(upbeat music) >> Announcer: theCUBE presents UiPath Forward5. Brought to you by UiPath. >> Hi everybody, we're back in Las Vegas. We're live with Cube's coverage of Forward 5 2022. Dave Vellante with Dave Nicholson Ted Kumer this year is the Executive Vice President, product and engineering at UiPath. Brought on to do a lot of the integration and bring on new capabilities for the platform and we've seen that over the last several years. And he's joined by Dr. Edward Challis, who's the co-founder of the recent acquisition that UiPath made, company called Re:infer. We're going to learn about those guys. Gents, welcome to theCUBE. Ted, good to see you again. Ed, welcome. >> Good to be here. >> First time. >> Thank you. >> Yeah, great to be here with you. >> Yeah, so we have seen, as I said, this platform expanding. I think you used the term business automation platform. It's kind of a new term you guys introduced at the conference. Where'd that come from? What is that? What are the characteristics that are salient to the platform? >> Well, I see the, the evolution of our platform in three chapters. You understand the first chapter, we call that the RPA chapter. And that's where we saw the power of UI automation applied to the old problems of how do I integrate apps? How do I automate processes? That was chapter one. You know, chapter two gets us to Forward3 in 2019, and the definition of this end-to-end automation platform you know, with the capabilities from discover to measure, and building out that core platform. And as the platform's progressed, what we've seen happen with our customers is the use of it goes from being very heavy in automating the repetitive and routine to being more balanced, to now where they're implementing new brought business process, new capability for their organization. So that's where the name, Business Automation Platform, came from. Reflecting now that it's got this central role, as a strategic tool, sitting between their application landscape, their processes, their people, helping that move forward at the rate that it needs to. >> And process mining and task mining, that was sort of the enabler of chapter two, is that right? >> Well, I'd say chapter two was, you know, first the robots got bigger in terms of what they could cover and do. API integration, long running workflows, AI and ML skills integrated document processing, citizen development in addition to professional development, engaging end users with things like user interfaces built with UiPath apps. And then the discovery. >> So, more robustness of the? Yeah, okay. >> Yeah. Just an expansion of the whole surface area which opened up a lot of things for our customers to do. That went much broader than where core RPA started. And so, and the other thing about this progression to the business automation platform is, you know, we see customers now talking more about outcomes. Early on they talk a lot about hours saved and that's great, but then what about the business outcomes it's enabling? The transformations in their business. And the other thing we're doing in the platform is thinking about, well, where can we land with solutions capabilities that more directly land on business, measurable business outcomes? And so we had started, for example, offering an email automation solution, big business problem for a lot of our customers last year. And we'd started encountering this company Re:infer as we were working with customers. And then, and we encountered Re:infer being used with our platform together. And we saw we can accelerate this. And what that is giving us now is a solution now that aligns with a very defined business outcome. And this way, you know, we can help you process communications and do it efficiently and provide better service for your customers. And that's beginning of another important progression for us in our platform. >> So that's a nice segue, Ed. Tell about Re:infer. Why did you start the company? >> Right, yeah, so my whole career has been in machine learning and AI and I finished my PhD around 2013, it was a very exciting time in AI. And me and my co-founders come from UCL, this university in London, and Deep Mind, this company which Google acquired a few years later, came from our same university. So very exciting time amongst the people that really knew about machine learning and AI. And everyone was thinking, you know, how do we, these are just really big breakthroughs. And you could just see there was going to be a whole bunch of subsequent breakthroughs and we thought NLP would be the next breakthrough. So we were really focused on machine reading problems. And, but we also knew as people that had like built machine learning production systems. 'Cause I'd also worked in industry that built that journey from having a hypothesis that machine learning can solve a problem to getting machine learning into production. That journey is of painful, painful journey and that, you know, you can see that you've got these advances, but getting into broad is just way too hard. >> So where do you fit in the platform? >> Yeah, so I think when you look in the enterprise just so many processes start with a message start with a no, start with a case ticket or, you know, some other kind of request from a colleague or a customer. And so it's super exciting to be able to, you know, take automation one step higher in that process chain. So, you could automatically read that request, interpret it, get all the structured data you need to drive that process forward. So it's about bringing automation into these human channels. >> So I want to give the audience a sense here. So we do a lot of events at the Venetian Conference Center, and it's usually very booth heavy, you know, brands and big giant booths. And here the booths are all very small. They're like kiosks, and they're all pretty much the same size. So it's not like one vendor trying to compete with the other. And there are all these elements, you know I feel like there's clouds and there's, you know, of course orange is the color here. And one of the spots is, it has this really kind of cool sitting area around customer stories. And I was in there last night reading about Deutsche Bank. Deutsche Bank was also up on stage. Deutsche Bank, you guys were talking about a Re:infer. So share with our audience what Deutsche Bank are doing with UiPath and Re:infer. >> Yeah, so I mean, you know, before we automate something, we often like to do what we call communications mining. Which is really understanding what all of these messages are about that might be hitting a part of the business. And at Deutsche Bank and in many, you know, like many large financial services businesses, huge volumes of messages coming in from the clients. We analyze those, interpret the high volume query types and then it's about automating against those to free up capacity. Which ultimately means you can provide faster, higher quality service because you've got more time to do it. And you're not dealing with all of those mundane tasks. So it's that whole journey of mining to automation of the coms that come into the corporate bank. >> So how do I invoke the service? So is it mother module or what's the customer onboarding experience like? >> So, I think the first thing that we do is we generate some understanding of actually the communications data they want to observe, right? And we call it mining, but you know, what we're trying to understand is like what are these communications about? What's the intent? What are they trying to accomplish? Tone can be interesting, like what's the sentiment of this customer? And once you understand that, you essentially then understand categories of conversations you're having and then you apply automations to that. And so then essentially those individual automations can be pointed to sets of emails for them to automate the processing of. And so what we've seen is customers go from things they're handling a hundred percent manual to now 95% of them are handled basically with completely automated processing. The other thing I think is super interesting here and why communications mining and automation are so powerful together is communications about your business can be very, very dynamic. So like, new conversations can emerge, something happens right in your business, you have an outage, whatever, and the automation platform, being a very rapid development platform, can help you adapt quickly to that in an automated way. Which is another reason why this is such a powerful thing to put the two things together. >> So, you can build that event into the automation very quickly you're saying? >> Speaker 1: Yeah. >> Speaker 2: That's totally right. >> Cool. >> So Ed, on the subject of natural language processing and machine learning versus machine teaching. If I text my wife and ask her would you like to go to an Italian restaurant tonight? And she replies, fine. Okay, how smart is your machine? And, of course, context usually literally denotes things within the text, and a short response like that's very difficult to do this. But how do you go through this process? Let's say you're implementing this for a given customer. And we were just talking about, you know, the specific customer requirements that they might have. What does that process look like? Do you have an auditor that goes through? And I mean do you get like 20% accuracy, and then you do a pass, and now you're at 80% accuracy, and you do a pass? What does that look? >> Yeah, so I mean, you know when I was talking about the pain of getting a machine learning model into production one of the principle drivers of that is this process of training the machine learning model. And so what we use is a technique called active learning which is effectively where the AI and ML model queries the user to say, teach me about this data point, teach me about this sentence. And that's a dynamic iterative process. And by doing it in that way you make that training process much, much faster. But critically that means that the user has, when you train the model the user defines how you want to encode that interpretation. So when you were training it you would say fine from my wife is not good, right? >> Sure, so it might be fine, do you have a better suggestion? >> Yeah, but that's actually a very serious point because one of the things we do is track the quality of service. Our customers use us to attract the quality of service they deliver to their clients. And in many industries people don't use flowery language, like, thank you so much, or you know, I'm upset with you, you know. What they might say is fine, and you know, the person that manages that client, that is not good, right? Or they might say I'd like to remind you that we've been late the last three times, you know. >> This is urgent. >> Yeah, you know, so it's important that the client, our client, the user of Re:infer, can encode what their notions of good and bad are. >> Sorry, quick follow up on that. Differences between British English and American English. In the U.K., if you're thinking about becoming an elected politician, you stand for office, right? Here in the U.S., you run for office. That's just the beginning of the vagaries and differences. >> Yeah, well, I've now got a lot more American colleagues and I realize my English phrasing often goes amiss. So I'm really aware of the problem. We have customers that have contact centers, some of them are in the U.K., some of them are in America, and they see big differences in the way that the customers get treated based on where the customer is based. So we've actually done analysis in Re:infer to look at how agents and customers interact and how you should route customers to the contact centers to be culturally matched. Because sometimes there can be a little bit of friction just for that cultural mapping. >> Ted, what's the what's the general philosophy when you make an acquisition like this and you bring in new features? Do you just wake up one day and all of a sudden there's this new capability? Is it a separate sort of for pay module? Does it depend? >> I think it depends. You know, in this case we were really led here by customers. We saw a very high value opportunity and the beginnings of a strategy and really being able to mine all forms of communication and drive automated processing of all forms of communication. And in this case we found a fantastic team and a fantastic piece of software that we can move very quickly to get in the hands of our customer's via UiPath. We're in private preview now, we're going to be GA in the cloud right after the first of the year and it's going to continue forward from there. But it's definitely not one size fits all. Every single one of 'em is different and it's important to approach 'em that way. >> Right, right. So some announcements, StudioWeb was one that I think you could. So I think it came out today. Can't remember what was today. I think we talked about it yesterday on the keynotes anyway. Why is that important? What is it all about? >> Well we talked, you know, at a very top level. I think every development platform thinks about two things for developers. They think, how do I make it more expressive so you can do other things, richer scenarios. And how do I make it simpler? 