very powerful. I'm interested in what you guys are doing together, just in terms of your vision. Are you going to market together, kind of what you're seeing in terms of promoting or enabling this self-service, self-care. Maybe you could talk a little bit about Io-Tahoe and Tata, the intersection at the customer? >> Sure. I think we've been very impressed with the TCS vision of 4.0, how the re-imagining traditional industries, whether it's insurance, banking, healthcare, and bringing together automation, agile processes, robotics, AI, and once those enablers, technology may have brought together to re-imagine how those services can be delivered digitally. All of those are dependent on data. So we see that there's a really good fit here to enable understanding the legacy, the historic situation that has built up over time in an organization, a business and to help shine a light on what's meaningful in that to migrate to the cloud or to drive a digital twin, data science project. >> Ved, anything you can add to that? >> Sure. I mean, we do take the business 4.0 model quite seriously in terms of a lens with which you look at any industry, and what I talked about in healthcare was an example of that. And for us business 4.0, means a few very specific things. The technology that we use in today's verse should be agile, automated, intelligent, and cloud-based. These have become kind of hygiene factors now. On top of that, the businesses we build should be mass customized. They should be risk embracing. They should engage ecosystems, and they should strive for exponential value, not 10% growth year on year, but doubling, tripling every three, four years, because that's the competition that most businesses are facing today. And within that, the Tata group itself, is an extremely purpose-driven business. We really believe that we exist to serve communities, not just one specific set, i.e. shareholders, but the broader community in which we live and work. And I think this framework also allows us to apply that to things like healthcare, to education and to a whole vast range of areas where, everybody has a vision of using data science or doing really clever stuff at the gradients. But what becomes clear is, to do any of that, the first thing you need is a foundational piece. And as a foundation isn't right, then no matter how much you invest in the data science tools you won't get the answers you want. And the work we're doing with the Io-Tahoe really, for me, is particularly exciting because it sorts out that foundational piece. And at the end of it, to make all of this, again, I will repeat that, to make it simple and easy to use for the end user, whoever that is. And I realized that I'm probably the first person who's used fast food as a shining example for healthcare in this discussion, but you can make a lot of different examples. And today, if you press a button and start a car, that's simplicity, but someone has solved for that. And that's what we want to do with data as well. >> Yeah, that makes a lot of sense to me. We talk a lot about digital transformation and a digital business, and I would observe that a digital business puts data at the core. And you can certainly be the best example. There is, of course, Google is an all digital business, but take a company like Amazon, Who's got obviously a massive physical component to its business. Data is at the core. And that's exactly my takeaway from this discussion. Both of you are talking about putting data at the core, simplifying it, making sure that it's compliant, and healthcare it's taking longer, 'cause it's such a high risk industry, but it's clearly happening, COVID I guess, was an accelerant. Guys, Ajay, I'll start with you. Any final thoughts that you want to leave the audience with? _ Yeah, we're really pleased to be working with TCS. We've been able to explore how we're able to put dates to work in a range of different industries. Ved has mentioned healthcare, telecoms, banking and insurance are others. And the same impact they speak to whenever we see the exciting digital transformations that are being planned, being able to accelerate those, unlock the value from data is where we're having a purpose. And it's good that we can help patients in the healthcare sector, consumers in banking realize a better experience through having a more joined up marketplace with their data. >> Ved, you know what excites me about this conversation is that, as a patient or as a consumer, if I'm helping loved ones, I can go to the web and I can search, and I can find a myriad of possibilities. What you're envisioning here is really personalizing that with real time data. And that to me is a game changer. Your final thoughts? >> Thanks, David. I absolutely agree with you that the idea of data centricity and simplicity are absolutely forefront, but I think if we were to design an organization today, you might design it very differently to how most companies today are structured. And maybe Google and Amazon are probably better examples of that because you almost have to think of a business as having a data engine room at its core. A lot of businesses are trying to get to that stage, whereas what we call digital natives, are people who have started life with that premise. So I absolutely agree with you on that, but extending that a little bit. If you think of most industries as eco-systems that have to collaborate, then you've got multiple organizations who will also have to exchange data to achieve some shared outcomes. Whether you look at supply chains of automobile manufacturers or insurance companies or healthcares we've been talking about. So I think that's the next level of change we want to be able to make, which is to be able to do this at scale across organizations at industry level or in population scheme for healthcare. >> Yeah, Thank you for that. Go ahead Ajay. >> David that's where it comes back to again, the origination where we've come from in big data. The volume of data combined with the specificity of individualizing, personalizing a service around an individual amongst that massive data from different providers is where is exciting, that we're able to have an impact. >> Well, and you know Ajay, I'm glad you brought that up because in the early days of big data, there were only a handful of companies, the biggest financial institutions. Obviously, the internet giants who had all these engineers that were able to take advantage of it. But with companies like Io-Tahoe and others, and the investments that the industry has made in terms of providing the tools and simplifying that, especially with machine intelligence and AI and machine learning, these are becoming embedded into the tooling so that everybody can have access to them, small, medium, and large companies. That's really, to me, the exciting part of this new era that we're entering. >> Yeah, and we have placed those, take it down to the level of not-for-profits and smaller businesses that want to innovate and leapfrog into, to growing their digital delivery of their service. >> And I know a lot of time, but Ved, what you were saying about TCS's responsibility to society, I think is really, really important. Large companies like yours, I believe, and you clearly do as well, have a responsibility to society more than just a profit. And I think, Big Tech it's a better app in a lot of cases, but so thank you for that and thank you gentlemen for this great discussion. I really appreciate it. >> Thanks David. >> Thank you. >> All right, keep it right there. I'll be right back right after this short break. This is Dave Vellante for theCUBE. (calm music)

