(upbeat music) >> Hey, welcome to theCUBE's coverage of AWS re:Invent 2021. I'm Lisa Martin, and I'm pleased to be joined by Jessica Alexander, who is the VP of Cloud Solutions Sales and Alliances at CrowdStrike. Jessica, welcome to the program. >> Thank you, Lisa. It's great to be here. >> So we're going to unpack a lot today, some news, what's going on with the threat landscape, what you're seeing across industries, but I want to get started talking a little bit about your team. As I mentioned, VP of Cloud Solutions Sales and Alliances. Talk to me about your team because you have a unique GTM here that I'd like to get into. >> Sure. Thank you, Lisa. Well, we recently launched our new cloud security products, Cloud Workload Protection and Horizon earlier this year. So we wanted to make sure that we accelerated our entry into this new product market, this new addressable market, and so we established not only a cloud sales specialist team that helps our core sellers as well as our partners sell our new cloud security products but we also wanted to make sure it was tightly integrated and aligned with our Cloud Alliances so specifically our co-sell relationship and partnership that we have with AWS. >> Got it. Let's talk about some of the things you mentioned, Aksino acceleration entering into the market. We saw a lot of acceleration in the last 20 months and counting, especially with respect to cloud adoption, digital transformation, but also the threat landscape things have accelerated. Wanted to get some information from you on what you've seen. We've seen and talked to a lot of folks on ransomware stats, you know, it's up nearly 11x in the first half of '21, but you guys have some unique stats and insights on that. Talk to me about what CrowdStrike is seeing with respect to that threat landscape and who it's impacting. >> Sure. You know, we have a unique perspective. CrowdStrike has millions of sensors out in our customer environments, they're feeding trillions of events into the cloud and we're able to correlate this data in real time, so this gives us a very unique perspective into what's happening in adversary activity out in the world. We also get feeds from our incident response teams that are actively responding to issues, as well as our Intel operatives out in the world. So, you know, we correlate these three sources of data into our threat graph in the cloud powered by AWS, which gives us very good insights into activity that we're seeing from an adversary perspective. So we also have a group called the OverWatch team, they are 24 by seven, you know, humans monitoring our cloud and monitoring our customer's networks to detect or, you know, get pre-breach activity information. And what they're seeing is that, you know, over this last year, an adversary is able to enter a network and move laterally into that network within one hour and 32 minutes. Now, you know, this is really fast, especially when you consider that in 2020, that average was four hours and 37 minutes for a threat actor to move laterally, you know, infiltrate a network and then move laterally. So, you know, the themes that we're seeing are adversaries are getting a lot faster and a lot more efficient, and, you know, as more companies are moving to remote work environments, you know, setting up virtual infrastructure for employees to use for work and productivity, you know, that threat landscape becomes more critical. >> Right? It becomes more critical. It becomes bigger. And of course we are in this work from anywhere environment that's going to last or some amount of it will persist permanently. So what you're saying is you're seeing a 4x increase in the speed with which adversaries can get in and laterally move within a network, so dramatically faster in a year over year period, where, so there's been so much flux in every market and of course in our lives, what are some of the things that you're helping customers do to combat this growing challenge? >> Well, it really goes back to being predictive and having that real time snapshot of what's going on and being able to proactively reach out to customers before anything bad happens and, you know, we're also seeing that ransomware continues to be an issue for customers, so, you know, having the ability to prevent these attacks and ransomware from happening in the first place and really taking the advantage that an adversary may have from a speed or intelligence perspective, taking that advantage away by having the Falcon Platform actively monitoring our customer environments is a big advantage. >> So let's talk about, speaking of advantages, what are you guys announcing at re:Invent this year? >> Sure. Well, we have two new service integrations with Amazon EKS, AWS Outpost and AWS Firelands to talk about this year. The cool thing is that, you know, customers are going to get our wonderful breach protection that we have, you know, the gold standard of breach protection, they'll have that available on various cloud services. And what it does is it provides consistent security and simplified operational management across AWS services, as customers extend those from public cloud to the data center, to the edge. And you know, the other great benefit is that it accelerates threat hunting, so we were talking about, you know, being able to predict and see what adversaries are doing. You know, one of the great customer benefits is that they can do that with their own teams and be able to do that on a cloud infrastructure as well. >> And how much of the events of the last 20 months was a catalyst or were catalysts for these integrations that you just mentioned? I imagine the threat landscape growing ransomware becoming a 'when we get hit not if' would have been some of those catalysts. >> Well, you know, we're seeing that the adoption of cloud services, especially for end user computing is growing much faster than traditional on-prem desktops, laptops, as people continue to work remotely and customers need to be, or corporations need to be efficient at how they manage end user computing environments. So, you know, we are seeing that adversary activity is picking up, they're getting smarter about, you know, leveraging cloud services and potential misconfigurations, there're really four key areas that we see customers struggle with, whether it be, you know, the complexity of cloud services, whether it be shadow IT, and a lot of the security folks don't necessarily know where all the cloud services are being deployed, then you've got, you know, kind of the advanced techniques that adversaries are using to get into networks. And then, you know, last but certainly not least is skills shortage. We're finding that a lot of customers want a turnkey solution, where they don't have to have a team of cloud security specialists to respond or handle any misconfigurations or issues that come up. They want to have a turnkey solution, a team that's already watching and reaching out to them to say, "Hey, you may want to look into XYZ and update a policy, or, you know, activate this new, you know, this feature in the platform." >> Yeah. That real time, the ability to have something that's turnkey is critical in this day and age where things are moving so quickly, there's so much being accelerated, good stuff and bad stuff. But also you mentioned that cybersecurity skills gap, which is in its, I think it's in its fifth year now, which is a big challenge for organizations as this scattered, work from anywhere persists as does the growth of the threat landscape. Let's get into now, for, you mentioned the adoption of cloud services has gone up considerably in this interesting time period, how is CrowdStrike helping customers do that securely, migrate from on-prem to the cloud with that security and that confidence that their landscape is protected? >> Yeah, well, we find obviously in the shared responsibility model, the great thing is that, you know, CrowdStrike and AWS team up to help, you know, customers have a better together experience as they migrate to the cloud. AWS is obviously responsible for the security of the cloud and customers are responsible for the security in the cloud. And in speaking with our customers who are moving or have moved to cloud services, and they really want a trusted and simple platform to use when securing their data and applications. So what, you know, they also have hybrid environments that can get complex to support, and, you know, we want to be able to provide them with a unified platform, a unified experience, regardless of where the workload is running or what services that it's using. You know, they have that unified visibility and protection across all of the cloud workloads. We're also, you know, seeing that, especially the reason we're doing this great integration with Outpost and EKS Anywhere is that customers are, you know, taking their cloud services out to their data centers as well as to the edge locations and branch offices, so they want to be able to run EKS on their own infrastructure. So it's important that customers have that portability that regardless of whether it's a laptop or an EC2 instance or an EKS container, you know, they have that portability throughout the continuum of their cloud journey. >> That continuum is absolutely critical as we, you know, talk about cloud and application or continuum from the customer's perspective, the cloud continuum is something that is front and center for customers, I imagine in every industry. >> Oh, for sure, 'cause every industry is adopting cloud maybe at a different speed, maybe for different applications, but, you know, everybody's moving to the cloud. >> So talk to me about what you're announcing with AWS, let's get into a little bit about the partnership that CloudStrike and AWS have, let's unpack that a bit. >> Sure. You know, we've been an AWS advanced technology partner for over five years. We've had our products, we now have six of our CrowdStrike products listed on AWS Marketplace. We're an active co-sell partner and, you know, have our security competency and our well-architected certification. And really it's about building trust with our customers. You know, AWS has a lot of wonderful partner products for customers to use and it's really about building trust that, you know, we're validated, we're vetted, we have a lot of customers who are using our products with AWS, and, you know, I think it's that tight collaboration, for example, if you look at what we're doing with Humio, we've implemented a quick start program, which AWS has to get customers quickly deployed with an integration or a new capability with a partner product. And what this does is it spins up a quick cloud formation template, customer can integrate it very quickly with the AWS Firelands and then, you know, all that log information coming from the AWS containers is easily ingested into the Humio platform. And so, you know, it really reduces the time to get the integration up and running as well as pulling all that data into the Humio platform so that customers can, like we said earlier, go back and threat hunt across, you know, different cloud service components in a quick and easy way. >> Quick and easy is good as is faster time to value. You mentioned the word trust, and, you know, we talk about trust, we've been talking about it for years as it relates to technology, but I'm curious, Jessica, in the last year and a half, if your customer conversations have changed, is trust now even more important than ever as there are so many things in flux, have you noticed any sort of change there in your customer conversations? >> Well, you know, I think trust is extensible. And over the last 10 years, CrowdStrike's done a really great job of building customer trust. And, you know, we started out as, you know, kind of primarily EDR and we've moved into prevention and now we're moving into identity protection and XDR so, you know, I see a pattern that, you know, we've built this amazing core of trust across our existing customers, and as we offer more capabilities, whether it be, you know, cloud security or XDR, identity protection, you know, customers trust us and so they're very willing to say, "ah well, I want to try out these new capabilities that CrowdStrike has because we trust you guys, you know, you've done a lot to protect our brand and, you know, really make our internal teams a lot more efficient and a lot smarter." So, you know, I think while trust is important, it's also something that we get to carry forward as we enter new markets and continue to innovate and provide new capabilities for our customers. >> And really extending that trusted, valued partner relationship that you've already established with customers in every industry. So where can customers go? So the joint GTM customers, and you said products available in the AWS marketplace, but where do you recommend customers go to learn more about how they can work with these joint solutions that CrowdStrike and AWS have together? >> Absolutely. We have a landing page on AWS, if you Google AWS and CrowdStrike, whether it be marketplace or EKS Anywhere, Amazon outposts, we're on all the joint product pages with Amazon, as well as always going to crowdstrike.com and looking up our cloud security products. >> Got it. And last question for you, Jessica, summarize the announcement in terms of business outcomes that it's going to enable your joint customers to achieve. >> Absolutely. You know, I think it goes back to probably the primary reason is complexity. And, you know, with complexity comes risk and blind spots so being able to have a unified platform that no matter where the workload is, or the employee may be, they are protected and have, you know, a unified platform and experience to manage their security risk. >> Excellent. Jessica, thank you so much for coming on the program today, sharing with me, what's new with CrowdStrike, some of the things that you're seeing, and what you're helping customers to accomplish in a very dynamic environment, we appreciate your time and your insights. >> Thank you for having me, Lisa. >> For Jessica Alexander, I'm Lisa Martin, and you're watching theCUBE's coverage of AWS re:Invent 2021. (gentle music)

(upbeat music) >> Hey, welcome to theCUBE's coverage of AWS re:Invent 2021. I'm Lisa Martin, and I'm pleased to be joined by Jessica Alexander, who is the VP of Cloud Solutions Sales and Alliances at CrowdStrike. Jessica, welcome to the program. >> Thank you, Lisa. It's great to be here. >> So we're going to unpack a lot today, some news, what's going on with the threat landscape, what you're seeing across industries, but I want to get started talking a little bit about your team. As I mentioned, VP of Cloud Solutions Sales and Alliances. Talk to me about your team because you have a unique GTM here that I'd like to get into. >> Sure. Thank you, Lisa. Well, we recently launched our new cloud security products, Cloud Workload Protection and Horizon earlier this year. So we wanted to make sure that we accelerated our entry into this new product market, this new addressable market, and so we established not only a cloud sales specialist team that helps our core sellers as well as our partners sell our new cloud security products but we also wanted to make sure it was tightly integrated and aligned with our Cloud Alliances so specifically our co-sell relationship and partnership that we have with AWS. >> Got it. Let's talk about some of the things you mentioned, Aksino acceleration entering into the market. We saw a lot of acceleration in the last 20 months and counting, especially with respect to cloud adoption, digital transformation, but also the threat landscape things have accelerated. Wanted to get some information from you on what you've seen. We've seen and talked to a lot of folks on ransomware stats, you know, it's up nearly 11x in the first half of '21, but you guys have some unique stats and insights on that. Talk to me about what CrowdStrike is seeing with respect to that threat landscape and who it's impacting. >> Sure. You know, we have a unique perspective. CrowdStrike has millions of sensors out in our customer environments, they're feeding trillions of events into the cloud and we're able to correlate this data in real time, so this gives us a very unique perspective into what's happening in adversary activity out in the world. We also get feeds from our incident response teams that are actively responding to issues, as well as our Intel operatives out in the world. So, you know, we correlate these three sources of data into our threat graph in the cloud powered by AWS, which gives us very good insights into activity that we're seeing from an adversary perspective. So we also have a group called the OverWatch team, they are 24 by seven, you know, humans monitoring our cloud and monitoring our customer's networks to detect or, you know, get pre-breach activity information. And what they're seeing is that, you know, over this last year, an adversary is able to enter a network and move laterally into that network within one hour and 32 minutes. Now, you know, this is really fast, especially when you consider that in 2020, that average was four hours and 37 minutes for a threat actor to move laterally, you know, infiltrate a network and then move laterally. So, you know, the themes that we're seeing are adversaries are getting a lot faster and a lot more efficient, and, you know, as more companies are moving to remote work environments, you know, setting up virtual infrastructure for employees to use for work and productivity, you know, that threat landscape becomes more critical. >> Right? It becomes more critical. It becomes bigger. And of course we are in this work from anywhere environment that's going to last or some amount of it will persist permanently. So what you're saying is you're seeing a 4x increase in the speed with which adversaries can get in and laterally move within a network, so dramatically faster in a year over year period, where, so there's been so much flux in every market and of course in our lives, what are some of the things that you're helping customers do to combat this growing challenge? >> Well, it really goes back to being predictive and having that real time snapshot of what's going on and being able to proactively reach out to customers before anything bad happens and, you know, we're also seeing that ransomware continues to be an issue for customers, so, you know, having the ability to prevent these attacks and ransomware from happening in the first place and really taking the advantage that an adversary may have from a speed or intelligence perspective, taking that advantage away by having the Falcon Platform actively monitoring our customer environments is a big advantage. >> So let's talk about, speaking of advantages, what are you guys announcing at re:Invent this year? >> Sure. Well, we have two new service integrations with Amazon EKS, AWS Outpost and AWS Firelands to talk about this year. The cool thing is that, you know, customers are going to get our wonderful breach protection that we have, you know, the gold standard of breach protection, they'll have that available on various cloud services. And what it does is it provides consistent security and simplified operational management across AWS services, as customers extend those from public cloud to the data center, to the edge. And you know, the other great benefit is that it accelerates threat hunting, so we were talking about, you know, being able to predict and see what adversaries are doing. You know, one of the great customer benefits is that they can do that with their own teams and be able to do that on a cloud infrastructure as well. >> And how much of the events of the last 20 months was a catalyst or were catalysts for these integrations that you just mentioned? I imagine the threat landscape growing ransomware becoming a 'when we get hit not if' would have been some of those catalysts. >> Well, you know, we're seeing that the adoption of cloud services, especially for end user computing is growing much faster than traditional on-prem desktops, laptops, as people continue to work remotely and customers need to be, or corporations need to be efficient at how they manage end user computing environments. So, you know, we are seeing that adversary activity is picking up, they're getting smarter about, you know, leveraging cloud services and potential misconfigurations, there're really four key areas that we see customers struggle with, whether it be, you know, the complexity of cloud services, whether it be shadow IT, and a lot of the security folks don't necessarily know where all the cloud services are being deployed, then you've got, you know, kind of the advanced techniques that adversaries are using to get into networks. And then, you know, last but certainly not least is skills shortage. We're finding that a lot of customers want a turnkey solution, where they don't have to have a team of cloud security specialists to respond or handle any misconfigurations or issues that come up. They want to have a turnkey solution, a team that's already watching and reaching out to them to say, "Hey, you may want to look into XYZ and update a policy, or, you know, activate this new, you know, this feature in the platform." >> Yeah. That real time, the ability to have something that's turnkey is critical in this day and age where things are moving so quickly, there's so much being accelerated, good stuff and bad stuff. But also you mentioned that cybersecurity skills gap, which is in its, I think it's in its fifth year now, which is a big challenge for organizations as this scattered, work from anywhere persists as does the growth of the threat landscape. Let's get into now, for, you mentioned the adoption of cloud services has gone up considerably in this interesting time period, how is CrowdStrike helping customers do that securely, migrate from on-prem to the cloud with that security and that confidence that their landscape is protected? >> Yeah, well, we find obviously in the shared responsibility model, the great thing is that, you know, CrowdStrike and AWS team up to help, you know, customers have a better together experience as they migrate to the cloud. AWS is obviously responsible for the security of the cloud and customers are responsible for the security in the cloud. And in speaking with our customers who are moving or have moved to cloud services, and they really want a trusted and simple platform to use when securing their data and applications. So what, you know, they also have hybrid environments that can get complex to support, and, you know, we want to be able to provide them with a unified platform, a unified experience, regardless of where the workload is running or what services that it's using. You know, they have that unified visibility and protection across all of the cloud workloads. We're also, you know, seeing that, especially the reason we're doing this great integration with Outpost and EKS Anywhere is that customers are, you know, taking their cloud services out to their data centers as well as to the edge locations and branch offices, so they want to be able to run EKS on their own infrastructure. So it's important that customers have that portability that regardless of whether it's a laptop or an EC2 instance or an EKS container, you know, they have that portability throughout the continuum of their cloud journey. >> That continuum is absolutely critical as we, you know, talk about cloud and application or continuum from the customer's perspective, the cloud continuum is something that is front and center for customers, I imagine in every industry. >> Oh, for sure, 'cause every industry is adopting cloud maybe at a different speed, maybe for different applications, but, you know, everybody's moving to the cloud. >> So talk to me about what you're announcing with AWS, let's get into a little bit about the partnership that CloudStrike and AWS have, let's unpack that a bit. >> Sure. You know, we've been an AWS advanced technology partner for over five years. We've had our products, we now have six of our CrowdStrike products listed on AWS Marketplace. We're an active co-sell partner and, you know, have our security competency and our well-architected certification. And really it's about building trust with our customers. You know, AWS has a lot of wonderful partner products for customers to use and it's really about building trust that, you know, we're validated, we're vetted, we have a lot of customers who are using our products with AWS, and, you know, I think it's that tight collaboration, for example, if you look at what we're doing with Humio, we've implemented a quick start program, which AWS has to get customers quickly deployed with an integration or a new capability with a partner product. And what this does is it spins up a quick cloud formation template, customer can integrate it very quickly with the AWS Firelands and then, you know, all that log information coming from the AWS containers is easily ingested into the Humio platform. And so, you know, it really reduces the time to get the integration up and running as well as pulling all that data into the Humio platform so that customers can, like we said earlier, go back and threat hunt across, you know, different cloud service components in a quick and easy way. >> Quick and easy is good as is faster time to value. You mentioned the word trust, and, you know, we talk about trust, we've been talking about it for years as it relates to technology, but I'm curious, Jessica, in the last year and a half, if your customer conversations have changed, is trust now even more important than ever as there are so many things in flux, have you noticed any sort of change there in your customer conversations? >> Well, you know, I think trust is extensible. And over the last 10 years, CrowdStrike's done a really great job of building customer trust. And, you know, we started out as, you know, kind of primarily EDR and we've moved into prevention and now we're moving into identity protection and XDR so, you know, I see a pattern that, you know, we've built this amazing core of trust across our existing customers, and as we offer more capabilities, whether it be, you know, cloud security or XDR, identity protection, you know, customers trust us and so they're very willing to say, "ah well, I want to try out these new capabilities that CrowdStrike has because we trust you guys, you know, you've done a lot to protect our brand and, you know, really make our internal teams a lot more efficient and a lot smarter." So, you know, I think while trust is important, it's also something that we get to carry forward as we enter new markets and continue to innovate and provide new capabilities for our customers. >> And really extending that trusted, valued partner relationship that you've already established with customers in every industry. So where can customers go? So the joint GTM customers, and you said products available in the AWS marketplace, but where do you recommend customers go to learn more about how they can work with these joint solutions that CrowdStrike and AWS have together? >> Absolutely. We have a landing page on AWS, if you Google AWS and CrowdStrike, whether it be marketplace or EKS Anywhere, Amazon outposts, we're on all the joint product pages with Amazon, as well as always going to crowdstrike.com and looking up our cloud security products. >> Got it. And last question for you, Jessica, summarize the announcement in terms of business outcomes that it's going to enable your joint customers to achieve. >> Absolutely. You know, I think it goes back to probably the primary reason is complexity. And, you know, with complexity comes risk and blind spots so being able to have a unified platform that no matter where the workload is, or the employee may be, they are protected and have, you know, a unified platform and experience to manage their security risk. >> Excellent. Jessica, thank you so much for coming on the program today, sharing with me, what's new with CrowdStrike, some of the things that you're seeing, and what you're helping customers to accomplish in a very dynamic environment, we appreciate your time and your insights. >> Thank you for having me, Lisa. >> For Jessica Alexander, I'm Lisa Martin, and you're watching theCUBE's coverage of AWS re:Invent 2021. (gentle music)

>> Announcer: Live, from the Moscone Center it's theCUBE. Covering AWS Summit San Francisco, 2018. Brought to you by, Amazon Web Services. >> Welcome back I'm Stu Miniman and this theCUBE's live coverage from AWS Summit San Francisco. Happy to have two industry analysts here. Also, they are founding partners of Kaleido Insights Jeremiah Owyang and Jessica Groopman. Join me and help me extract the signal from the noise that is our industry today. Thanks so much for joining us. >> Great to be here. >> Jessica it's actually the first time I've met you. Why don't you give our audience a little bit about your background and what led to the finding of Kaleido Insights. >> Of course, so I have been covering Internet of things, IOT for many years, and also in the last couple of years have gone very deep in both AI and blockchain. So, have this sort of umbrella category, which we call automation at Kaleido, that I cover and basically we formed the firm because what we saw was companies pursuing single technologies. What's your AI strategy, what's your IOG strategy what's your AR strategy? When in reality, all of these things are impacting each other. so we take a kaleidoscopic sort of converged lens. >> I love that, so Jeremiah, I can't believe it's your first time on our program, John Furrier's taking photos. You're one of the first people I followed on Twitter when I got on, I've known you for many years, so thanks. You've watched so many of these waves. Give us your take as to how you fit into the Kaleidoscope of what's happening. >> Yeah thanks a lot, so I've been in Silicon Valley for over 20 years, and I've seen threewaves.com, social media, collaborative, and now autonomous is the fourth wave that we're seeing right now. And, it's just amazing to see. I see the frequency of technologies is happening at a faster pace, and the impacts they're having to business models and what companies have to do to keep up, so it is a really exciting time. A few years ago, Uber and Airbnb were really hot and I was focused in on that topic. And now, it seems like that is a lifetime ago. We're focused on autonomous technologies; blockchain, IOT. And the things that Amazon announced today on stage like machine learning and drones and self-driving cars. It's a dizzying pace on what's going on it's like it explodes. >> Just in the last couple of weeks, look what happened to Facebook and Amazon with some of the internal and external pressures on those companies. I like what you say, we get excited by the new shiny. It was like, oh everything that was big data is now kind of AI well, IOT and ML. At WikiBound, on our research side, we say it's data at the center of it, data data data. And we've been talking about this for years. Jeremiah and I worked in the boring old storage industry. Which was never about storing the information, it was, how do I allow it to be shared and leverage it. So it's like it's maturation, you know, what's your take what's at the center over here, what are some of the biggest challenges, what's real what's not, and you know, doing it in under a minute. >> It continues to be the central focus, I mean it's been very interesting watching in the IOT space for the past couple of years where we've been fixated on things, right, the objects. But in reality it's about extracting data either between or about or in aggregate or about individuals sensor data, around those things. So the same is true, now we're seeing this shift into cognitive IOT, where devices themselves can analyze and process at the edge, or send learnings across a whole fleet of vehicles or a whole ray of devices about a given environment. Same story, different technologies continuing the cycle. >> Jeremiah, you know, that pace of change you talked about is so challenging, how do you go from I've got an idea to I'm going to start rolling it out by the time I use it, aren't I out of date? What do you see, how do you help customers look at this holistically and not constantly be tripping over themselves? >> And for the bigger the company the harder it is for them to keep up. The technology paces are coming faster, so one trend that we're seeing is corporations are launching innovation programs. It's an actual team, they have a dotted line to the CEO or the Chief Product Officer, and they're responsible for testing all of these new technologies. Maybe in a secluded area or tying it back to a business unit but their job is to experiment like a startup in the big company. So that's what we're seeing right now, these innovation programs that are merging. >> Why don't you tell us, we're here at the Amazon show. How are they doing, what's good? Where are some of the competitors leading them, you know? What are customers asking for? >> It's fascinating to see how Amazon is effectively taking different strategies at every single part of the stack. I believe this morning Verner said, offering egalitarian access to data storage, to data compute to machine learning algorithms. Effectively, it makes the company's only job to have a great idea and then sort of bringing in Amazon to do the rest. What I also see is that it's shifting the Venn diagrams or the complex diagrams of who's competitive and where. Competitive landscapes are shifting all the time at each of these new announcements. >> It's like the only thing you need from IT is bandwidth, the pipe. And Amazon is promising to do just about all the rest of that. >> Yeah, but the challenges. Remember when cloud computing was supposed to be simple and now it's like, oh okay. I'm going to build a database on Amazon. Well which one of the 15 do you want? All the languages, all the choices. >> 125 products, they listed on stage. >> Yeah, there are over 1,000 releases every year. They have two to three new products almost every day. When they do this Summit and they did a bunch of announcements most of those weren't planned for this it just happened to be what's coming out of the CIDC pipeline, if you will from them. >> Imagine being a salesperson for Amazon just to sell the products. >> Or imagine being a customer trying to figure out just what to use in the architecture. >> Unfortunately we don't have a lot more time to talk. Give us some of the things your firm is looking at what we look to see in this year from you. >> Yeah, so broadly speaking, we're really focused on these different technology convergences. Just published new research on where IOT and blockchain are coming together, that's a space we're following very closely. The next report working on right now is around AI readiness. There's much ado about data pipelines and data preparedness as there should be, but there's a whole realm of people process, governance, leadership preparedness. So we're really focused on how companies can prepare for this new technology. >> I'm also looking at how the new business models from automation will impact different enterprise business units. And our other partners are looking at content and automation in the marketing side, and we just had a report released from Jaime Szymanski on how virtual reality and mixed reality is going to impact enterprise. And there's six used cases for the business and Rebecca is working on the marketing report. >> Jeremiah and Jess, hope we can get back with you soon to discuss all this, you hit a whole bunch of things. You mentioned blockchain, so we'll get 10X of the views of what we would have had otherwise. We'll be back with lots more coverage. Thanks to Kaleido Insights for joining us on this segment. We'll be back with lots more. I'm Stu Miniman, you're watching theCUBE. >> Man: Thank you. (digital music)