'Cause fast is always better, and lower learning curves is always better, and those sorts of things. So, Re:infer's a great example of look the runtime is becoming more and more expressive and now you can buy in communications state as part of your automation, which is super cool. And then, you know StudioWeb is about kind of that second point and Studios and Studio X are already low code visual, but they're desktop. And part of our strategy here is to elevate all of that experience into the web. Now we didn't elevate all of studio there, it's a subset. It is API integration and web based application automation, Which is a great foundation for a lot of apps. It's a complete reimagining of the studio user interface and most importantly it's our first cross-platform developer strategy. And so that's been another piece of our strategy, is to say to the customers we want to be everywhere you need us to be. We did cross-platform deployment with the automation suite. We got cross-platform robots with linear robots, serverless robots, Mac support and now we got a cross-platform devs story. So we're starting out with a subset of capabilities maybe oriented toward what you would associate with citizen scenarios. But you're going to see more roadmap, bringing more and more of that. But it's pretty exciting for us. We've been working on this thing for a couple years now and like this is a huge milestone for the team to get to this, this point. >> I think my first conversation on theCUBE with a customer was six years ago maybe at one of the earlier Forwards, I think Forward2. And the pattern that I saw was basically people taking existing processes and making them better, you know taking the mundane away. I remember asking customers, yeah, aren't you kind of paving the cow path? Aren't there sort of new things that you can do, new process? And they're like, yeah, that's sort of the next wave. So what are you seeing in terms of automating existing processes versus new processes? I would see Re:infer is going to open up a whole new vector of new processes. How should we think about that? >> Yeah, I think, you know, I mean in some ways RPA has this reputation because there's so much value that's been provided in the automating of the repetitive and routine. But I'd say in my whole time, I've been at the company now for two and a half years, I've seen lots of new novel stuff stood up. I mean just in Covid we saw the platform being used in PPP loan processing. We saw it in new clinical workflows for COVID testing. We see it and we've just seen more and more progression and it's been exciting that the conference, to see customers now talking about things they built with UiPath apps. So app experiences they've been delivering, you know. I talked about one in healthcare yesterday and basically how they've improved their patient intake processing and that sort of thing. And I think this is just the front end. I truly believe that we are seeing the convergence happen and it's happening already of categories we've talked about separately, iPass, BPM, low-code, RPA. It's happening and it's good for customers 'cause they want one thing to cover more stuff and you know, I think it just creates more opportunity for developers to do more things. >> Your background at Microsoft probably well prepared you for a company that you know, was born on-prem and then went all in on the cloud and had, you know, multiple code bases to deal with. UiPath has gone through a similar transformation and we talked to Daniel last night about this and you're now cloud first. So how is that going just in terms of managing multiple code bases? >> Well it's actually not multiple Code bases. >> Oh, it's the same one, Right, deployment models I should say. >> Is the first thing, Yeah, the deployment models. Another thing we did along the way was basically replatform at an infrastructure level. So we now can deploy into a Kubernetes Docker world, what you'd call the cloud native platform. And that allows us to have much more of a shared infrastructure layer as we look to deliver to the automation cloud. The same workload to the automation cloud that we now deliver in the automation suite for deployment on-prem or deploying a public cloud for a customer to manage. Interesting and enough, that's how Re:infer was built, which is it was built also in the cloud native platform. So it's going to be pretty easy. Well, pretty easy, there's some work to do, but it's going to be pretty easy for us to then bring that into the platform 'cause they're already working on that same platform and provide those same services both on premises and in the cloud without having your developers have to think too much about both. >> Okay, I got to ask you, so I could wrap my stack in a container and put it into AWS or Azure or Google and it'll run great. As well, I could tap some of the underlying primitives of those respective clouds, which are different and I could run them just fine. Or/and I could create an abstraction layer that could hide those underlying primitives and then take the best of each and create an automation cloud, my own cloud. Does that resonate? Is that what you're doing architecturally? Is that a roadmap, or? >> Certainly going forward, you know, in the automation cloud. The automation cloud, we announced a great partnership or a continued partnership with Microsoft. And just Azure and our platform. We obviously take advantage of anything we can to make that great and native capabilities. And I think you're going to see in the Automation Suite us doing more and more to be in a deployment model on Azure, be more and more optimized to using those infrastructure services. So if you deploy automation suite on-prem we'll use our embedded distro then when we deploy it say on Azure, we'll use some of their higher level managed services instead of our embedded distro. And that will just give customers a better optimized experience. >> Interesting to see how that'll develop. Last question is, you know what should we expect going forward? Can you show us a little leg on on the future? >> Well, we've talked about a number of directions. This idea of semantic automation is a place where you know, you're going to, I think, continue to see things, shoots, green shoots, come up in our platform. And you know, it's somewhat of an abstract idea but the idea that the platform is just going to become semantically smarter. You know, I had to serve Re:infer as a way, we're semantically smarter now about communications data and forms of communications data. We're getting semantically smarter about documents, screens you know, so developers aren't dealing with, like, this low level stuff. They can focus on business problem and get out of having to deal with all this lower level mechanism. That is one of many areas I'm excited about, but I think that's an area you're going to see a lot from us in the next coming years. >> All right guys, hey, thanks so much for coming to theCUBE. Really appreciate you taking us through this. Awesome >> Yeah Always a pleasure. >> Platform extension. Ed. All right, keep it right there, everybody. Dave Nicholson, I will be back right after this short break from UiPath Forward5, Las Vegas. (upbeat music)

[Music] welcome back to aws storage day 2022 i'm dave vellante and we're pleased to have back on thecube edname the gm of aws file storage ed how you doing good to see you i'm good dave good good to see you as well you know we've been tracking aws storage for a lot of years 16 years actually we we've seen the evolution of services of course we started with s3 and object and saw that expand the block and file and and now the pace is actually accelerating and we're seeing aws make more moves again today and block an object but what about file uh it's one format in the world and the day wouldn't really be complete without talking about file storage so what are you seeing from customers in terms of let's start with data growth how are they dealing with the challenges what are those challenges if you could address you know specifically some of the issues that they're having that would be great and then later we're going to get into the role that cloud file storage plays take it away well dave i'm definitely increasingly hearing customers talk about the challenges in managing ever-growing data sets and they're especially challenged in doing that on-premises when we look at the data that's stored on premises zettabytes of data the fastest growing data sets consist of unstructured data that are stored as files and many cups have tens of petabytes or hundreds of petabytes or even exabytes of file data and this data is typically growing 20 30 percent a year and in reality on-premises models really designed to handle this amount of data in this type of growth and i'm not just talking about keeping up with hardware purchases and hardware floor space but a big part of the challenge is labor and talent to keep up with the growth they're seeing companies managing storage on-prem they really need an unprecedented number of skilled resources to manage the storage and these skill sets are in really high demand and they're in short supply and then another big part of the challenge that customers tell me all the time is that that operating at scale dealing with these ever-growing data sets at scale is really hard and it's not just hard in terms of the the people you need and the skill sets that you need but operating at scale presents net new challenges so for example it becomes increasingly hard to know what data you have and what storage media your data stored on when you have a massive amount of data that's spanning hundreds of thousands or uh thousands of applications and users and it's growing super fast each year and at scale you start seeing edge technical issues get triggered more commonly impacting your availability or your resiliency or your security and you start seeing processes that used to work when you were a much smaller scale no longer work it's just scale is hard it's really hard and then finally companies are wanting to do more with their fast growing data sets to get insights from it and they look at the machine learning and the analytics and the processing services and the compute power that they have at their fingertips on the cloud and having that data be in silos on-prem can really limit how they get the most out of their data you know i've been covering glad you brought up the skills gap i've been covering that quite extensively with my colleagues at etr you know our survey partner so that's a really important topic and we're seeing it across the board i mean really acute in cyber security but for sure just generally in i.t and frankly ceos they don't want to invest in training people to manage storage i mean it wasn't that long ago that managing loans was a was a talent and that's of course nobody does that anymore but they'd executives would much rather apply skills