>> From theCUBE studios in Palo Alto in Boston, connecting with thought leaders all around the world, this a CUBE conversation. >> Hello, and welcome to this CUBE conversation, I'm John Furrier, host of theCUBE here, in our Palo Alto, California studios, here with our quarantine crew. We're getting all the remote interviews during this time of COVID-19. We've got two great remote guests here, Rachini Moosavi who's the Executive Director of Analytical Services and Data Governance at UNC Healthcare, and Sonya Jordan, Enterprise Analytics Manager of Data Governance at UNC Health. Welcome to theCUBE, thanks for coming on. >> Thank you. >> Thanks for having us. >> So, I'm super excited. University of North Carolina, my daughter will be a freshman this year, and she is coming, so hopefully she won't have to visit UNC Health, but looking forward to having more visits down there, it's a great place. So, thanks for coming on, really appreciate it. Okay, so the conversation today is going to be about how data and how analytics are helping solve problems, and ultimately, in your case, serve the community, and this is a super important conversation. So, before we get started, talk about UNC Health, what's going on there, how you guys organize, how big is it, what are some of the challenges that you have? >> SO UNC Health is comprised of about 12 different entities within our hospital system. We have physician groups as well as hospitals, and we serve, we're spread throughout all of North Carolina, and so we serve the patients of North Carolina, and that is our primary focus and responsibility for our mission. As part of the offices Sonya and I are in, we are in the Enterprise Analytics and Data Sciences Office that serves all of those entities and so we are centrally located in the triangle area of North Carolina, which is pretty central to the state, and we serve all of our entities equally from our Analytics and Data Governance needs. >> John: You guys got a different customer base, obviously you've got the clinical support, and you got the business applications, you got to be agile, that's what it's all about today, you don't need to rely on IT support. How do you guys do that? What's the framework? How do you guys tackle that problem of being agile, having the data be available, and you got two different customers, you got all the compliance issues with clinical, I can only imagine all the regulations involved, and you've got the business applications. How do you handle those? >> Yeah, so for us in the roles that we are in, we are fully responsible for more of the data and analytics needs of the organization, and so we provide services that truly are balanced across our clinician group, so we have physicians, and nurses, and all of the other ancillary clinical staff that we support, as well as the operational needs as well, so revenue cycle, finance, pharmacy, any of those groups that are required in order to run a healthcare system. So, we balance our time amongst all of those and for the work that we take on and how we continuously support them is really based on governance at the end of the day. How we make decisions around what the priorities are and what needs to happen next, and requires the best insights, is really how we focus on what work we do next. As for the applications that we build, in our office, we truly only build analytical applications or products like visualizations within Tableau as well as we support data governance platforms and services and so we provide some of the tools that enable our end users to be able to interact with the information that we're providing around analytics and insights, at the end of the day. >> Sonya, what's your job? Your title is Analytics Manager of Data Governance, obviously that sounds broad but governance is obviously required in all things. What is your job, what is your day-to-day roles like? What's your focus? >> Well, my day-to-day operations is first around building a data governance program. I try to work with identifying customers who we can start partnering with so that we can start getting documentation and utilizing a lot of the programs that we currently have, such as certification, so when we talk about initiatives, this is one of the initiatives that we use to partner with our stakeholders in order to start bringing visibilities to the various assets, such as metrics, or universes that we want to certify, or dashboards, algorithm, just various lists of different types of assets that we certify that we like to partner with the customers in order for them to start documenting within the tools, so that we can bring visibility to what's available, really focusing on data literacy, helping people to understand what assets are available, not only what assets are available, but who owns them, and who own the asset, and what can they do with it, making sure that we have great documentation in order to be able to leverage literacy as well. >> So, I can only imagine with how much volume you guys are dealing from a data standpoint, and the diversity, that the data warehouse must be massive, or it must be architected in a way that it can be agile because the needs, of the diverse needs. Can you guys share your thoughts on how you guys look on the data warehouse challenge and opportunity, and what you guys are currently doing? >> Well, so- >> Yeah you go ahead, Rachini. >> Go ahead, Sonya. >> Well, last year we implemented a tool, an enterprise warehouse, basically behind a tool that we implemented, and that was an opportunity for Data Governance to really lay some foundation and really bring visibility to the work that we could provide for the enterprise. We were able to embed into probably about six or seven of the 13 initiatives, I was actually within that project, and with that we were able to develop our stewardship committee, our data governance council, and because Rachini managed Data Solutions, our data solution manager was able to really help with the architect and integration of the tools. >> Rachini, your thoughts on running the data warehouse, because you've got to have flexibility for new types of data sources. How do you look at that? >> So, as Sonya just mentioned, we upgraded our data warehouse platform just recently because of these evolving needs, and like a lot of healthcare providers out there, a lot of them are either one or the other EMRs that are top in the market. With our EMR, they provide their own data warehouse, so you have to factor almost the impact of what they bring to the table in with an addition to all of those other sources of data that you're trying to co-mingle and bring together into the same data warehouse, and so for us, it was time for us to evolve our data warehouse. We ended up deciding on trying to create a virtual data warehouse, and in doing so, with virtualization, we had to upgrade our platform, which is what created that opportunity that Sonya was mentioning. And by moving to this new platform we are now able to bring all of that into one space and it's enabled us to think about how does the community of analysts interact with the data? How do we make that available to them in a secure way? In a way that they can take advantage of reusable master data files that could be our source of truth within our data warehouse, while also being able to have the flexibility to build what they need in their own functional spaces so that they can get the wealth of information that they need out of the same source and it's available to everyone. >> Okay, so I got to ask the question, and I was trying to get the good stuff out first, but let's get at the reality of COVID-19. You got pre-COVID-19 pandemic, we're kind of in the middle of it, and people are looking at strategies to come out of it, obviously the world will be changed, higher with a lot of virtualization, virtual meetings, and virtual workforce, but the data still needs to be, the business still needs to run, but data will be changing different sources, how are you guys responding to that crisis because you're going to be leaned on heavily for more and more support? >> Yeah it's been non-stop since March (laughs). So, I'm going to tell you about the reporting aspects of it, and then I'd love to turn it over to Sonya to tell you about some of the great things that we've actually been able to do to it and enhance our data governance program by not wasting this terrible event and this opportunity that's come up. So, with COVID, when it kicked off back in March, we actually formed a war room to address the needs around reporting analytics and just insights that our executives needed, and so in doing so, we created within the first week, our first weekend actually, our first dashboard, and within the next two weeks we had about eight or nine other dashboards that were available. And we continuously add to that. Information is so critical to our executives, to our clinicians, to be able to know how to address the evolving needs of COVID-19 and how we need to respond. We literally, and I'm not even exaggerating, at this very moment we have probably, let's see, I think it's seven different forecasts that we're trying to build all at the same time to try and help us prepare for this