(inspirational music) (music ends) >> Okay, so now that we've heard Scott talk about smart data fabrics, it's time to see this in action. Right now we're joined by Jess Jowdy, who's the manager of Healthcare Field Engineering at InterSystems. She's going to give a demo of how smart data fabrics actually work, and she's going to show how embedding a wide range of analytics capabilities, including data exploration business intelligence, natural language processing and machine learning directly within the fabric makes it faster and easier for organizations to gain new insights and power intelligence predictive and prescriptive services and applications. Now, according to InterSystems, smart data fabrics are applicable across many industries from financial services to supply chain to healthcare and more. Jess today is going to be speaking through the lens of a healthcare focused demo. Don't worry, Joe Lichtenberg will get into some of the other use cases that you're probably interested in hearing about. That will be in our third segment, but for now let's turn it over to Jess. Jess, good to see you. >> Hi, yeah, thank you so much for having me. And so for this demo, we're really going to be bucketing these features of a smart data fabric into four different segments. We're going to be dealing with connections, collections, refinements, and analysis. And so we'll see that throughout the demo as we go. So without further ado, let's just go ahead and jump into this demo, and you'll see my screen pop up here. I actually like to start at the end of the demo. So I like to begin by illustrating what an end user's going to see, and don't mind the screen 'cause I gave you a little sneak peek of what's about to happen. But essentially what I'm going to be doing is using Postman to simulate a call from an external application. So we talked about being in the healthcare industry. This could be, for instance, a mobile application that a patient is using to view an aggregated summary of information across that patient's continuity of care or some other kind of application. So we might be pulling information in this case from an electronic medical record. We might be grabbing clinical history from that. We might be grabbing clinical notes from a medical transcription software, or adverse reaction warnings from a clinical risk grouping application, and so much more. So I'm really going to be simulating a patient logging in on their phone and retrieving this information through this Postman call. So what I'm going to do is I'm just going to hit send, I've already preloaded everything here, and I'm going to be looking for information where the last name of this patient is Simmons, and their medical record number or their patient identifier in the system is 32345. And so as you can see, I have this single JSON payload that showed up here of, just, relevant clinical information for my patient whose last name is Simmons, all within a single response. So fantastic, right? Typically though, when we see responses that look like this there is an assumption that this service is interacting with a single backend system, and that single backend system is in charge of packaging that information up and returning it back to this caller. But in a smart data fabric architecture, we're able to expand the scope to handle information across different, in this case, clinical applications. So how did this actually happen? Let's peel back another layer and really take a look at what happened in the background. What you're looking at here is our mission control center for our smart data fabric. On the left we have our APIs that allow users to interact with particular services. On the right we have our connections to our different data silos. And in the middle here, we have our data fabric coordinator which is going to be in charge of this refinement and analysis, those key pieces of our smart data fabric. So let's look back and think about the example we just showed. I received an inbound request for information for a patient whose last name is Simmons. My end user is requesting to connect to that service, and that's happening here at my patient data retrieval API location. Users can define any number of different services and APIs depending on their use cases. And to that end, we do also support full life cycle API management within this platform. When you're dealing with APIs, I always like to make a little shout out on this, that you really want to make sure you have enough, like a granular enough security model to handle and limit which APIs and which services a consumer can interact with. In this IRIS platform, which we're talking about today we have a very granular role-based security model that allows you to handle that, but it's really important in a smart data fabric to consider who's accessing your data and in what context. >> Can I just interrupt you for a second, Jess? >> Yeah, please. >> So you were showing on the left hand side of the demo a couple of APIs. I presume that can be a very long list. I mean, what do you see as typical? >> I mean you could have hundreds of these APIs depending on what services an organization is serving up for their consumers. So yeah, we've seen hundreds of these services listed here. >> So my question is, obviously security is critical in the healthcare industry, and API securities are like, really hot topic these days. How do you deal with that? >> Yeah, and I think API security is interesting 'cause it can happen at so many layers. So, there's interactions with the API itself. So can I even see this API and leverage it? And then within an API call, you then have to deal with all right, which end points or what kind of interactions within that API am I allowed to do? What data am I getting back? And with healthcare data, the whole idea of consent to see certain pieces of data is critical. So, the way that we handle that is, like I said, same thing at different layers. There is access to a particular API, which can happen within the IRIS product, and also we see it happening with an API management layer, which has become a really hot topic with a lot of organizations. And then when it comes to data security, that really happens under the hood within your smart data fabric. So, that role-based access control becomes very important in assigning, you know, roles and permissions to certain pieces of information. Getting that granular becomes the cornerstone of the security. >> And that's been designed in, it's not a bolt on as they like to say. >> Absolutely. >> Okay, can we get into collect now? >> Of course, we're going to move on to the collection piece at this point in time, which involves pulling information from each of my different data silos to create an overall aggregated record. So commonly, each data source requires a different method for establishing connections and collecting this information. So for instance, interactions with an EMR may require leveraging a standard healthcare messaging format like Fire. Interactions with a homegrown enterprise data warehouse for instance, may use SQL. For a cloud-based solutions managed by a vendor, they may only allow you to use web service calls to pull data. So it's really important that your data fabric platform that you're using has the flexibility to connect to all of these different systems and applications. And I'm about to log out, so I'm going to (chuckles) keep my session going here. So therefore it's incredibly important that your data fabric has the flexibility to connect to all these different kinds of applications and data sources, and all these different kinds of formats and over all of these different kinds of protocols. So let's think back on our example here. I had four different applications that I was requesting information for to create that payload that we saw initially. Those are listed here under this operations section. So these are going out and connecting to downstream systems to pull information into my smart data fabric. What's great about the IRIS platform is, it has an embedded interoperability platform. So there's all of these native adapters that can support these common connections that we see for different kinds of applications. So using REST, or SOAP, or SQL, or FTP, regardless of that protocol, there's an adapter to help you work with that. And we also think of the types of formats that we typically see data coming in as in healthcare we have HL7, we have Fire, we have CCDs, across the industry, JSON is, you know, really hitting a market strong now, and XML payloads, flat files. We need to be able to handle all of these different kinds of formats over these different kinds of protocols. So to illustrate that, if I click through these when I select a particular connection on the right side panel, I'm going to see the different settings that are associated with that particular connection that allows me to collect information back into my smart data fabric. In this scenario, my connection to my chart script application in this example, communicates over a SOAP connection. When I'm grabbing information from my clinical risk grouping application I'm using a SQL based connection. When I'm connecting to my EMR, I'm leveraging a standard healthcare messaging format known as Fire, which is a REST based protocol. And then when I'm working with my health record management system, I'm leveraging a standard HTTP adapter. So you can see how we can be flexible when dealing with these different kinds of applications and systems. And then it becomes important to be able to validate that you've established those connections correctly, and be able to do it in a reliable and quick way. Because if you think about it, you could have hundreds of these different kinds of applications built out and you want to make sure that you're maintaining and understanding those connections. So I can actually go ahead and test one of these applications and put in, for instance my patient's last name and their MRN, and make sure that I'm actually getting data back from that system. So it's a nice little sanity check as we're building out that data fabric to ensure that we're able to establish these connections appropriately. So turnkey adapters are fantastic, as you can see we're leveraging them all here, but sometimes these connections are going to require going one step further and building something really specific for an application. So why don't we go one step further here and talk about doing something custom or doing something innovative. And so it's important for users to have the ability to develop and go beyond what's an out-of-the box or black box approach to be able to develop things that are specific to their data fabric, or specific to their particular connection. In this scenario, the IRIS data platform gives users access to the entire underlying code base. So you not only get an opportunity to view how we're establishing these connections or how we're building out these processes, but you have the opportunity to inject your own kind of processing, your own kinds of pipelines into this. So as an example, you can leverage any number of different programming languages right within this pipeline. And so I went ahead and I injected Python. So Python is a very up and coming language, right? We see more and more developers turning towards Python to do their development. So it's important that your data fabric supports those kinds of developers and users that have standardized on these kinds of programming languages. This particular script here, as you can see actually calls out to our turnkey adapters. So we see a combination of out-of-the-box code that is provided in this data fabric platform from IRIS, combined with organization specific or user specific customizations that are included in this Python method. So it's a nice little combination of how do we bring the developer experience in and mix it with out-of-the-box capabilities that we can provide in a smart data fabric. >> Wow. >> Yeah, I'll pause. (laughs) >> It's a lot here. You know, actually- >> I can pause. >> If I could, if we just want to sort of play that back. So we went to the connect and the collect phase. >> Yes, we're going into refine. So it's a good place to stop. >> So before we get there, so we heard a lot about fine grain security, which is crucial. We heard a lot about different data types, multiple formats. You've got, you know, the ability to bring in different dev tools. We heard about Fire, which of course big in healthcare. And that's the standard, and then SQL for traditional kind of structured data, and then web services like HTTP you mentioned. And so you have a rich collection of capabilities within this single platform. >> Absolutely. And I think that's really important when you're dealing with a smart data fabric because what you're effectively doing is you're consolidating all of your processing, all of your collection, into a single platform. So that platform needs to be able to handle any number of different kinds of scenarios and technical challenges. So you've got to pack that platform with as many of these features as you can to consolidate that processing. >> All right, so now we're going into refinement. >> We're going into refinement. Exciting. (chuckles) So how do we actually do refinement? Where does refinement happen? And how does this whole thing end up being performant? Well the key to all of that is this SDF coordinator, or stands for Smart Data Fabric coordinator. And what this particular process is doing is essentially orchestrating all of these calls to all of these different downstream systems. It's aggregating, it's collecting that information, it's aggregating it, and it's refining it into that single payload that we saw get returned to the user. So really this coordinator is the main event when it comes to our data fabric. And in the IRIS platform we actually allow users to build these coordinators using web-based tool sets to make it intuitive. So we can take a sneak peek at what that looks like. And as you can see, it follows a flow chart like structure. So there's a start, there is an end, and then there are these different arrows that point to different activities throughout the business process. And so there's all these different actions that are being taken within our coordinator. You can see an action for each of the calls to each of our different data sources to go retrieve information. And then we also have the sync call at the end that is in charge of essentially making sure that all of those responses come back before we package them together and send them out. So this becomes really crucial when we're creating that data fabric. And you know, this is a very simple data fabric example where we're just grabbing data and we're consolidating it together. But you can have really complex orchestrators and coordinators that do any number of different things. So for instance, I could inject SQL logic into this or SQL code, I can have conditional logic, I can do looping, I can do error trapping and handling. So we're talking about a whole number of different features that can be included in this coordinator. So like I said, we have a really very simple process here that's just calling out, grabbing all those different data elements from all those different data sources and consolidating it. We'll look back at this coordinator in a second when we introduce, or we make this data fabric a bit smarter, and we start introducing that analytics piece to it. So this is in charge of the refinement. And so at this point in time we've looked at connections, collections, and refinements. And just to summarize what we've seen 'cause I always like to go back and take a look at everything that we've seen. We have our initial API connection, we have our connections to our individual data sources and we have our coordinators there in the middle that are in charge of collecting the data and refining it into a single payload. As you can imagine, there's a lot going on behind the scenes of a smart data fabric, right? There's all these different processes that are interacting. So it's really important that your smart data fabric platform has really good traceability, really good logging, 'cause you need to be able to know, you know, if there was an issue, where did that issue happen in which connected process, and how did it affect the other processes that are related to it? In IRIS, we have this concept called a visual trace. And what our clients use this for is basically to be able to step through the entire history of a request from when it initially came into the smart data fabric, to when data was sent back out from that smart data fabric. So I didn't record the time, but I bet if you recorded the time it was this time that we sent that request in and you can see my patient's name and their medical record number here, and you can see that that instigated four different calls to four different systems, and they're represented by these arrows going out. So we sent something to chart script, to our health record management system, to our clinical risk grouping application, into my EMR through their Fire server. So every request, every outbound application gets a request and we pull back all of those individual pieces of information from all of those different systems, and we bundle them together. And from my Fire lovers, here's our Fire bundle that we got back from our Fire server. So this is a really good way of being able to validate that I am appropriately grabbing the data from all these different applications and then ultimately consolidating it into one payload. Now we change this into a JSON format before we deliver it, but this is those data elements brought together. And this screen would also be used for being able to see things like error trapping, or errors that were thrown, alerts, warnings, developers might put log statements in just to validate that certain pieces of code are executing. So this really becomes the one stop shop for understanding what's happening behind the scenes with your data fabric. >> Sure, who did what when where, what did the machine do what went wrong, and where did that go wrong? Right at your fingertips. >> Right. And I'm a visual person so a bunch of log files to me is not the most helpful. While being able to see this happened at this time in this location, gives me that understanding I need to actually troubleshoot a problem. >> This business orchestration piece, can you say a little bit more about that? How people are using it? What's the business impact of the business orchestration? >> The business orchestration, especially in the smart data fabric, is really that crucial part of being able to create a smart data fabric. So think of your business orchestrator as doing the heavy lifting of any kind of processing that involves data, right? It's bringing data in, it's analyzing that information it's transforming that data, in a format that your consumer's not going to understand. It's doing any additional injection of custom logic. So really your coordinator or that orchestrator that sits in the middle is the brains behind your smart data fabric. >> And this is available today? It all works? >> It's all available today. Yeah, it all works. And we have a number of clients that are using this technology to support these kinds of use cases. >> Awesome demo. Anything else you want to show us? >> Well, we can keep going. I have a lot to say, but really this is our data fabric. The core competency of IRIS is making it smart, right? So I won't spend too much time on this, but essentially if we go back to our coordinator here, we can see here's that original, that pipeline that we saw where we're pulling data from all these different systems and we're collecting it and we're sending it out. But then we see two more at the end here, which involves getting a readmission prediction and then returning a prediction. So we can not only deliver data back as part of a smart data fabric, but we can also deliver insights back to users and consumers based on data that we've aggregated as part of a smart data fabric. So in this scenario, we're actually taking all that data that we just looked at, and we're running it through a machine learning model that exists within the smart data fabric pipeline, and producing a readmission score to determine if this particular patient is at risk for readmission within the next 30 days. Which is a typical problem that we see in the healthcare space. So what's really exciting about what we're doing in the IRIS world, is we're bringing analytics close to the data with integrated ML. So in this scenario we're actually creating the model, training the model, and then executing the model directly within the IRIS platform. So there's no shuffling of data, there's no external connections to make this happen. And it doesn't really require having a PhD in data science to understand how to do that. It leverages all really basic SQL-like syntax to be able to construct and execute these predictions. So, it's going one step further than the traditional data fabric example to introduce this ability to define actionable insights to our users based on the data that we've brought together. >> Well that readmission probability is huge, right? Because it directly affects the cost for the provider and the patient, you know. So if you can anticipate the probability of readmission and either do things at that moment, or, you know, as an outpatient perhaps, to minimize the probability then that's huge. That drops right to the bottom line. >> Absolutely. And that really brings us from that data fabric to that smart data fabric at the end of the day, which is what makes this so exciting. >> Awesome demo. >> Thank you! >> Jess, are you cool if people want to get in touch with you? Can they do that? >> Oh yes, absolutely. So you can find me on LinkedIn, Jessica Jowdy, and we'd love to hear from you. I always love talking about this topic so we'd be happy to engage on that. >> Great stuff. Thank you Jessica, appreciate it. >> Thank you so much. >> Okay, don't go away because in the next segment, we're going to dig into the use cases where data fabric is driving business value. Stay right there. (inspirational music) (music fades)

>> Okay, so now that we've heard Scott talk about smart data fabrics, it's time to see this in action. Right now we're joined by Jess Jowdy, who's the manager of Healthcare Field Engineering at InterSystems. She's going to give a demo of how smart data fabrics actually work, and she's going to show how embedding a wide range of analytics capabilities including data exploration, business intelligence natural language processing, and machine learning directly within the fabric, makes it faster and easier for organizations to gain new insights and power intelligence, predictive and prescriptive services and applications. Now, according to InterSystems, smart data fabrics are applicable across many industries from financial services to supply chain to healthcare and more. Jess today is going to be speaking through the lens of a healthcare focused demo. Don't worry, Joe Lichtenberg will get into some of the other use cases that you're probably interested in hearing about. That will be in our third segment, but for now let's turn it over to Jess. Jess, good to see you. >> Hi. Yeah, thank you so much for having me. And so for this demo we're really going to be bucketing these features of a smart data fabric into four different segments. We're going to be dealing with connections, collections, refinements and analysis. And so we'll see that throughout the demo as we go. So without further ado, let's just go ahead and jump into this demo and you'll see my screen pop up here. I actually like to start at the end of the demo. So I like to begin by illustrating what an end user's going to see and don't mind the screen 'cause I gave you a little sneak peek of what's about to happen. But essentially what I'm going to be doing is using Postman to simulate a call from an external application. So we talked about being in the healthcare industry. This could be for instance, a mobile application that a patient is using to view an aggregated summary of information across that patient's continuity of care or some other kind of application. So we might be pulling information in this case from an electronic medical record. We might be grabbing clinical history from that. We might be grabbing clinical notes from a medical transcription software or adverse reaction warnings from a clinical risk grouping application and so much more. So I'm really going to be assimilating a patient logging on in on their phone and retrieving this information through this Postman call. So what I'm going to do is I'm just going to hit send, I've already preloaded everything here and I'm going to be looking for information where the last name of this patient is Simmons and their medical record number their patient identifier in the system is 32345. And so as you can see I have this single JSON payload that showed up here of just relevant clinical information for my patient whose last name is Simmons all within a single response. So fantastic, right? Typically though when we see responses that look like this there is an assumption that this service is interacting with a single backend system and that single backend system is in charge of packaging that information up and returning it back to this caller. But in a smart data fabric architecture we're able to expand the scope to handle information across different, in this case, clinical applications. So how did this actually happen? Let's peel back another layer and really take a look at what happened in the background. What you're looking at here is our mission control center for our smart data fabric. On the left we have our APIs that allow users to interact with particular services. On the right we have our connections to our different data silos. And in the middle here we have our data fabric coordinator which is going to be in charge of this refinement and analysis those key pieces of our smart data fabric. So let's look back and think about the example we just showed. I received an inbound request for information for a patient whose last name is Simmons. My end user is requesting to connect to that service and that's happening here at my patient data retrieval API location. Users can define any number of different services and APIs depending on their use cases. And to that end we do also support full lifecycle API management within this platform. When you're dealing with APIs I always like to make a little shout out on this that you really want to make sure you have enough like a granular enough security model to handle and limit which APIs and which services a consumer can interact with. In this IRIS platform, which we're talking about today we have a very granular role-based security model that allows you to handle that, but it's really important in a smart data fabric to consider who's accessing your data and in what contact. >> Can I just interrupt you for a second? >> Yeah, please. >> So you were showing on the left hand side of the demo a couple of APIs. I presume that can be a very long list. I mean, what do you see as typical? >> I mean you can have hundreds of these APIs depending on what services an organization is serving up for their consumers. So yeah, we've seen hundreds of these services listed here. >> So my question is, obviously security is critical in the healthcare industry and API securities are really hot topic these days. How do you deal with that? >> Yeah, and I think API security is interesting 'cause it can happen at so many layers. So there's interactions with the API itself. So can I even see this API and leverage it? And then within an API call, you then have to deal with all right, which end points or what kind of interactions within that API am I allowed to do? What data am I getting back? And with healthcare data, the whole idea of consent to see certain pieces of data is critical. So the way that we handle that is, like I said, same thing at different layers. There is access to a particular API, which can happen within the IRIS product and also we see it happening with an API management layer, which has become a really hot topic with a lot of organizations. And then when it comes to data security, that really happens under the hood within your smart data fabric. So that role-based access control becomes very important in assigning, you know, roles and permissions to certain pieces of information. Getting that granular becomes the cornerstone of security. >> And that's been designed in, >> Absolutely, yes. it's not a bolt-on as they like to say. Okay, can we get into collect now? >> Of course, we're going to move on to the collection piece at this point in time, which involves pulling information from each of my different data silos to create an overall aggregated record. So commonly each data source requires a different method for establishing connections and collecting this information. So for instance, interactions with an EMR may require leveraging a standard healthcare messaging format like FIRE, interactions with a homegrown enterprise data warehouse for instance may use SQL for a cloud-based solutions managed by a vendor. They may only allow you to use web service calls to pull data. So it's really important that your data fabric platform that you're using has the flexibility to connect to all of these different systems and and applications. And I'm about to log out so I'm going to keep my session going here. So therefore it's incredibly important that your data fabric has the flexibility to connect to all these different kinds of applications and data sources and all these different kinds of formats and over all of these different kinds of protocols. So let's think back on our example here. I had four different applications that I was requesting information for to create that payload that we saw initially. Those are listed here under this operations section. So these are going out and connecting to downstream systems to pull information into my smart data fabric. What's great about the IRIS platform is it has an embedded interoperability platform. So there's all of these native adapters that can support these common connections that we see for different kinds of applications. So using REST or SOAP or SQL or FTP regardless of that protocol there's an adapter to help you work with that. And we also think of the types of formats that we typically see data coming in as, in healthcare we have H7, we have FIRE we have CCDs across the industry. JSON is, you know, really hitting a market strong now and XML, payloads, flat files. We need to be able to handle all of these different kinds of formats over these different kinds of protocols. So to illustrate that, if I click through these when I select a particular connection on the right side panel I'm going to see the different settings that are associated with that particular connection that allows me to collect information back into my smart data fabric. In this scenario, my connection to my chart script application in this example communicates over a SOAP connection. When I'm grabbing information from my clinical risk grouping application I'm using a SQL based connection. When I'm connecting to my EMR I'm leveraging a standard healthcare messaging format known as FIRE, which is a rest based protocol. And then when I'm working with my health record management system I'm leveraging a standard HTTP adapter. So you can see how we can be flexible when dealing with these different kinds of applications and systems. And then it becomes important to be able to validate that you've established those connections correctly and be able to do it in a reliable and quick way. Because if you think about it, you could have hundreds of these different kinds of applications built out and you want to make sure that you're maintaining and understanding those connections. So I can actually go ahead and test one of these applications and put in, for instance my patient's last name and their MRN and make sure that I'm actually getting data back from that system. So it's a nice little sanity check as we're building out that data fabric to ensure that we're able to establish these connections appropriately. So turnkey adapters are fantastic, as you can see we're leveraging them all here, but sometimes these connections are going to require going one step further and building something really specific for an application. So let's, why don't we go one step further here and talk about doing something custom or doing something innovative. And so it's important for users to have the ability to develop and go beyond what's an out of the box or black box approach to be able to develop things that are specific to their data fabric or specific to their particular connection. In this scenario, the IRIS data platform gives users access to the entire underlying code base. So you cannot, you not only get an opportunity to view how we're establishing these connections or how we're building out these processes but you have the opportunity to inject your own kind of processing your own kinds of pipelines into this. So as an example, you can leverage any number of different programming languages right within this pipeline. And so I went ahead and I injected Python. So Python is a very up and coming language, right? We see more and more developers turning towards Python to do their development. So it's important that your data fabric supports those kinds of developers and users that have standardized on these kinds of programming languages. This particular script here, as you can see actually calls out to our turnkey adapters. So we see a combination of out of the box code that is provided in this data fabric platform from IRIS combined with organization specific or user specific customizations that are included in this Python method. So it's a nice little combination of how do we bring the developer experience in and mix it with out of the box capabilities that we can provide in a smart data fabric. >> Wow. >> Yeah, I'll pause. >> It's a lot here. You know, actually, if I could >> I can pause. >> If I just want to sort of play that back. So we went through the connect and the collect phase. >> And the collect, yes, we're going into refine. So it's a good place to stop. >> Yeah, so before we get there, so we heard a lot about fine grain security, which is crucial. We heard a lot about different data types, multiple formats. You've got, you know the ability to bring in different dev tools. We heard about FIRE, which of course big in healthcare. >> Absolutely. >> And that's the standard and then SQL for traditional kind of structured data and then web services like HTTP you mentioned. And so you have a rich collection of capabilities within this single platform. >> Absolutely, and I think that's really important when you're dealing with a smart data fabric because what you're effectively doing is you're consolidating all of your processing, all of your collection into a single platform. So that platform needs to be able to handle any number of different kinds of scenarios and technical challenges. So you've got to pack that platform with as many of these features as you can to consolidate that processing. >> All right, so now we're going into refine. >> We're going into refinement, exciting. So how do we actually do refinement? Where does refinement happen and how does this whole thing end up being performant? Well the key to all of that is this SDF coordinator or stands for smart data fabric coordinator. And what this particular process is doing is essentially orchestrating all of these calls to all of these different downstream systems. It's aggregating, it's collecting that information it's aggregating it and it's refining it into that single payload that we saw get returned to the user. So really this coordinator is the main event when it comes to our data fabric. And in the IRIS platform we actually allow users to build these coordinators using web-based tool sets to make it intuitive. So we can take a sneak peek at what that looks like and as you can see it follows a flow chart like structure. So there's a start, there is an end and then there are these different arrows that point to different activities throughout the business process. And so there's all these different actions that are being taken within our coordinator. You can see an action for each of the calls to each of our different data sources to go retrieve information. And then we also have the sync call at the end that is in charge of essentially making sure that all of those responses come back before we package them together and send them out. So this becomes really crucial when we're creating that data fabric. And you know, this is a very simple data fabric example where we're just grabbing data and we're consolidating it together. But you can have really complex orchestrators and coordinators that do any number of different things. So for instance, I could inject SQL Logic into this or SQL code, I can have conditional logic, I can do looping, I can do error trapping and handling. So we're talking about a whole number of different features that can be included in this coordinator. So like I said, we have a really very simple process here that's just calling out, grabbing all those different data elements from all those different data sources and consolidating it. We'll look back at this coordinator in a second when we introduce or we make this data fabric a bit smarter and we start introducing that analytics piece to it. So this is in charge of the refinement. And so at this point in time we've looked at connections, collections, and refinements. And just to summarize what we've seen 'cause I always like to go back and take a look at everything that we've seen. We have our initial API connection we have our connections to our individual data sources and we have our coordinators there in the middle that are in charge of collecting the data and refining it into a single payload. As you can imagine, there's a lot going on behind the scenes of a smart data fabric, right? There's all these different processes that are interacting. So it's really important that your smart data fabric platform has really good traceability, really good logging 'cause you need to be able to know, you know, if there was an issue, where did that issue happen, in which connected process and how did it affect the other processes that are related to it. In IRIS, we have this concept called a visual trace. And what our clients use this for is basically to be able to step through the entire history of a request from when it initially came into the smart data fabric to when data was sent back out from that smart data fabric. So I didn't record the time but I bet if you recorded the time it was this time that we sent that request in. And you can see my patient's name and their medical record number here and you can see that that instigated four different calls to four different systems and they're represented by these arrows going out. So we sent something to chart script to our health record management system, to our clinical risk grouping application into my EMR through their FIRE server. So every request, every outbound application gets a request and we pull back all of those individual pieces of information from all of those different systems and we bundle them together. And for my FIRE lovers, here's our FIRE bundle that we got back from our FIRE server. So this is a really good way of being able to validate that I am appropriately grabbing the data from all these different applications and then ultimately consolidating it into one payload. Now we change this into a JSON format before we deliver it, but this is those data elements brought together. And this screen would also be used for being able to see things like error trapping or errors that were thrown alerts, warnings, developers might put log statements in just to validate that certain pieces of code are executing. So this really becomes the one stop shop for understanding what's happening behind the scenes with your data fabric. >> Etcher, who did what, when, where what did the machine do? What went wrong and where did that go wrong? >> Exactly. >> Right in your fingertips. >> Right, and I'm a visual person so a bunch of log files to me is not the most helpful. Well, being able to see this happened at this time in this location gives me that understanding I need to actually troubleshoot a problem. >> This business orchestration piece, can you say a little bit more about that? How people are using it? What's the business impact of the business orchestration? >> The business orchestration, especially in the smart data fabric is really that crucial part of being able to create a smart data fabric. So think of your business orchestrator as doing the heavy lifting of any kind of processing that involves data, right? It's bringing data in, it's analyzing that information, it's transforming that data, in a format that your consumer's not going to understand it's doing any additional injection of custom logic. So really your coordinator or that orchestrator that sits in the middle is the brains behind your smart data fabric. >> And this is available today? This all works? >> It's all available today. Yeah, it all works. And we have a number of clients that are using this technology to support these kinds of use cases. >> Awesome demo. Anything else you want to show us? >> Well we can keep going. 'Cause right now, I mean we can, oh, we're at 18 minutes. God help us. You can cut some of this. (laughs) I have a lot to say, but really this is our data fabric. The core competency of IRIS is making it smart, right? So I won't spend too much time on this but essentially if we go back to our coordinator here we can see here's that original that pipeline that we saw where we're pulling data from all these different systems and we're collecting it and we're sending it out. But then we see two more at the end here which involves getting a readmission prediction and then returning a prediction. So we can not only deliver data back as part of a smart data fabric but we can also deliver insights back to users and consumers based on data that we've aggregated as part of a smart data fabric. So in this scenario, we're actually taking all that data that we just looked at and we're running it through a machine learning model that exists within the smart data fabric pipeline and producing a readmission score to determine if this particular patient is at risk for readmission within the next 30 days. Which is a typical problem that we see in the healthcare space. So what's really exciting about what we're doing in the IRIS world is we're bringing analytics close to the data with integrated ML. So in this scenario we're actually creating the model, training the model, and then executing the model directly within the IRIS platform. So there's no shuffling of data, there's no external connections to make this happen. And it doesn't really require having a PhD in data science to understand how to do that. It leverages all really basic SQL like syntax to be able to construct and execute these predictions. So it's going one step further than the traditional data fabric example to introduce this ability to define actionable insights to our users based on the data that we've brought together. >> Well that readmission probability is huge. >> Yes. >> Right, because it directly affects the cost of for the provider and the patient, you know. So if you can anticipate the probability of readmission and either do things at that moment or you know, as an outpatient perhaps to minimize the probability then that's huge. That drops right to the bottom line. >> Absolutely, absolutely. And that really brings us from that data fabric to that smart data fabric at the end of the day which is what makes this so exciting. >> Awesome demo. >> Thank you. >> Fantastic people, are you cool? If people want to get in touch with you? >> Oh yes, absolutely. So you can find me on LinkedIn, Jessica Jowdy and we'd love to hear from you. I always love talking about this topic, so would be happy to engage on that. >> Great stuff, thank you Jess, appreciate it. >> Thank you so much. >> Okay, don't go away because in the next segment we're going to dig into the use cases where data fabric is driving business value. Stay right there.