to get value from data so my specific question is what can be done what is aws doing to address this problem well with the growth of data that that we're seeing it it's just it's really hard for a lot of it teams to keep up with just the infrastructure management part that's needed so things like deploying capacity and provisioning resources and patching and conducting compliance reviews and that stuff is just table stakes the asks on these teams to your point are growing to be much bigger than than those pieces so we're really seeing fast uptake of our amazon fsx service because it's such an easy path for helping customers with these scaling challenges fsx enables customers to launch and to run and to scale feature rich and highly performant network attached file systems on aws and it provides fully managed file storage which means that we handle all of the infrastructure so all of that provisioning and that patching and ensuring high availability and customers simply make api calls to do things like scale up their storage or change their performance level at any point or change a backup policy and a big part of why fsx has been so feeling able to customers is it really enables them to to choose the file system technology that powers their storage so we provide four of the most popular file system technologies we provide windows file server netapp ontap open zfs and luster so that storage and application admins can use what they're familiar with so they essentially get the full capabilities and even the management clis that they're used to and that they've built workflows and applications around on-premises but they get along with that of course the benefits of fully managed elastic cloud storage that can be spin up and spun spin down and scaled on demand and performance changed on demand etc and what storage and application admins are seeing is that fsx not only helps them keep up with their scale and growth but it gives them the bandwidth to do more of what they want to do supporting strategic decision making helping their end customers figure out how they can get more value from their data identifying opportunities to reduce cost and what we realize is that for for a number of storage and application admins the cloud is is a different environment from what they're used to and we're making it a priority to help educate and train folks on cloud storage earlier today we talked about aws storage digital badges and we announced a dedicated file badge that helps storage admins and professionals to learn and demonstrate their aws skills in our aws storage badges you can think of them as credentials that represent cloud computing learning that customers can add to their repertoire add to their resume as they're embarking on this cloud journey and we'll be talking more in depth on this later today especially around the file badge which i'm very excited about so a couple things there that i wanted to comment on i mean i was there for the netapp you know your announcement we've covered that quite extensively this is just shows that it's not a zero-sum game necessarily right it's a win-win-win for customers you've got your you know specific aws services you've got partner services you know customers want want choice and then the managed service model you know to me is a no-brainer for most customers we learned this in the hadoop years i mean it just got so complicated then you saw what happened with the managed services around you know data lakes and lake houses it's just really simplified things for customers i mean there's still some customers that want to do it yourself but a managed service for the file storage sounds like a really easy decision especially for those it teams that are overburdened as we were talking about before and i also like you know the education component is nice touch too you get the badge thing so that's kind of cool so i'm hearing that if the fully managed file storage service is a catalyst for cloud adoption so the question is which workloads should people choose to move into the cloud where's the low friction low risk sweet spot ed well that's one of the first questions that customers ask when they're about to embark on their cloud journey and i wish i could give a simple or a single answer but the answer is really it varies and it varies per customer and i'll give you an example for some customers the cloud journey begins with what we call extending on-premises workloads into the cloud so an example of that is compute bursting workloads where customers have data on premises and they have some compute on premises but they want to burst their processing of that data to the cloud because they really want to take advantage of the massive amount of compute that they get on aws and that's common with workloads like visual effects ringer chip design simulation genomics analysis and so that's an example of extending to the cloud really leveraging the cloud first for your workloads another example is disaster recovery and that's a really common example customers will use a cloud for their secondary or their failover site rather than maintaining their their second on-prem location and so that's a lot of customers start with some of those workloads by extending to the cloud and then there's there's a lot of other customers where they've made the decision to migrate most or all of their workloads and they're not they're skipping the whole extending step they aren't starting there they're instead focused on going all in as fast as possible because they really want to get to the full benefits of the cloud as fast as possible and for them the migration journey is really it's a matter of sequencing sequencing which specific workloads to move and when and what's interesting is we're increasingly seeing customers prioritizing their most important and their most mission-critical applications ahead of their other workloads in terms of timing and they're they're doing that to get their workloads to benefit from the added resilience they get from running on the cloud so really it really does uh depend dave yeah thank you i mean that's pretty pretty good description of the options there and i i just come something you know bursting obviously i love those examples you gave around genomics chip design visual effects rendering the dr piece is again very common sort of cloud you know historical you know sweet spots for cloud but then the point about mission critical is interesting because i hear a lot of customers especially with the digital transformation push wanting to change their operating model i mean on the one hand not changing things put it in the cloud the lift and shift you have to change things low friction but then once they get there they're like wow we can do a lot more with the cloud so that was really helpful those those examples now last year at storage day you released a new file service and then you followed that up at re-event with another file service introduction sometimes i can admit i get lost in the array of services so help us understand when a customer comes to aws with like an nfs or an smb workload how do you steer them to the right managed service you know the right horse for the right course yeah well i'll start by saying uh you know a big part of our focus has been in providing choice to customers and what customers tell us is that the spectrum of options that we provide to them really helps them in their cloud journey because there really isn't a one-size-fits-all file system for all workloads and so having these options actually really helps them to to be able to move pretty easily to the cloud um and so my answer to your question about uh where do we steer a customer when they have a file workload is um it really depends on what the customer is trying to do and uh in many cases where they're coming from so i'll walk you through a little bit of of of how we think about this with customers so for storage and application admins who are extending existing workloads to the cloud or migrating workloads to aws the easiest path generally is to move to an fsx file system that provides the same or really similar underlying file system engine that they use on premises so for example if you're running a netapp appliance on premises or a windows file server on premises choosing that option within fsx provides the least effort for a customer to lift their application and their data set and they'll get the full safe set of capabilities that they're used to they'll get the performance profiles that they're used to but of course they'll get all the benefits of the cloud that i was talking about earlier like spin up and spin down and fully managed and elastic capacity then we also provide open source file systems within the fsx family so if you're a customer and you're used to those or if you aren't really wedded to a particular file system technology these are really good options and they're built on top of aws's latest infrastructure innovations which really allows them to provide pretty significant price and performance benefits to customers so for example the file system file servers for these offerings are powered by aws's graviton family of processors and under the hood we use storage technology that's built on top of aws's scalable reliable datagram transport protocol which really optimizes for for speed on the cloud and so for those two open source file systems we have open zfs and that provides a really powerful highly performant nfs v3 and v4 and 4.1 and 4.2 file system built on a fast and resilient open source linux file system it has a pretty rich set of capabilities it has things like point-to-time snapshots and in-place data cloning and our customers are really using it because of these capabilities and because of its performance for a pretty broad set of enterprise i.t workloads and vertically focused workloads like within the financial services space and the healthcare life sciences space and then luster is a scale-out file system that's built on the world's most popular high-performance file system which is the luster open source file system and customers are using it for compute intensive workloads where they're throwing tons of compute at massive data sets and they need to drive tens or hundreds of gigabytes per second of throughput it's really popular for things like machine learning training and high performance computing big data analytics video rendering and transcoding so really those scale out compute intensive workloads and then we have a very different type of customer very different persona and this is the individual that we call the aws builder and these are folks who are running cloud native workloads they leverage a broad spectrum of aws's compute and analytic services and they have really no history of on-prem examples are data scientists who require a file share for training sets research scientists who are performing analysis on lab data developers who are building containerized or serverless workloads and cloud practitioners who need a simple solution for storing assets for their cloud workflows and and these these folks are building and running a wide range of data focused workloads and they've grown up using services like lambda and building containerized workloads so most of these individuals generally are not storage experts and they look for storage that just works s3 and consumer file shares uh like dropbox are their reference point for how cloud storage works and they're indifferent to or unaware of bio protocols like smb or nfs and performing typical nas administrative tasks is just not it's not a natural experience for them it's not something they they do and we built amazon efs to meet the needs of that group it's fully elastic it's fully serverless spreads data across multiple availability zones by default it scales infinitely it works very much like s3 so for example you get the same durability and availability profile of s3 you get intelligent tiering of colder data just like you do on s3 so that service just clicks with cloud native practitioners it's it's intuitive and it just works there's mind-boggling the number