new recovery, this sort of ramp up efforts, so to your point, it started off as we're shutting down so that we can flatten the curve, but now as we try to also reopen at the same time while we're still meeting the needs of our COVID patients, there's this balancing act that we're trying to keep up with and so analytics is playing a critical factor in doing that. >> Sonya, your thoughts. First of all, congratulations, and action is what defines the players from the pretenders in my mind, you're seeing that play out, so congratulations for taking great action, I know you're working hard. Sonya, your thoughts, COVID, it's putting a lot of pressure? It highlights the weaknesses and strengths of what's kind of out there, what's your thoughts? >> Well, it just requires a great deal of collaboration and making sure that you're documenting metrics in a way where you're factoring true definition because at the end of the day, this information can go into a dashboard that's going to be visualized across the organization, I think what COVID has done was really enhanced the need and the understanding of why data governance is important and also it has allowed us to create a lot of standardization, where we we're standardizing a lot of processes that we currently had in correct place but just enhancing them. >> You know, not to go on a tangent, but I will, it's funny how the reality has kind of pulled back, exposed a lot of things, whether it's the remote work situation, people are VPNing, not under provision with the IT side. On the data side, everyone now understands the quality of the data. I mean, I got my kids talking progression analysis, "Oh, the curves are all wrong," I mean people are now seeing the science behind the data and they're looking at graphs all the time, you guys are in the visualization piece, this really highlights the need of data as a story, because there's an impact, and two, quality data. And if you don't have the data, the story isn't being told and then misinformation comes out of it, and this is actually playing out in real time, so it's not like it's just a use case for the most analytics but this again highlights the value of proposition of what you guys do. What's your personal thoughts on all this because this really is playing out globally. >> Yeah, it's been amazing how much information is out there. So, we have been extremely blessed at times but also burdened at times by that amount of information. So, there's the data that's going through our healthcare system that we're trying to manage and wrangle and do that data storytelling so that people can drive those insights to very effective decisions. But there's also all of this external data that we're trying to be able to leverage as well. And this is where the whole sharing of information can sometimes become really hard to try and get ahead of, we leverage the Johns Hopkins data for some time, but even that, too, can have some hiccups in terms of what's available. We try to use our State Department of Health and Human Services data and they just about updated their website and how information was being shared every other week and it was making it impossible for us to ingest that into our dashboards that we were providing, and so there's really great opportunities but also risks in some of the information that we're pulling. >> Sonya, what's your thoughts? I was just having a conversation this morning with the Chief of Analytics and Insight from NOA which is the National Oceanic Administration, about weather data and forecasting weather, and they've got this community model where they're trying to get the edges to kind of come in, this teases out a template. You guys have multiple locations. As you get more democratized in the connection points, whether it's third-party data, having a system managing that is hard, and again, this is a new trend that's emerging, this community connection points, where I think you guys might also might be a template, and your multiple locations, what's your general thoughts on that because the data's coming in, it's now connected in, whether it's first-party to the healthcare system or third-party. >> Yeah, well we have been leveraging our data governance tool to try to get that centralized location, making sure that we obtain the documentations. Due to COVID, everything is moving very fast, so it requires us to really sit down and capture the information and when you don't have enough resources in order to do that, it's easy to miss some very important information, so really trying to encourage people to understand the reason why we have data governance tools in order for them to leverage, in order to capture the documentation in a way that it can tell the story about the data, but most of all, to be able to capture it in a way so that if that person happened to leave the organization, we're not spending a lot of time trying to figure out how was this information created, how was this dashboard designed, where are the requirements, where are the specifications, where are the key elements, where does that information live, and making sure we capture that up front. >> So, guys, you guys are using Informatica, how are they helping you? Obviously, they have a system they're getting some great feedback on, how are you using Informatica, how is it going, and how has that enabled you guys to be successful? >> Yeah, so we decided on Informatica after doing a really thorough vetting of all of the other vendors in the industry that could provide us these services. We've really loved the capabilities that we've been able to provide to our customers at this point. It's evolving, I think, for us, the ability to partner with a group like Prominence, to be able to really leverage the capabilities of Informatica and then be really super, super hyper focused on providing data literacy back to our end users and making that the full intent of what we're doing within data governance has really enabled us to take the tools and make it something that's specific to UNC Health and the needs that our end users are verbalizing and provide that to them in a very positive way. >> Sonya, they talk about this master catalog, and I've talked to the CEO of Informatica and all their leaders, governance is a big part of it, and I've always said, I've always kind of had a hard time, I'm an entrepreneur, I like to innovate, move fast, break things, which is kind of not the way you work in the data world, you don't want to be breaking anything, so how do you balance governance and compliance with innovation? This has been a key topic and I know that you guys are using their enterprise data catolog. Is that helping? How does that fit in, is that part of it? >> Well, yeah, so during our COVID initiatives and building these telos dashboards, these visualizations and forecast models for executive leaders, we were able to document and EMPower you, which we rebranded Axon to EMPower, we were able to document a lot of our dashboards, which is a data set, and pretty much document attributes and show lineage from EMPower to EDC, so that users would know exactly when they start looking at the visualization not only what does this information mean, but they're also able to see what other sources that that information impacts as well as the data lineage, where did the information come from in EDC. >> So I got to ask the question to kind of wrap things up, has Informatica helped you guys out now that you're in this crisis? Obviously you've implemented before, now that you're in the middle of it, have you seen any things that jumped out at you that's been helpful, and are there areas that need to be worked on so that you guys continue to fight the good fight, come out of this thing stronger than before you came in? >> Yeah, there is a lot of new information, what we consider as "aha" moments that we've been learning about, and how EMPower, yes there's definitely a learning curve because we implemented EDC and EMPower last year doing our warehouse implementation, and so there's a lot of work that still needs to be done, but based on where we were the first of the year, I can say we have evolved tremendously due to a lot of the pandemic issues that arised, and we're looking to really evolve even greater, and pilot across the entire organization so that they can start leveraging these tools for their needs. >> Rachini you got any thoughts on your end on what's worked, what you see