>>Hey everyone. Welcome back to the cubes. Live coverage of women in data science, worldwide conference widths 2022. I'm Lisa Martin coming to you from Stanford university at the Arriaga alumni center. And I'm pleased to welcome my next guest. Hannah Sperling joins me business process intelligence or BPI, academic and research alliances at SAP HANA. Welcome to the program. >>Hi, thank you so much for having me. >>So you just flew in from Germany. >>I did last week. Yeah. Long way away. I'm very excited to be here. Uh, but before we get started, I would like to say that I feel very fortunate to be able to be here and that my heart and vicious still goes out to people that might be in more difficult situations right now. I agree >>Such a it's one of my favorite things about Wiz is the community that it's grown into. There's going to be about a 100,000 people that will be involved annually in woods, but you walk into the Arriaga alumni center and you feel this energy from all the women here, from what Margo and teams started seven years ago to what it has become. I was happened to be able to meet listening to one of the panels this morning, and they were talking about something that's just so important for everyone to hear, not just women, the importance of mentors and sponsors, and being able to kind of build your own personal board of directors. Talk to me about some of the mentors that you've had in the past and some of the ones that you have at SAP now. >>Yeah. Thank you. Um, that's actually a great starting point. So maybe talk a bit about how I got involved in tech. Yeah. So SAP is a global software company, but I actually studied business and I was hired directly from university, uh, around four years ago. And that was to join SAP's analytics department. And I've always had a weird thing for databases, even when I was in my undergrad. Um, I did enjoy working with data and so working in analytics with those teams and some people mentoring me, I got into database modeling and eventually ventured even further into development was working in analytics development for a couple of years. And yeah, still am with a global software provider now, which brought me to women and data science, because now I'm also involved in research again, because yeah, some reason couldn't couldn't get enough of that. Um, maybe learn about the stuff that I didn't do in my undergrad. >>And post-grad now, um, researching at university and, um, yeah, one big part in at least European data science efforts, um, is the topic of sensitive data and data privacy considerations. And this is, um, also topic very close to my heart because you can only manage what you measure, right. But if everybody is afraid to touch certain pieces of sensitive data, I think we might not get to where we want to be as fast as we possibly could be. And so I've been really getting into a data and anonymization procedures because I think if we could random a workforce data usable, especially when it comes to increasing diversity in stem or in technology jobs, we should really be, um, letting the data speak >>And letting the data speak. I like that. One of the things they were talking about this morning was the bias in data, the challenges that presents. And I've had some interesting conversations on the cube today, about data in health care data in transportation equity. Where do you, what do you think if we think of international women's day, which is tomorrow the breaking the bias is the theme. Where do you think we are from your perspective on breaking the bias that's across all these different data sets, >>Right. So I guess as somebody working with data on a daily basis, I'm sometimes amazed at how many people still seem to think that data can be unbiased. And this has actually touched upon also in the first keynote that I very much enjoyed, uh, talking about human centered data science people that believe that you can take the human factor out of any effort related to analysis, um, are definitely on the wrong path. So I feel like the sooner that we realize that we need to take into account certain bias sees that will definitely be there because data is humanly generated. Um, the closer we're going to get to something that represents reality better and might help us to change reality for the better as well, because we don't want to stick with the status quo. And any time you look at data, it's definitely gonna be a backward looking effort. So I think the first step is to be aware of that and not to strive for complete objectivity, but understanding and coming to terms with the fact just as it was mentioned in the equity panel, that that is logically impossible, right? >>That's an important, you bring up a really important point. It's important to understand that that is not possible, but what can we work with? What is possible? What can we get to, where do you think we are on the journey of being able to get there? >>I think that initiatives like widths of playing an important role in making that better and increasing that awareness there a big trend around explainability interpretability, um, an AI that you see, not just in Europe, but worldwide, because I think the awareness around those topics is increasing. And that will then, um, also show you the blind spots that you may still have, no matter how much you think about, um, uh, the context. Um, one thing that we still need to get a lot better at though, is including everybody in these types of projects, because otherwise you're always going to have a certain selection in terms of prospectus that you're getting it >>Right. That thought diversity there's so much value in thought diversity. That's something that I think I first started talking about thought diversity at a Wood's conference a few years ago, and really understanding the impact there that that can make to every industry. >>Totally. And I love this example of, I think it was a soap dispenser. I'm one of these really early examples of how technology, if you don't watch out for these, um, human centered considerations, how technology can, can go wrong and just, um, perpetuate bias. So a soap dispenser that would only recognize the hand, whether it was a certain, uh, light skin type that w you know, be placed underneath it. So it's simple examples like that, um, that I think beautifully illustrate what we need to watch out for when we design automatic decision aids, for example, because anywhere where you don't have a human checking, what's ultimately decided upon you end up, you might end up with much more grave examples, >>Right? No, it's, it's I agree. I, Cecilia Aragon gave the talk this morning on the human centered guy. I was able to interview her a couple of weeks ago for four winds and a very inspiring woman and another herself, but she brought up a great point about it's the humans and the AI working together. You can't ditch the humans completely to your point. There are things that will go wrong. I think that's a sends a good message that it's not going to be AI taking jobs, but we have to have those two components working better. >>Yeah. And maybe to also refer to the panel discussion we heard, um, on, on equity, um, I very much liked professor Bowles point. Um, I, and how she emphasized that we're never gonna get to this perfectly objective state. And then also during that panel, um, uh, data scientists said that 80% of her work is still cleaning the data most likely because I feel sometimes there is this, um, uh, almost mysticism around the role of a data scientist that sounds really catchy and cool, but, um, there's so many different aspects of work in data science that I feel it's hard to put that all in a nutshell narrowed down to one role. Um, I think in the end, if you enjoy working with data, and maybe you can even combine that with a certain domain that you're particularly interested in, be it sustainability, or, you know, urban planning, whatever that is the perfect match >>It is. And having that passion that goes along with that also can be very impactful. So you love data. You talked about that, you said you had a strange love for databases. Where do you, where do you want to go from where you are now? How much more deeply are you going to dive into the world of data? >>That's a good question because I would, at this point, definitely not consider myself a data scientist, but I feel like, you know, taking baby steps, I'm maybe on a path to becoming one in the future. Um, and so being at university, uh, again gives me, gives me the opportunity to dive back into certain courses and I've done, you know, smaller data science projects. Um, and I was actually amazed at, and this was touched on in a panel as well earlier. Um, how outdated, so many, um, really frequently used data sets are shown the realm of research, you know, AI machine learning, research, all these models that you feed with these super outdated data sets. And that's happened to me like something I can relate to. Um, and then when you go down that path, you come back to the sort of data engineering path that I really enjoy. So I could see myself, you know, keeping on working on that, the whole data, privacy and analytics, both topics that are very close to my heart, and I think can be combined. They're not opposites. That is something I would definitely stay true to >>Data. Privacy is a really interesting topic. We're seeing so many, you know, GDPR was how many years did a few years old that is now, and we've got other countries and states within the United States, for example, there's California has CCPA, which will become CPRA next year. And it's expanding the definition of what private sensitive data is. So we're companies have to be sensitive to that, but it's a huge challenge to do so because there's so much potential that can come from the data yet, we've got that personal aspect, that sensitive aspect that has to be aware of otherwise there's huge fines. Totally. Where do you think we are with that in terms of kind of compliance? >>So, um, I think in the past years we've seen quite a few, uh, rather shocking examples, um, in the United States, for instance, where, um, yeah, personal data was used or all proxies, um, that led to, uh, detrimental outcomes, um, in Europe, thanks to the strong data regulations. I think, um, we haven't had as many problems, but here the question remains, well, where do you draw the line? And, you know, how do you design this trade-off in between increasing efficiency, um, making business applications better, for example, in the case of SAP, um, while protecting the individual, uh, privacy rights of, of people. So, um, I guess in one way, SAP has a, as an easier position because we deal with business data. So anybody who doesn't want to care about the human element maybe would like to, you know, try building models and machine generated data first. >>I mean, at least I would feel much more comfortable because as soon as you look at personally identifiable data, you really need to watch out, um, there is however ways to make that happen. And I was touching upon these anonymization techniques that I think are going to be, um, more and more important in the, in the coming years, there is a proposed on the way by the European commission. And I was actually impressed by the sophisticated newness of legislation in, in that area. And the plan is for the future to tie the rules around the use of data science, to the specific objectives of the project. And I think that's the only way to go because of the data's out there it's going to be used. Right. We've sort of learned that and true anonymization might not even be possible because of the amount of data that's out there. So I think this approach of, um, trying to limit the, the projects in terms of, you know, um, looking at what do they want to achieve, not just for an individual company, but also for us as a society, think that needs to play a much bigger role in any data-related projects where >>You said getting true anonymization isn't really feasible. Where are we though on the anonymization pathway, >>If you will. I mean, it always, it's always the cost benefit trade off, right? Because if the question is not interesting enough, so if you're not going to allocate enough resources in trying to reverse engineer out an old, the tie to an individual, for example, sticking true to this, um, anonymization example, um, nobody's going to do it right. We live in a world where there's data everywhere. So I feel like that that's not going to be our problem. Um, and that is why this approach of trying to look at the objectives of a project come in, because, you know, um, sometimes maybe we're just lucky that it's not valuable enough to figure out certain details about our personal lives so that nobody will try, because I am sure that if people, data scientists tried hard enough, um, I wonder if there's challenges they wouldn't be able to solve. >>And there has been companies that have, you know, put out data sets that were supposedly anonymized. And then, um, it wasn't actually that hard to make interferences and in the, in the panel and equity one lab, one last thought about that. Um, we heard Jessica speak about, uh, construction and you know, how she would, um, she was trying to use, um, synthetic data because it's so hard to get the real data. Um, and the challenge of getting the synthetic data to, um, sort of, uh, um, mimic the true data. And the question came up of sensors in, in the household and so on. That is obviously a huge opportunity, but for me, it's somebody who's, um, very sensitive when it comes to privacy considerations straight away. I'm like, but what, you know, if we generate all this data, then somebody uses it for the wrong reasons, which might not be better urban planning for all different communities, but simple profit maximization. Right? So this is something that's also very dear to my heart, and I'm definitely going to go down that path further. >>Well, Hannah, it's been great having you on the program. Congratulations on being a Wood's ambassador. I'm sure there's going to be a lot of great lessons and experiences that you'll take back to Germany from here. Thank you so much. We appreciate your time for Hannah Sperling. I'm Lisa Martin. You're watching the QS live coverage of women in data science conference, 2020 to stick around. I'll be right back with my next guest.

>>and welcome to this cube conversation. I'm john for a host of the queue here in Palo alto California. We've got two great remote guests to talk about, some big news hitting with scalability and Hewlett Packard enterprise drill, MCAT ceo of sexuality and chris Tinker, distinguished technologist from H P E. Hewlett Packard enterprise U room chris, Great to see you both. Cube alumni's from an original gangster days. As we say Back then when we started almost 11 years ago. Great to see you both. >>It's great to be back. >>So let's see. So >>really compelling news around kind of this next generation storage, cloud native solution. Okay. It's a, it's really kind of an impact on the next gen. I call, next gen devops meets application, modern application world and some, we've been covering heavily, there's some big news here around sexuality and HP offering a pretty amazing product. You guys introduced essentially the next gen piece of it are pesca, we'll get into in a second. But this is a game changing announcement you guys announces an evolution continuing I think it's more of a revolution but I think you know storage is kind of abstraction layer of evolution to this app centric world. So talk about this environment we're in and we'll get to the announcement which is object store for modern workloads but this whole shift is happening jerome, this is a game changer to storage, customers are gonna be deploying workloads. >>Yeah skeleton. Really I mean I personally really started working on Skele T more than 10 years ago 15 now And if we think about it I mean cloud has really revolutionized IT. and within the cloud we really see layers and layers of technology. I mean we all started around 2006 with Amazon and Google and finding ways to do initially we was consumer it at very large scale, very low incredible reliability and then slowly it creeped into the enterprise and at the very beginning I would say that everyone was kind of wizards trying things and and really coupling technologies together uh and to some degree we were some of the first wizard doing this But we're now close to 15 years later and there's a lot of knowledge and a lot of experience, a lot of schools and this is really a new generation, I'll call it cloud native, you can call it next year and whatever, but there is now enough experience in the world, both at the development level and at the infrastructure level to deliver truly distributed automate systems that run on industry standard service. Obviously good quality server deliver a better service than the service. But there is now enough knowledge for this to truly go at scale and call this cloud or call this cloud native. Really the core concept here is to deliver scalable I. T at very low cost, very high level of reliability. All based on software. We've we've been participated in this solution but we feel that now the draft of what's coming is at the new level and it was time for us to think, develop and launch a new product that specifically adapted to that. And chris I will let you comment on this because customers or some of them you can add a custom of you to that. >>Well, you know, you're right. You know, I've been in there have been like you have been in this industry for uh, well a long time, a little longer to 20, years. This HPV and engineering and look at the actual landscape has changed with how we're doing scale out, suffered to find storage for particular workloads and were a catalyst has evolved. Here is an analytic normally what was only done in the three letter acronyms and massively scale out politics name, space, file systems, parallel file systems. The application space has encroached into the enterprise world where the enterprise world needed a way to actually take a look at how to help simplify the operations. How do I actually be able to bring about an application that can run in the public cloud or on premise or hybrid. Be able to actually look at a workload off my stat that aligns the actual cost to the actual analytics that I'm going to be doing the work load that I'm going to be doing and be able to bridge those gaps and be able to spin this up and simplify operations. And you know, and if you if you are familiar with these parallel fossils, which by the way we we actually have on our truck. I do engineer those. But they are they are they are they have their own unique challenges. But in the world of enterprise where customers are looking to simplify operations, then take advantage of new application, analytic workloads, whether it be sparred may so whatever it might be right. If I want to spend the Mongol BB or maybe maybe a last a search capability, how do I actually take those technologies embrace a modern scale out storage stack that without without breaking the bank but also provide a simple operations. And that's that's why we look for object storage capabilities because it brings us this massive parallelization. Thank you. >>Well, before we get into the product, I want to just touch on one thing from you mentioned and chris you, you brought up the devoPS piece, next gen, next level, whatever term you use it is cloud Native. Cloud Native has proven that deVOPS infrastructure as code is not only legit being operationalized in all enterprises, add security in there. You have def sec ops this is the reality and hybrid cloud in particular has been pretty much the consensus. Is that standard. So or de facto saying whatever you want to call it, that's happening. Multi cloud on the horizon. So these new workloads have these new architectural changes, cloud on premises and edge, this is the number one story and the number one challenge, all enterprises are now working on how do I build the architecture for the cloud on premises and edge. This is forcing the deVOPS team to flex and build new apps. Can you guys talk about that particular trend and is and is that relevant here? >>Yeah, I, I not talk about uh really storage anywhere and cloud anywhere. And and really the key concept is edged to go to cloud. I mean we all understand now that the Edge will host a lot of data and the edges many different things. I mean it's obviously a smartphone, whatever that is, but it's also factories, it's also production, it's also, you know, moving uh moving machinery, trains, playing satellites, um that that's all the Edge cars obviously uh and a lot of that, I will be both produced and processed there. But from the Edge you will want to be able to send that uh for analysis for backup for logging to a court. And that core could be regional maybe not, you know, one call for the whole planet, but maybe one corporate region uh state in the US. Uh and then from there, you will also want to push some of the data to probably cloud. Uh One of the things that we see more and more is that the the our data center, the disaster recovery is not another physical data center, it's actually the cloud and that's a very efficient infrastructure, very cost efficient. Especially so really it's changing the padding on how you think about storage because you really need to integrate these three layers in a consistent approach, especially around the topic of security because you want the data to be secure all along the way and the data is not just data data and who can access the data, can modify the data. What are the conditions that allow modification or automatically ratios that are in some cases it's super important that data be automatically raised 10 years and all this needs to be transported fromage Co two cloud. So that that's one of the aspects, another aspect that resonates for me with what you said is a word you didn't say but it's actually crucial this whole revolution. It's kubernetes mean Cuban it isn't now a mature technology and it's just, you know, the next level of automaticity operation for distributed system Which we didn't have five or 10 years ago and that is so powerful that it's going to allow application developers to develop much faster system that can be distributed again edge to go to crowd because it's going to be an underlying technology that spans the three layers >>chris your thoughts. Hybrid cloud, I've been, I've been having conscious with the HP folks for got years and years on hybrid clouds now here. >>Well, you know, and it's exciting in a layout, right? So if you look at like a whether it be enterprise virtualization that is a scale out gender purpose fertilization workload. Whether the analytic workloads, whether we know data protection is a paramount to all of this orchestration is paramount. Uh if you look at that depth laptops absolutely you mean securing the actual data. The digital last set is absolutely paramount. And if you look at how we do this, look at the investments we're making we're making. And if you look at the collaborative platform development which goes to our partnership with reality it is we're providing them an integral aspect of everything we do. Whether we're bringing as moral which is our suffer be used orchestration. Look at the veneer of its control plane controlling kubernetes being able to actually control the african area clusters in the actual backing store for all the analytics. And we just talked about whether it be a web scale out That is traditionally using politics. Name space has now been modernized to take advantage of newer technologies running an envy me burst buffers or 100 gig networks with slingshot network at 200 and 400 gigabit. Looking at how do we actually get the actual analytics the workload to the CPU and have it attached to the data at rest? Where is the data? How do we land the data and how do we actually align essentially locality, locality of the actual asset to the compute. This is where, you know, we can leverage whether it be a juror or google or name your favorite hyper scaler, leverage those technologies leveraging the actual persistent store and this is where scale it is with this object store capability has been an industry trend setter, uh setting the actual landscape of how to provide an object store on premise and hybrid cloud running into public cloud but be able to facilitate data mobility and tie it back to and tie it back to an application. And this is where a lot of things have changed in the world of the, of analytics because the applications, the newer technologies that are coming on the market have taken advantage of this particular protocol as three so they can do web scale massively parallel concurrent workloads, >>you know what, let's get into the announcement, I love cool and relevant products and I think this hits the Mark Scaletta you guys have are Tesco which is um, just announced and I think, you know, we obviously we reported on it. You guys have a lightweight, true enterprise grade object store software for kubernetes. This is the announcement, Jerome. Tell us about it. >>What's the big >>deal? Cool and >>relevant? Come on, >>this is cool. All right, tell us >>I'm super excited. I'm not sure that it did. That's where on screen, but I'm super, super excited. You know, we, we introduced the ring 11 years ago and this is our biggest announcements for the past 11 years. So yes, do pay attention. Uh, you know, after after looking at all these trends and understanding where we see the future going, uh, we decided that it was time to embark block. So there's not one line of code that's the same as the previous generation product. They will both could exist. They both have space in the market, uh, and artist that was specifically this design for this cloud native era. And what we see is that people want something that's lightweight, especially because it had to go to the edge. They still want the enterprise grade, the security is known for and it has to be modern. What we really mean by modern is uh, we see object storage now being the primary storage for many application more and more applications and so we have to be able to deliver the performance that primary storage expects. Um this idea of skeletons serving primary storage is actually not completely new When we launched guilty 10 years ago, the first application that we were supporting West consumer email for which we were and we are still today the primary story. So we have we know what it is to be the primary store, we know what's the level of reliability you need to hit. We know what, what latest thinking and latency is different from fruit, but you really need to optimize both. Um, and I think that's still today. We're the only object storage company that protects that after both replication and the red recording because we understand that replication is factor the recording is better and more larger file were fast in terms of latency doesn't matter so much. So we, we've been bringing all that experience but really rethinking a product for that new generation that really is here now. And so we're truly excited against a little bit more about the product. It's a software was guilty is a software company and that's why we love to partner with HP who's producing amazing service. Um, you know, for the record and history, the very first deployment of skeleton in 2000 and 10 was on the HP service. So this is a, a long love story here. Um, and so to come back to artistic, uh, is lightweight in the sense that it's easy to use. We can start small, we can start from just one server or 11 VM instance. I mean start really small. Can grow infinitely. The fact that we start small, we didn't, you know, limit the technology because of that. Uh, so you can start from one too many. Um, and uh, it's contaminated in the sense that it's completely Cuban, it is compatible. It's communities orchestrated. It will deploy on many Cuban distributions. We're talking obviously with Admiral, we're also talking with Ponzu and with the other in terms of uh, communities distribution will also be able to be run in the cloud. I'm not sure that there will be many uh, true production deployment of artists in the club because you already have really good object storage by the cloud providers. But when you are developing something and you want to test their, um, you know, just doing it in the cloud is very practical. So you'll be able to deploy our discount communities cloud distribution and it's modern object storage in the sense that its application century. A lot of our work is actually validating that our storage is fit for a single purpose application and making sure that we understand the requirement of this application that we can guide our customers on how to deploy. And it's really designed to be the primary storage for these new workloads. >>The big part of the news is your relationship with Hewlett Packard Enterprises? Some exclusivity here as part of this announced, you mentioned, the relationship goes back many, many years. We've covered your relationship in the past chris also, you know, we cover HP like a blanket. Um, this is big news for h P E as >>well. >>What is the relationship talk about this? Exclusivity could you share about the partnership and the exclusivity piece? >>Well, the partnership expands into the pan HPV portfolio. We look we made a massive investment in edge IOT devices. Uh, so we actually have, how do we align the cost to the demand for our customers come to us wanting to looking at? Uh think about what we're doing with green, like a consumption based modeling, they want to be able to be able to consume the asset without having to do a capital outlay out of the gate uh, number to look at, you know, how do you deploy? Technology really demand? It depends on the scale. Right? So in a lot of your web skill, you know, scale out technologies, uh, putting them on a diet is challenging, meaning how skinny can you get it getting it down into the 50 terabyte range and then the complexities of those technologies at as you take a day one implementation and scale it out over, you know, you know, multiple iterations of recorders. The growth becomes a challenge. So, working with scalability, we we believe we've actually cracked this nut. We figured out how to a number one, how to start small but not limited customers ability to scale it out incrementally or grotesquely grotesque. A you can depending on the quarters the month, whatever whatever the workload is, how do you actually align and be able to consume it? Uh So now, whether it be on our edge line products are D. L. Products go back there. Now what the journalist talking about earlier, you know, we ship a server every few seconds. That won't be a problem. But then of course into our density optimized compute with the Apollo product. Uh This where uh our two companies have worked in an exclusivity where the, the scaly software bonds on the HP ecosystem. Uh and then we can of course provide you our customers the ability to consume that through our Green link financial models or through a complex parts of >>awesome. So jerome and chris who's the customer here? Obviously there's an exclusive period talk about the target customer. And how do customers get the product? How do we get the software? And how does this exclusivity with HP fit into it? >>Yeah. So there's really three types of customers and we really, we've worked a lot with a company called use design to optimize the user interface for each of the three types of customers. So we really thought about each uh customer role and providing with each of them the best product. Uh So the first type of customer application owners who are deploying application that requires an object storage in the back end. They typically want a simple objects to of one application. They wanted to be temple and work. I mean yesterday they want no freedom to just want an object store that works and they want to be able to start as small as they start with their application. Often it's, you know, the first department, maybe a small deployment. Um, you know, applications like backup like female rubric or uh, analytics like Stone Carver, tikka or false system now available as a software. Uh, you know, like Ceta does a really great department or nass that works very well. That means an object store in the back end of high performance computing. Wake up file system is an amazing file system. Um, we also have vertical application like broad peak, for example, who provides origin and view the software, the broadcasters. So all these applications, they request an object store in the back end and you just need a simple, high performance, working well object store and I'll discuss perfect. The second type of people that we think will be interested by artists. Uh essentially developers who are currently developing some communities of collaborative application your next year. Um and as part of their development stack, um it's getting better and better when you're developing a cloud native application to really target an object storage rather than NFS as you're persistently just, you know, think about generations of technologies and um, NFS and file system were great 25 years ago. I mean, it's an amazing technology. But now when you want to develop a distributed scalable application, objects toys a better fit because it's the same generation and so same thing. I mean, you know, developing something, they need uh an object so that they can develop on so they wanted very lightweight, but they also want the product that they're enterprise or their customers will be able to rely on for years and years on and this guy is really great for today. Um, the third type of customer are more architecture with security architects that are designing, uh, System where they're going to have 50 factories, 1000 planes, a million cars are going to have some local storage, which will they want to replicate to the core and possibly also to the club. And uh, as the design is really new generation workloads that are incredibly distributed. But with local storage, uh, these guys are really grateful for that >>and talk about the HP exclusive chris what's the, how does that fit into? They buy through sexuality. Can they get it for the HP? Are you guys working together on how customers can procure >>place? Yeah. Both ways they can procure it through security. They can secure it through HP. Uh, and it is the software stack running on our density, optimized compute platforms which you would choose online does. And to provide an enterprise quality because if it comes back to it in all of these use cases it's how do we align up into a true enterprise step? Um bringing about multi Tennessee, bringing about the fact that, you know, if you look at like a local racial coding, uh one of the things that they're bringing to it so that we can get down into the deal 3 25. So with the exclusivity, uh you actually get choice and that choice comes into our entire portfolio, whether it be the edge line platform, the D. L 3:25 a.m. B. Processing stack or the intel deal three eighties or whether whether it be the Apollo's or Alexa, there's there's so many ample choices there that facilitates this and it just allows us to align those two strategies >>awesome. And I think the kubernetes pieces really relevant because, you know, I've been interviewing folks practitioners um and kubernetes is very much maturing fast. It's definitely the centerpiece of the cloud native, both below the line, if you will under the hood for the, for the infrastructure and then for apps, um they want to program on top of it. That's critical. I mean, jeremy, this is like this is the future. >>Yeah. And if you don't mind, like to come back for a minute on the exclusive with HP. So we did a six month exclusive and the very reason we could do this is because HP has suffered such wrath of server portfolio and so we can go from, you know, really simple, very cheap, you know, HDD on the L 3 80 means a machine that retails for a few $4. I mean it's really like Temple System 50 terabyte. Uh we can have the dl 3 25. That uh piece mentioned there is really a powerhouse. All envy any uh slash uh all the storage is envy any uh very fast processors or uh you know, dance large large system like the Apollo 4500. So it's a very large breath of portfolio. We support the whole portfolio and we work together on this. So I want to say that you know, one of the reasons I want to send kudos to HP for for the breath of the silver lining rio as mentioned, um Jessica can be ordered from either company, hand in hand together. So anyway you'll see both of us uh and our field is working incredibly well together. >>We'll just on that point, I think just for clarification, uh was this co design by scalability and H P E. Because chris you mentioned, you know, the configuration of your systems. Can you guys quickly talk about the design, co design >>from from from the code base? The software entirely designed and developed by security from a testing and performance. So this really was a joint work with HP providing both hardware and manpower so that we could accelerate the testing phase. >>You know, chris H P E has just been doing such a great job of really focused on this. And you know, I've been Governor for years before it was fashionable the idea of apps working no matter where it lives. Public Cloud data center Edge, you mentioned. Edge line has been around for a while. You know, apps centric, developer friendly cloud first has been an H P E. Kind of guiding first principle for many, many years. >>But it has and you know, you know as our our ceo internal areas cited by 2022 everything will be able to be consumed as a service in our portfolio. Uh And then this stack allows us the simplicity and the consume ability of the technology and degranulation of it allows us to simplify the installation, simplify the actual deployment bringing into a cloud ecosystem. But more importantly for the end customer, they simply get an enterprise quality product running on identity optimized stack that they can consume through a orchestrated simplistic interface. That's that's cos that's what they're warning for today is where they come to me and asked hey how do I need a, I've got this new app new project and you know it goes back to who's actually coming, it's no longer the I. T. People who are actually coming to us, it's the lines of business. It's it's that entire dimension of business owners coming to us going this is my challenge and how can you HP help us And we rely on our breath of technology but also a breath of partners to come together and are of course reality is hand in hand and are collaborative business unit are collaborative storage product engineering group that actually brought this market. So we're very excited about this solution >>chris thanks for that input. Great insight, Jerome, congratulations on a great partnership with H. P. E. Obviously um great joint customer base congratulations on the product release here. Big moving the ball down the field as they say new functionality, clouds cloud native object store, phenomenal um So wrap wrap wrap up the interview. Tell us your vision for scalability in the future of storage. >>Yeah. Yeah I start I mean skeleton is going to be an amazing leader is already um but yeah so you know I have three themes that I think will govern how storage is going and obviously um Mark Andrews had said it software is everywhere and software is eating the world so definitely that's going to be true in the data center in storage in particular. Uh But the free trends that are more specific. First of all I think that security performance and agility is now basic expectation. It's not you know, it's not like an additional feature. It's just the best table, stakes, security performance and a job. Um The second thing is and we've talked about it during this conversation is edged to go you need to think your platform with Edge Co and cloud. You know you don't want to have separate systems separate design interface point for edge and then think about corn and think about clouds and then think about the divers. All this needs to be integrated in the design. And the third thing that I see as a major trend for the next 10 years is that a sovereignty uh more and more. You need to think about where is the data residing? What are the legal challenges? What is the level of protection against who are you protected? What what is your independence uh strategy? How do you keep as a company being independent from the people? You need to be independent. And I mean I say companies, but this is also true for public services. So these these for me are the three big trends. I do believe that uh software find distributed architecture are necessary for these tracks. But you also need to think about being truly enterprise grade. And there has been one of our focus with the design of a fresca. How do we combine a lot with product With all of the security requirements and that our sovereignty requirements that we expect to have in the next 10 years? >>That's awesome. Congratulations on the news scale. D Artois ca the big release with HP exclusive um, for six months, chris tucker, distinguished engineer at H P E. Great to ceo, jeremy, katz, ceo sexuality. Great to see you as well. Congratulations on the big news. I'm john for the cube. Thanks for watching. >>Mhm. >>Yeah.