of use cases you just went through and this is where it's so you know it's you know a lot of times people roll their eyes oh here's amazon talking about you know customer obsession again but if you don't stay close to your customers there's no way you could have predicted when you're building these services how they were going to be put to use the only way you can understand it is watch what customers do with it i loved the conversation about graviton we've written about that a lot i mean nitro we've written about that how it's you've completely rethought virtualization the security components in there the hpc luster piece and and the efs for data scientists so really helpful there thank you i'm going to change uh topics a little bit because there's been this theme that you've been banging on at storage day putting data to work and i tell you it's a bit of a passion of mine ed because frankly customers have been frustrated with the return on data initiatives it's been historically complicated very time consuming and expensive to really get value from data and often the business lines end up frustrated so let's talk more about that concept and i understand you have an announcement that fits with this scene can you tell us more about that absolutely today we're announcing a new service called amazon file cache and it's a service on aws that accelerates and simplifies hybrid workflows and specifically amazon file cache provides a high speed cache on aws that makes it easier to process file data regardless of where the data is stored and amazon file cache serves as a temporary high performance storage location and it's for data that's stored in on-premise file servers or in file systems or object stores in aws and what it does is it enables enterprises to make these dispersed data sets available to file based applications on aws with a unified view and at high speeds so think of sub millisecond latencies and and tens or hundreds of gigabytes per second of throughput and so a really common use case it supports is if you have data stored on premises and you want to burst the processing workload to the cloud you can set up this cache on aws and it allows you to have the working set for your compute workload be cached near your aws compute so what you would do as a customer when you want to use this is you spin up this cache you link it to one or more on-prem nfs file servers and then you mount this cache to your compute instances on aws and when you do this all of your on-prem data will appear up automatically as folders and files on the cache and when your aws compute instances access a file for the first time the cache downloads the data that makes up that file in real time and that data then would reside on the cache as you work with it and when it's in the cache your application has access to that data at those sub millisecond latencies and at up to hundreds of gigabytes per second of throughput and all of this data movement is done automatically and in the background completely transparent to your application that's running on the compute instances and then when you're done with your workload with your data processing job you can export the changes and all the new data back to your on-premises file servers and then tear down the cache another common use case is if you have a compute intensive file-based application and you want to process a data set that's in one or more s3 buckets you can have this cache serve as a really high speed layer that your compute instances mount as a network file system you can also place this cache in front of a mix of on-prem file servers and s3 buckets and even fsx file systems that are on aws all of the data from these locations will appear within a single name space that clients that mount the cache have access to and those clients get all the performance benefits of the cache and also get a unified view of their data sets and and to your point about listening to customers and really paying attention to customers dave we built this service because customers asked us to a lot of customers asked us to actually it's a really helpful enable enabler for a pretty wide variety of cloud bursting workloads and hybrid workflows ranging from media rendering and transcoding to engineering design simulation to big data analytics and it really aligns with that theme of extend that we were talking about earlier you know i often joke that uh aws has the best people working on solving the speed of light problem so okay but so this idea of bursting as i said has been a great cloud use case from the early days and and bringing it to file storage is very sound and approach with file cache looks really practical um when is the service available how can i get started you know bursting to aws give us the details there yeah well stay tuned we we announced it today at storage day and it will be generally available later this year and once it becomes available you can create a cache via the the aws management console or through the sdks or the cli and then within minutes of creating the cache it'll be available to your linux instances and your instances will be able to access it using standard file system mount commands and the pricing model is going to be a pretty familiar one to cloud customers customers will only pay for the cash storage and the performance they need and they can spin a cash up and use it for the duration of their compute burst workload and then tear it down so i'm really excited that amazon file cache will make it easier for customers to leverage the agility and the performance and the cost efficiency of aws for processing data no matter where the data is stored yeah cool really interested to see how that gets adopted ed always great to catch up with you as i said the pace is mind-boggling it's accelerating in the cloud overall but storage specifically so by asking us can we take a little breather here can we just relax for a bit and chill out uh not as long as customers are asking us for more things so there's there's more to come for sure all right ed thanks again great to see you i really appreciate your time thanks dave great catching up okay and thanks for watching our coverage of aws storage day 2022 keep it right there for more in-depth conversations on thecube your leader in enterprise and emerging tech coverage [Music] you

>>We're back in storage day at Amazon in Boston, on detente with the Cube. Ed name is here. He's the general manager of X ed. Welcome to the Cube. Good to say thanks for having me, Dave. Okay, So explain to me why you guys launched FSX for Windows File server. You know why now? >>Well, we did it because customers asked us to do it. What customers told us was that they were tired of all of the effort and overhead in managing windows, file systems and Windows file servers on their own, everything from routine maintenance, like patching to provisioning. They just didn't wanna have to do all of that heavy lifting. So they asked us for a simple solution. Fully manage solution on the cloud. There's a lot of windows data out there. A lot of data that's access from windows computers. Eight of us is the cloud that has the most windows workloads running on it. So it was a very natural ask for customers to ask us as they're moving their windows workloads onto eight of us to have a file system that's fully managed for them that could be accessed by those workloads. So it was It was actually very natural and, uh, unexpected. Ask from customers, >>you know, love. You may not know that, but it does kind of make sense. Is so much windows out there You're the cloud leader. So peanut butter and jelly. Um, how do you see customers using FSX for Windows? >>Yeah, What's really exciting is they're using it for a really broad spectrum of workloads eso everything from traditional user shares and home directories, Thio development environments to analytics, workloads, tau video, trance coating. So it's a very wide spectrum of workloads that they're on the service and we're continuing to see new new types of workloads every day, which is really exciting. >>So we're hearing stories. What exactly is new around FSX for Windows file service Specifically. >>Yeah, Well, we've launched a number of capabilities this year throughout the year s 01 of the significant ones that we launched was the ability for customers to use their self managed active directories on dhe join their FSX file systems to those. So we now have two options. Customers can use a fully managed AWS fully managed active directory or their own with FSX. We launched a number of capabilities around access from on premises. For example, customers can now access. Or when we launched it, we announced that they could now access their file systems over direct connect connections over VPN so they can access the Windows file systems from computers and from end users that are running on premises. So quite a few announcements this year Those are just two examples, and we're really excited about really a slew of announcements and feature features that we're launching now. And I can get into those if you like, give me some examples of your work. So one of the, uh, the most common questions we've had from customers is. Can we offer a native multi daisy capability, multi availabilities own capability? So a lot of customers are running enterprise grade workloads on FXX, and they want to move more and more of those workloads onto AWS, and they don't wanna have to, ah, manage the overhead of using something like a distributed file system or D F s replication between fsx file systems and different disease. So we're launching a fully managed, super simple, multi easy capability, and that's a deployment options that custom the customers will have in addition to what we already had, which was the single easy deployment options. >>Let me see some recurring themes when you talkto folks at Amazon announced service is it's the it's the same sort of mantra. Be able to reduce that heavy lifting, shift your focus to things that will add more value to your business. Take advantage of these other service is through these integrations that that we're doing. So I mean, it kind of feels like a no brainer, but I give you the last the last word. I mean, is it Why is it why should customers, you know, sell me on why I should move by dated to the cloud? >>Yeah. I mean, we we like to think of it as a no brainer because we are fully managing everything for the customer. Um, the the service is built on top of Windows server, so provides a fully compatible Windows file system, and we've managed that fully four customers, So you get complete compatibility with us and be complete compatibility with Auntie if s file system semantics and features. So it's a very simple move for customers to move their existing workloads onto the service and have it before we managed a couple of the other features that we're launching that I do want to mention our We're launching data D duplication we're launching. Ah, whole bunch of administrative capabilities, like user quotas were extending. Our administrative CIA lied to do things like a lot of customers to create shares programmatically so really a very exciting set of capabilities that we really think make this a ah no brainer for customers. >>Well, that's another recurring themes. You guys, you know, you dropped prices and look at the moors losses. Prices continue to drop. The differences them is on. You make it transparent on DDE. If I use a service is lower cost, my bill goes down and then, of course, I end up using more because this is an elastic world. So that's a good thing. But, Ed, thanks so much for coming on. The key. Thank you. Share is that any other thing is you guys only window specialists. It's just kind of ironic, you know, leader in windows. And, uh, >>well, it really comes from What are our customers are asking us for? So they see moving their windows. Workloads is the first step to the full modernization and being all in on the cloud. >>Great. We'll get exit. Thank you. All right. And thank you for watching everybody right back after this. Short break, Dave. A lot with the Cube.