improvements coming, anything to share? >> Yeah, so we're excited about some of the new capabilities like the marketplace for example that's available in Axon, we're looking forward to being able to take advantage of some of these great new aspects of the tool so that we can really focus more on providing those insights back to our end users. I think for us, during COVID, it's really been about how do we take advantage of the immediate needs that are surfacing. How do we build all of these dashboards in record-breaking time but also make sure that folks understand exactly what's being represented within those dashboards, and so being able to provide that through our Informatica tools and service it back to our end users, almost in a seamless way like it's built into our dashboards, has been a really critical factor for us, and feeling like we can provide that level of transparency, and so I think that's where as we evolve that we would look for more opportunities, too. How do we make it simple for people to get that immediate answers to their questions, of what does the information need without it feeling like they're going elsewhere for the information. >> Rachini, thank you so much for your insight, Sonya as well, thanks for the insight, and stay safe. Sonya, behind you, I was pointing out, that's your artwork, you painted that picture. >> Yes. >> Looks beautiful. >> Yes, I did. >> You got two jobs, you're an artist, and you're doing data governance. >> Yes, I am, and I enjoy painting, that's how I relax (laughs). >> Looks great, get that on the market soon, get that on the marketplace, let's get that going. Appreciate the time, thank you so much for the insights, and stay safe and again, congratulations on the hard work you're doing, I know there's still a lot more to do, thanks for your time, appreciate it. >> Thank you. >> Thank you. >> It's theCUBE conversation, I'm John Furrier at the Palo Alto studios, for the remote interviews with Informatica, I'm John Furrier, thanks for watching. (upbeat music)

>>from around the globe. It's the Cube with digital coverage of CONMEBOL. Future ready 2020. Brought to you by combo. >>Hi and welcome back. I'm Stew Minuteman, and we're at the Cube's coverage of Con Volt Future Ready. You've got the power panel to really dig in on the product announcements that happened at the event today. Joining me? We have three guests. First of all, we have Brenda Rajagopalan. He's the vice president of products. Sitting next to him is Don Foster, vice president of Storage Solutions. And in the far piece of the panel Mersereau, vice president of Global Channels and Alliances. All three of them with Conn Volt. Gentlemen, thanks all three of you for joining us. Exactly. All right, so first of all, great job on the launch. You know, these days with a virtual event doing, you know, the announcements, the engagement with the press and analyst, you know, having demos, customer discussions. It's a challenge to put all those together. And it has been, you know, engaging in interesting watch today. So we're going to start with you. You've been quite busy today explaining all the pieces, so just at a very high level if you put this really looks like the culmination of the update with Conn Volt portfolio new team new products compared to kind of a year, year and 1/2 ago. So just if you could start us off with kind of the high points, >>thank you still, yeah, absolutely exciting day for us today. You did comrade multiple reasons for that excitement and go through that we announced an exciting new portfolio today knows to not the culmination. It's a continuation off our journey, a bunch of new products that we launched today Hyper scaler X as a new integrated data protection appliance. We've also announced new offerings in data protection, backup and recovery, disaster recovery and complete data protection and lots of exciting updates for Hedwig and a couple of weeks like we introduced updates for metallic. So, yes, it's been a really exciting pain. Also, today happens to be the data, and we got to know that we are the leader in Gartner Magic Quadrant for the ninth consecutive. I am so a lot of goodness today for us. >>Excellent. Lots of areas that we definitely want to dig deep in to the pieces done. You know, we just heard a little bit about Hedvig was an acquisition a year ago that everybody's kind of looking at and saying Okay, you know, will this make them compete against some of their traditional partners? How we get integrated in So, baby, just give us one level deeper on the Hedvig piece on what that means to the portfolio? Yeah, sure, So I >>guess I mean, one of the key things that the random mentioned was the fact that had hyper scale that's is built off the head Day files. So that's a huge milestone for us. As we teased out maybe 10 months ago. Remember, Tomball, Go on the Cube and talking about, you know, kind of what our vision and strategy was of unifying data and storage management. Those hyper hyper scale X applying is a definite milestone improving out that direction. But beyond just the hyper scale ECs, we've also been driving on some of the more primary or modern workloads such as containers and the really interesting stuff we've come out with your recently is the kubernetes native integration that ties in all of the advanced component of the head to distribute storage architecture on the platform itself across multi cloud and on premise environments, making it really easy and policy driven. Um, for Dev, ops users and infrastructure users, the tie ins applications from a group, Friction >>Great and Mercer. There's some updates to the partner program and help us understand how all of these product updates they're gonna affect the kind of the partnerships and alliances beasts that you want. >>Absolutely. So in the time since our last meeting that go in the fall, which is actually right after I had just doing combo, we spent a good portion of the following six months really talking with partners, understanding the understand the impact of the partner program that we introduced last summer, looking at the data and really looking at barriers to evolve the program, which fell around three difference specific. Once you bet one was simplicity of the simplicity of the program, simplicity of understanding, rewards, levers and so forth. The second was paying for value was really helping, helping our partners to be profitable around things like deal registration on other benefits and then third was around co investment. So making sure that we get the right members in place to support our partners and investing in practices. Another training, another enablement around combo and we launched in over these things last week is a part of an evolution of that program. Today is a great follow on because in addition to all of the program evolutions that we we launched last week now we have an opportunity with our partners to have many more opportunities or kind of a thin into the wedge to open up new discussions with our customers now around all of these different use cases and capabilities. So back to that simplification angle, really driving more and more opportunities for those partners toe specific conversations around use cases. >>Okay, for this next question, I think it makes sense for you to start. Maybe maybe Don, you can get some commentary in two. But when he's firstly the announcements, there are some new products in the piece that you discuss but trying to understand, you know, when you position it, you know, do you call the portfolio? Is it a platform? You know, if I'm an existing Conn Volt customer, you know, how do I approach this? If I use something like metallic, how does that interplay with some of the new pieces that were discussed today. >>Sure, I can take the business. I'm sure Don and mostly will have more data to it. The simplest way to think about it is as a port for you. But contrary to how you would think about portfolio as independent products, what we have is a set off data management services granular. We're very aligned to the use case, which can all inter operate with each other. So maybe launched backup and recovery and disaster recovery. These can be handled separately, purchased separately and deployed standalone or for customers who want a combination of those capabilities. We also have a complete data protection are fine storage optimization, data governance E discovery in complaints are data