>> Announcer: Live from Orlando Florida, it's theCUBE, covering Microsoft Ignite. Brought to you by Cohesity. >> Good morning everyone. You are watching theCUBE's live coverage of Microsoft Ignite 2019 here in Orlando, Florida. I'm your host Rebecca Knight, co-hosting alongside of Stu Miniman. We are joined by Donovan Brown. He is the Principal Cloud Advocate Manager of Methods and Practices Organizations at Microsoft. (laughing) A mouthful of a title. >> Yes. >> Rebecca: We are thrilled to welcome you on. >> Thank you so much. >> You are the man in the black shirt. >> I have been dubbed the man in the black shirt. >> So tell us what that's all about. You're absolutely famous. Whenever we were saying Donovan Brown's going to be here. "The man in the black shirt?" >> Yes. >> So what's that about? >> So it was interesting. The first time I ever got to keynote in an event was in New York in 2015 for Scott Guthrie, the guy who only wears a red shirt. And I remember, I was literally, and this is no exaggeration, wearing this exact black shirt, right, because I bring it with me and I can tell because the tag in the back is worn more than the other black shirts I have just like this one. And I bring this one out for big events because I was in a keynote yesterday and I knew I was going to be on your show today. And I wore it and it looked good on camera. I felt really good. I'm an ex-athlete. We're very superstitious. I'm like I have to wear that shirt in every keynote that I do from now on because if you look further back, you'll see me in blue shirts and all other colored shirts. But from that day forward, it's going to be hard pressed for you to find me on camera on stage without this black shirt on or a black shirt of some type. And there's a really cool story about the black shirt that was. This is what\ I knew it was a thing. So I pack about six or seven black shirts in every luggage. I'm flying overseas to Germany to go Kampf to do a keynote for, I think it was Azure Saturday. Flights were really messed up. they had to check my bag which makes me very uncomfortable because they lose stuff. I'm not too worried about it, it'll be okay. Check my bag, get to Europe. They've been advertising that the black shirt is coming for months and they lose my luggage. And I am now, heart's pounding out of my chest. (laughing) We go to the airport. I'm shopping in the airport because I don't even have luggage. I cannot find a black shirt and I am just thinking this is devastating. How am I going to go to a conference who's been promoting "the black shirt's coming" not wearing a black shirt? And my luggage does not show up. I show up at the event I'm thinking okay, maybe I'll get lucky and the actual conference shirt will be black and then we're all good. I walk in and all I see are white shirts. I'm like this could not be worse. And then now the speakers show up. They're wearing blue shirts, I'm like this cannot be happening. So I'm depressed, I'm walking to the back and everyone's starts saying, "Donovan's here, Donovan's here." And I'm looking to find my polo, my blue polo I'm going to put on. They're like no, no, no, no Donovan. They printed one black shirt just for me. I was like oh my goodness, this is so awesome. So I put the black shirt on, then I put a jacket on over it and I go out and I tell the story of how hard it was to get here, that they lost my luggage, I'm not myself without a black shirt. But this team had my back. And when I unzipped my shirt, the whole place just starts clapping 'cause I'm wearing >> Oh, I love it. >> a black shirt. >> Exactly. So now to be seen without a black shirt is weird. Jessica Dean works for me. We were in Singapore together and it was an off day. So I just wore a normal shirt. She had to take a double take, "Oh no, is that Donovan, my manager "'cause he's not wearing a black shirt?" I don't wear them all the time but if I'm on camera, on stage you're going to see me in a black shirt. >> Rebecca: All right, I like it. >> Well, Donovan, great story. Your team, Methods and Practices makes up a broad spectrum of activities and was relatively recently rebranded. >> Yeah. >> We've talked to some of your team members on theCUBE before, so tell our audience a little bit about the bridges Microsoft's building to help the people. >> Great. No, so that's been great. Originally, I built a team called The League. Right, there's a really small group of just DevOps focused diehards. And we still exist. A matter of fact, we're doing a meet and greet tonight at 4:30 where you can come and meet all five of the original League members. Eventually, I got tasked with a much bigger team. I tell the story. I was in Norway, I went to sleep, I had four direct reports. I literally woke up and I had 20 people reporting to me and I'm like what just happened? And the team's spanned out a lot more than just DevOps. So having it branded as the DevOps Guy doesn't really yield very well for people who aren't diehard DevOps people. And what we feared was, "Donovan there's people who are afraid of DevOps "who now report to you." You can't be that DevOps guy anymore. You have to broaden what you do so that you can actually focus on the IT pros in the world, the modern operations people, the lift and shift with Jeremy, with what Jeramiah's doing for me right, with the lift and shift of workloads . And you still have to own DevOps. So what I did is I pulled back, reduced my direct reports to four and now I have teams underneath me. Abel Wang now runs DevOps. He's going to be the new DevOps guy for me. Jeramiah runs our lift and shift. Rick Klaus or you know the Hat, he runs all my IT Pro and then Emily who's just an amazing speaker for us, runs all of my modern operations. So we span those four big areas right. Modern operations which is sort of like the ops side of DevOps, IT pros which are the low level infrastructure, diehard Windows server admins and then we have DevOps run by Abel which is still, the majority of The League is over there. And then we have obviously the IT pros, modern ops, DevOps and then the left and shift with Jeramiah. >> I'd like to speak a little bit as to why you've got these different groups? How do you share information across the teams but you know really meet customers where they are and help them along 'cause my background's infrastructure. >> Donovan: Sure. >> And that DevOps, was like that religion pounding at you, that absolutely, I mean, I've got a closet full of hoodies but I'm not a developer. Understand? >> Understood. (laughs) It's interesting because when you look at where our customers are today, getting into the cloud is not something you do overnight. It takes lots of steps. You might start with a lift and shift, right? You might start with just adding some Azure in a hybrid scenario to your on-prem scenario. So my IT pros are looking after that group of people that they're still on prem majority, they're trying to dip those toes into the cloud. They want to start using things like file shares or backups or something that they can have, disaster recovery offsite while they're still running the majority of what they're doing on-prem. So there's always an Azure pool to all four of the teams that I actually run. But I need them to take care of where our customers are today and it's not just force them to be where we want them tomorrow and they're not ready to go there. So it's kind of interesting that my team's kind of have every one of those stages of migration from I'm on-prem, do I need to lift and shift do I need to do modern operations, do I need to be doing full-blown DevOps pull all up? So, I think it's a nice group of people that kind of fit the spectrum of where our customers are going to be taking that journey from where they are to enter the cloud. So I love it. >> One of the things you said was getting to the cloud doesn't happen overnight. >> No, it does not. >> Well, you can say that again because there is still a lot of skepticism and reluctance and nervousness. How do you, we talked so much about this digital transformation and technology is not the hard part. It's the people that pose the biggest challenges to actually making it happen. >> Donovan: Right. >> So we're talking about meeting customers where they are in terms of the tools they need. But where do you meet them in terms of where they are just in their approach and their mindset, in terms of their cloud readiness? >> You listen. Believe it or not, you can't just go and tell people something. You need to listen to them, find out what hurts and then start with that one thing is what I tell people. Focus on what hurts the most first. Don't do a big bang change of any type. I think that's a recipe for disaster. There's too many variables that could go wrong. But when I sit down with a customer is like tell me where you are, tell me what hurts, like what are you afraid of? Is it a compliancies? Let me go get you in contact with someone who can tell you about all the comp. We have over 90 certifications on Azure. Let me. whatever your fear is, I bet you I can get you in touch with someone that's going to help you get past that fear. But I don't say just lift, shift, move it all like stop wasting, like no. Let's focus on that one thing. And what you're going to do is you're going to start to build confidence and trust with that customer. And they know that I'm not there just trying to rip and replace you and get out high levels of ACR. I'm trying to succeed with you, right, empower every person in every organization on the planet to achieve more. You do that by teaching them first, by helping them first. You can sell them last, right? You shouldn't have to sell them at all once they trust that what we we're trying to do together is partner with you. I look at every customer more as a partner than a customer, like how can I come with you and we do better things together than either one of us could have done apart. >> You're a cloud psychologist? Almost, right because I always put myself in their position. If I was a customer, what would I want that vendor to do for me? How would they make me feel comfortable and that's the way that I lead. Right, I don't want you going in there selling anything right. We're here to educate them and if we're doing our job on the product side, the answer is going to be obvious that you need to be coming with us to Azure. >> All right. So Donovan, you mentioned you used to be an athlete? >> Donovan: Yes. >> According to your bio, you're still a bit of an athlete. >> Donovan: A little bit, a little bit. >> So there's the professional air hockey thing which has a tie to something going on with the field. Give us a little bit of background. I've got an air hockey table in my basement. Any tips for those of us that aren't, you know? You were ranked 11th in the world. >> At one point, yeah, though I went to the World Championships. It was interesting because that World Championships I wasn't prepared. My wife plays as well. We were like we're just going to go, we're going to support the tournament. We had no expectations whatsoever. Next thing you know, I'm in the round playing for the top 10 in the world. And that's when it got too serious for me and I lost, because I started taking it too serious. I put too much pressure on myself. But professionally, air hockey's like professional foosball or pool. It's grown men taking this sport way too seriously. It's the way I'd describe it. It is not what you see at Chuck E. Cheese. And what was interesting is Damien Brady who works for me found that there is an AI operated air hockey table here on this floor. And my wife was like, oh my gosh, we have to find this machine. Someone tape Donovan playing it. Six seconds later, my first shot I scored it. And I just looked at the poor people who built it and I'm like yeah, I'm a professional air hockey player. This thing is so not ready for professional time but they took down all my information and said we'd love to consult with you. I said I'd love to consult with you too because this could be a lot of fun. Maybe also a great way for professionals to practice, right, because you don't always have someone who's willing to play hours and hours which it takes to get at the professional level. But to have an AI system that I could even teach up my attack, forcing me to play outside of my comfort zone, to try something other than a left wall under or right well over but have to do more cuts because it knows to search for that. I can see a lot of great applications for the professionalized player with this type of AI. It would actually get a lot better. Literally, someone behind me started laughing. "That didn't take long" because it in six seconds I had scored on it already. I'm like okay, I was hoping it was going to be harder than this. >> I'm thinking back to our Dave Cahill interview of AI for everyone, and this is AI for professional air hockey players. >> It is and in one of my demos, Kendra Havens showed AI inside of your IDE. And I remember I tell the story that I remember I started writing software back in the 90s. I remember driving to a software store. You remember we used to have to drive and you'd buy a box and the box would be really heavy because the manuals are in there, and not to mention a stack of floppy discs that you're going to spend hours putting in your computer. And I bought visual C++ 1.52 was my first compiler. I remember going home so excited. And it had like syntax highlighting and that was like this cool new thing and you had all these great breakpoints and line numbers. And now Kendra's on stage typing this repetitives task and then the editor stops her and says, "It looks like you need to do this a little bit more. "You want me to do this for you?" And I'm like what just happened? This is not syntax highlighting. This is literally watching what you do, identifying a repetitive task, seeing the pattern in your code and suggesting that I can finish writing this code for you. It's unbelievable. >> You bring up a great point. Back when I used to write, it was programming. >> Yes. >> And we said programming was you learn the structure, you learn the logic and you write all the lines of what's going to be there. Coding on the other hand usually is taking something that is there, pulling in the pieces, making the modification. >> Right. >> It sounds like we're talking about even the next generation where the intelligence is going to take over. >> It's built right inside of your IDE which is amazing. You were talking about artificial intelligence, not only for the air hockey. But I love the fact that in Azure, we have so many cognitive services and you just like pick these off the shelf. When I wanted to learn artificial intelligence when I was in the university, you had to go for another language called Lisp. That scared half of us away from artificial intelligence because you have to learn another language just to go do this cool thing that back then was very difficult to do and you could barely get it to play chess, let alone play air hockey. But today, cognitive services search, decision-making, chat bots, they're so easy. Anyone, even a non developer, can start adding the power of AI into their products thanks to the stuff that we're doing in Azure. And this is just lighting up all these new possibilities for us, air hockey, drones that are able to put out fires. I've just seen amazing stuff where they're able to use AI and they add it with as little as two lines of code. And all of a sudden, your app is so much more powerful than it was before. >> Donovan, one of the things that really struck me over the last couple years, looking at Microsoft, is it used to be, you'd think about the Microsoft stack. When I think about developers it's like, oh wait are you a .NET person? Well, you're going to be there. The keynote this morning, one of your team members was on stage with Scott Hanselman and was you know choose your language, choose your tools and you're going to have all of them out there. So talk to us a little bit about that transition inside Microsoft. >> Sure. One of the mantras that I've been saying for a while is "any language, any platform". No one believes me . So I had to start proving it. I'm like so I got on stage one year. It was interesting and this is a really rough year because I flew with three laptops. One had Mac OS on it, one of them had Linux on it and one of them had Windows. And what I did is I created a voting app and what I would do is I'd get on stage and say okay everyone that's in this session, go to this URL and start voting. They got to pick what computer I use, they got to pick what language I programmed in and they got to pick where in Azure-eyed I deployed it to. Was it to an app service was it to Docker? I'm like I'm going to prove to you I can do any language in any platform. So I honestly did not know what demo I was going to do. 20 minutes later, after showing them some slides, I would go back to the app and say what did you pick? And I would move that computer in front of me and right there on stage completely create a complete CI/CD pipeline for the language that that audience chose to whatever resources that they wanted on whatever platform that they wanted me. Was like, have I proven this to you enough or not? And I did that demo for an entire year. Any language that you want me to program in and any platform you want me to target, I'm going to do that right now and I don't even know what it's going to be. You're going to choose it for me. I can't remember the last time I did a .NET demo on stage. I did Python this week when I was on stage with Jason Zander. I saw a lot of Python and Go and other demos this year. We love .NET. Don't get us wrong but everyone knows we can .NET. What we're trying to prove right now is that we can do a lot of other things. It does not matter what language you program in. It does not matter where you want to deploy. Microsoft is here to help you. It's a company created by developers and we're still obsessed with developers, not just .NET developers, all developers even the citizen developer which is a developer which is a developer who doesn't have to see the code anymore but wants to be able to add that value to what they're doing in their organization. So if you're a developer, Microsoft is here to help full-stop. It's a powerful mission and a powerful message that you are really empowering everyone here. >> Donovan: Right. >> Excellent. >> And how many developers only program in one language now, right? I thought I remember I used to be a C++ programmer and I thought that was it, right. I knew the best language, I knew the fastest language. And then all of a sudden, I knew CSharp and I knew Java and I knew JavaScript and I brought a lot of PowerShell right now and I write it on and noticed like wow, no one knows one language. But I never leave Visual Studio code. I deploy all my workloads into Azure. I didn't have to change my infrastructure or my tools to switch languages. I just switched languages that fit whatever the problem was that I was trying to solve. So I live the mantra that we tell our customers. I don't just do .NET development. Although I love .NET and it's my go-to language if I'm starting from scratch but sometimes I'm going to go help in an open source project that's written in some other language and I want to be able to help them. With Visual Studio online, we made that extremely easy. I don't even have to set up my development machine anymore. I can only click a link in a GitHub repository and the environment I need will be provisioned for me. I'll use it, check in my commits and then throw it away when I'm done. It's the world of being a developer now and I always giggle 'cause I'm thinking I had to drive to a store and buy my first compiler and now I can have an entire environment in minutes that is ready to rock and roll. It's just I wish I would learn how to program now and not when I was on bulletin boards asking for help and waiting three days for someone to respond. I didn't have Stack Overflow or search engines and things like that. It's just an amazing time to be a developer. >> Yes, indeed. Indeed it is Donovan Brown, the man in the black shirt. Thank you so much for coming on theCUBE. >> My pleasure. Thank you for having me. >> It was really fun. Thank you. >> Take care. >> I'm Rebecca Knight for Stu Miniman. Stay tuned for more of theCUBE's live coverage of Microsoft Ignite. (upbeat music)

(upbeat techno music) >> Live from Barcelona Spain, it's theCUBE. Covering KubeCon CloudNativeCon Europe 2019. Brought to you by Red Hat, The Cloud Native Computing Foundation and Ecosystem Partners. >> Welcome back, this is The Cube's coverage of KubeCon CloudNativeCon 2019. I'm Stu Miniman with Corey Quinn as my cohost, even though he says kucon. And joining us on this segment, we're not going debate how we pronounce certain things, but I will try to make sure that I get Bridget Kromhout correct. She is a Principle Cloud Advocate at Microsoft. Thank you for coming back to The Cube. >> Thank you for having me again. This is fun! >> First of all I do have to say, the bedazzled shirt is quite impressive. We always love the sartorial, ya know, view we get at a show like this because there are some really interesting shirts and there is one guy in a three-piece suit. But ya know-- >> There is, it's the high style, got to have that. >> Oh, absolutely. >> Bringing some class to the joint. >> Wearing a suit is my primary skill. (laughing) >> I will tell you that, yes, they sell this shirt on the Microsoft company store. And yes, it's only available in unisex fitted. Which is to say much like Alice Goldfuss likes to put it, ladies is gender neutral. So, all of the gentleman who say, but I have too much dad bod to wear that shirt! I say, well ya know get your bedazzlers out. You too can make your own shirt. >> I say it's not dad bod, it's a father figure, but I digress. (laughing) >> Exactly! >> Alright, so Bridget you're doing some speaking at the conference. You've been at this show a few times. Tell us, give us a bit of an overview of what you're doing here and your role at Microsoft these days. >> Absolutely. So, my talk is tomorrow and I think that, I'm going to go with its a vote of confidence that they put your talk on the last day at 2:00 P.M. instead of the, oh gosh, are they trying to bury it? But no, it's, I have scheduled enough conferences myself that I know that you have to put some stuff on the last day that people want to go to, or they're just not going to come. And my talk is about, and I'm co-presenting with my colleague, Jessica Deen, and we're talking about Helm 3. Which is to say, I think a lot of times it would, with these open-sourced shows people say, oh, why do you have to have a lot of information about the third release of your, third major release of your project? Why? It's just an iterative release. It is, and yet there are enough significant differences that it's kind of valuable to talk about, at least the end user experience. >> Yeah, so it actually got an applause in the keynote, ya know. (Bridget laughing) There are certain shows where people are hootin' and hollerin' for every, different compute instance that that is released and you look at it a little bit funny. But at the keynote there was a singular moment where it was the removal of Tiller which Corey and I have been trying to get feedback from the community as to what this all means. >> It seems, from my perspective, it seemed like a very strange thing. It's, we added this, yay! We added this other thing, yay! We're taking this thing and ripping it out and throwing it right into the garbage and the crowd goes nuts. And my two thoughts are first, that probably doesn't feel great if that was the thing you spent a lot of time working on, but secondly, I'm not as steep in the ecosystem as perhaps I should be and I don't really know what it does. So, what does it do and why is everyone super happy to con sine it to the dub rubbish bin of history? >> Right, exactly. So, first of all, I think it's 100% impossible to be an expert on every single vertical in this ecosystem. I mean, look around, KubeCon has 7,000 plus people, about a zillion vendor booths. They're all doing something that sounds slightly, overlapping and it's very confusing. So, in the Helm, if you, if people want to look we can say there's a link in the show notes but there, we can, people can go read on Helm.sh/blog. We have a seven part, I think, blog series about exactly what the history and the current release is about. But the TLDR, the too long didn't follow the link, is that Helm 1 was pretty limited in scope, Helm 2 was certainly more ambitious and it was born out of a collaboration between Google actually and a few other project contributors and Microsoft. And, the Tiller came in with the Google folks and it really served a need at that specific time. And it was, it was a server-side component. And this was an era when the Roll by Stacks has control and Kubernetes was, well nigh not existent. And so there were a lot of security components that you kind of had to bolt on after the fact, And once we got to, I think it was Kubernetes 1.7 or 1.8 maybe, the security model had matured enough that instead of it being great to have this extra component, it became burdensome to try to work around the extra component. And so I think that's actually a really good example of, it's like you were saying, people get excited about adding things. People sometimes don't get excited about removing things, but I think people are excited about the work that went into, removing this particular component because it ends up reducing the complexity in terms of the configuration for anyone who is using this system. >> It felt very spiritually aligned in some ways, with the announcement of Open Telemetry, where you're taking two projects and combining them into one. >> Absolutely. >> Where it's, oh, thank goodness, one less thing that-- >> Yes! >> I have to think about or deal with. Instead of A or B I just mix them together and hopefully it's a chocolate and peanut butter moment. >> Delicious. >> One of the topics that's been pretty hot in this ecosystem for the last, I'd say two years now it's been service matched, and talk about some complexity. And I talk to a guy and it's like, which one of these using? Oh I'm using all three of them and this is how I use them in my environment. So, there was an announcement spearheaded by Microsoft, the Service Mesh Interface. Give us the high level of what this is. >> So, first of all, the SMI acronym is hilarious to me because I got to tell you, as a nerdy teenager I went to math camp in the summertime, as one did, and it was named SMI. It was like, Summer Mathematics Institute! And I'm like, awesome! Now we have a work project that's named that, happy memories of lots of nerdy math. But my first Unix system that I played with, so, but what's great about that, what's great about that particular project, and you're right that this is very much aligned with, you're an enterprise. You would very much like to do enterprise-y things, like being a bank or being an airline or being an insurance company, and you super don't want to look at the very confusing CNCF Project Map and go, I think we need something in that quadrant. And then set your ships for that direction, and hopefully you'll get to what you need. And it's especially when you said that, you mentioned that, this, it basically standardizes it, such that whichever projects you want to use, whichever of the N, and we used to joke about JavaScript framework for the week, but I'm pretty sure the Service Mesh Project of the week has outstripped it in terms of like speed, of new projects being released all the time. And like, a lot of end user companies would very much like to start doing something and have it work and if the adorable start-up that had all the stars on GitHub and the two contributors ends up, and I'm not even naming a specific one, I'm just saying like there are many projects out there that are great technically and maybe they don't actually plan on supporting your LTS. And that's fine, but if we end up with this interface such that whatever service mesh, mesh, that's a hard word. Whatever service mesh technology you choose to use, you can be confident that you can move forward and not have a horrible disaster later. >> Right, and I think that's something that a lot of developers when left to our own devices and in my particular device, the devices are pretty crappy. Where it becomes a, I want to get this thing built, and up and running and working, and then when it finally works I do a happy dance. And no one wants to see that, I promise. It becomes a very different story when, okay, how do you maintain this? How do you responsibly keep this running? And it's, well I just got it working, what do you mean maintain it? I'm done, my job is done, I'm going home now. It turns out that when you have a business that isn't being the most clever person in the room, you sort of need to have a longer term plan around that. >> Yeah, absolutely. >> And it's nice to see that level of maturation being absorbed into the ecosystem. >> I think the ecosystem may finally be ready for it. And this is, I feel like, it's easy for us to look at examples of the past, people kind of shake their heads at OpenStack as a cautionary tale or of Sprawl and whatnot. But this is a thriving, which means growing, which means changing, which means very busy ecosystem. But like you're pointing out, if your enterprises are going to adapt some of this technology, they look at it and everyone here was, ya know, eating cupcakes or whatever for the Kubernetes fifth birthday, to an enterprise just 'cause that launched in 2014, June 2014, that sounds kind of new. >> Oh absolutely. >> Like, we're still, we're still running that mainframe that is still producing business value and actually that's fine. I mean, I think this maybe is one of the great things about a company like Microsoft, is we are our customers. Like we also respect the fact that if something works you don't just yolo a new thing out into production to replace it for what reason? What is the business value of replacing it? And I think for this, that's why this, kind of Unix philosophy of the very modular pieces of this ecosystem and we were talking about Helm a little earlier, but there's also, Draft, Brigade, etc. Like the Porter, the CNET spec implementation stuff, and this Cloud Native application bundles, that's a whole mouthful. >> Yes, well no disrespect to your sparkly shirt, but chasing the shiny thing, and this is new and exciting is not necessarily a great thing. >> Right? >> I heard some of the shiny squad that were on the show floor earlier, complaining a little bit about the keynotes, that there haven't been a whole lot of new service and feature announcements. (Bridget laughing) And my opinion on that is feature not bug. I, it turns out most of us have jobs that aren't keeping up with every new commit to an open-source project. >> I think what you were talking about before, this idea of, I'm the developer, I yolo'd out this co-load into production, or I yolo'd this out into production. It is definitely production grade as long as everything stays on the happy path, and nothing unexpected happens. And I probably have air handling, and, yay! We had the launch party, we're drinkin' and eatin' and we're happy and we don't really care that somebody is getting paged. And, it's probably burning down. And a lot of human misery is being poured into keeping it working. I like to think that, considering that we're paying attention to our enterprise customers and their needs, they're pretty interested in things that don't just work on day one, but they work on day two and hopefully day 200 and maybe day 2000. And like, that doesn't mean that you ship something once and you're like, okay, we don't have to change it for three years. It's like, no, you ship something, then you keep iterating on it, you keep bug fixing, you keep, sure you want features, but stability is a feature. And customer value is a feature. >> Well, Bridget I'm glad you brought that up. Last thing I want to ask you 'cause Microsoft's a great example, as you say, as a customer, if you're an Azure customer, I don't ask you what version of Azure you're running or whether you've done the latest security patch that's in there because Microsoft takes care of you. Now, your customers that are pulled between their two worlds is, oh, wait, I might have gotten rid of patch Tuesdays, but I still have to worry and maintain that environment. How are they dealing with, kind of that new world and still have, certain things that are going to stay the old way that they have been since the 90's or longer? >> I mean, obviously it's a very broad question and I can really only speak to the Kubernetes space, but I will say that the customers really appreciate, and this goes for all the Cloud providers, when there is something like the dramatic CVE that we had in December for example. It's like, oh, every Kubernetes cluster everywhere is horribly insecure! That's awesome! I guess, your API gateway is also an API welcome mat for everyone who wants to, do terrible things to your clusters. All of the vendors, Microsoft included, had their managed services patched very quickly. They're probably just like your Harple's of the world. If you rolled your own, you are responsible for patching, maintaining, securing your own. And this is, I feel like that's that tension. That's that continuum we always see our customers on. Like, they probably have a data center full of ya know, veece, fear and sadness, and they would very much like to have managed happiness. And that doesn't mean that they can easily pickup everything in the data center, that they have a lease on and move it instantly. But we can work with them to make sure that, hey, say you want to run some Kubernetes stuff in your data center and you also want to have AKS. Hey, there's this open-source project that we instantiated, that we worked on with other organizations called Vertual Kubelet. There was actually a talk happening about it I think in the last hour, so people can watch the video of that. But, we have now offered, we now have Virtual Node, our product version of it in GA. And I think this is kind of that continuum. It's like, yes of course, you're early adapters want the open-source to play with. Your enterprises want it to be open-source so they can make sure that their security team is happy having reviewed it. But, like you're saying, they would very much like to consume a service so they can get to business value. Like they don't necessarily want to, take, Kelsey's wonderful Kubernetes The Hard Way Tutorial and put that in production. It's like, hmm, probably not, not because they can't, these are smart people, they absolutely could do that. But then they spent their, innovation tokens as, the McKinley blog post puts it, the, it's like, choose boring technology. It's not wrong. It's not that boring is the goal, it's that you want the exciting to be in the area that is producing value for your organization. Like that's where you want most of your effort to go. And so if you can use well vetted open-source that is cross industry standard, stuff like SMI that is going to help you use everything that you chose, wisely or not so wisely, and integrate it and hopefully not spend a lot of time redeveloping. If you redevelop the same applications you already had, its like, I don't think at the end of the quarter anybody is getting their VP level up. If you waste time. So, I think that is, like, one of the things that Microsoft is so excited about with this kind of open-source stuff is that our customers can get to value faster and everyone that we collaborate with in the other clouds and with all of these vendor partners you see on the show floor, can keep the ecosystem moving forward. 'Cause I don't know about you but I feel like for a while we were all building different things. I mean like, instead of, for example, managed services for something like Kubernetes, I mean a few jobs that would go out was that a start up that we, we built our own custom container platform, as one did in 2014. And, we assembled it out of all the LEGOs and we built it out of I think Docker and Packer and Chef and, AWS at the time and, a bunch of janky bash because like if someone tells you there's no janky bash underneath your home grown platform, they are lying. >> It's always a lie, always a lie. >> They're lying. There's definitely bash in there, they may or may not be checking exit codes. But like, we all were doing that for a while and we were all building, container orchestration systems because we didn't have a great industry standard, awesome! We're here at KubeCon. Obviously Kubernetes is a great industry standard, but everybody that wants to chase the shiny is like but surface meshes. If I review talks for, I think I reviewed talks for KubeCon in Copenhagen, and it was like 50 or 60 almost identical service mesh talk proposals. And it's like, and then now, like so that was last year and now everyone is like server lists and its like, you know you still have servers. Like you don't add sensation to them, which is great, but you still have them. I think that that hype train is going to keep happening and what we need to do is make sure that we keep it usable for what the customers are trying to accomplish. Does that make sense? >> Bridget, it does, and unfortunately, we're going to have to leave it there. Thank you so much for sharing everything with our audience here. For Corey, I'm Stu, we'll be back with more coverage. Thanks for watching The Cube. (upbeat techno music)