>>Lai from Orlando, Florida. It's the cube covering Microsoft ignite brought to you by Cohesity. >>Good afternoon, cube viewers. We are here at Microsoft ignite at the orange County convention center. I'm your host, Rebecca Knight. Along with my cohost Stu Miniman. We're joined by Edward Thompson. He is the product manager at get hub. Thank you so much for coming on the queue. So the get hub acquisition closed this time last year, uh, for our viewers who are maybe unfamiliar with get hub, explain what get hub is and then also tell us a little bit how it's going since the, >>yeah, I'd be happy to. So yeah, get hub is like the home for software development. If you're a, if you're a software developer, uh, you know, get hub rehost, you know, most of the open source repositories in the world. Um, you know, just to give you some stats. So at this time, last year, about the time the acquisition happened, um, we announced ad get hub universe, which is our annual developer conference, uh, that we had 30 million developers on GitHub and a hundred million repositories. So that's, that's a huge number of developers. I haven't seen the latest numbers. We'll announce the newest, uh, at get hub university this year, which is coming up next week. Uh, but the last number I saw was 40 million developers. So that's a growth of, you know, 10 million developers in just a year. Unbelievable. And that, that also means the 25% of our developers on get hub have joined within the last year. So that's just absolutely incredible. Um, and so yeah, I get hope. Is, is, is that, is that place for development? >>Yeah, it's really interesting when I look at some acquisitions that Microsoft has made back in 2016, they spent $26 billion for LinkedIn, which is most people's resume. And if you look last year it was seven and a half billion dollars for my friends in the software world. Get hub is their resume. That's right. Oh, when you talk about how you do things online, so you've got an interesting perspective on this because you've worked for Microsoft and get hub a couple of times. So give us a little bit about, you know, the relationship when you joined Microsoft 10 years ago, you know, open source developers, developers, developers weren't exactly on everyone's lips. So it gives a little bit of viewpoint through the various incarnations. >>So as you said, I joined Microsoft about 10 years ago. I came in through a little acquisition. Uh, we were just a very small software company, but we were building enterprise cross platform developer tools and we were about five engineers. And when you're building for, you know, Mac OS, Linux, Sonos, all these different platforms you use with so many people with so few rather, so few developers, you really need to take as much off the shelf as possible. You can't build all that yourself, you know. So if, if you needed a logging library, we would just go and use some open source products. We're not going to spend our time working on that when we could be building customer value in step. So when Microsoft acquired that company, they looked at, you know, they did their due diligence, they looked at the source code and they saw all this open source and they, I mean it was almost a deal breaker. >>They really lost their mind. Um, they were not geared up to deal with open source, to use open source, certainly not to contribute to open source. Uh, and so that's the Microsoft that I first saw. And, and to get from there to here is, is incredible. You know, over time. Um, we worked closely with some open source tools. We worked closely with get hub at Microsoft and that was really one of the early sort of unions between Microsoft and get hub was starting to work together on, on some open source software. And so we kind of started to know each other. We started to understand each other's companies and each other's cultures. And we started to, I don't know, I dare say like each other. Like I still count some of those early get hub employees that I met, uh, as some of my closest friends. Uh, and so at some point, uh, they became such close friends that I went to go work with them and get hub and then of course the Microsoft acquisition and so on. But I really think that that, you know, the, the transformation in Microsoft between, uh, the 10 years ago, Microsoft that really didn't get open source and today is, is just incredible. >>Well, let me just sit in that, in that culture and maybe culture clash a little bit the first time around because Microsoft developers have their own culture and their own uniform and their own way of interacting with each other. The, the, the hours that they work, which is very different from Microsoft, which is a pretty middle-aged Volvo driving kind of organization. So how, how does that work and, and what is, what has it been like the second time around the Microsoft as a middle aged Volvo driver? I think you can, you can >>wear a hoodie in and drive a Volvo. Um, no, I think it's been, I think it's been really great. The interesting thing about Microsoft is that it's not, you know, with so many people, it's not just like a homogenous big company. Um, we do have, you know, the developer tools division is a little bit different than offices, a little bit different than windows. And so they all have their own sort of unique cultures and, and now get hub slots in as its own unique culture. And we can, you know, we can talk to each other and we can understand each other, but we don't necessarily have to be all the same, you know, we can get hub team does kind of work some, some of us do work kind of weird hours. And, and I think that somehow that that works, especially with, you know, new tools coming to, um, coming to the marketplace, uh, you know, chat applications, we can be a lot less synchronous. We can be a lot more online and leave a message for each other. You know, we get out, we use get hub issues and pull requests to collaborate on almost everything, whether it's legal, uh, or, you know, our, our PR department. And it's not just developers. So we're trying to take these, these tools and, and sort of apply them to allow us to have the culture that we want at get hub. And I think Microsoft's doing the same thing as well. >>So speaking of new tools and you're, you're speaking here at ignite, you're about to announce the new repository with lots of new capabilities, enabling users to deploy at to any cloud. So tell us a little bit about, about the, this new tool. >>Yeah, so, uh, we announced, we call it get hub actions. We announced it last year at, at get hub universe. Our, uh, again, our, our annual developer conference. And our goal with GitHub actions was to allow people to take, you know, we've got 100 million repositories on get hub. We wanted our users to, to take those repositories and automate common tasks. Let me, let me give you a concrete example. Um, a lot of times somebody will open an issue on a, on a good hub repository, you know, uh, Hey, this doesn't work. I've got a bug report, you know, and they'll fill out an issue. And often either they didn't understand things or, um, the issue resolved itself, you know, who knows. We call that, uh, an issue that goes stale. And so you can build a workflow around that repository that will look for these stale issues and it will, uh, you know, just close them automatically. >>That gets rid of the mental tacks for somebody who, for a, for a developer who owns this repository to allow this, you know, this workload to just do it automatically. And so that's an example of a, a get hub actions workflow. Um, some people, uh, don't like swearing in their repository and you know, so if somebody were to open a bug report, you know, they might be angry. And so you could actually have a get hub workflow that looks for certain words and then replies and says, Hey, that's, here's our code of conduct. That's not the way we roll here. And actually a lot of people find that that feedback coming from a robot, uh, is a lot easier to take than a feedback coming from a human cause. They might want to meet with a person, can't argue with a robot. Well, not successfully. >>I think I have argued with the chat bot in my day. But anyway, >>yeah. So that's what we did a year ago and we opened it up into the beta program and we really quickly got feedback that, that people liked it and people were doing some really innovative things. But the one thing that people really wanted to automate was their bills. They wanted it to be able to build their code and deploy it. And we were just not set up for that. We, we, we didn't build, get hub actions as that platform in 2018 so we kind of had to pause our beta program. You know, I, they, they, they say that no, uh, no good plan survives first contact with the customer. So we had to, we had to hit pause on that. Uh, and we retooled. Um, we, we just sort of, I don't know, iterated on it, I guess. Uh, and we basically built a new platform that supported all of that repository automation capability that we had planned for in the first place. But also allowed for continuous integration build and deployments. So, um, we brought Macko S we brought Linux and windows runners, uh, that we host, uh, in our cloud, um, that people can use to build their software and then deploy it. And again, yeah, we want to be absolutely a tool agnostic. So any, any operating system, any, uh, language and cloud agnostic, we want to let anybody deploy anywhere, whether it's to a public cloud or on premises. >>Yeah. Uh, so, and with this, the second year we've done our program at this show and we really feel it's gone through a transformation. You know, this is a multi decade in a windows office. Uh, the business applications, uh, you know, cloud seeped in, developers are all over the place here. The day two keynote was all about app dev. Um, I'd love to get a little compare and contrast as to, you know, what you see here at Microsoft ignite versus, and I guess what I would call a pure dev show next week. Get hub universe happening in San Francisco. >>It's true. Get up universe is pretty