management services that build on top off any of these capabilities now a very differentiating factor in our platform owners. All the services that you're talking about are delivered off the same software to make it simpler to manage to the same year. So it's very easy to start with one service and then just turn on the license and go to other services so I can understand the confusion is coming from but it's all the same. The customer simplicity and flexibility in mind, and it's all delivered off the same platform. So it is a portfolio built on a single Don. Would you like to add more to it? >>Yeah, I think the interesting thing due to add on top of that is where we're going with Hedvig Infrastructure, the head of distributed storage platform, uh, to to run this point, how everything is integrated and feed and work off of one another. That's the same idea that we have. We talked about unifying data and storage manager. So the intricate storage architecture components the way data might be maneuvered, whether it's for kubernetes for virtual machines, database environments, secondary storage, you name it, um, we are. We're quickly working to continue driving that level of of unification and integration between the portfolio and heads storage, distribute storage platforms and also deliver. So what you're seeing today going back to, I think wrong his first point. It's definitely not the culmination. It's just another step in the direction as we continue to innovate and integrate this >>product, and I think for our partners what this really does, it allows them to sell around customer use cases because it'll ask now if I have a d. Our use case. I can go after just PR. If I have a backup use case, I can just go after backup, and I don't have to try to sell more than that. Could be on what the customer is looking for in parallel that we can steal these things in line with the customer use case. So the customer has a lot of remote offices. They want to scale Hedvig across those they want to use the art of the cloud. They can scale these things independently, and it really gives us a lot of optionality that we didn't have before when we had a few monolithic products. >>Excellent. Really reminds me more of how I look at products if I was gonna go buy it from some of the public cloud providers living in a hybrid cloud. World, of course, is what your customers are doing. Help us understand a little bit, you know, Mercer talked about metallic and the azure partnership, but for the rest of the products, the portfolio that we're talking about, you know, does this >>kind >>of work seamlessly across my own data center hosting providers Public Cloud, you know, how does this fit into the cloud environment for your customer? >>Yes, it does. And I can start with this one goes to, um it's our strategy is cloud first, right? And you see it in every aspect of our product portfolio. In fact, I don't know if you got to see a keynote today, but Ron from Johns Hopkins University was remarking that comment has the best cloud native architectures. And that's primarily because of the innovation that we drive into the multi cloud reality. We have very deep partnerships with pretty much all the cloud vendors, and we use that for delivering joint innovation, a few things that when you think of it from a hybrid customers perspective, the most important need for them is to continue working on pram while still leveraging the cloud. And we have a lot of optimization is built into that, and then the next step of the journey is of course, making sure that you can recover to the cloud would be it work load. Typically your data quality and there's a lot of automation that we provide to our solutions and finally, Of course, if you're already in the cloud, whether you're running a science parents or cloud native, our software protects across all those use cases, either true sass with metallic auto downloadable software, backup and recovery so we can cover the interest victims of actual presence. You. We do definitely help customers in every stage of their hybrid cloud acceleration journey. >>And if you take a look at the Hedvig protect if you take a look at the head back to, um, the ability to work in a cloud native fast, it is essentially a part of the DNA of that storage of the storage, right? So whether you're running on Prem, whether you're running it about adjacent, set up inside the cloud head, that can work with any compute environment and any storage environment that you went to essentially then feed, we build this distributed storage, and the reason that becomes important. It's pretty much highlighted with our announcement around the kubernetes and container support is that it makes it really easy to start maneuvering data from on Prem to the cloud, um, from cloud to cloud region to region, sort of that high availability that you know as customers make cloud first a reality and their organizations starts to become a critical requirement or ensuring the application of and some of the things that we've done now with kubernetes in making all of our integration for how we deliver storage for the kubernetes and container environments and being that they're completely kubernetes native and that they can support a Google in AWS and Azure. And of course, any on premises community set up just showcases the value that we can provide in giving them that level of data portability. And it basically provides a common foundation layer, or how any sort of the Dev ops teams will be operating in the way that those state full container state workloads. Donna Oh, sorry. Go >>ahead, mark area >>because you mentioned the metallic and azure partnership announcement and I just want to get on that. And one thing that run dimension, which is we are really excited about the announcement of partnership with Microsoft and all the different news cases that opens up that are SAS platform with Azure with office 3 65 and all of the great application stack it's on. If you're at the same time, to run this point. We are a multi cloud company. And whether that is other of the hyper scale clouds Mess GC, P. Ali at Oracle and IBM, etcetera, or Oliver, Great service writer burners. We continue to believe in customer choice, and we'll continue to drive unique event innovations across all of those platforms. >>All right, Don, I was wondering if we could just dig in a little bit more on some other kubernetes pieces you were talking about. Let me look at just the maturation of storage in general. You know, how do we had state back into containers in kubernetes environments? Help us see, You know what you're hearing from your customers. And you know how you how you're ready to meet their needs toe not only deliver storage, but as you say, Really? You know, full data protection in that environment? >>Certainly it So I mean, there's been a number of enhancements that happened in the kubernetes environment General over the last two years. One of the big ones was the creation of what the visit environment calls a persistent volume. And what that allows you to do is to really present storage to a a communities application. Do it be typically through what's called a CSR container storage interface that allows for state full data to be written, storage and be handled and reattached applications as you leverage them about that kubernetes. Um, as you can probably imagine that with the addition of the additional state full applications, some of the overall management now of stateless and state collapse become very talent. And that's primarily because many customers have been using some of the more traditional storage solutions to try to map that into these new state. Full scenario. And as you start to think about Dev ops organization, most Dev ops organizations want to work in the environment of their choice. Whether that's Google, whether that's AWS, Microsoft, uh, something that might be on Prem or a mix of different on Prem environments. What you typically find, at least in the kubernetes world, is there's seldom ever one single, very large kubernetes infrastructure cluster that's set to run, Dev asked. The way and production all at once. You usually have this spread out across a fairly global configuration, and so that's where some of these traditional mechanisms from traditional storage vendors really start to fall down because you can apply the same level of automation and controls in every single one of those environments. When