>> Ladies and gentlemen, please welcome Red Hat President Products and Technologies. Paul Cormier. Boring. >> Welcome back to Boston. Welcome back. And welcome back after a great night last night of our opening with with Jim and talking to certainly saw ten Jenny and and especially our customers. It was so great last night to hear our customers in how they set their their goals and how they met their goals. All possible because certainly with a little help from red hat, but all possible because of because of open source. And, you know, sometimes we have to all due that has set goals. And I'm going to talk this morning about what we as a company and with community, have set for our goals along the way. And sometimes you have to do that. You know, audacious goals. It can really change the perception of what's even possible. And, you know, if I look back, I can't think of anything, at least in my lifetime, that's more important. Or such a big golden John F. Kennedy setting the gold to the American people to go to the moon. I believe it or not, I was really, really only three years old when he said that, honestly. But as I grew up, I remember the passion around the whole country and the energy to make that goal a reality. So let's sort of talk about in compare and contrast, a little bit of where we are technically at that time, you know, tto win and to beat and winning the space race and even get into the space race. There was some really big technical challenges along the way. I mean, believe it or not. Not that long ago. But even But back then, math Malik mathematical calculations were being shifted from from brilliant people who we trusted, and you could look in the eye to A to a computer that was programmed with the results that were mostly printed out. This this is a time where the potential of computers was just really coming on the scene and, at the time, the space race at the time of space race it. It revolved around an IBM seventy ninety, which was one of the first transistor based computers. It could perform mathematical calculations faster than even the most brilliant mathematicians. But just like today, this also came with many, many challenges And while we had the goal of in the beginning of the technique and the technology to accomplish it, we needed people so dedicated to that goal that they would risk everything. And while it may seem commonplace to us today to trust, put our trust in machines, that wasn't the case. Back in nineteen sixty nine, the seven individuals that made up the Mercury Space crew were putting their their lives in the hands of those first computers. But on Sunday, July twentieth, nineteen sixty nine, these things all came together. The goal, the technology in the team and a human being walked on the moon. You know, if this was possible fifty years ago, just think about what Khun B. Accomplished today, where technology is part of our everyday lives. And with technology advances at an ever increasing rate, it's hard to comprehend the potential that sitting right at our fingertips every single day, everything you know about computing is continuing to change. Today, let's look a bit it back. A computing In nineteen sixty nine, the IBM seventy ninety could process one hundred thousand floating point operations per second, today's Xbox one that sitting in most of your living rooms probably can process six trillion flops. That's sixty million times more powerful than the original seventy ninety that helped put a human being on the moon. And at the same time that computing was, that was drastically changed. That this computing has drastically changed. So have the boundaries of where that computing sits and where it's been where it lives. At the time of the Apollo launch, the computing power was often a single machine. Then it moved to a single data center, and over time that grew to multiple data centers. Then with cloud, it extended all the way out to data centers that you didn't even own or have control of. But but computing now reaches far beyond any data center. This is also referred to as the edge. You hear a lot about that. The Apollo's, the Apollo's version of the Edge was the guidance system, a two megahertz computer that weighed seventy pounds embedded in the capsule. Today, today the edge is right here on my wrist. This apple watch weighs just a couple of ounces, and it's ten ten thousand times more powerful than that seventy ninety back in nineteen sixty nine But even more impactful than computing advances, combined with the pervasive availability of it, are the changes and who in what controls those that similar to social changes that have happened along the way. Shifting from mathematicians to computers, we're now facing the same type of changes with regards to operational control of our computing power. In its first forms. Operational control was your team, your team within your control? In some cases, a single person managed everything. But as complexity grows, our team's expanded, just like in the just like in the computing boundaries, system integrators and public cloud providers have become an extension of our team. But at the end of the day, it's still people that are still making all the decisions going forward with the progress of things like a I and software defined everything. It's quite likely that machines will be managing machines, and in many cases that's already happening today. But while the technology at our finger tips today is so impressive, the pace of changing complexity of the problems we aspire to solve our equally hard to comprehend and they are all intertwined with one another learning from each other, growing together faster and faster. We are tackling problems today on a global scale with unsinkable complexity beyond anyone beyond what any one single company or even one single country Khun solve alone. This is why open source is so important. This is why open source is so needed today in software. This is why open sources so needed today, even in the world, to solve other types of complex problems. And this is why open source has become the dominant development model which is driving the technology direction. Today is to bring two brother to bring together the best innovation from every corner of the planet. Toe fundamentally change how we solve problems. This approach and access the innovation is what has enabled open source To tackle The challenge is big challenges, like creating the hybrid cloud like building a truly open hybrid cloud. But even today it's really difficult to bridge the gap of the innovation. It's available in all in all of our fingertips by open source development, while providing the production level capabilities that are needed to really dip, ploy this in the enterprise and solve RIA world business problems. Red Hat has been committed to open source from the very, very beginning and bringing it to solve enterprise class problems for the last seventeen plus years. But when we built that model to bring open source to the enterprise, we absolutely knew we couldn't do it halfway tow harness the innovation. We had to fully embrace the model. We made a decision very early on. Give everything back and we live by that every single day. We didn't do crazy crazy things like you hear so many do out there. All this is open corps or everything below. The line is open and everything above the line is closed. We didn't do that, and we gave everything back Everything we learned in the process of becoming an enterprise class technology company. We gave it all of that back to the community to make better and better software. This is how it works. And we've seen the results of that. We've all seen the results of that and it could only have been possible within open source development model we've been building on the foundation of open source is most successful Project Lennox in the architecture of the future hybrid and bringing them to the Enterprise. This is what made Red Hat, the company that we are today and red hats journey. But we also had the set goals, and and many of them seemed insert insurmountable at the time, the first of which was making Lennox the Enterprise standard. And while this is so accepted today, let's take a look at what it took to get there. Our first launch into the Enterprise was rail two dot one. Yes, I know we two dot one, but we knew we couldn't release a one dato product. We knew that and and we didn't. But >> we didn't want to >> allow any reason why anyone of any customer anyone shouldn't should look past rail to solve their problems as an option. Back then, we had to fight every single flavor of Unix in every single account. But we were lucky to have a few initial partners and Big Eyes v partners that supported Rehl out of the gate. But while we had the determination, we knew we also had gaps in order to deliver on our on our priorities. In the early days of rail, I remember going to ask one of our engineers for a past rehl build because we were having a customer issue on it on an older release. And then I watched in horror as he rifled through his desk through a mess of CDs and magically came up and said, I found it here It is told me not to worry that the build this was he thinks this was the bill. This was the right one, and at that point I knew that despite the promise of Lennox, we had a lot of work ahead of us. The not only convinced the world that Lennox was secure, stable, an enterprise ready, but also to make that a reality. But we did. And today this is our reality. It's all of our reality. From the Enterprise Data Center standard to the fastest computers on the planet, Red Hat Enterprise, Lennox has continually risen to the challenge and has become the core foundation that many mission critical customers run and bet their business on. And an even bigger today Lennox is the foundation of which practically every single technology initiative is built upon. Lennox is not only standard toe build on today, it's the standard for innovation that builds around it. That's the innovation that's driving the future as well. We started our story with rail two dot one, and here we are today, seventeen years later, announcing rally as we did as we did last night. It's specifically designed for applications to run across the open hybrid. Clyde Cloud. Railed has become the best operating simp system for on premise all the way out to the cloud, providing that common operating model and workload foundation on which to build hybrid applications. Let's take it. Let's take a look at how far we've come and see this in action. >> Please welcome Red Hat Global director of developer experience, burst Sutter with Josh Boyer, Timothy Kramer, Lars Carl, it's Key and Brent Midwood. All right, we have some amazing things to show you. In just a few short moments, we actually have a lot of things to show you. And actually, Tim and Brandt will be with us momentarily. They're working out a few things in the back because we have a lot of this is gonna be a live demonstration, some incredible capabilities. Now you're going to see clear innovation inside the operating system where we worked incredibly hard to make it vast cities. You're free to manage many, many machines. I want you thinking about that as we go to this process. Now, also, keep in mind that this is the basis our core platform for everything we do here. Red hat. So it is an honor for me to be able to show it to you live on stage today. And so I recognize the many of you in the audience right now. Her hand's on systems administrators, systems, architect, citizens, engineers. And we know that you're under ever growing pressure to deliver needed infrastructure. Resource is ever faster, and that is a key element to what you're thinking about every day. Well, this has been a core theme, and our design decisions find red Odd Enterprise Lennox eight and intelligent operating system, which is making it fundamentally easier for you manage machines that scale. So hold what you're about to see next. Feels like a new superpower and and that redhead azure force multiplier. So first, let me introduce you to a large. He's totally my limits guru. >> I wouldn't call myself a girl, but I I guess you could say that I want to bring Lennox and light meant to more people. >> Okay, Well, let's let's dive in. And we're not about the clinic's eight. >> Sure. Let me go. And Morgan, >> wait a >> second. There's windows. >> Yeah, way Build the weft Consul into Really? That means that for the first time, you can log in from any device including your phone or this standard windows laptop. So you just go ahead and and to my Saturday lance credentials here. >> Okay, so now >> you're putting >> your limits password and over the web. >> Yeah, that might sound a bit scary at first, but of course, we're using the latest security tech by T. L s on dh csp on. Because that's the standard Lennox off site. You can use everything that you used to like a stage keys, OTP, tokens and stuff like this. >> Okay, so now I see the council right here. I love the dashboard overview of the system, but what else can you tell us about this council? >> Right? Like right here. You see the load of the system, some some of its properties. But you can also dive into logs everything that you're used to from the command line, right? Or lookit, services. This's all the services I've running, can start and stuff them and enable >> OK, I love that feature right there. So what about if I have to add a whole new application to this environment? >> Good that you're bringing that up. We build a new future into hell called application streams. Which the way for you to install different versions of your half stack that are supported I'LL show you with Youngmin a command line. But since Windows doesn't have a proper terminal, I'll just do it in the terminal that we built into the Web console Since the browser, I can even make this a bit bigger. Go to, for example, to see the application streams that we have for Poskus. Ijust do module list and I see you know we have ten and nine dot six Both supported tennis a default on defy enable ninety six Now the next time that I installed prescribes it will pull all their lady towards from them at six. >> Ok, so this is very cool. I see two verses of post Chris right here What tennis to default. That is fantastic and the application streams making that happen. But I'm really kind of curious, right? I loved using know js and Java. So what about multiple versions of those? >> Yeah, that's exactly the idea way. Want to keep up with the fast moving ecosystems off programming language? Isn't it a business? >> Okay, now, But I have another key question. I know some people were thinking it right now. What about Python? >> Yeah. In fact, in a minimum and still like this, python gives you command. Not fact. Just have to type it correctly. You can't just install which everyone you want two or three or whichever your application needs. >> Okay, Well, that is I've been burned on that one before. Okay, so no actual. Have a confession for all you guys. Right here. You guys keep this amongst yourselves. Don't let Paul No, I'm actually not a linnet systems administrator. I'm an application developer, an application architect, And I recently had to go figure out how to extend the file system. This is for real. And I'm going to the rat knowledge base and looking up things like, you know, PV create VD, extend resized to f s. And I have to admit, that's hard, >> right? I've opened the storage space for you right here, where you see an overview of your storage. And the council has made for people like you as well not only for people that I knew that when you two lunatics, right? It's if you're running, you're running some of the commands only, you know, some of the time you don't remember them. So, for example, I haven't felt twosome here. That's a little bit too small. Let me just throw it. It's like, you know, dragging this lighter. It calls all the command in the background for you. >> Oh, that is incredible. Is that simple? Just drag and drop. That is fantastic. Well, so I actually, you know, we'll have another question for you. It looks like now this linen systems administration is no longer a dark heart involving arcane commands typed into a black terminal. Like using when those funky ergonomic keyboards you know I'm talking about right? Do >> you know a lot of people, including me and people in the audience like that dark out right? And this is not taking any of that away. It's on additional tool to bring limits to more people. >> Okay, well, that is absolute fantastic. Thank you so much for that Large. And I really love him installing everything is so much easier, including a post gra seeker and, of course, the python that we saw right there. So now I want to change gears for a second because I actually have another situation that I'm always dealing with. And that is every time I want to build a new Lenox system, not only I don't want to have to install those commands again and again, it feels like I'm doing it over and over. So, Josh, how would I create a golden image? One VM image that can use and we have everything pre baked in? >> Yeah, absolutely. But >> we get that question all the time. So really includes image builder technology. Image builder technology is actually all of our hybrid cloud operating system image tools that we use to build our own images and rolled up in a nice, easy to integrate new system. So if I come here in the web console and I go to our image builder tab, it brings us to blueprints, right? Blueprints or what we used to actually control it goes into our golden image. Uh, and I heard you and Lars talking about post present python. So I went and started typing here. So it brings us to this page, but you could go to the selected components, and you can see here I've created a blueprint that has all the python and post press packages in it. Ah, and the interesting thing about this is it build on our existing kickstart technology. But you can use it to deploy that whatever cloud you want. And it's saved so that you don't actually have to know all the various incantations from Amazon toe azure to Google, whatever it's all baked in on. When you do this, you can actually see the dependencies that get brought in as well. Okay. Should we create one life? Yes, please. All right, cool. So if we go back to the blueprints page and we click create blueprint Let's, uh let's make a developer brute blueprint here. So we click great, and you can see here on the left hand side. I've got all of my content served up by Red Hat satellite. We have a lot of great stuff, and really, But we can go ahead and search. So we'LL look for post grows and you know, it's a developer image at the client for some local testing. Um, well, come in here and at the python bits. Probably the development package. We need a compiler if we're going to actually build anything. So look for GCC here and hey, what's your favorite editor? >> A Max, Of course, >> Max. All right. Hey, Lars, about you. I'm more of a person. You Maxim v I All right, Well, if you want to prevent a holy war in your system, you can actually use satellite to filter that out. But we're going to go ahead and Adam Ball, sweetie, I'm a fight on stage. So wait, just point and click. Let the graphical one. And then when we're all done, we just commit our changes, and our image is ready to build. >> Okay, So this VM image we just created right now from that blueprint this is now I can actually go out there and easily deploys of deploy this across multiple cloud providers. And as well as this on stage are where we have right now. >> Yeah, absolutely. We can to play on Amazon as your google any any infrastructure you're looking for so you can really hit your Clyburn hybrid cloud operating system images. >> Okay. All right, listen, we >> just go on, click, create image. Uh, we can select our different types here. I'm gonna go ahead and create a local VM because it's available image, and maybe they want to pass it around or whatever, and I just need a few moments for it to build. >> Okay? So while that's taking a few moments, I know there's another key question in the minds of the audience right now, and you're probably thinking I love what I see. What Right eye right hand Priceline say. But >> what does it >> take to upgrade from seven to eight? So large can you show us and walk us through an upgrade? >> Sure, this's my little Thomas Block that I set up. It's powered by what Chris and secrets over, but it's still running on seven six. So let's upgrade that jump over to my house fee on satellite on. You see all my relate machines here, including the one I showed you what Consul on before. And there is that one with my sun block and there's a couple others. Let me select those as well. This one on that one. Just go up here. Schedule remote job. And she was really great. And hit Submit. I made it so that it makes the booms national before. So if anything was wrong Kans throwback! >> Okay, okay, so now it's progressing. Here, >> it's progressing. Looks like it's running. Doing >> live upgrade on stage. Uh, >> seems like one is failing. What's going on here? Okay, we checked the tree of great Chuck. Oh, yeah, that's the one I was playing around with Butter fest backstage. What? Detective that and you know, it doesn't run the Afghan cause we don't support operating that. >> Okay, so what I'm hearing now? So the good news is, we were protected from possible failed upgrade there, So it sounds like these upgrades are perfectly safe. Aiken, basically, you know, schedule this during a maintenance window and still get some sleep. >> Totally. That's the idea. >> Okay, fantastic. All right. So it looks like upgrades are easy and perfectly safe. And I really love what you showed us there. It's good point. Click operation right from satellite. Ok, so Well, you know, we were checking out upgrades. I want to know Josh. How those v ems coming along. >> They went really well. So you were away for so long. I got a little bored and I took some liberties. >> What do you mean? >> Well, the image Bill And, you know, I decided I'm going to go ahead and deploy here to this Intel machine on stage Esso. I have that up and running in the web. Counsel. I built another one on the arm box, which is actually pretty fast, and that's up and running on this. Our machine on that went so well that I decided to spend up some an Amazon. So I've got a few instances here running an Amazon with the web console accessible there as well. On even more of our pre bill image is up and running an azure with the web console there. So the really cool thing about this bird is that all of these images were built with image builder in a single location, controlling all the content that you want in your golden images deployed across the hybrid cloud. >> Wow, that is fantastic. And you might think that so we actually have more to show you. So thank you so much for that large. And Josh, that is fantastic. Looks like provisioning bread. Enterprise Clinic Systems ate a redhead. Enterprise Enterprise. Rhetta Enterprise Lennox. Eight Systems is Asian ever before, but >> we have >> more to talk to you about. And there's one thing that many of the operations professionals in this room right now no, that provisioning of'em is easy, but it's really day two day three, it's down the road that those viens required day to day maintenance. As a matter of fact, several you folks right now in this audience to have to manage hundreds, if not thousands, of virtual machines I recently spoke to. Gentleman has to manage thirteen hundred servers. So how do you manage those machines? A great scale. So great that they have now joined us is that it looks like they worked things out. So now I'm curious, Tim. How will we manage hundreds, if not thousands, of computers? >> Welbourne, one human managing hundreds or even thousands of'em says, No problem, because we have Ansel automation. And by leveraging Ansel's integration into satellite, not only can we spin up those V em's really quickly, like Josh was just doing, but we can also make ongoing maintenance of them really simple. Come on up here. I'm going to show you here a satellite inventory and his red hat is publishing patches. Weaken with that danceable integration easily apply those patches across our entire fleet of machines. Okay, >> that is fantastic. So he's all the machines can get updated in one fell swoop. >> He sure can. And there's one thing that I want to bring your attention to today because it's brand new. And that's cloud that red hat dot com And here, a cloud that redhead dot com You can view and manage your entire inventory no matter where it sits. Of Redhead Enterprise Lennox like on Prem on stage. Private Cloud or Public Cloud. It's true Hybrid cloud management. >> OK, but one thing. One thing. I know that in the minds of the audience right now. And if you have to manage a large number servers this it comes up again and again. What happens when you have those critical vulnerabilities that next zero day CV could be tomorrow? >> Exactly. I've actually been waiting for a while patiently for you >> to get to the really good stuff. So >> there's one more thing that I wanted to let folks know about. Red Hat Enterprise. The >> next eight and some features that we have there. Oh, >> yeah? What is that? >> So, actually, one of the key design principles of relate is working with our customers over the last twenty years to integrate all the knowledge that we've gained and turn that into insights that we can use to keep our red hat Enterprise Lennox servers running securely, inefficiently. And so what we actually have here is a few things that we could take a look at show folks what that is. >> OK, so we basically have this new feature. We're going to show people right now. And so one thing I want to make sure it's absolutely included within the redhead enterprise in that state. >> Yes. Oh, that's Ah, that's an announcement that we're making this week is that this is a brand new feature that's integrated with Red Hat Enterprise clinics, and it's available to everybody that has a red hat enterprise like subscription. So >> I believe everyone in this room right now has a rail subscriptions, so it's available to all of them. >> Absolutely, absolutely. So let's take a quick look and try this out. So we actually have. Here is a list of about six hundred rules. They're configuration security and performance rules. And this is this list is growing every single day, so customers can actually opt in to the rules that are most that are most applicable to their enterprises. So what we're actually doing here is combining the experience and knowledge that we have with the data that our customers opt into sending us. So customers have opted in and are sending us more data every single night. Then they actually have in total over the last twenty years via any other mechanism. >> Now there's I see now there's some critical findings. That's what I was talking about. But it comes to CVS and things that nature. >> Yeah, I'm betting that those air probably some of the rail seven boxes that we haven't actually upgraded quite yet. So we get back to that. What? I'd really like to show everybody here because everybody has access to this is how easy it is to opt in and enable this feature for real. Okay, let's do that real quick, so I gotta hop back over to satellite here. This is the satellite that we saw before, and I'll grab one of the hosts and we can use the new Web console feature that's part of Railly, and via single sign on I could jump right from satellite over to the Web console. So it's really, really easy. And I'LL grab a terminal here and registering with insights is really, really easy. Is one command troops, and what's happening right now is the box is going to gather some data. It's going to send it up to the cloud, and within just a minute or two, we're gonna have some results that we can look at back on the Web interface. >> I love it so it's just a single command and you're ready to register this box right now. That is super easy. Well, that's fantastic, >> Brent. We started this whole series of demonstrations by telling the audience that Red Hat Enterprise Lennox eight was the easiest, most economical and smartest operating system on the planet, period. And well, I think it's cute how you can go ahead and captain on a single machine. I'm going to show you one more thing. This is Answerable Tower. You can use as a bell tower to managing govern your answerable playbook, usage across your entire organization and with this. What I could do is on every single VM that was spun up here today. Opt in and register insights with a single click of a button. >> Okay, I want to see that right now. I know everyone's waiting for it as well, But hey, you're VM is ready. Josh. Lars? >> Yeah. My clock is running a little late now. Yeah, insights is a really cool feature >> of rail. And I've got it in all my images already. All >> right, I'm doing it all right. And so as this playbook runs across the inventory, I can see the machines registering on cloud that redhead dot com ready to be managed. >> OK, so all those onstage PM's as well as the hybrid cloud VM should be popping in IRC Post Chris equals Well, fantastic. >> That's awesome. Thanks to him. Nothing better than a Red Hat Summit speaker in the first live demo going off script deal. Uh, let's go back and take a look at some of those critical issues affecting a few of our systems here. So you can see this is a particular deanna's mask issue. It's going to affect a couple of machines. We saw that in the overview, and I can actually go and get some more details about what this particular issue is. So if you take a look at the right side of the screen there, there's actually a critical likelihood an impact that's associated with this particular issue. And what that really translates to is that there's a high level of risk to our organization from this particular issue. But also there's a low risk of change. And so what that means is that it's really, really safe for us to go ahead and use answerable to mediate this so I can grab the machines will select those two and we're mediate with answerable. I can create a new playbook. It's our maintenance window, but we'LL do something along the lines of like stuff Tim broke and that'LL be our cause. We name it whatever we want. So we'Ll create that playbook and take a look at it, and it's actually going to give us some details about the machines. You know what, what type of reboots Efendi you're going to be needed and what we need here. So we'LL go ahead and execute the playbook and what you're going to see is the outputs goingto happen in real time. So this is happening from the cloud were affecting machines. No matter where they are, they could be on Prem. They could be in a hybrid cloud, a public cloud or in a private cloud. And these things are gonna be remediated very, very easily with answerable. So it's really, really awesome. Everybody here with a red hat. Enterprise licks Lennox subscription has access to this now, so I >> kind of want >> everybody to go try this like, we really need to get this thing going and try it out right now. But >> don't know, sent about the room just yet. You get stay here >> for okay, Mr. Excitability, I think after this keynote, come back to the red hat booth and there's an optimization section. You can come talk to our insights engineers. And even though it's really easy to get going on your own, they can help you out. Answer any questions you might have. So >> this is really the start of a new era with an intelligent operating system and beauty with intelligence you just saw right now what insights that troubles you. Fantastic. So we're enabling systems administrators to manage more red in private clinics, a greater scale than ever before. I know there's a lot more we could show you, but we're totally out of time at this point, and we kind of, you know, when a little bit sideways here moments. But we need to get off the stage. But there's one thing I want you guys to think about it. All right? Do come check out the in the booth. Like Tim just said also in our debs, Get hands on red and a prize winning state as well. But really, I want you to think about this one human and a multitude of servers. And if you remember that one thing asked you upfront. Do you feel like you get a new superpower and redhead? Is your force multiplier? All right, well, thank you so much. Josh and Lars, Tim and Brent. Thank you. And let's get Paul back on stage. >> I went brilliant. No, it's just as always, >> amazing. I mean, as you can tell from last night were really, really proud of relate in that coming out here at the summit. And what a great way to showcase it. Thanks so much to you. Birth. Thanks, Brent. Tim, Lars and Josh. Just thanks again. So you've just seen this team demonstrate how impactful rail Khun b on your data center. So hopefully hopefully many of you. If not all of you have experienced that as well. But it was super computers. We hear about that all the time, as I just told you a few minutes ago, Lennox isn't just the foundation for enterprise and cloud computing. It's also the foundation for the fastest super computers in the world. In our next guest is here to tell us a lot more about that. >> Please welcome Lawrence Livermore National Laboratory. HPC solution Architect Robin Goldstone. >> Thank you so much, Robin. >> So welcome. Welcome to the summit. Welcome to Boston. And thank thank you so much for coming for joining us. Can you tell us a bit about the goals of Lawrence Livermore National Lab and how high high performance computing really works at this level? >> Sure. So Lawrence Livermore National >> Lab was established during the Cold War to address urgent national security needs by advancing the state of nuclear weapons, science and technology and high performance computing has always been one of our core capabilities. In fact, our very first supercomputer, ah Univac one was ordered by Edward Teller before our lab even opened back in nineteen fifty two. Our mission has evolved since then to cover a broad range of national security challenges. But first and foremost, our job is to ensure the safety, security and reliability of the nation's nuclear weapons stockpile. Oh, since the US no longer performs underground nuclear testing, our ability to certify the stockpile depends heavily on science based science space methods. We rely on H P C to simulate the behavior of complex weapons systems to ensure that they can function as expected, well beyond their intended life spans. That's actually great. >> So are you really are still running on that on that Univac? >> No, Actually, we we've moved on since then. So Sierra is Lawrence Livermore. Its latest and greatest supercomputer is currently the Seconds spastic supercomputer in the world and for the geeks in the audience, I think there's a few of them out there. We put up some of the specs of Syrah on the screen behind me, a couple of things worth highlighting our Sierra's peak performance and its power utilisation. So one hundred twenty five Pata flops of performance is equivalent to about twenty thousand of those Xbox one excess that you mentioned earlier and eleven point six megawatts of power required Operate Sierra is enough to power around eleven thousand homes. Syria is a very large and complex system, but underneath it all, it starts out as a collection of servers running Lin IX and more specifically, rail. >> So did Lawrence. Did Lawrence Livermore National Lab National Lab used Yisrael before >> Sierra? Oh, yeah, most definitely. So we've been running rail for a very long time on what I'll call our mid range HPC systems. So these clusters, built from commodity components, are sort of the bread and butter of our computer center. And running rail on these systems provides us with a continuity of operations and a common user environment across multiple generations of hardware. Also between Lawrence Livermore in our sister labs, Los Alamos and Sandia. Alongside these commodity clusters, though, we've always had one sort of world class supercomputer like Sierra. Historically, these systems have been built for a sort of exotic proprietary hardware running entirely closed source operating systems. Anytime something broke, which was often the Vander would be on the hook to fix it. And you know, >> that sounds >> like a good model, except that what we found overtime is most the issues that we have on these systems were either due