much a pure dev show. Um, we, we have fewer booths, we have smaller booths. Uh, but, uh, and, and honestly, we have fewer sort of, um, I don't know, enterprise sorta. It, it pro crowd is what we used to call them. Um, but we do of course have a lot of dev ops. So, you know, we get up university has a lot of developers, but, uh, we're seeing a lot of dev ops, so there's a lot of meeting in the middle because, you know, I started out my career as assistant man actually. So I remember just, you know, doing everything manually. Um, but that's not the way we do things anymore. We automate all of our, uh, automate, uh, deployments. We automate all of our builds. You know, I don't want to sit there and type something into a console cause I'm going to get it wrong. Um, you know, I've accidentally deleted config files on production servers and that's, that's no good. So I think that they're, uh, get up universe is very different. A to ignite, it's much smaller, it's more intimate, but at the same time, there's a lot of, uh, overlap, especially around dev ops. >>Yeah. Uh, Satya Nadella yesterday in the keynote talked about the citizen developer as a big push for Microsoft. He said 61% of job openings for developers are outside the tech sector. Um, w what do you see in that space? Uh, the different developer roles these days? >>Uh, I think it's, it's absolutely fascinating. When I, uh, when I started my career, you know, you were, you were a developer and you, and you wrote code probably at a development company. Um, but now like everybody is automating tools, everybody's adopting machine learning. Um, when I look around at some of my friends in finance, uh, it's not about, it's not about anything but tech anymore. That's th they're, they're putting technology into absolutely everything that they do to succeed. Uh, and I think that, I think that it's amazing. Um, uh, like I said earlier, uh, 25% of developers on get hub have joined within the last year. So it's clear that it's just exploding. Um, everybody is doing, uh, software now. Yeah. >>There's something for the citizen developer on get hub though. Or is it too high level? I think >>I don't think it's too high level. I think that, uh, I think that that's a great challenge that we need to really step up to. Yeah. So Edward, >>the other big themes we heard here is talking about trust. So, you know, we talked about how Microsoft is different today than it wasn't in past, but I'm curious what good hub seen because you know, in social media when the acquisition first happened, it was, wait, I love GoodHub hub, I love all those people, but Hey, get lab. Hey, some of these other things I'm, you know, I'm fleeing for the woods. And every time I've seen an open source company get bought by a public company, there's always that online backlash. What are you seeing? How has the community reacted over the last year? >>I understand that skepticism. Uh, you know, I would be skeptical of any, uh, sort of change really. I, you know, the, the whole notion of who moved my cheese. But I think that the only way that we can, we can counter that is just to prove ourselves. And I think that we have, I think that Microsoft has allowed get hub to operate independently. And I think that, you know, I think a lot of people expect it to all of a sudden everything to change. And I don't think everything did change. I think that, uh, get hub now has more resources than it used to to be able to tackle bigger and more challenging problems. I think that get hub, uh, now can hire more and, and, and deploy to more places. And so I really just think that we're just going to keep doing exactly what we've been doing just better. So I think it's great. >>So universe happening next week teed up a little bit for us. What are some of the most exciting things that you're looking forward to? What kinds of conversations that will you be having? Presentations? >>So the big one for me is, is actions. I've, I, I've been just completely heads down working on, on get hub actions. So I'm really excited to be able to put that out there and, and you know, finally give it to everybody. Cause you know, we've been in beta now. Uh, like I said, we've been in beta for a year, which sounds like a ridiculous amount of time. Uh, but you know, it, it did involve a lot of retooling and rethinking and, and iteration with our, our beta testers. Um, and so the biggest thing for me is, is talking to people about actions and showing what they can do with actions. I'm super excited about that, but we've got a lot of other interesting stuff. You know, we've done a lot in the last year since our last universe. We've done a lot in the security space. Um, we've done, uh, we've both built tools and we've acquired some. Um, and so we'll be talking about those, uh, get hood package registry, which goes along really well with get hub actions. Uh, I'm super excited about that too. But yeah, I mean my, my calendar is, is, is just booked. Um, it's great. So many people like want to want to sit down and talk that I'm, I'm super excited about it. >>Excellent. Well great note to end on Edgar Thompson. Thank you so much for coming on the queue. We appreciate it. Thank you. I'm Rebecca Knight. First two minutes, stay tuned for more of the cubes live coverage from Microsoft ignite.

>> Live from San Francisco. It's theCUBE covering DockerCon '18. Brought to you by Docker and it's ecosystem partners. >> Welcome back to theCUBE's coverage of DockerCon 2018. I'm Lisa Martin, in San Francisco, with John Troyer and we're excited to welcome to theCUBE for the first time, Ed Hsu, the V.P. of Product and Product Marketing at Mesosphere. Great to have you on, Ed. >> Thank you. Pleasure to be here. >> So, Mesosphere. Tell us about you guys, what do you do? Why are you at DockerCon? >> Yeah. So, Mesosphere is a hybrid cloud software platform. We basically enable you to very easily adopt all types of new cloud-native technologies like Docker, Kubernetes, Spark, all the things that you think about to build these world changing applications. We automate that for you to run on hybrid cloud infrastructures. >> Nice. So, maybe you could break it down a little bit more. I know people can sometimes get confused. Mesosphere the company, Mesosphere the project, DC/OS the product, and then Kubernetes, and we're here at DockerCon, so maybe untangle some of those things a little bit. >> Sure. Maybe I'll go in chronological order. So Apache Mesos was actually created way back, I think around 2010 as a project to figure out if you had to rebuild Google's proprietary architecture for hyper-scale computing, what might that look like? So that became this project called Apache Mesos. Later on, at companies like Twitter, Airbnb, it started being used to solve some real challenges around scale-ability and performance. Arguably, without Mesos as a technology, I don't think Twitter would probably exist today because Twitter used to crash a lot. You guys remember that. You got the fail whale picture and all that stuff. Apparently, Justin Bieber used to crash Twitter, right? And Mesos became part of the solution. Now, you fast forward a few years later, containerization really caught on, right? And then Docker became a game changer in terms of making sure people start using and adopting container technologies, really popularize containerization, and of course, Kubernetes later came along as a way to orchestrate the operations of these containers. Now, where Mesosphere fits in is our platform is actually below a container-orchestrator, right so, Kubernetes is actually the fifth container-orchestrator to run on Mesos. There's earlier ones like Netflix, I think Twitter themselves. There's different types of container orchestration tools, and Kubernetes became the most recent and frankly most popular container-orchestration tool, and Mesosphere enables customers to really get one turn-key installation and operations of that technology. >> You mentioned Netflix, and I'm thinking, it powers a lot of our lives. But thinking about IoT data-driven applications like that, how does Mesosphere help power IoT and those data-driven applications? >> So, any IoT application probably needs at least three major sets of capabilities. The first is, you have to ingest tons of data. If you're a connected car or a home appliance company, there's a lot of data coming in from all these internet-connected devices. You need a way to ingest all that data without losing any of it and making sure you can be responsible. You also want to be able to analyze that data. So tools like Spark and other things become very important. You also need to be able to host an application or service, and Kubernetes becoming the most popular way to serve these applications. The last and by far, I think, most important piece for hybrid-cloud or for, excuse me, for IoT use cases, is the concept of hybrid-cloud and edge computing. At Mesosphere, we have many connected car companies that are doing connected car or self-driving car projects are actually working with us. And the reason for this is, we provide consistency for running containers like with Kubernetes or data services like Spark and Kafka on a really elastic infrastructure that can be on a data center, on AWS, on Google, or beneath a cell tower or even a cruise ship. Those are all actual use cases. We provide a consistent operating model for operators to just install and run all of this stuff. >> Super nice. I love in 2018 we're past some of the press conversation around who's gonna win or there's only gonna be one way of doing one stack that's gonna win, and Kubernetes versus whatever, and that was a conversation a few years ago. What I love about 2018 is people are in production. And live and time-to-value are very quick and very powerful and very deep and enlightens big data apps. Huge footprint apps as well. So, can you talk a little bit about some of your customers and also, in terms of the hybrid cloud. Are we seeing, are people on Pram? Are you seeing a lot of multi-cloud uses? Do apps span on Pram and clouds? What are