you don't control the storage, let's say and that's really where interfacing Hedvig and allowing that sort of extension distribute storage platform brings about all of this automation policy control and really storage execution definition for the state. Full statehood workloads so that now managing the stateless and the state full becomes pretty easy and pretty easy to maintain when it comes to developing another Dev branch or simply trying to do disaster recovery or a J for production, >>any family actively do. That's a very interesting response, and the reality is customers are beginning to experiment with business. Very often they only have a virtual environment, and now they're also trying to expand into continuous. So Hedwig's ability to service primary storage for virtualization as well as containers actually gives their degree of flexibility and freedom for customers to try out containers and to start their contingent. Thank you familiar constructs. Everything is mellow where you just need to great with continuous >>Alright, bring a flexibility is something that I heard when you talk about the portfolio and the pricing as to how you put these pieces together. You actually talked about in the presentation this morning? Aggressive pricing. If you talk about, you know, kind of backup and recovery, help us understand, You know, convo 2020 how you're looking at your customers and you know how you put together your products, that to meet what they need at that. As you said, aggressive pricing? >>Absolutely. And you use this phrase a little bit earlier is to blow like flexibility. That's exactly what we're trying to get to the reason why we are reconstructing our portfolio so that we have these very granular use case aligned data management services to provide the cloud like flexibility. Customers don't have the same data management needs all the time. Great. So they can pick and choose the exact solution that need because there are delivered on the same platform that can enable out the solution investment, you know, And that's the reality. We know that many of our customers are going to start with one and keep adding more and more services, because that's what we see as ongoing conversations that gives us the ability to really praise the entry products very aggressively when compared to competition, especially when we go against single product windows. This uses a lot of slammed where we can start with a really aggressively priced product and enable more capabilities as we move forward to give you an idea, we launched disaster recovery today. I would say that compared to the so the established vendors India, we would probably come in at about 25 to 40% of the Priceline because it depends on the environment and what not. But you're going to see that that's the power of bringing to the table. You start small and then depending on what your needs are, you have the flexibility to run on either. More data management capabilities are more workloads, depending on what your needs will be. I think it's been a drag from a partner perspective, less with muscle. If you want a little bit more than that, >>yes, I mean, that goes back to the idea of being ableto simply scale across government use functionality. For example, things like the fact that our disaster recovery offering the Newman doesn't require backup really allows us to have those Taylor conversations around use cases, applications >>a >>zealous platforms. You think about one of the the big demands that we've had coming in from customers and partners, which is help me have a D R scenario or a VR set up in my environment that doesn't require people to go put their hands on boxes and cables, which was one of those things that a year ago we were having. This conversation would not necessarily have been as important as it is now, but that ability to target those specific, urgent use cases without having to go across on sort of sell things that aren't necessarily associated with the immediate pain points really makes those just makes us ineffective. Offer. >>Yeah, you bring up some changing priorities. I think almost everybody will agree that the number one priority we're hearing from customers is around security. So whether I'm adopting more cloud, I'm looking at different solutions out there. Security has to be front and center. Could we just kind of go down the line and give us the update as to how security fits and all the pieces we've been discussing? >>I guess I'm talking about change, right, so I'll start. The security for us is built into everything that we do the same view you're probably going to get from each of us because security is burden. It's not a board on, and you would see it across a lot of different images. If you take our backup and recovery and disaster recovery, for instance, a lot of ransomware protection capabilities built into the solution. For instance, we have anomaly detection that is built into the platform. If we see any kind of spurious activity happening all of a sudden, we know that that might be a potential and be reported so that the customer can take a quick look at air Gap isolation, encryption by default. So many features building. And when you come to disaster recovery, encryption on the wire, a lot of security aspects we've been to every part of the portfolio don't. >>Consequently, with Hedvig, it's probably no surprise that when that this platform was developed and as we've continued development, security has always been at the core of what we're doing is stored. So what? It's for something as simple as encryption on different volume, ensuring the communication between applications and the storage platform itself, and the way the distributors towards platform indicates those are all incredibly secured. Lock down almost such for our own our own protocols for ensuring that, um, you know, only we're able to talk within our own, our own system. Beyond that, though, I mean it comes down to ensure that data in rest data in transit. It's always it's always secure. It's also encrypted based upon the level of control that using any is there one. And then beyond just the fact of keeping the data secure. You have things like immutable snapshots. You have declared of data sovereignty to ensure that you can put essentially virtual fence barriers for where data can be transported in this highly distributed platform. Ah, and then, from a user perspective, there's always level security for providing all seeking roll on what groups organization and consume storage or leverage. Different resource is the storage platform and then, of course, from a service provider's perspective as well, providing that multi tenanted access s so that users can have access to what they want when they want it. It's all about self service, >>and the idea there is that obviously, we're all familiar with the reports of increased bad actors in the current environment to increased ransomware attacks and so forth. And be a part of that is addressed by what wrong and done said in terms of our core technology. Part of that also, though, is addressed by being able to work across platforms and environments because, you know, as we see the acceleration of state tier one applications or entire data center, evacuations into service provider or cloud environments has happened. You know, this could have taken 5 10 years in a in a normal cycle. But we've seen this happen overnight has cut this. Companies have needed to move those I T environments off science into managed environments and our ability to protect the applications, whether they're on premises, whether they're in the cloud or in the most difficult near where they live. In both cases, in both places at once, is something that it's really important to our customers to be able to ensure that in the end, security posture >>great Well, final thing I have for all three of you is you correctly noted that this is not the end, but along the journey that you're going along with your customers. So you know, with all three of you would like to get a little bit. Give us directionally. What should we be looking at? A convo. Take what was announced today and a little bit of look forward towards future. >>Directionally we should be looking at a place where we're delivering even greater simplicity to our customers. And that's gonna be achieved through multiple aspects. 