to the extreme scale or the complexity of our workloads. Vendors seldom had a system anywhere near the size of ours, and we couldn't give them our classified codes. So their ability to reproduce our problem was was pretty limited. In some cases, they've even sent an engineer on site to try to reproduce our problems. But even then, sometimes we wouldn't get a fix for months or else they would just tell us they weren't going to fix the problem because we were the only ones having it. >> So for many of us, for many of us, the challenges is one of driving reasons for open source, you know, for even open source existing. How has how did Sierra change? Things are on open source for >> you. Sure. So when we developed our technical requirements for Sierra, we had an explicit requirement that we want to run an open source operating system and a strong preference for rail. At the time, IBM was working with red hat toe add support Terrell for their new little Indian power architecture. So it was really just natural for them to bid a red. A rail bay system for Sierra running Raylan Cyril allows us to leverage the model that's worked so well for us for all this time on our commodity clusters any packages that we build for X eighty six, we can now build those packages for power as well as our market texture using our internal build infrastructure. And while we have a formal support relationship with IBM, we can also tap our in house colonel developers to help debug complex problems are sys. Admin is Khun now work on any of our systems, including Sierra, without having toe pull out their cheat sheet of obscure proprietary commands. Our users get a consistent software environment across all our systems. And if the security vulnerability comes out, we don't have to chase around getting fixes from Multan slo es fenders. >> You know, you've been able, you've been able to extend your foundation from all the way from X eighty six all all the way to the extract excess Excuse scale supercomputing. We talk about giving customers all we talked about it all the time. A standard operational foundation to build upon. This isn't This isn't exactly what we've envisioned. So So what's next for you >> guys? Right. So what's next? So Sierra's just now going into production. But even so, we're already working on the contract for our next supercomputer called El Capitan. That's scheduled to be delivered the Lawrence Livermore in the twenty twenty two twenty timeframe. El Capitan is expected to be about ten times the performance of Sierra. I can't share any more details about that system right now, but we are hoping that we're going to be able to continue to build on a solid foundation. That relish provided us for well over a decade. >> Well, thank you so much for your support of realm over the years, Robin. And And thank you so much for coming and tell us about it today. And we can't wait to hear more about El Capitan. Thank you. Thank you very much. So now you know why we're so proud of realm. And while you saw confetti cannons and T shirt cannons last night, um, so you know, as as burned the team talked about the demo rail is the force multiplier for servers. We've made Lennox one of the most powerful platforms in the history of platforms. But just as Lennox has become a viable platform with access for everyone, and rail has become viable, more viable every day in the enterprise open source projects began to flourish around the operating system. And we needed to bring those projects to our enterprise customers in the form of products with the same trust models as we did with Ralph seeing the incredible progress of software development occurring around Lennox. Let's let's lead us to the next goal that we said tow, tow ourselves. That goal was to make hybrid cloud the default enterprise for the architecture. How many? How many of you out here in the audience or are Cesar are? HC sees how many out there a lot. A lot. You are the people that our building the next generation of computing the hybrid cloud, you know, again with like just like our goals around Lennox. This goals might seem a little daunting in the beginning, but as a community we've proved it time and time again. We are unstoppable. Let's talk a bit about what got us to the point we're at right right now and in the work that, as always, we still have in front of us. We've been on a decade long mission on this. Believe it or not, this mission was to build the capabilities needed around the Lenox operating system to really build and make the hybrid cloud. When we saw well, first taking hold in the enterprise, we knew that was just taking the first step. Because for a platform to really succeed, you need applications running on it. And to get those applications on your platform, you have to enable developers with the tools and run times for them to build, to build upon. Over the years, we've closed a few, if not a lot of those gaps, starting with the acquisition of J. Boss many years ago, all the way to the new Cuban Eddie's native code ready workspaces we launched just a few months back. We realized very early on that building a developer friendly platform was critical to the success of Lennox and open source in the enterprise. Shortly after this, the public cloud stormed onto the scene while our first focus as a company was done on premise in customer data centers, the public cloud was really beginning to take hold. Rehl very quickly became the standard across public clouds, just as it was in the enterprise, giving customers that common operating platform to build their applications upon ensuring that those applications could move between locations without ever having to change their code or operating model. With this new model of the data center spread across so many multiple environments, management had to be completely re sought and re architected. And given the fact that environments spanned multiple locations, management, real solid management became even more important. Customers deploying in hybrid architectures had to understand where their applications were running in how they were running, regardless of which infrastructure provider they they were running on. We invested over the years with management right alongside the platform, from satellite in the early days to cloud forms to cloud forms, insights and now answerable. We focused on having management to support the platform wherever it lives. Next came data, which is very tightly linked toe applications. Enterprise class applications tend to create tons of data and to have a common operating platform foyer applications. You need a storage solutions. That's Justus, flexible as that platform able to run on premise. Just a CZ. Well, as in the cloud, even across multiple clouds. This let us tow acquisitions like bluster, SEF perma bitch in Nubia, complimenting our Pratt platform with red hat storage for us, even though this sounds very condensed, this was a decade's worth of investment, all in preparation for building the hybrid cloud. Expanding the portfolio to cover the areas that a customer would depend on to deploy riel hybrid cloud architectures, finding any finding an amplifying the right open source project and technologies, or filling the gaps with some of these acquisitions. When that necessarily wasn't available by twenty fourteen, our foundation had expanded, but one big challenge remained workload portability. Virtual machine formats were fragmented across the various deployments and higher level framework such as Java e still very much depended on a significant amount of operating system configuration and then containers happened containers, despite having a very long being in existence for a very long time. As a technology exploded on the scene in twenty fourteen, Cooper Netease followed shortly after in twenty fifteen, allowing containers to span multiple locations and in one fell swoop containers became the killer technology to really enable the hybrid cloud. And here we are. Hybrid is really the on ly practical reality in way for customers and a red hat. We've been investing in all aspects of this over the last eight plus years to make our customers and partners successful in this model. We've worked with you both our customers and our partners building critical realm in open shift deployments. We've been constantly learning about what has caused problems and what has worked well in many cases. And while we've and while we've amassed a pretty big amount of expertise to solve most any challenge in in any area that stack, it takes more than just our own learning's to build the next generation platform. Today we're also introducing open shit for which is the culmination of those learnings. This is the next generation of the application platform. This is truly a platform that has been built with our customers and not simply just with our customers in mind. This is something that could only be possible in an open source development model and just like relish the force multiplier for servers. Open shift is the force multiplier for data centers across the hybrid cloud, allowing customers to build thousands of containers and operate them its scale. And we've also announced open shift, and we've also announced azure open shift. Last night. Satya on this stage talked about that in depth. This is all about extending our goals of a common operating platform enabling applications across the hybrid cloud, regardless of whether you run it yourself or just consume it as a service. And with this flagship release, we are also introducing operators, which is the central, which is the central feature here. We talked about this work last year with the operator framework, and today we're not going to just show you today. We're not going to just show you open shift for we're going to show you operators running at scale operators that will do updates and patches for you, letting you focus more of your time and running your infrastructure and running running your business. We want to make all this easier and intuitive. So let's have a quick look at how we're doing. Just that >> painting. I know all of you have heard we're talking to pretend to new >> customers about the travel out. So new plan. Just open it up as a service been launched by this summer. Look, I know this is a big quest for not very big team. I'm open to any and all ideas. >> Please welcome back to the stage. Red Hat Global director of developer Experience burst Sutter with Jessica Forrester and Daniel McPherson. All right, we're ready to do some more now. Now. Earlier we showed you read Enterprise Clinic St running on lots of different hardware like this hardware you see right now And we're also running across multiple cloud providers. But now we're going to move to another world of Lennox Containers. This is where you see open shift four on how you can manage large clusters of applications from eggs limits containers across the hybrid cloud. We're going to see this is where suffer operators fundamentally empower human operators and especially make ups and Deb work efficiently, more efficiently and effectively there together than ever before. Rights. We have to focus on the stage right now. They're represent ops in death, and we're gonna go see how they reeled in application together. Okay, so let me introduce you to Dan. Dan is totally representing all our ops folks in the audience here today, and he's telling my ops, comfort person Let's go to call him Mr Ops. So Dan, >> thanks for with open before, we had a much easier time setting up in maintaining our clusters. In large part, that's because open shit for has extended management of the clusters down to the infrastructure, the diversity kinds of parent. When you take >> a look at the open ship console, >> you can now see the machines that make up the cluster where machine represents the infrastructure. Underneath that Cooper, Eddie's node open shit for now handles provisioning Andy provisioning of those machines. From there, you could dig into it open ship node and see how it's configured and monitor how it's behaving. So >> I'm curious, >> though it does this work on bare metal infrastructure as well as virtualized infrastructure. >> Yeah, that's right. Burn So Pa Journal nodes, no eternal machines and open shit for can now manage it all. Something else we found extremely useful about open ship for is that it now has the ability to update itself. We can see this cluster hasn't update available and at the press of a button. Upgrades are responsible for updating. The entire platform includes the nodes, the control plane and even the operating system and real core arrests. All of this is possible because the infrastructure components and their configuration is now controlled by technology called operators. Thes software operators are responsible for aligning the cluster to a desired state. And all of this makes operational management of unopened ship cluster much simpler than ever before. All right, I >> love the fact that all that's been on one console Now you can see the full stack right all way down to the bare metal right there in that one console. Fantastic. So I wanted to scare us for a moment, though. And now let's talk to Deva, right? So Jessica here represents our all our developers in the room as my facts. He manages a large team of developers here Red hat. But more importantly, she represents our vice president development and has a large team that she has to worry about on a regular basis of Jessica. What can you show us? We'LL burn My team has hundreds of developers and were constantly under pressure to deliver value to our business. And frankly, we can't really wait for Dan and his ops team to provisioned the infrastructure and the services that we need to do our job. So we've chosen open shift as our platform to run our applications on. But until recently, we really struggled to find a reliable source of Cooper Netease Technologies that have the operational characteristics that Dan's going to actually let us install through the cluster. But now, with operator, How bio, we're really seeing the V ecosystem be unlocked. And the technology's there. Things that my team needs, its databases and message cues tracing and monitoring. And these operators are actually responsible for complex applications like Prometheus here. Okay, they're written in a variety of languages, danceable, but that is awesome. So I do see a number of options there already, and preaches is a great example. But >> how do you >> know that one? These operators really is mature enough and robust enough for Dan and the outside of the house. Wilbert, Here we have the operator maturity model, and this is going to tell me and my team whether this particular operator is going to do a basic install if it's going to upgrade that application over time through different versions or all the way out to full auto pilot, where it's automatically scaling and tuning the application based on the current environment. And it's very cool. So coming over toothy open shift Consul, now we can actually see Dan has made the sequel server operator available to me and my team. That's the database that we're using. A sequel server. That's a great example. So cynics over running here in the cluster? But this is a great example for a developer. What if I want to create a new secret server instance? Sure, we're so it's as easy as provisioning any other service from the developer catalog. We come in and I can type for sequel server on what this is actually creating is, ah, native resource called Sequel Server, and you can think of that like a promise that a sequel server will get created. The operator is going to see that resource, install the application and then manage it over its life cycle, KAL, and from this install it operators view, I can see the operators running in my project and which resource is its managing Okay, but I'm >> kind of missing >> something here. I see this custom resource here, the sequel server. But where the community's resource is like pods. Yeah, I think it's cool that we get this native resource now called Sequel Server. But if I need to, I can still come in and see the native communities. Resource is like your staple set in service here. Okay, that is fantastic. Now, we did say earlier on, though, like many of our customers in the audience right now, you have a large team of engineers. Lost a large team of developers you gotta handle. You gotta have more than one secret server, right? We do one for every team as we're developing, and we use a lot of other technologies running on open shift as well, including Tomcat and our Jenkins pipelines and our dough js app that is gonna actually talk to that sequel server database. Okay, so this point we can kind of provisions, Some of these? Yes. Oh, since all of this is self service for me and my team's, I'm actually gonna go and create one of all of those things I just said on all of our projects, right Now, if you just give me a minute, Okay? Well, right. So basically, you're going to knock down No Jazz Jenkins sequel server. All right, now, that's like hundreds of bits of application level infrastructure right now. Live. So, Dan, are you not terrified? Well, I >> guess I should have done a little bit better >> job of managing guests this quota and historically just can. I might have had some conflict here because creating all these new applications would admit my team now had a massive back like tickets to work on. But now, because of software operators, my human operators were able to run our infrastructure at scale. So since I'm long into the cluster here as the cluster admin, I get this view of pods across all projects. And so I get an idea of what's happening across the entire cluster. And so I could see now we have four hundred ninety four pods already running, and there's a few more still starting up. And if I scroll to the list, we can see the different workloads Jessica just mentioned of Tomcats. And no Gs is And Jenkins is and and Siegel servers down here too, you know, I see continues >> creating and you have, like, close to five hundred pods running >> there. So, yeah, filters list down by secret server, so we could just see. Okay, But >> aren't you not >> running going around a cluster capacity at some point? >> Actually, yeah, we we definitely have a limited capacity in this cluster. And so, luckily, though, we already set up auto scale er's And so because the additional workload was launching, we see now those outer scholars have kicked in and some new machines are being created that don't yet have noticed. I'm because they're still starting up. And so there's another good view of this as well, so you can see machine sets. We have one machine set per availability zone, and you could see the each one is now scaling from ten to twelve machines. And the way they all those killers working is for each availability zone, they will. If capacities needed, they will add additional machines to that availability zone and then later effect fast. He's no longer needed. It will automatically take those machines away. >> That is incredible. So right now we're auto scaling across multiple available zones based on load. Okay, so looks like capacity planning and automation is fully, you know, handle this point. But I >> do have >> another question for year logged in. Is the cluster admin right now into the console? Can you show us your view of >> operator suffer operators? Actually, there's a couple of unique views here for operators, for Cluster admits. The first of those is operator Hub. This is where a cluster admin gets the ability to curate the experience of what operators are available to users of the cluster. And so obviously we already have the secret server operator installed, which which we've been using. The other unique view is operator management. This gives a cluster I've been the ability to maintain the operators they've already installed. And so if we dig in and see the secret server operator, well, see, we haven't set up for manual approval. And what that means is if a new update comes in for a single server, then a cluster and we would have the ability to approve or disapprove with that update before installs into the cluster, we'LL actually and there isn't upgrade that's available. Uh, I should probably wait to install this, though we're in the middle of scaling out this cluster. And I really don't want to disturb Jessica's application. Workflow. >> Yeah, so, actually, Dan, it's fine. My app is already up. It's running. Let me show it to you over here. So this is our products application that's talking to that sequel server instance. And for debugging purposes, we can see which version of sequel server we're currently talking to. Its two point two right now. And then which pod? Since this is a cluster, there's more than one secret server pod we could be connected to. Okay, I could see right there the bounder screeners they know to point to. That's the version we have right now. But, you know, >> this is kind of >> point of software operators at this point. So, you know, everyone in this room, you know, wants to see you hit that upgrade button. Let's do it. Live here on stage. Right, then. All >> right. All right. I could see where this is going. So whenever you updated operator, it's just like any other resource on communities. And so the first thing that happens is the operator pot itself gets updated so we actually see a new version of the operator is currently being created now, and what's that gets created, the overseer will be terminated. And that point, the new, softer operator will notice. It's now responsible for managing lots of existing Siegel servers already in the environment. And so it's then going Teo update each of those sickle servers to match to the new version of the single server operator and so we could see it's running. And so if we switch now to the all projects view and we filter that list down by sequel server, then we should be able to see us. So lots of these sickle servers are now being created and the old ones are being terminated. So is the rolling update across the cluster? Exactly a So the secret server operator Deploy single server and an H A configuration. And it's on ly updates a single instance of secret server at a time, which means single server always left in nature configuration, and Jessica doesn't really have to worry about downtime with their applications. >> Yeah, that's awesome dance. So glad the team doesn't have to worry about >> that anymore and just got I think enough of these might have run by Now, if you try your app again might be updated. >> Let's see Jessica's application up here. All right. On laptop three. >> Here we go. >> Fantastic. And yet look, we're We're into two before we're onto three. Now we're on to victory. Excellent on. >> You know, I actually works so well. I don't even see a reason for us to leave this on manual approval. So I'm going to switch this automatic approval. And then in the future, if a new single server comes in, then we don't have to do anything, and it'll be all automatically updated on the cluster. >> That is absolutely fantastic. And so I was glad you guys got a chance to see that rolling update across the cluster. That is so cool. The Secret Service database being automated and fully updated. That is fantastic. Alright, so I can see how a software operator doesn't able. You don't manage hundreds if not thousands of applications. I know a lot of folks or interest in the back in infrastructure. Could you give us an example of the infrastructure >> behind this console? Yeah, absolutely. So we all know that open shift is designed that run in lots of different environments. But our teams think that as your redhead over, Schiff provides one of the best experiences by deeply integrating the open chief Resource is into the azure console, and it's even integrated into the azure command line toll and the easy open ship man. And, as was announced yesterday, it's now available for everyone to try out. And there's actually one more thing we wanted to show Everyone related to open shit, for this is all so new with a penchant for which is we now have multi cluster management. This gives you the ability to keep track of all your open shift environments, regardless of where they're running as well as you can create new clusters from here. And I'll dig into the azure cluster that we were just taking a look at. >> Okay, but is this user and face something have to install them one of my existing clusters? >> No, actually, this is the host of service that's provided by Red hat is part of cloud that redhead that calm and so all you have to do is log in with your red hair credentials to get access. >> That is incredible. So one console, one user experience to see across the entire hybrid cloud we saw earlier with Red update. Right and red embers. Thank Satan. Now we see it for multi cluster management. But home shift so you can fundamentally see. Now the suffer operators do finally change the game when it comes to making human operators vastly more productive and, more importantly, making Devon ops work more efficiently together than ever before. So we saw the rich ice vehicle system of those software operators. We can manage them across the Khyber Cloud with any, um, shift instance. And more importantly, I want to say Dan and Jessica for helping us with this demonstration. Okay, fantastic stuff, guys. Thank you so much. Let's get Paul back out here >> once again. Thanks >> so much to burn his team. Jessica and Dan. So you've just seen how open shift operators can help you manage hundreds, even thousands of applications. Install, upgrade, remove nodes, control everything about your application environment, virtual physical, all the way out to the cloud making, making things happen when the business demands it even at scale, because that's where it's going to get. Our next guest has lots of experience with demand at scale. and they're using open source container management to do it. Their work, their their their work building a successful cloud, First platform and there, the twenty nineteen Innovation Award winner. >> Please welcome twenty nineteen Innovation Award winner. Cole's senior vice president of technology, Rich Hodak. >> How you doing? Thanks. >> Thanks so much for coming out. We really appreciate it. So I guess you guys set some big goals, too. So can you baby tell us about the bold goal? Helped you personally help set for Cole's. And what inspired you to take that on? Yes. So it was twenty seventeen and life was pretty good. I had no gray hair and our business was, well, our tech was working well, and but we knew we'd have to do better into the future if we wanted to compete. Retails being disrupted. Our customers are asking for new experiences, So we set out on a goal to become an open hybrid cloud platform, and we chose Red had to partner with us on a lot of that. We set off on a three year journey. We're currently in Year two, and so far all KP eyes are on track, so it's been a great journey thus far. That's awesome. That's awesome. So So you Obviously, Obviously you think open source is the way to do cloud computing. So way absolutely agree with you on that point. So So what? What is it that's convinced you even more along? Yeah, So I think first and foremost wait, do we have a lot of traditional IAS fees? But we found that the open source partners actually are outpacing them with innovation. So I think that's where it starts for us. Um, secondly, we think there's maybe some financial upside to going more open source. We think we can maybe take some cost out unwind from these big fellas were in and thirdly, a CZ. We go to universities. We started hearing. Is we interviewed? Hey, what is Cole's doing with open source and way? Wanted to use that as a lever to help recruit talent. So I'm kind of excited, you know, we partner with Red Hat on open shift in in Rail and Gloucester and active M Q and answerable and lots of things. But we've also now launched our first open source projects. So it's really great to see this journey. We've been on. That's awesome, Rich. So you're in. You're in a high touch beta with with open shift for So what? What features and components or capabilities are you most excited about and looking forward to what? The launch and you know, and what? You know what? What are the something maybe some new goals that you might be able to accomplish with with the new features. And yeah, So I will tell you we're off to a great start with open shift. We've been on the platform for over a year now. We want an innovation award. We have this great team of engineers out here that have done some outstanding work. But certainly there's room to continue to mature that platform. It calls, and we're excited about open shift, for I think there's probably three things that were really looking forward to. One is we're looking forward to, ah, better upgrade process. And I think we saw, you know, some of that in the last demo. So upgrades have been kind of painful up until now. So we think that that that will help us. Um, number two, A lot of our open shift workloads today or the workloads. We run an open shifts are the stateless apse. Right? And we're really looking forward to moving more of our state full lapse into the platform. And then thirdly, I think that we've done a great job of automating a lot of the day. One stuff, you know, the provisioning of, of things. There's great opportunity o out there to do mohr automation for day two things. So to integrate mohr with our messaging systems in our database systems and so forth. So we, uh we're excited. Teo, get on board with the version for wear too. So, you know, I hope you, Khun, we can help you get to the next goals and we're going to continue to do that. Thank you. Thank you so much rich, you know, all the way from from rail toe open shift. It's really exciting for us, frankly, to see our products helping you solve World War were problems. What's you know what? Which is. Really? Why way do this and and getting into both of our goals. So thank you. Thank you very much. And thanks for your support. We really appreciate it. Thanks. It has all been amazing so far and we're not done. A critical part of being successful in the hybrid cloud is being successful in your data center with your own infrastructure. We've been helping our customers do that in these environments. For almost twenty years now, we've been running the most complex work loads in the world. But you know, while the public cloud has opened up tremendous possibilities, it also brings in another type of another layer of infrastructure complexity. So what's our next goal? Extend your extend your data center all the way to the edge while being as effective as you have been over the last twenty twenty years, when it's all at your own fingertips. First from a practical sense, Enterprises air going to have to have their own data centers in their own environment for a very long time. But there are advantages of being able to manage your own infrastructure that expand even beyond the public cloud all the way out to the edge. In fact, we talked about that very early on how technology advances in computer networking is storage are changing the physical boundaries of the data center every single day. The need, the need to process data at the source is becoming more and more critical. New use cases Air coming up every day. Self driving cars need to make the decisions on the fly. In the car factory processes are using a I need to adapt in real time. The factory floor has become the new edge of the data center, working with things like video analysis of a of A car's paint job as it comes off the line, where a massive amount of data is on ly needed for seconds in order to make critical decisions in real time. If we had to wait for the video to go up to the cloud and back, it would be too late. The damage would have already been done. The enterprise is being stretched to be able to process on site, whether it's in a car, a factory, a store or in eight or nine PM, usually involving massive amounts of data that just can't easily be moved. Just like these use cases couldn't be solved in private cloud alone because of things like blatant see on data movement, toe address, real time and requirements. They also can't be solved in public cloud alone. This is why open hybrid is really the model that's needed in the only model forward. So how do you address this class of workload that requires all of the above running at the edge? With the latest technology all its scale, let me give you a bit of a preview of what we're working on. We are taking our open hybrid cloud technologies to the edge, Integrated with integrated with Aro AM Hardware Partners. This is a preview of a solution that will contain red had open shift self storage in K V M virtual ization with Red Hat Enterprise Lennox at the core, all running on pre configured hardware. The first hardware out of the out of the gate will be with our long time. Oh, am partner Del Technologies. So let's bring back burn the team to see what's right around the corner. >> Please welcome back to the stage. Red Hat. Global director of developer Experience burst Sutter with Kareema Sharma. Okay, We just how was your Foreign operators have redefined the capabilities and usability of the open hybrid cloud, and now we're going to show you a few more things. Okay, so just be ready for that. But I know many of our customers in this audience right now, as well as the customers who aren't even here today. You're running tens of thousands of applications on open chef clusters. We know that disappearing right now, but we also know that >> you're not >> actually in the business of running terminators clusters. You're in the business of oil and gas from the business retail. You're in a business transportation, you're in some other business and you don't really want to manage those things at all. We also know though you have lo latest requirements like Polish is talking about. And you also dated gravity concerns where you >> need to keep >> that on your premises. So what you're about to see right now in this demonstration is where we've taken open ship for and made a bare metal cluster right here on this stage. This is a fully automated platform. There is no underlying hyper visor below this platform. It's open ship running on bare metal. And this is your crew vanities. Native infrastructure, where we brought together via mes containers networking and storage with me right now is green mush arma. She's one of her engineering leaders responsible for infrastructure technologies. Please welcome to the stage, Karima. >> Thank you. My pleasure to be here, whether it had summit. So let's start a cloud. Rid her dot com and here we can see the classroom Dannon Jessica working on just a few moments ago From here we have a bird's eye view ofthe all of our open ship plasters across the hybrid cloud from multiple cloud providers to on premises and noticed the spare medal last year. Well, that's the one that my team built right here on this stage. So let's go ahead and open the admin console for that last year. Now, in this demo, we'LL take a look at three things. A multi plaster inventory for the open Harbor cloud at cloud redhead dot com. Second open shift container storage, providing convert storage for virtual machines and containers and the same functionality for cloud vert and bare metal. And third, everything we see here is scuba unit is native, so by plugging directly into communities, orchestration begin common storage. Let working on monitoring facilities now. Last year, we saw how continue native actualization and Q Bert allow you to run virtual machines on Cabinet is an open shift, allowing for a single converge platform to manage both containers and virtual machines. So here I have this dark net project now from last year behead of induced virtual machine running it S P darknet application, and we had started to modernize and continue. Arise it by moving. Parts of the application from the windows began to the next containers. So let's take a look at it here. I have it again. >> Oh, large shirt, you windows. Earlier on, I was playing this game back stage, so it's just playing a little solitaire. Sorry about that. >> So we don't really have time for that right now. Birds. But as I was saying, Over here, I have Visions Studio Now the window's virtual machine is just another container and open shift and the i d be service for the virtual machine. It's just another service in open shift open shifts. Running both containers and virtual machines together opens a whole new world of possibilities. But why stop there? So this here be broadened to come in. It is native infrastructure as our vision to redefine the operation's off on premises infrastructure, and this applies to all matters of workloads. Using open shift on metal running all the way from the data center to the edge. No by your desk, right to main benefits. Want to help reduce the operation casts And second, to help bring advance good when it is orchestration concept to your infrastructure. So next, let's take a look at storage. So open shift