some of the use cases and patterns that you see? >> Yeah. So, I think, maybe I'll start with the one I find is most interesting which is Royal Caribbean. If I were to ask you what is the largest computing cluster in the world by geography, you probably wouldn't say Royal Caribbean. So I haven't been on a cruise in a while, but apparently... I remember back in the day when I was a child, when I went on a cruise, you get a daily print-out of today's activities, and if you wanna go upgrade to a meal plan or do a tour or scuba diving, you go line up somewhere, and then you register for it, and if there's enough inventory, you get to do it. And so Royal Caribbean is actually trying to move all of this into a mobile app experience where based on your preferences, based on your history, based on what's available, they'll push certain campaigns to get you to "John, you really gotta try this scuba diving because we've got excess inventory, and we know you have a history of wanting to do surfing excursion" and so forth. So what Royal Caribbean has done is create an infrastructure where they're doing Test and Dev on campaigns and things like that on AWS. They actually do a lot of analytics on Pram in their own data center, and then when a ship is out at sea, serving those mobile applications from on Pram cloud-computing environment. All of this on Mesosphere's DC/OS. And what this means is that the data for interacting with passengers and the campaigns that are available, the management of the inventory, all that data, when the ship is in dock, flies from a data center, through a satellite, through Kafka into the ship. When the ship goes out to sea, all the internet connection is used for, people Skyping with grandma and grandpa and all that stuff, so the ship can actually, from an edge computing standpoint, provide all the resources it needs for these personalized interaction commission. >> That's a big example, Royal Caribbean. It was a very interesting use case, and I know you mentioned Netflix, Verizon. I think I saw a Verizon customer video on your website. When you're talking with companies of either those sizes or Royal Caribbean that's been around for a long time versus a cloud-native like Netflix, what are some of the common data center modernization concerns that you're hearing consistently across company sizes and maybe even consistently across industries? >> Sure. I think that's a great point. I think some of the early, early adopters, like Netflix, Twitter, they have their own way of building out their hyper-scale infrastructures. And so we work very closely with them to address their needs. What we're starting to see as the technology becomes mainstream... There are a lot of common challenges that these mainstream enterprises are either not experienced with, not staffed for, or just don't have the budget to blow a lot on these types of projects. And so, what becomes a key concern is a lot of companies today recognize containerization is interesting, it's important. It has the potential to deliver cost savings, and they recognize they have to move to a Dev/Ops model to deliver code very quickly. But then they also realize that we're starting to live in an always connected economy where you can't just sell a product and not expect to hear from the customer until they have a problem with it. You wanna interact with them, you wanna use that data to help improve the experience for the customer. How do you manage all this information? So the whole concept of data engineering, data operations, and data science becomes really a key factor for many enterprises. And for a lot of them, they just don't have the resources to really address it. Now, there are many different companies that provide individual point solutions for those technologies, but how do you bring it all together in a multi-tenet way, right? How do you make sure if you have one team that's using one version of Spark and another team using a different version of Spark that they can actually share infrastructure? And that's where Mesosphere's uniqueness has really come front and center. We basically pull these data services the way VMware pulled the traditional model basic applications. So the cost saving you saw from server consolidation, we're doing from cluster consolidation and dramatically reducing costs while automating operations at the same time. >> I'd like to follow up on that a little bit. I think ever since the launch of DC/OS a few years back, big data was a differentiator for Mesosphere. And, again, another term that's been through it's own hype cycle, right? But it's real today. Can you maybe go a little deeper with the consolidation piece? How are Mesosphere admins interacting with data scientists or even on the container side and the infrastructure side, what do you have to do differently to make sure the memory footprints and all the various big data platforms are able to be supported? >> Yeah. So I think big data 1.0, let's call it, was really a batch operating model. Wait 'til the data comes in at the end of the quarter, make some recommendations on how the business can improve the next quarter. You guys have all seen reports. I think Gardner talked about one where 80% of due projects have failed. And the reason for this is that it was hard to justify the benefit right up front. The cost and the complexity of rolling out these projects was very prohibitive. Now, what Mesosphere brings is the ability to adopt many different types of these next generation data technologies. Spark, Cassandra distributed database, Kafka message queue, TensorFlow, Elasticsearch, these are all technologies that have become increasingly popular, but the challenge for most enterprises is it's hard to have a whole team just dedicated to learning Kafka and another one on Spark and another one on Cassandra. What if your competitors hire them away? And how do you run all these different technologies that are clustered systems that require a lot of infrastructure? They're not designed to run together and pull together efficiently. That's what Mesosphere really brings to these technologies. One is the ability to automate all these technologies, so instead of getting a whole team to figure out how to run stuff, it's literally one click installation, or a single command on the DC/OS command console. And then two being able to run all these different types of data services in a highly pulled way so that you don't have different clusters that are turning into snowflakes that cannot be reused by other teams. This gives you dramatic changes in how people operate. If you were a big data team at a major bank and somebody said "I wanna do transactions on your infrastructure," you would probably say "No, stay out of my infrastructure because I want to make sure I have the resources to do analytics," and the same would be true for the people who are actually doing the real-time transaction-processing with customers. What if I told you I can give you a way to do application-aware automations so that these services can be automated very easily? And two, these resources can share an infrastructure while maintaining resource guarantees. Now, all of a sudden, the individual functional leads or business unit leads would go "Okay, I'm okay with sharing resources with these other BU's, especially if it gives me the benefit over time of helping different BU's cross-pollinate information." >> A whole different way of interacting with big data, right? And actually making it useful. >> Maybe forcing collaboration. I wish we had more time, but we wanna thank you so much for stopping by theCUBE, telling us what's new at Mesosphere. Sounds like never a dull moment. >> Oh, absolutely. Thank you very much. >> We wanna thank you for watching theCUBE. I am Lisa Martin with John Troyer from DockerCon 2018. Stick around, John and I will be right back with our last guest. (techno music)

(upbeat electronic music) >> Announcer: Live from New Orleans, it's theCUBE. Covering VeeamOn 2017, brought to you by Veeam. >> Welcome back to New Orleans, everybody, I'm Dave Vellante with my co-host Stu Miniman. There's been a lot of talk of course this week because of WannaCry about ransomware. Edward Haletki is here, he is the principal at TVP Strategy and he and I were having a conversation the other night about ransomware. Edward is a security expert, strategist, been around a long time, Edward, good to see you, thanks for coming on theCUBE. >> Thank you for having me again. >> Let's riff on this a little bit. You had some really, I thought, thought-provoking ideas about ransomware. I was making the point that look, if you got an air gap, you're good, right, and you said, "Well, no," I said, "Well, what if you have an offsite tape?" And you said, "Well, it's not that simple." >> Edward: It really isn't. >> What's the deal with how to protect myself against ransomware? >> Well, let's just start with a few things. This particular about of ransomware is actually in version 2.0. So the guy found the kill switch for the first version, they already fixed that bug and put it out again. So now it's hitting over 200,000 machines in 99 countries. It's spreading around the world like crazy. The only way that I found to protect yourself is to actually have the ability to do, in a lot of ways, versioned writes. In other words, you keep a version of everything. That's important, but you got to first figure out what's important. But it's more than that. It's an entire architecture around data protection, security and even your business. You need to start with, if you're talking about from the security perspective, you need to start with a way to prevent what's known. If I can prevent what's known from getting to you, like phishing attacks and other attacks, I can prevent you from spreading ransomware into your company. So that's kind of a gate, but if that comes through the gate which it could and it did, you need something able to detect ransomware. And that is a detection that data protection's prime to do. >> But like, okay, explain this. Sort of revisit the conversation