1st 1 it's more technologies coming together. Integrating. We announced three important integration story. We announced the Microsoft partnership a couple of weeks back. You're gonna see us more longer direction. The second piece is technology innovation. We believe in it. That's what Differentiators has a very different company and we'll continue building it along the dimensions off data awareness, data, automation and agility. And the last one continued obsession with data. What more can we do with it? How can we drive more insights for our customers We're going to see is introducing more capabilities along those dimensions? No. >>And I think Rhonda tying directly into what you're highlighting there. I'm gonna go back to what we teased out 10 months ago at calm Bolt. Go there in Colorado in this very on this very program and talk about how, in the unification of ah ah, data and storage management, that vision, we're going to make more and more reality. I think the, uh, the announcements we've made here today let some of the things that we've done in between the lead up to this point is just proof of our execution. And ah, I can happily and excitedly tell you, we're just getting warmed up. It's going to be, ah, gonna be some fun future ahead. >>And I think studio in the running that out with the partner angle. Obviously, we're going to continue to produce great products and solutions that we're going to make our partners relevant. In those conversations with customers, I think we're also going to continue to invest in alternative business models, services, things like migration services, audit services, other things that build on top of this core technology to provide value for customers and additional opportunities for our partners >>to >>build out their their offerings around combo technologies. >>All right, well, thank you. All three of you for joining us. It was great to be able to dig in, understand those pieces. I know you've got lots of resources online for people to learn more. So thank you so much for joining us. Thank you too. Thank you. Alright, and stay with us. So we've got one more interview left for the Cube's coverage of con vault. Future Ready, students. Mannan. Thanks. As always for watching the Cube. Yeah, Yeah, yeah, yeah, yeah, yeah

>>from around the globe. It's the Cube with digital coverage of CONMEBOL. Future Ready 2020. Brought to you by combo. Hi, I'm Stew Minuteman. And this is the Cube's coverage of Con Volt Future ready event Welcoming back to the program. Fresh off the keynote stage. Sanjay Mirchandani. He's the CEO of Con Volt. Sanjay. Nice job on the keynote. And thanks so much for joining us. >>Thanks to Good to see you again. >>Nice to see you too. So, Sanjay, about a year and 1/2 into your journey with Conn Volt, you took over. And you know what it looks like? You've almost completely refreshed the portfolio there. Start a little bit, you know, future. Ready. Tell us how you're getting Conn Volt and its customers ready to be prepared for what happened today as well as the >>right. So, you know, we've we've given visit The past 18 months, have flown by in the past four or five. Even faster. Um, the change. You know, the change that we've had all deal with us as organizations has been tremendous. We've been hard at work. When I came on board, I should have talked about how we were setting out to simplify, innovate and execute all three of those pillars and, ah, future ready, which I love as a term completely embodies what I think the work we've been up to and what the world needs today, which is really getting it ready for whatever's next. And, you know, and it's coming together of innovation, simplification and and hopefully you'll agree some good execution to bring it all together. Yeah, so we've been busy. >>Sanjay, you talked a bit about just the moment in time that we're in. Wonder if you could bring us inside. You know your customers. So there's certain things that we saw for a couple of months. People put a pause on. Other things absolutely have been accelerated. We talk to customers about their adoption of cloud, you know, digital transformation. It's one of those things. That boy, I hope I'm through some of those or you know, can be as agile as possible. But, you know, what do you hearing specifically from our customer base and how they're dealing with things? >>You know, Cto, I touched a little bit on that during my keynote. And you know this this this this time that we're in has really caused, I think a couple of shifts. The first structural shift was Oh, hey, this thing is here to stay and let's get our employees Working and productive and keep the business is running and keeping them safe and everything else. That first shift happened right on. Honest about What was it that March, April and businesses small and big had to figure out how to take go from their their their operating model into, ah, remote. With the remote model, you re prioritize and you thought through what was important at the time and what it was was really getting laptops into the hands of your employees, getting them safe into their working environment, making sure your business processes leaning in that direction. You could take care of your customers. And so that was sort of the first structural faith, the second structural failures. Okay, how do we really drive productivity? One of the new priorities. What do we need to do, what you want to invest in? What do you want to pull back from? And from our vantage point from A from a technology and data point of view, what we're hearing is the themes that if I had a paraphrase of conversations I have with CIOs, it's NGOs. It's really around a simplification. This is a This is a great time to really simplify and, you know, and make sure that you're working with the tried and tested. This is not the time to experiment. This is not the time for esoteric. This is really about simplifying and working with the tried and tested. The second is really about focusing on skills, you know, this is you need you need to be able to leverage, and you need to be able to bring productivity from the from the people that you have an I t. And really focus around that that's, you know, that sometimes for gotten, you know that I like to call them. The unsung heroes of technology has just been pushed into their homes. They're now doing their jobs, longer hours, tougher scenarios. They have no access to their data centers. So it's over. So let's think about skills and the third, you know, the third thing, really that has been propelled into this conversation is cloud. So if you were on a journey, you're off the journey you need to get there quickly, okay? And you need to really newly leverage a light touch, low touch, remote sort of capability. A So fast is you can't call a digital transformation. Call it whatever you'd like to say. But it is about truly leveraging the cloud in a way that that was no longer, you know, a one year, two year three applying. You just have to bring it right to those kinds of things we're hearing and dealing with. >>Yeah, it's so important, Sanjay. Especially that simplicity piece. You know, I remember a few years ago there were certain customers that were adopting cloud, and it was the reminder. Oh, hey, your data protection in your security, you need to make sure you take care of that when you go to the cloud. And unfortunately, you know, some of the people that are now accelerating things you have to quickly say Oh, wait. I can't work this in a few months. I need to take care of this upfront, so help us understand a little bit. You know, the announcements that you've made. How are you making sure that you're ready for customers? The simplicity that they need to take advantage of the innovation and opportunity that the cloud on solutions provider >>absolutely and and make a mistake for me to. Simplification is not just the technology is easy to use, even though that is a big part of what we're working on and working and delivering through these announcements. But we've also got to make sure that the partnerships that we that we that we have lend themselves to what customers need, you know, engineered better its source not in the field, you know, and then and then the ecosystem to make the technology available and consumed commercially in the way that customers would like to keep that simple to. But today, if I just focus on the portfolio, you know, we've we've you could say we've completely rebuilt this incredible stack of technology that we've built