container storage is software defined storage, providing the same functionality for both the public and the private lads. By leveraging the operator framework, open shift container storage automatically detects the available hardware configuration to utilize the discs in the most optimal vein. So then adding my note, you don't have to think about how to balance the storage. Storage is just another service running an open shift. >> And I really love this dashboard quite honestly, because I love seeing all the storage right here. So I'm kind of curious, though. Karima. What kind of storage would you What, What kind of applications would you use with the storage? >> Yeah, so this is the persistent storage. To be used by a database is your files and any data from applications such as a Magic Africa. Now the A Patrick after operator uses school, been at this for scheduling and high availability, and it uses open shift containers. Shortest. Restore the messages now Here are on premises. System is running a caf co workload streaming sensor data on DH. We want toe sort it and act on it locally, right In a minute. A place where maybe we need low latency or maybe in a data lake like situation. So we don't want to send the starter to the cloud. Instead, we want to act on it locally, right? Let's look at the griffon a dashboard and see how our system is doing so with the incoming message rate of about four hundred messages for second, the system seems to be performing well, right? I want to emphasize this is a fully integrated system. We're doing the testing An optimization sze so that the system can Artoo tune itself based on the applications. >> Okay, I love the automated operations. Now I am a curious because I know other folks in the audience want to know this too. What? Can you tell us more about how there's truly integrated communities can give us an example of that? >> Yes. Again, You know, I want to emphasize everything here is managed poorly by communities on open shift. Right. So you can really use the latest coolest to manage them. All right. Next, let's take a look at how easy it is to use K native with azure functions to script alive Reaction to a live migration event. >> Okay, Native is a great example. If actually were part of my breakout session yesterday, you saw me demonstrate came native. And actually, if you want to get hands on with it tonight, you can come to our guru night at five PM and actually get hands on like a native. So I really have enjoyed using K. Dated myself as a software developer. And but I am curious about the azure functions component. >> Yeah, so as your functions is a function is a service engine developed by Microsoft fully open source, and it runs on top of communities. So it works really well with our on premises open shift here. Right now, I have a simple azure function that I already have here and this azure function, you know, Let's see if this will send out a tweet every time we live My greater Windows virtual machine. Right. So I have it integrated with open shift on DH. Let's move a note to maintenance to see what happens. So >> basically has that via moves. We're going to see the event triggered. They trigger the function. >> Yeah, important point I want to make again here. Windows virtue in machines are equal citizens inside of open shift. We're investing heavily in automation through the use of the operator framework and also providing integration with the hardware. Right, So next, Now let's move that note to maintain it. >> But let's be very clear here. I wanna make sure you understand one thing, and that is there is no underlying virtual ization software here. This is open ship running on bear. Meddle with these bare metal host. >> That is absolutely right. The system can automatically discover the bare metal hosts. All right, so here, let's move this note to maintenance. So I start them Internets now. But what will happen at this point is storage will heal itself, and communities will bring back the same level of service for the CAFTA application by launching a part on another note and the virtual machine belive my great right and this will create communities events. So we can see. You know, the events in the event stream changes have started to happen. And as a result of this migration, the key native function will send out a tweet to confirm that could win. It is native infrastructure has indeed done the migration for the live Ian. Right? >> See the events rolling through right there? >> Yeah. All right. And if we go to Twitter? >> All right, we got tweets. Fantastic. >> And here we can see the source Nord report. Migration has succeeded. It's a pretty cool stuff right here. No. So we want to bring you a cloud like experience, but this means is we're making operational ease a fuse as a top goal. We're investing heavily in encapsulating management knowledge and working to pre certify hardware configuration in working with their partners such as Dell, and they're dead already. Note program so that we can provide you guidance on specific benchmarks for specific work loads on our auto tuning system. >> All right, well, this is tow. I know right now, you're right thing, and I want to jump on the stage and check out the spare metal cluster. But you should not right. Wait After the keynote didn't. Come on, check it out. But also, I want you to go out there and think about visiting our partner Del and their booth where they have one. These clusters also. Okay, So this is where vmc networking and containers the storage all come together And a Kurban in his native infrastructure. You've seen right here on this stage, but an agreement. You have a bit more. >> Yes. So this is literally the cloud coming down from the heavens to us. >> Okay? Right here, Right now. >> Right here, right now. So, to close the loop, you can have your plaster connected to cloud redhead dot com for our insights inside reliability engineering services so that we can proactively provide you with the guidance through automated analyses of telemetry in logs and help flag a problem even before you notice you have it Beat software, hardware, performance, our security. And one more thing. I want to congratulate the engineers behind the school technology. >> Absolutely. There's a lot of engineers here that worked on this cluster and worked on the stack. Absolutely. Thank you. Really awesome stuff. And again do go check out our partner Dale. They're just out that door I can see them from here. They have one. These clusters get a chance to talk to them about how to run your open shift for on a bare metal cluster as well. Right, Kareema, Thank you so much. That was totally awesome. We're at a time, and we got to turn this back over to Paul. >> Thank you. Right. >> Okay. Okay. Thanks >> again. Burned, Kareema. Awesome. You know, So even with all the exciting capabilities that you're seeing, I want to take a moment to go back to the to the first platform tenant that we learned with rail, that the platform has to be developer friendly. Our next guest knows something about connecting a technology like open shift to their developers and part of their company. Wide transformation and their ability to shift the business that helped them helped them make take advantage of the innovation. Their Innovation award winner this year. Please, Let's welcome Ed to the stage. >> Please welcome. Twenty nineteen. Innovation Award winner. BP Vice President, Digital transformation. Ed Alford. >> Thanks, Ed. How your fake Good. So was full. Get right into it. What we go you guys trying to accomplish at BP and and How is the goal really important in mandatory within your organization? Support on everyone else were global energy >> business, with operations and over seventy countries. Andi. We've embraced what we call the jewel challenge, which is increasing the mind for energy that we have as individuals in the world. But we need to produce the energy with fuel emissions. It's part of that. One of our strategic priorities that we >> have is to modernize the whole group on. That means simplifying our processes and enhancing >> productivity through digital solutions. So we're using chlo based technologies >> on, more importantly, open source technologies to clear a community and say, the whole group that collaborates effectively and efficiently and uses our data and expertise to embrace the jewel challenge and actually try and help solve that problem. That's great. So So how did these heart of these new ways of working benefit your team and really the entire organ, maybe even the company as a whole? So we've been given the Innovation Award for Digital conveyor both in the way it was created and also in water is delivering a couple of guys in the audience poll costal and brewskies as he they they're in the team. Their teams developed that convey here, using our jail and Dev ops and some things. We talk about this stuff a lot, but actually the they did it in a truly our jail and develops we, um that enabled them to experiment and walking with different ways. And highlight in the skill set is that we, as a group required in order to transform using these approaches, we can no move things from ideation to scale and weeks and days sometimes rather than months. Andi, I think that if we can take what they've done on DH, use more open source technology, we contain that technology and apply across the whole group to tackle this Jill challenge. And I think that we use technologists and it's really cool. I think that we can no use technology and open source technology to solve some of these big challenges that we have and actually just preserve the planet in a better way. So So what's the next step for you guys at BP? So moving forward, we we are embracing ourselves, bracing a clothed, forced organization. We need to continue to live to deliver on our strategy, build >> over the technology across the entire group to address the jewel >> challenge and continue to make some of these bold changes and actually get into and really use. Our technology is, I said, too addresses you'LL challenge and make the future of our planet a better place for ourselves and our children and our children's children. That's that's a big goal. But thank you so much, Ed. Thanks for your support. And thanks for coming today. Thank you very much. Thank you. Now comes the part that, frankly, I think his best part of the best part of this presentation We're going to meet the type of person that makes all of these things a reality. This tip this type of person typically works for one of our customers or with one of with one of our customers as a partner to help them make the kinds of bold goals like you've heard about today and the ones you'll hear about Maura the way more in the >> week. I think the thing I like most about it is you feel that reward Just helping people I mean and helping people with stuff you enjoy right with computers. My dad was the math and science teacher at the local high school. And so in the early eighties, that kind of met here, the default person. So he's always bringing in a computer stuff, and I started a pretty young age. What Jason's been able to do here is Mohr evangelize a lot of the technologies between different teams. I think a lot of it comes from the training and his certifications that he's got. He's always concerned about their experience, how easy it is for them to get applications written, how easy it is for them to get them up and running at the end of the day. We're a loan company, you know. That's way we lean on accounting like red. That's where we get our support front. That's why we decided to go with a product like open shift. I really, really like to product. So I went down. The certification are out in the training ground to learn more about open shit itself. So my daughter's teacher, they were doing a day of coding, and so they asked me if I wanted to come and talk about what I do and then spend the day helping the kids do their coding class. The people that we have on our teams, like Jason, are what make us better than our competitors, right? Anybody could buy something off the shelf. It's people like him. They're able to take that and mold it into something that then it is a great offering for our partners and for >> customers. Please welcome Red Hat Certified Professional of the Year Jason Hyatt. >> Jason, Congratulations. Congratulations. What a what a big day, huh? What a really big day. You know, it's great. It's great to see such work, You know that you've done here. But you know what's really great and shows out in your video It's really especially rewarding. Tow us. And I'm sure to you as well to see how skills can open doors for for one for young women, like your daughters who already loves technology. So I'd liketo I'd like to present this to you right now. Take congratulations. Congratulations. Good. And we I know you're going to bring this passion. I know you bring this in, everything you do. So >> it's this Congratulations again. Thanks, Paul. It's been really exciting, and I was really excited to bring my family here to show the experience. It's it's >> really great. It's really great to see him all here as well going. Maybe we could you could You guys could stand up. So before we leave before we leave the stage, you know, I just wanted to ask, What's the most important skill that you'LL pass on from all your training to the future generations? >> So I think the most important thing is you have to be a continuous learner you can't really settle for. Ah, you can't be comfortable on learning, which I already know. You have to really drive a continuous Lerner. And of course, you got to use the I ninety. Maxwell. Quite. >> I don't even have to ask you the question. Of course. Right. Of course. That's awesome. That's awesome. And thank you. Thank you for everything, for everything that you're doing. So thanks again. Thank you. You know what makes open source work is passion and people that apply those considerable talents that passion like Jason here to making it worked and to contribute their idea there. There's back. And believe me, it's really an impressive group of people. You know you're family and especially Berkeley in the video. I hope you know that the redhead, the certified of the year is the best of the best. The cream of the crop and your dad is the best of the best of that. So you should be very, very happy for that. I also and I also can't wait. Teo, I also can't wait to come back here on this stage ten years from now and present that same award to you. Berkeley. So great. You should be proud. You know, everything you've heard about today is just a small representation of what's ahead of us. We've had us. We've had a set of goals and realize some bold goals over the last number of years that have gotten us to where we are today. Just to recap those bold goals First bait build a company based solely on open source software. It seems so logical now, but it had never been done before. Next building the operating system of the future that's going to run in power. The enterprise making the standard base platform in the op in the Enterprise Olympics based operating system. And after that making hybrid cloud the architecture of the future make hybrid the new data center, all leading to the largest software acquisition in history. Think about it around us around a company with one hundred percent open source DNA without. Throughout. Despite all the fun we encountered over those last seventeen years, I have to ask, Is there really any question that open source has won? Realizing our bold goals and changing the way software is developed in the commercial world was what we set out to do from the first day in the Red Hat was born. But we only got to that goal because of you. Many of you contributors, many of you knew toe open source software and willing to take the risk along side of us and many of partners on that journey, both inside and outside of Red Hat. Going forward with the reach of IBM, Red hat will accelerate. Even Mohr. This will bring open source general innovation to the next generation hybrid data center, continuing on our original mission and goal to bring open source technology toe every corner of the planet. What I what I just went through in the last hour Soul, while mind boggling to many of us in the room who have had a front row seat to this overto last seventeen plus years has only been red hats. First step. Think about it. We have brought open source development from a niche player to the dominant development model in software and beyond. Open Source is now the cornerstone of the multi billion dollar enterprise software world and even the next generation hybrid act. Architecture would not even be possible without Lennox at the core in the open innovation that it feeds to build around it. This is not just a step forward for software. It's a huge leap in the technology world beyond even what the original pioneers of open source ever could have imagined. We have. We have witnessed open source accomplished in the last seventeen years more than what most people will see in their career. Or maybe even a lifetime open source has forever changed the boundaries of what will be possible in technology in the future. And in the one last thing to say, it's everybody in this room and beyond. Everyone outside continue the mission. Thanks have a great sum. It's great to see it

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

>> And one topic. I want to get onto that. You mentioned it up and you opened the can of worms on this. So I blame you. His blood flow restriction training you called B F R. And Freeman listening chases the well, the most well versed individuals in this area. I was, I learned from him probably weekly on it, and I get studies from him. I used to be daily. Probably. It will lessen consistent now, because he's probably realizing that I can't read that fast. But I'm gonna chase to talk a little bit about some of protocols that you used be a far and harder you can use it for. Not yet. That's like development for individuals who might just be seeking an alternative way to work out whether the older adults, people who travel on the road and what it does physiologically for not only muscle growth, but the tendon thickness, like you said, and some of the other other >> protocols. Such a cellular swelling protocols. >> Yeah, yeah, I think you know, the one thing I would say about our previous of conversation with incense Thing is, I'm not telling people not to take him out like running around saying that that's the devil and all that. So I make sure that I'm not like one of those zealots about that stuff. It's it's just Hey, do you need it? You know, like this, that thought process is critical. Is this necessary? Not let me just problem cause I'm sore today, right? I think that's the caveat I want people to walk away with is that everything is necessary if it's necessary. And if it's not, is there a better alternative, or is it just part of life? Is that part of being a division one athlete or, you know, somebody who's recreational? E fit is you're going to feel a little sore and tired. Is it necessary to take that pill that made negatively? Thank you. So I think that's one thing I want to say, but kind of moving on to the >> You are not a dealer. I will vouch for it. Yeah. Interesting topic to talk about. And I give you credit for being open minded on both ends. Yes, everyone was concerned. >> Yeah, Yeah, I want to throw that out there. But I think with the Bee Afar stuff, it's I'm so ill. I've learned a lot from the man. Dr Headless Sarah. Hey, Works is Smart tools company, which they're just absolutely revolutionising how available and the education that's associative willful restrictions. So I you know, I I'm gonna kind of pass on that credit and say that, uh, they're really pushing the field forward, and I'm not affiliated with the company. I just think what they're doing is is fantastic work, because local restriction obviously has been around for a long time. It's not new, you know, we're not pretending it's new, but you know, it's really the availability of cuffs for sort of affordable prices has made it seem no refreshed and kind of a new life to it started in the late nineties in Japan, really doing a lot of the early research on it. Ah, lot of people started with tine off with different straps and and, ah, bands that they're just wrapping around their arms and looking for, you know, in a partial occlusion and some cases probably dangerously a full ischemia. But I think you saw it. And most recent years, with some of the owns recovery and the Delphi's, which come in a pretty high price tag and as I mentioned, smart tools has come out. They have much more affordable. I think it's, you know, a tenth of the price. And so now you're able tto. But these types of you know it's tool and everybody's hands. And I think it's is changing the landscape as faras, a modality that has multiple uses. And that's one thing when we talk sports science, we talked technology. You know, everything has a time in place. But when I look and evaluate and vet out technology, or whatever we're going to bring on is as a new resource. I always looked forward to have multiple uses, doesn't have a bang for your buck, and I think the blood flow restriction does. It's versatile. It can be used in rehab. You can be used to build muscle confused for strength. It can be used as, ah, activity potentially ater so you can use it. Potentially increase your subsequent performance with an acute time window. You can use it as a recovery tool, so I think the the utilization of it is still we're learning about it. There's still no definitive. Here's how this happens in this sequence but I think that's what Everything right? The human body. We're learning so much about it. But the science that's there has proven that low load with local restriction, where we're including one hundred percent venous return, but partially including arterial inflow. So there is blood flow going into the muscles and the periphery, but there is no blood flow returning, and so it creates a cooling effect. We're essentially you're gonna limit the availability of oxygen. You're going to decrease the pH and more acidic. You're goingto deplete foster creating stores. You're essentially going to run through the size of principle and use up small of slow twitch fibers and skip essentially rights of fast switch fivers with a low load or even a non loaded exercise. So I think when you talk about somebody who's got limitations, maybe they just had surgery. They can't run. They can't have the impulse of the impact that you would need or you would want to see toe. I kind of developed the most cultures. They come back. Little restriction is a great way because takes a low load exercise and you realise, is that restricted bowling and you get a subsequent fast, which adaptation? So you're you're simulating the big boys, the ones that move us, the ones that make us jump and run faster. Ah, and I think you're seeing time Windows of adaptation that air a sixth of the time Faster, you're getting strength. And I purchased three Adaptation in two weeks, whereas in traditional resistance training it was taking eight to twelve. Um, so And when you talk about, I had an athlete rolled her ankle and I want to make sure that they're not having atrophy is they walk around in a boot. I need to make sure that the muscles around the knees and the hamstrings, the name of the elders, critical drivers and sport aren't just wasting away. So we would have athletes obviously in the rehab sitting, doing protocols to develop muscle but also just sitting the act of just sitting with occlusion passively not doing anything has been shown to cut atrophy by fifty percent. So it's fantastic because it's not invasive. You're not doing anything into him. They're just sitting. So, uh, we don't you know, promote them to play on their phones constantly, but they can sit there and have their phone out and, you know, twenty minutes goes by and they just hopefully of, you know, benefited their return to play and a, you know, a faster, more efficient way than just sitting around. So lots of lots of utility for it. >> Interesting. So for those not familiar bloodflow restriction training the way it works, you gotta cuss. Arms hopefully cast. Not just, uh, elastic band, you tying on. But that's how I started originally from Kat to training out in Japan. So it's a cuff. The attach is approximately on the whim, typically by the shoulder or up along the thigh, and it includes the amount of blood so reduces the amount of blood. Don't go into the muscle, which then allows these Siri's of physiological effects that chase alluded to. That is a difference between Venus and arterial occlusion and chase in. Regards to that were Some of the specifics are for people who aren't as familiar with blood flow. You rattle off a bunch of stuff regarding blood flow and from the adaptations of it. But people who aren't familiar with it you measure the occlusion through Doppler. I believe Smart tools uses a remote Doppler. They're attached to you on the distal limb and everyone using this, what percentages do use? How do you know what you too much occlusion that to type that not tight enough. And we're the protocols that you use once you have the right conclusion for that limb to increase some of these hypertrophy, some muscle growing activities or, you know, just sitting there play on your phone activities that reduces hypertrophy for your athletes. >> Yeah. So what you're doing is you're actually going to take an external Doppler or something that's gonna allow you to magnify the sound of the pulse, right? So if you take radio pulse, you know, right here you would replace the Doppler on it. You would actually be able to hear the heartbeat as it from service, >> due stew, stew, sh >> and up top. They're wearing the cuff. You're going to slowly start to inflate it. It gets tighter, tighter, tighter. And you will eventually get to a point where that, uh, false will start to fade of >> this dish dish. >> And it comes to a point where it's non existent. And so that's when you know that there's been full arterial occlusion that's there one hundred percent. There is no blood flow into that arm. There's no blood flow out. It is included. And so research has shown that basically anywhere from thirty percent in ninety percent, you're gonna have the same amount of occlusion. So if I was explained that, ah, a little bit more detail is so I'm going to take that one hundred percent occlusion number. So if you've ever done your blood pressure and the typical one of perfect blood pressure's one twenty of Brady and that's the same device we're going to use I mean its's stigmata. I'm anemometer the tough one to say, um and you're going to get a number up there like, let's just say two fifty. Alright, so that's your hundred percent occlusion. What again research has shown is that in thirty percent of two. Fifty all the way up to ninety percent of two. Fifty, that's the sweet spot or including arterial, that actually doesn't improve occlusion as the higher you go. So we stick to fifty percent. So, you know, fifty per cent of two fifty is one twenty five. And, ah, you're goingto have Justus. Much of you did it at ninety percent. And really, the differences is pain perception. Because if you start getting up one hundred percent inclusion and telling somebody to exercise, they're not going to like it. It's not going to feel good. So it's a nice sweet spot of saying, Hey, we have included Arterial but not fully restricted, but we have researched it, Venus. But we can still move and be act on DSO with that what you're really looking to do. There's a thirty fifteen fifteen fifteen protocol that's seen pretty commonly, but ultimately you just need to fatigue the muscles. Ito have a low load exercise that's done for high volume, typically fifteen plus wraps for multiple sets with a minimal respirations. So what we're trying to do is we're trying Teo, allow for blood to be flung, pumped into the muscle. You're goingto actively, you know, contract. Over time, it's going to stimulate fast twitch fibers. You're going to rest for a very short period. More blood flow is going to go to the area. It's gonna keep getting more acidic. It's going to keep activating Mohr fast twitch, and you're going to just repeat that. And so I mean it really, really magnifies the response of typically a weight or resistance that would be almost no impact on you at all. You would have no performance benefit from using a weight that light. So you can really use it as you know, when I was in a rehab setting with an athlete who has very little capability to handle load. Or you could use it as a finisher in your body builder. And you wantto stimulate ah, muscle group that's lagging, and you really want to build it up. Ah, it's the fantastic thing I think about It is it's a minimally damaging activity. And what I mean by that is that you're gonna have a dramatic reduction and creating stores of CK levels. Lt's myoglobin. You're not going to get the same mechanical breakdown that you see what too difficult resistance training when we start talking about internal load and H R V. If you were to substitute and in season lift with the Afar, you're still going to get strengthened and have virtually adaptation without the potential systemic load. That may be a typical resistance training session. Does the now you start talking about minimizing, uh, internal responses? Bye. Still getting annotation, so it's it's pretty, pretty amazing. >> Yeah, that's that's something. So I've seen personally as well. I use smart tools, smart tools. I'm not feeling it with a big fan of whom, because they made it affordable for individuals like you, of myself actually use them. So we're talking about occlusion. We're talking about reducing amount of arterial occlusion, but not with the amount of Venus inclusions here allowing blood to pool. It's an extent you get large amounts of violation. You increase the amount of capital area is in that area, but you're also not breaking down the muscle in the same way that you would otherwise. So we're lifting a heavy load. You have the fibers himself begin to essentially tear apart. Your body has to rebuild these, but now we're increasing hypertrophy, so growing them also, without having to have this break down response in the muscle itself. But that being said, the loads that you're using are also twenty percent of your one rat max. So a very, very light load you're using to fatigue. How does that affect the tendon itself? Because one thing I've noticed personally, this is I'm not I'm not saying you should do this, Okay, this is what I did and maybe stupid or whatever you wanna call it. I had a really bad Tanaka, the issue of my knee where I couldn't play basket. I couldn't go upstairs well, and I didn't be afar. Traditional trailer at tempo work. But when I started doing be fr low level plyometrics when I started inducing some of the shearing forces on the tendon to increase adaptation that area that otherwise might not be there with a >> low load, >> I started Teo see much better results in my knee compared to some of the tempo work. Do you do anything specifically with B a far that might target attendant outside of the traditional thirty wraps, fifteen wraps, fifteen reps. Fifteen reps with >> a low load. >> Yeah, yeah, absolutely. I think you know some of the ice of measures that we talked about when you were working in Stanford and having that Anil Jessica effect. So having the ability to have the mitigation on acute windows of what, fifteen, forty five minutes, but also the college and proliferation. So you're getting an increase in human growth hormone that there's like one hundred seventy percent times greater after ah workout, which we know. H gh doesn't necessarily build bigger muscles, but it does stimulate collagen growth. So when you're having somebody who is maybe coming back from a ruptured Achilles or another, you know IDA cirrhosis issue, You know, it's a great way to help promote and environment and maybe in a vascular area and the kind of forces, nutrients and a hormonal shift that may promote a more appealing environment. I think you know, we talked about it briefly. The training piece, I think you know, the more that you can start to get people into. I'm not overly dramatic, sport specific person, but I think the more you can get people into activities that are going to be replicated on the field, know whether it's sled pushes and walks or whether it's, you know, having some type of, um, you know, activity. If your picture where you're getting your arm through these range of emotions that are going to be necessary while using the inclusion is actually gonna promote a lot of ongoing benefit. I think toe rehabilitate the area on a functional manner and develop not only the musculature, but also remote the properties around that specific tissue that needs to be healed. So I think there's some really cool things that are just now kind of being played with Just because we can actually die. Elin, the proper collusions. We can actually die. Elin. What we want to see happen with you whether it's, uh, some of the cells, whole protocols that we're doing are these giving preconditions. Bread falls. Where were haven't athletes sit for extended period time passively with their occlusion of set? And then they're gonna reap, refuse. We're in, Allow blood flow back, and we're going to do that repeated intervals prior to activity and see a potential for increased power output. Oxygen. Connectix. The research is pretty amazing with some of the human reconditioning and that they're saying, um, increase time to exhaustion, decrease time trial performances. But they don't really know why. You know, there isn't like a clear mechanisms for performance gains that's been totally identified just yet. There has been stuff where it's shown to attenuate lacked eight levels. So you're obviously no cellular. Respiration is enhanced because you're not getting that amount of hydrogen present in the blood. So you may be potentially more efficient energy user using more, more fat and oxygen, so that's great there. But I think you know, as the research are sketching out, that piece is that's one thing that I'm looking at doing for my research focus for school. Is that potentially a shin piece? If I'm already going to be sitting around before a game, or I'm gonna have time between events like a track and field event are, you know, Cool event. And I know I can sit here passively, not use energy, provide a stimulus to the body that's gonna potentially open up neural pathways or physiological mechanisms to increase contract ability of the muscles. I'm going to, then maybe get that extra tenth of a second. I'm going to throw an extra, you know, a couple feet on the javelin. I'm going to do whatever I need to dio potentially at a higher level. I think that's really as we're pushing towards performance. Why do you take, you know, choose during the game like you want increase performance, you want to run longer, and I think this is going to add one more a little layer to it. That from an investment piece is minimally invasive is minimally changing to their to their schedule. They're not. They don't have to do anything crazy. They feel good. And that's the biggest thing. Is the anecdotal feedback on it is man, I feel great. I feel like I have to I don't have to do a full warm up. I feel like I can just kind of get out there, move around. We still have him do stuff, but they just feel like they've warmed up faster. And I think of that piece is gonna be really cool to see if we can demonstrate some of empirical evidence on it. >> Yeah, that I'm excited to see the research, >> and I know you're working hard on it. >> It's kind of a great stop. Making Brava kind really brings us full circle because you look at be fr it, increases their sit in the area and lacked a production and increases economic nervous system arousal, which has been shown both to increase cognitive abilities. Um, neural plasticity and ability to enhance memory. And so why you're doing this? It's also the only prime main the body for the coming activity. We also prime ing the body is a hole in regards to it's mental capacity and not just the muscular area. And so when you start looking at that, you know, full system, the human body and how we can talk about a little bit here, some dynamical systems where you know the body is really complex. What happens in one area affects another. You can't differentiate between your physical mental side because the physical side of the Afar is now enhancing your mental side. Just like your perception. Ten hands a workout. And so you have feedback up and feedback back down. And that's just a great, you know, highlight You brought up because now it's really inclusive. Were we're so often thinking this isolated manner. Oh, if we've been to this or we run this, this will happen. But we don't think about it in this recursive loop manor where what I did to my muscle, right, our muscle releases these myo times. I go