this company out and, you know, and we weave in a nutshell. What we've done is announced A. We've taken our backup and recovery suite and be saying we've got a new company, backup and recovery product. We've got a brand new con Volt disaster recovery product. You can get them together as a unit Azaz the complete backup and recovery suite, if you would. So that's one big set of offerings. The second and you know the second is is we bought Hedvig sort of next generation software defined storage technology company last year, and we've been feverishly work quietly at work, integrating Hedvig into calm bolt not just as a company, but in the technology and our new hyper scale technology. Hyper scale. ECs is the embodiment of those two things coming together, the best of data protection from Con Volt and the best storage subsystem to drive that from Hedvig, also from console. So the two come together on all of this technology, whether it's the suite that I mentioned or the hyper scaler, all of it you can. You can mix and match any way you want with it with a world class user interface or user interfaces if you want command lines. If you want AP ICE will keep it open, all of it to you. In addition, we've got announcements or under Activate Suite on. Recently, we talked about our partnership with Microsoft with the metallic azure sort of combination for customers. So it's ah, it's a left to right set of announcement with simplification threatened right through it. >>Sanjay, you mentioned partnerships. Ah, a little bit before the show, you had, of course, the extended partnership with Microsoft with metallic. Maybe give us just a little bit more color about you know how, Con Volt make sure their position and working closely with those hyper scale >>hours. Yeah, you know, and we work with all the hyper scaler. So, you know, there we are probably the most prevalent data protection technology, if you would in the public cloud. And most of the way we talk about over an exabyte that we've helped customers, right, that the cloud is just one data point we've we've been, you know, seen is from the outside in as being the transport capability across across hybrid cloud scenarios. The partnership, the partnership with Microsoft and Microsoft Azure in particular, is the coming together of these things because customers, when we talk to customers and Microsoft office of customers be here from them, they want the ability to be, if you know, as they get more prevalent in the cloud as their workloads get more more pervasive in the cloud, they want to make sure that the same industrial strength data protection cloud in that they had well while they were on prayer for primarily on Prem. Our solutions are completely hybrid. And so the partnership really brings together again. You know, technology that's engineered better together, our data protection and their their cloud best in class our channels working, working together and making sure that it's easy for customers to work work with us. And we're available on the azure marketplace and our field forces also aligned around it. So it's again a 3 60 kind of conversation that we have with customers as much as much of today's announcements. >>Yeah, Sanjay, you talked about the hyper scale er's. You mentioned that the integration of the Hedwig Solution work with Dev Ops and really the cloud native type solutions. Of course, one of the things everybody's looking at when you were hired to this job is you've got background in the automation in developer world. So you know, how is that scene in the update? The portfolio really that embracing of cloud native and develop our environments? >>Cloud without automation is not a cloud, right? It's just it's just it's just infrastructure that's put somewhere else. It's deep, deep degrees of it off automation that really bring cloud to life. Right? And I was fortunate that have been in the Dev ops world for a while in a market leading with marketing product. And I was very pleasantly surprised when I when I came to convert and sell the deep degrees of automation and work flows that are core technology had, with Hedvig acquisition being a platform layer being the storage layer that is multi protocol and appeals incredibly to Dev Ops engineers because everything in the product you know is call a bill through an A p I for a set of AP eyes. It's it's Richard's got work flows and and it's multi critical. So whether you're using VMC or you're building the next generation container applications or you're just using object storage, it doesn't matter. We can mix and match it across, you know, private and public cloud environments, and it's all culpable and it's all programmable. It's all automated on as much as you want >>it. All right, So, Sanjay, I know we can't talk too much about Financial Piece is where we are in the quarter. But one of the things Dave Volante and I were discussing and looking at Kahn Volt. You know, there's some good data, you know, especially if you look at win rates against some of the some of the newer players in this space that the data that we have from ET R was showing, you know, increased win rates for Con Volt. Just could you give us a little bit of your competitive landscape view you talked about? Customers don't want to take too much risk, you know? How do you balance between being, you know, a company with a large install base? But you want to be, you know, more modern? >>Oh, yeah. And you know, the use cases we're talking about. The cloud that we're seeing those leaders are today's use cases, not yesterday's use cases, and we're winning in the base is the fact that we respect that customers are coming from Okay, There's a lot of stuff that runs that business that is still good. That isn't in the cloud that they're they're working their plants journey from that to something else as well. That's where we're leading in areas where they have it in the public cloud, and we always like to stay 1 to 2 steps ahead of the hard problems our customers going to encounter. So our portfolio is is absolutely cloud ready. Our portfolio is rich in that in that capability, and we're not slowing down. You know, we're winning because we have the breath of technology that we support. Both, You know, source source data that customers want o protect and target scenarios where maybe the hyper scaler or anything else where customers want to take it. And the flexibility, the second thing. And if you heard the interview I did with Run from from Johns Hopkins, it's the optimization off our technology around each of those cloud scenarios that gives our customer's true, you know, true value around the compute and storage decisions they have to make. And we helped them make through deep through deep degrees of AI and ML built in. So so it's not just about moving bits. It's about optimizing all of that on the entire life cycle of that data, from the point it's created to the point. >>Excellent. Well, Sunday. Want to let you have the final word? Give us what you want customers to have as the take away from today's future. Ready event? >>Sure. So, first of all, I wanted to, you know, I want to thank all our our audience here, our customers for being with us. It's being with us as a customer, being looking at us as a prospect for technology. We are investing like, you know, we've invested over a $1,000,000,000 over over a period of time as a company in data protection, and we're taking that to a whole new level with the innovations that we're bringing to the table. So, you know, we truly believe that the journey with as it pertains to data the journey to the cloud requires you to be able to think through the life cycle from storing, protecting, optimizing and using that data all the way through. And our solutions can be used independently. Best of class across each of them or together better together. And, you know, we I I urge you to take a few minutes and look at some of the some of the great innovations we've brought to table and rest assured that everything we're doing eyes with hybrid cloud in mind and is it is completely cloud optimized. >>All right. Well, Sanjay Mirchandani. Thank you so much for joining us. Congratulations to you and the team on the work on the updates. Definitely. Look forward to hearing more in the future. >>Thanks. Too good to be here. >>Alright, stay tuned. We've got more from Con vault Future ready on student a man. And thank you for watching the Cube. Yeah, yeah.