talk to our brain, which then go back and talk to our muscle. And we have the endocrine system working together to orchestrate this all and just the whole idea of be a farm for a game It's not just right the muscles and the scheming Preconditioning, but it's also a fact that you're putting the person in a state That's more conducive. Two performance itself, because so often and this isn't to go on a rant and I apologise. And this is something you buy a top about, right? Avoiding the sympathetic states, All right, we don't want to be sitting there before game doing deep belly breathing because we need to be ready to roll. There's a reason why you get excited in these situations and a really excellent full loop example. How Don't comes together there. >> Yeah, I think one last little piece with that, too, is black. Tate has been shown and exercise of a specific lactate now to have been associated with BDNF, right? So that brain derived neurotrophic factor that exercise stimulates like Miracle Gro for the brain, >> and that if >> you're sitting around watching, you know, lecture for an hour, get up to ten SWATs. Walk around, and all of a sudden you have a renewed focus. And so with that to your point of it's all connected is you have an athlete who essentially is going to get a benefit from that. But we're also, you know, and there they'll never watch this, so I'll say it. I do planting that placebo. My burbage is really, really careful. And hey, just so you know, you wear this attempt ten, fifteen minutes before you do some ISOs, your ankle will feel better. It has an ability to mitigate. Think like him. Planting that sense of this is gonna work because we'll see Bo Effect works. We know it does. So there's a little bit of, you know, mix of art and science and how we imply these technologies and saying they like, Hey, Logan, just say no, you wear this before that game, your ankle will feel better. You're gonna feel looser, going to hell faster and just letting them roll with that and don't need to tell him anything else. And I think that to your point of it's all connected can then maximise whatever intervention you want to, then increase performance. >> Yeah, and I'll avoid a rant here. I'll keep it short, I promise. But what you hit on? Perfect. Especially since that. Look at some of studies regarding attendance, they'll look at it and see that the timid itself is healthy, yet they feel pain, and they've done lost studies where they're saying an external stimulus. So something like a metre gnome in the background going Ping Ping Ping and you're focused on the stimulus instead of the pain. And you now begin to de associate your knee with pain because the stimulus and regards to the tempo that's going on the background, you're doing it. Why didn't exercise So now? Because you're focused on this external stimulus fall during exercise, you begin to disassociate pain with your, you know, near tendon during that movement and just really shows how coupled the system is and how our brain talks your body body. And if we perceive that we're healthy right? You said, Oh, mixing the heart and the science while you're mixing the science of the science, right? Your you understand that perception is reality is not necessarily. We like to call it art because there's no number to put behind it. Really. It's, you know, the science that our body is deeply into connected and how are neurons from the brain talked to our muscles? Are muscles tough back to our brain are all essentially one and how everything from your nutrition, your perception to your stress from school, you're emotional state, whether you got a text message from someone that made you upset all effects, your internal load off the body itself. And regardless of what external only put and no matter how hard you want to work, if your internal system isn't able to handle the stimulus they're going to put on it in terms of the load you're going to give then what we're doing is it? It's really falling short of what we're actually trying to accomplish because we're essentially using external load to infer what's going on. But there's so many things that go on inside the body outside of external load that we're only using one system to monitor the internal system. We're kind of I was a falling short, but not maybe doing all that we can. >> D'oh Yeah, I mean, I think the you know not to rant myself, but that's one of the biggest mistakes that we as a sissy practitioners make, is the assumption with general adaptation Centrum theory that you're getting people and that they're adapting at the rate into the dose that you think is appropriate that we're making that assumption as to where they're at. So when we say, Oh, they're at home, you know, stasis. And we're going to apply to weeks of ah loading scheme, and then we're gonna unload, and then we're gonna push it higher because they're going to super compensate. I think that is a load of crap. I think that we want that to be the case because we want to feel justified and feel good ofwhat we d'oh. But in many cases, you really have to dial in all the factors associated with overreaching all the factors associated with performance and mix them and have checks and balances to see truly, if somebody is where you think they are and if you got them where they are and if not, what was the reason why was there an energy insufficiency? Was there a Micronesian problem? Was there associated stress damaging the functioning, The A access All those things have you know they come in to play, but we are so rigid and and a lot of our thinking me included Holy, guilty. This we work in four to six week block. So yeah, you know, my own load is gonna be a three week three. Well, maybe your own unload should be a week nine. You know, like, how do you know that they're not ready for Maura. Maura, Amore. Um, you know, so that I think that assumption of not necessarily taking into consideration that connectedness between all these systems Ah, can get us into trouble to make us have false positives. I think I think we really congrats pawn the stuff that's not there >> now, that's that's couldn't be said better because we like to make it simple, because we can understand Simple. And when we make it complex, we realize we don't really understand that much. But the more we appreciate as complex, the more we can appreciate how applying something simple, like we think a load ten push ups really isn't as simple as it may be. And that at times, can cause paralysis by analysis. Where you have so many things >> going on at once and to consider I'm not saying that we just sit there and measure every single subsystem. I know you're not either, >> but the idea that we need to appreciate that and see where can we maybe refer. Teo, Turn, Tio. That isn't just in the lane off. How much weight do we lift? How much low do we give someone But what other factors could be involved and that athletes life. That's not getting the results that we think this external load should be leading. Tio, it's a great check engine light, because now we have this external load. Hey, I expected to be here in three months, and you're not there. That's okay. Who knows whose fault it is? No one's. But the idea is that now we can turn different people because we didn't see the expected results. We can dive a little deeper, and that's allowing us to utilize our resource is whether it's a friend. You know, a doctor. You know, another practitioner, you know, to help arm us with the information to be the best that we can be. >> Yeah, I think that's what the external load comes in, right. You gotta know if they're not meeting expectations or the desired outcomes. No. Are they typically matching people in practice? You know that are similar positional demands. Are they typically being asked to do something that isn't looking normal? That would then we can kind of backtrack and see how they were doing it. What the fuck? Jack is associated with an internal load work, and again, we don't. We don't monitor everything. We don't think it's necessary. We try and find what's appropriate for his team and scenario. But I think again, if you're mindful and you know you're athletes and you know the scenario of what you're trying to put them in, you can then kind of use your your coaching, I to say, Okay, what are the things that I think may be influencing? Yeah, providing Malad a patient, you know, orange, the desired stimulus, you know, desired outcome. Now, what are we doing to them that we should be seeing or think we should be saying. And if I know them, what is essentially a confounding variable to that? >> Yeah, No, that's perfect. You don't assess everything. A because you can't and be known as time. But you assess what's pertinent and you're aware of what's apartment and you act out the check engine light and facilitate where you can now, well said, because I think both ends resettle. Let's be so simple and just do this or let's on Lee do this aspect over here. But when you take in consideration, all of it, you allow yourself to be the best you can be in your position that you're in because you're not trying to solve everything. You just try to facilitate where you can. Yeah, perfect for Chase. And I want to hold you up too long, and I really appreciate you being here. I want to wrap it up before finishing up here. I got, I guess, two questions for you. I didn't send them to you ahead of time so that I can if you don't have a quick answer, that's fine. The first one is it's pretty simple. I'm not going. I don't mean Resource is in terms of O go to Pub Med or go to this paper. But are there any individuals out there that you can possibly listen to or find that you have found the very informative and not just in terms of all that's good information, but sometimes change the way you think about how you do your job. >> I'm talking to you right now. It's a lot of my my thoughts and know how I address of, you know, some of the the bio mechanics and physics of what we're doing. You know, it's definitely not an area that I'm strong in, and I think you've done a great job of putting information out there for the public tio toe, you know, be able to digest an easy manner, man, you know, a public resource. You know, this may sound kind of cheesy and maybe a little bit of roast sci fi, but I still re t Nation and Goto like all those you know, you know, Jim Wendler sites and freed all the Westside stuff. And, you know, I think you can't isolate sports science and sail. It's just Dad are, Oh, it's just, you know, pumping out research out of the lab or Oh, it's physiology or urge technology. I think each practitioners gonna have their own flavour and what they like and what they bring to the table. And I think that we need to cater to that. Each person should say, Hey, this is what I'm good at. These are my skills. I want to learn more about tax and if X s o happens to be baseball and throwing and overhead athletes than you're going to find the Mike Ryan holds air crises and really dive into that. And if you want to know about traditional pure ization schemes and force plays, you're gonna look at the stone stuff. You're gonna look at half, you're going to look at people who are early pioneers in it. So I think, you know, I don't have ah, necessarily a one person go follow, but it's more of a question to the question is what do you want to know about? What do you like? What's something that's really really, you know, kind of hits the button for you and then just start Googling stuff start, you know, typing these these keywords in and people will start popping up. And I think that's my development has come has jumped. The greatest, I guess Leaves is when I started diving into these rabbit holes of what I want to learn about right now and just saying for the next two weeks, I'm going all in on, you know, let's see saturation lost muscle from Samo, too. You know, I'm just learn everything I can about my loving and hemoglobin and mad a crit and all that stuff. So it's really more about finding what you want to know at that time and just doing a deep dive and then finding something else, doing a deep that and before you know it, you're times years to that and you have a, you know, a well rounded hopefully, you know, face of knowledge to pull from. >> And my last question for you chase. And this might be a tough one for you to answer the that you are the ghost of social media. Yeah, That the king of the King of trolling my page. You know that you are interested. People are interested in following up on what you're doing. Where can they find more information about yourself? What links or handles either. Twitter, Instagram. Would you advise him to look up into and keep a tab on yourself? >> So the only thing I'm using, as I have on Instagram and at Underscore Chase felt so It's It's simple. It's like toe like to troll you and fight in every now and then. But, ah, that's basically what I got. I got a couple post up there. But maybe maybe if, uh, I get a little help, we'll see how it Ah, how it grows. >> Yeah. I highly advise you guys following him because we continue to push him to post more stuff. I shouldn't be the only one privileged to get his text messages at obscure hours, highlighting some interesting topics I would love for it to be shared publicly. So I'm not being the third party siphoning off his knowledge and posting there. Yeah, well, they could chase. I really appreciate you hanging here and be able to be our first guest again here. The reason why I wanted you on first you quite a bit played a big role in my development and continue, Tio. And we all wish the best for you. Um, it really was great to have you here and thank you. >> All right, man, I appreciate it was a lot of fun. >> All right. Awesome. Well, thank you guys for listening again. My handle here is strong. Sorry. At strong underscore by science. I did that all wrong. It's at strong. Underscored by underscore science. I should know my own handled by now. I use Instagram, I think my Twitter's handles at strong underscore science. Who knows? We'll make a link to it. We'll be sharing this podcast here shortly with different clips as well. For those of you who don't have the attention span to listen to an hour toy mint podcast will die some of this up. So thank you guys for listening. Really appreciate it and take care.

>> Announcer: Covering Spark Summit 2017, brought to you by Databricks. >> This is theCUBE, and we're having a great time at Spark Summit 2017. One of our last guests of the day is Shafaq Abdullah, who is the director of data infrastructure at the Honest Company. Shafaq, welcome to the show. >> Thank you. >> Now, I heard about The Honest Company because of the celebrity founder, right, Jessica Alba? >> Shafaq: That's correct. >> Okay, but how did you end up at the company, weren't you at a start-up before? >> That's exactly correct. So, basically, we did a start-up called InSnap before we actually got into Honest, and the way it happened is that, Insnap was more about instantaneous building personas and using machine learning and Big Data Stack, and Honest at that time was trying to find someone who could them with the data challenges. So, Insnap was the right piece in some of its technology and expertise in big data and machine learning, so we basically built a real-time, instantaneous personas to increase engagement and monetization. It was backed up by Big Data machine learning and Spark instead of our technology. So we used that to basically help Honest to really become data driven, to solve their next generation problem of making products which drive value out of data, and understand their customers better, operate better business, optimize business better. That is why they acquired us, and essentially, we deal with the technology in their stack, not only the technology, but also the culture, the business processes, and the teams which operate those. >> Okay, we're going to dive into some of the technical details about what you're developing with George in just a second, but I have to ask, the company culture is really important at The Honest Company, right? They're well known for being eco-friendly and socially responsible. What was it like moving from a start-up into that company environment, or was it just a natural? >> Basically, of course, Honest was a much bigger start-up for four or five years after it was initially created, so we at Insnap, very lean, agile and much more data driven. That was a bigger difference. So the way we solved it was, we actually, they actually allowed us to create our data organization called Data Signs, which was heading all the data initiatives. And then, we worked with other cross function teams, with finance, with accounting, with growth, with sales to basically help them understand what their needs are, and how to become really data driven by driving the value out of the data by using the state of the art technology. So it was a mix of team alignment and cultural change, focused on the business goal, and getting agrigate to gather around it to make the change. I really enjoyed that while we actually carried out this journey of Honest from being just descriptive, which is essentially just finding what has happened in the data, just generating reports for revenue. By becoming more predictive and prescriptive, which is more like advanced analytics and also advanced advisory role, which together plays in making decisions around features, around businesses and the operations. >> And George, you talked to a lot of customers today, and some of the same themes. Do you want to drill down some of the details of what they're doing. >> I'm curious about how you chose the first projects to get quick wins and to establish credibility? >> Yeah, that's actually a very good question. Basically, we were focused around the low hanging fruit in order to give us a jump-start and to build our reputation so that we can actually take much more advanced technology projects. And in order to do that, what we did was, if you go to Honest.com, and you search in their search bar, their search was very flimsy, and it was not revealing good results. We already built our engine, like a matching engine, so it was very easy to extend it into a full search engine. That was the first deliverable which we could deliver, and we delivered it under a month and a half or two months, right when we came in. And it was like, hey, these guys just improved our search by 10x or 100x; we are getting much more hits, much more coverage of the third strums And that served the tone. Then it was like we also wanted to, another piece which we wanted to tackle was, how do we improve Honest recommendations. That was another project. But before doing that, Honest did not even have a data warehouse, which it could call an advisor warehouse, so that you can get all the data in one place, like a like a data lake, because the data was siloed in organizations, and the analysts could not really get the data into one place and mix and match and analyze the data. So that was another big piece which we did, but we did it very early on. That was the second big deliverable, even before recommendation, the data warehouse. So basically, we plugged in Spark right in the middle, suck up all the data from different places, shove the data in, made this ETL king, which basically extracted, transformed and loaded the data into the data warehouse. Now, this data warehouse basically broke away those silos and made them a cohesive data lake which could be used for driving value and understanding patterns, especially for machine learning, analysts and all the decision makers. >> Was it a data warehouse, or was it a data lake? The reason I ask for distinction is, data warehouse is usually extremely well curated for navigation and discoverability, whereas the data lake is, as some people say, nuts, a little step up from a swamp. >> That's right, so basically, when I call it a data lake, I actually call it, because we have two data aggregation or data gathering infrastructure. One is backed by Spark and S3, which we call a data lake, where unstructured, structured data, there are all kinds of data there, mix and match, and it's not that easy sometimes, you need to do some transformation on top of the data, which is sitting there in order to really get to the needle in the haystack. But data warehouse has in grad shift, which basically gets the data from the data lake, or like the Spark ideal engine, and then makes it more like a metric-driven report, so that it's easily discoverable and it is more like what the business requires right now. It's more like formal reports, and the dimensions and all those attributes are much more well thought of. Whereas data lake is kind of like throwing it all in one piece so that at least we have the data in one place, and then we can analyze and process it. >> In putting all the data first in the data lake and then, essentially, refining it into the data warehouse, what did you use to keep track of the lineage and to make sure that you knew the truth, or truthfulness, behind all the data in the data warehouse once it got there? >> So basically, we built data model on top of S3 and Spark. We used that data model as a basis, as a source of truth to feed in the reports, and that data model was consistent across wherever you find it. So we want to make sure that those attributes, those dimensions and anything related to that data model for the e-com as well as offline patron is consistent. And so we use Spark, we use S3, essentially, to get that data model consistent, and also, we use a bunch of advanced monitoring stuff for that. When we are processing jobs, we want to make sure that we don't lose the data, and we remove the coupling between the systems by decoupling them, and essentially, in the next version, we made it even stream, even based streams, so that was like general strategy which we adopted in order to make sure that we have consistency around data lake and data warehouse. >> What would be the next step? So, now you've significantly enhanced business intelligence, and you have the richest repository behind that data warehouse. What would you do either with the data in the data warehouse or the data in the data lake repository? >> So we are constantly enriching our data lake because that needs to be updated all the time, but at the same time, we want to connect business with our metrics; they essentially derive all of that data which is sitting in the data lake to help optimize a problem. For example, we are working on sales optimization. We are working on operations optimization, demand planning, supply planning, in addition to customer insights. We are also working on other strategic project. For example, instead of just recommending or predicting LTV return, what we are doing is, we are trying to be more descriptive in our analytics in which it takes an advisory role, and looks over all the marketing spend, not just predict the high LTV customers, but actually allocates budget for different marketing spend across different channels for omni comment. For example, TV display ads, you know, all of that, so that's also happening as we speak, as we enrich our data lake and essentially generate those reports. Now, then we also need to circle back with the business folks or decision makers in order to really convince them to use that. So that's why we created these cross-functional teams, aligned to a business goal contextually aware teams, which know their roles and responsibilities, but at the same time, which can collaborate effectively and produce a result which drives the bottom line. >> What kind of customer insights were you looking for? Do they deliver family products, diapers to the home and that sort of thing? What sort of customer insights were you looking for and how is it working? >> Basically, Honest, in all our target customers, we need to better understand what their needs are. So customer insights, for example, the demographics of the customers. In addition we also wanted to see what are the things, what are the patterns which are common in customer, so that we can recommend products which are being bought by one segment of customer versus another. Those common properties, it could be mothers, who have recently had children, but who live in this neighborhood and have this kind of income level. So how do we ensure that we actually predict their demands before it actually happens. So we need to understand their habits, we need to understand the context behind it, if we are making some search, how many pages they use for this kind of product or that kind of a product, and similarly other things which enhance the understanding of the customers, make them into different buckets of segments, and then using those segments to target, because we already have data about LTV and turn as predictive models revealing if a customer is going to turn for whatever reason, we know by doing a similar campaign for other customers this has successfully given us more subscriptions or helped us to reduce a turn, that is how we target them and optimize our campaigns or our promotions for that. >> David: Sure. >> We're also looking for the overall lifestyle of the people who are passionate about Honest brands or brands that exhibit similar values, for example, eco-friendly, safe, and trusted products. >> Right, so we have just a couple of minutes to go before we get to the break. This is great stuff and George, I'll come back to you for a final question in just a moment, but in 30 seconds or so, tell us why you selected Databricks. You probably looked at other options, right? >> Shafaq: Absolutely. >> Can you give us a quick, why you made the decision? >> Absolutely, when we came in at Honest, all they had was a bunch of my secret developers, and very limited big data knowledge. So, now that they need a jump start in order to really get to that level in a very small time. How that's even achievable? We don't even have dedicated data-ops on our team. So basically, Databricks helped to bridge that gap by allowing us to get the infrastructure efficiency we needed by spinning up in hassle free manner. They also had this notebooks feature where we can scale the code and scale the team by actually reusing the boiler plate code, and similarly, different teams have different expertise. For example data science teams like Biton and data engineers like Scallop. So now those Scallop people write function which can be called by teams in data science in the same notebook, essentially giving them the ability to collaborate effectively. And then we also needed some tool to give more traction and visualization for data scientists well as data engineers. Databricks has a big visualization built in which helps to understand the causation corelation at least corelation right of the band, without even importing the data into our, or some other external tool, and making those charts. So there are a bunch of advantages around which we wanted. And then it has a platform API, like DBFS, like a disability files, it's similar to our vestry, which are cool APIs which again provide us the jump start which we needed, in so less amount of time, we actually made those, not only data warehouse, but also data driven parts. >> It sounds like Databricks has delivered. >> Shafaq: Oh yeah. >> Awesome. All right, George, just enough time for one more question if you want to throw on in. >> This one is kind of technical, but not on the technology side so much as, how do you guys measure attribution between channels and omni-channel marketing? >> That's a very good question. We have this project called Marketing Attribution, and essentially, the scope of that project is, we want to give the right ways to the right clicks of the customer as a journey of subscription or conversion. So, we have a model which basically use a bunch of techniques, including weighted and linear regression to basically come up with some kind of a weighted way of allowing those weights to be distributed among different channels. And then we also, the first problem to solve is that we needed to instrument logging so that we get those clicks and searches, all of that, into our data lake. That was done before hand, before starting the MT project, because we have a bunch of touch points. Customer could be doing search, he could be calling our sales rep, he could be tracking his order online, or he could be just leaving his cart in a state which is not fulfilled. And then, now we are trying to get it offline also, on top of that, and we are working on to get so that we know what a customer is doing in store and we have seamless experience using this MTA as a next version of it to give them a seamless experience in brick and mortar store or online. >> Great, that's great stuff, Shafaq. I wish we had more time to go. We'll talk to you more after we stop rolling. Thank you for being so honest, and we appreciate you being on the show. >> Thank you, I really appreciate it. >> Thank you so much. >> George: Shafaq, that was Great. >> All right, to all of you, thank you so much. We're going to be back in a few moments with the daily wrap up. You don't want to miss that. Thank you for joining us on theCUBE for Spark Summit 2017.

>> Live from Las Vegas it's The Cube covering NAB 2017. Brought to you by HGST. >> Welcome back to The Cube. We are live at NAB 2017. I'm Lisa Martin. Very, very excited, kind of geeking out right now to be joined by our next two guests. Sam Blackman, the co-founder and CEO of AWS Elemental, welcome to The Cube. >> Sam: Thank you so much. >> And we have NASA astronaut, Tracy Caldwell Dyson. Both of you, welcome to The Cube. >> Thank you. >> Today has been a very historic day for technology and space. This was the first ever live 4k video stream that happened between you on Earth, Sam, and Doctor Peggy Whitson, aboard the International Space Station. >> Sam: Yes. >> Wow. Tell us about that. >> It was truly amazing to be part of history and the amount of technology that came into play to make this possible. You know, sitting in the conference room in NAB in the middle of Las Vegas, seeing astronauts 250 miles ahead, going around the Earth, 17,000 miles an hour and a seamless, beautiful 4k picture. It was mind blowing. Hard to believe it's happened still. >> I can't even imagine. I'm getting goosebumps for you. Tell us some of the things that Dr. Whitson shared about her experiences. What was the interaction like? >> Well, Commander Whitson and Colonel Fisher was also in the interview and that guy is hilarious, by the way. >> Yeah, he is. >> He is hilarious. They talked about how advanced imaging technology really helps NASA perform experiments and bring experiments that are happening on the space station down to Earth for researchers to use that data and discover how the world works inside the universe. Some of the really interesting examples revolved around some experiments they showed. With thin film technology they had a very small, metallic structure that they could pull water out of and then corral that water, convert it into a spherical shape and in the 4k resolution, you could just see every element of that thin film in a way that looked like it was right next to us. I mean, it was transformative. >> Tracy: Yeah. >> I bet it was. Well, speaking of transformative, this was, I mentioned, a really historic event for a number of reasons. Obviously, for those of us on the ground, for AWS Elemental. But, Tracy, from your perspective, you've been in space for 188... I had it here somewhere, hours. >> Yeah, days. >> You've been on STS118, you've been on the Soyuz to the station on expeditions 23 and 24. What does this capability now mean in the life of an astronaut? >> I think what it does is it helps us bring the experience to everybody here on Earth. It is so hard to capture what we are not just seeing, but experiencing. The richness, the detail, the vividness of the colors and how they're changing are all a part of looking at our beautiful planet. And just from that alone, being able to bring that to the American people, the world, really, is, I think to me a great relief. Because it grieves me to think about how in the world I would describe this beautiful, magnificent view to everybody back home. >> I can imagine. You've done extra-vehicular space walks. >> Tracy: Yes. >> And I can imagine it's indescribable. >> It is. And from the fact you're looking at our planet from 250 miles above, you see the curvature of the Earth, you see it moving at a super high speed, you don't feel the wind in your face, but there's no doubt you're traveling very fast. Just the fact that you are out in the vacuum of space. If you could bring parts of that experience to people back home ... I'm excited to think about how that would transform just the way people think, not to mention the way that they act towards our planet. >> I also think inspiration ... We were talking before we went on that you were about 14 when the Challenger incident happened, we all kind of remember exactly where we were, and that really, a teacher being in space was so inspirational to you. Can you imagine shifting the conversation and what this technology is able to do inspiring the next generation of people that want to be the next Tracy Caldwell Dyson? >> Well, I think what the technology does today, especially in imaging capabilities, is it provides so much more detail than I could even describe. That a young person today watching that, and our generation today is so visual, that they're going to pick up on things that I wouldn't even think to describe to them. And it's going to capture their imagination in ways that are astounding. Compared to I, who, just the sheer knowledge of knowing there was a teacher that was going into space, propelled me to work really hard. I can only imagine what this generation's going to be capable of because of the images that we're bringing to them. >> It's so exciting. Sam, this is really kind of the tip of the iceberg. From AWS Elemental's perspective, first of all, you just had a rebrand. But what does this mean for the future of the video ecosystem? >> Well, I think it really shows you how the technology components came come together to create unbelievable pictures no matter where you are on the planet or in space. We had a live 4k encoder on the space station itself sending down signals to Johnson Space Center, then Johnson Space Center sending redundant links to Las Vegas, here, and the convention center. And then processing the video, the interview with Tracy, here in the space center-- or, here in NAB and then using the cloud to distribute that all over the world. So these 4k images, which take a significant amount of bandwidth, can be created in space, delivered here, produced and delivered anywhere in the world using the power of the cloud and advanced networking technology. And that's pretty amazing, when you think about it. >> Lisa: It really is. I don't think the three of us are smiling big enough. >> I know. It hurts! >> There's so much relief in this face. >> Lisa: I can imagine >> I bet. >> I absolutely can imagine, I think. One of the cool things about-- This is our first time at NAB with The Cube, but we're here: Media, entertainment, Hollywood. What this shows is this transcendence of technology to space. And there's so much interest in space. In fact, Tracy, you were an advisor to Jessica Chastain on "The Martian," which is probably pretty exciting. >> Oh, absolutely. It is. >> But just the transcendence of that and how this technology can be used to power things that everybody can understand, movies and things. But also the future of space exploration, which I can imagine, right now in the era of the space shuttle being retired now, depending on Soyuz rockets to get to the space station as the next vehicle is delivered, this must be quite inspirational for you as an astronaut, as not only is the next vehicle in development, but also, the exploration of Mars. In fact, you were just last month with President Trump. >> Tracy: Yes. >> As they signed a bill. What are your thoughts about that and how do you see imaging technology being an instrumental part of Mars exploration? >> In so many ways, but at the top is the momentum. Like you said, with Hollywood has captured space in some real endearing ways. And the images from NASA, from the human space flight program to Hubble to deep space, it is propelling ... it's momentum. And I think we need that momentum, especially with our young folks because they're going to be the ones, let's face it, who are going to be in the best condition to be on the planet of Mars. So, if we can continue to feed them the images as lifelike as we can, so that they feel they're there, I think we are heading in the right direction to actually being there. >> Wow, fantastic! Congratulations to both of you. Thank you both so much for joining us on The Cube. We can't wait to see what's next. >> Sam: Thank you so much. >> Tracy: Thank you. Thank you. >> Well, for Tracy and Sam, I'm Lisa Martin. You've been watching The Cube live from NAB 2017. Stick around, we'll be right back. (funky music)