we had. If I have an air gap, meaning I've got a separate data center that's disconnected somehow or periodically disconnected, as some vendors have suggested, I'll rotate the connection. And I've got data off site. Let's say I've even got it off site in tape, even though I would ideally not like to recover from tape. Why am I not protected in that scenario? >> It depends on the retention schedule. If the retention schedule's long enough, you'd probably be fine. Most people don't find out there's ransomware until they reboot a machine. >> Dave: And they've rotated through their tapes by then, you're saying. >> They could possibly do that. Some of the smaller businesses, they probably have. Some of the larger businesses that keep yearly and monthly and so forth, and they keep them for seven years probably haven't. But as we move move further and further away from tape and more to the connected universe, even multiple copies of something doesn't necessarily protect you, unless they're immutable copies. >> Well, Phil, Bill Philbin said it today, he said, in a different way, he said, "When we make boo-boos "and we replicate the boo-boos, we replicate really fast," and I tweeted out, I said, well, if there's malicious encryption, that probably replicates really fast. >> Edward: It does. >> Okay, and so. I mean, maybe we should explain the basics here as that's really what the ransomware folks are doing, right, they're encrypting your data and then saying, "Hey, you want the keys back, you got to pay us," is that-- >> Well, and actually, the new breed is, "Hey, pay us and we won't even give you the keys." >> Well, you know, I was watching CNBC the other day when WannaCry hit and one of the experts that they had on, the CNBC analysts asked them, the anchor's asked them, "Well, what do you do?" And they said, "Well, unfortunately, "you just might have to pay the ransom," which was surprising to me because there's no guarantee you're going to get the keys. >> The keys, but it's actually 60 million dollars worth of ransom right now. That's a lot of money. >> Okay, so-- >> I mean, this is, it's 300 dollars a bitcoin to get your key. >> Dave: Right, you're paying in bitcoin, obviously. >> Which is also, that's expensive to get. And a lot of companies just don't have bitcoins lying around, so they have to go out to either mine them or-- >> Dave: Or go to a marketplace. >> Go to marketplace and buy them. >> Especially the people that are still running Windows XP aren't necessarily the people that are bitcoin experts. >> Exactly. >> Okay, so now, what you had suggested to me was that the backup software vendor, we're here at VeeamOn and we're at a Veeam event, backup software vendor actually has data because they're pushing change data to the network periodically. And in theory, they could use analytics to identify anomalous behavior. >> Edward: Exactly. >> In terms of encryption activity that's higher than normal. Explain that. >> Well, there's a couple of ways you can do that. One is that you could look at the CPU utilization, say hey, it's a high CPU utilization, something's going on. Unfortunately, you can't tell if that's a normal action or a non-action, an encryption action, especially with the new chipsets, encryption's very very fast. And the overhead's very very little, could just hide in the noise. When you look at data though, as it gets encrypted, when I do data protection, normally in a virtualized environment or even in a physical environment these days we do something called change block tracking. Or the equivalent thereof in the physical world. And what that does is that, for every block that changes of the file system, I can, that gets sent over to be protected. So as those increase because I'm encrypting more and more and more, you're going to see an increase in the number of blocks that have changed. You could say normally that machine does maybe a kilobyte per backup. And suddenly you're doing a gigabyte. That's a huge difference, that's a big red flag saying hey, something's gone wrong, that's not normal. >> What about this idea of like, honeypot files, like here's where we store all the credit cards file. >> Edward: Oh, we call them canary files. >> Canary files, great. >> And this is, canary files are another way you can detect things. If you have a file server, you should just put a canary file out there, nice juicy name, you know, CEO's whatever, something like that, a spreadsheet, it could be an expense report that you know is ancient. It doesn't make any difference. What that canary file is used for is you just periodically query the file, like, can I read you? It doesn't have to be a big file, it just means I can read you, 'cause it's going to encrypt the whole thing. Once I can't read it anymore, you know, you've been hit by ransomware usually. >> Right, because there's no reason you would've encrypted that file. >> Or even touched it, no one should be touching it. >> Dave: Right, some zombie file. >> Exactly. >> Okay. Now, for a company like Veeam to put a solution, I mean, I'm making the case that there should be specific solutions in the marketplace for ransomware. >> Edward: Oh, absolutely. >> Not just a sort of hand waving and buy our product because of ransomware, it should be a specific solution geared towards solving the problem. What does that solution look like, how would a company like Veeam, who would the partners be that they would put that together, what types of companies would they need, what type of capabilities would be required? >> Well, for Veeam, I think you need four general capabilities. They have one of them, that's the recovery stage. They have instant, the capability to do instant recoveries. That is a must, so if you have ransomware, to recover the business, you just do an instant recovery of a known good source. The other one is on the front end, you really need the prevention. In other words, I'm going to prevent people from doing fishing or I'm going to prevent attacks coming in with that type of payload. So if it's an encrypted payload, don't let it through. Those are possible. The middle of it is the detection, and then what we call legal hold. In other words, I want to say, okay, I detected the possibility of ransomware. And then I want to mark this recover point, the one that I'm currently backing up, as potential for ransomware so the one before that is the one I say, "Hey, don't delete that one "until I've inspected it," and that's the one you may do the instant recovery off of. >> Okay, so prevention, I mean, that's just good practice. But let's assume for a second-- >> That's a security company has those capabilities, some of them do a really good job at that, but even with something like WannaCry, you can't prevent someone from clicking on a link. >> Right, so assume for a second that I didn't prevent it. So I should do that as best practice, but assume I didn't prevent it, so I got to have detection. >> Edward: Absolutely. >> They've penetrated, now I'm using what, analytics to look for anomalous behavior? >> I'm either using a canary file or I'm using analytics at the data protection layer. I could even use analytics at the storage layer to say, "Hey, there's a lot of changes happening," that's going to go down the storage path and I'm going to be able to see it there as well. >> Okay, and then legal hold, in 2006 when the federal rules of civil procedure changed and they said electronic documents are now admissible. Most large companies and certainly large companies in regulated industries began to implement techniques to do legal holds, particularly around email archiving, which was just one piece of the problem. That's a complicated problem. >> It is, but it's really legal hold like. It's the concepts of legal hold, but applied specifically to data protection. In other words, you want to say the recover point that I'm currently writing to could be bad. We don't know, so mark the recover point previous to that as don't delete. Don't mark the one you're just doing, it's the one previous to that. 'Cause what could happen is you may not do the instant restore 'cause they're fine. But three days later when that one's going to roll off, it rolls off and it may go away. And if it goes away, you're sunk. >> Okay, and then fast recovery, which is the capability that you said Veeam has, obviously. >> Edward: I would say some recovery, yeah. >> Am I to infer that an air gap is not required? >> Well, when you start doing the... It is and isn't. If you have a good architecture, that architecture's going to include things like going to an immutable storage source. So I'm going to store my backups on an immutable source or target. And that immutable target, the best one today is really an object store where it has versioned rights. Every version that gets written is immutable. So as you do data protection, you write to a new version a full image, so it's a synthetic full image that gets put into that blob of storage. So I have my target for, my Veeam target, let's say, and then Veeam would replicated that or do something to put that on this object store for versioned writes. Then what happens is I can either restore from the Veeam target, but let's say that gets corrupted, now I can go back to the object store as the ultimate source saying, "Hey, I'll just go back "to the immutable versions." >> Okay, when I hear immutability, I often think of blockchain. Can blockchain, does it fit in here in the future, can it help solve problems like this? >> Yes and no, blockchain is actually very old. We've been doing blockchain encryption for ages. EBC was an electronic blockchain for encryption. I'm not sure it's actually going to solve that problem. But immutable is basically non-writable, that's what I'm talking about, you can't change it once it's written. And if you can protect that using blockchain and the metadata and all that, that's fine. But I don't think that's necessary. >> It's like containers too. Everything's been around forever. (laughs) >> It has been. I mean, when you think about, but this particular one is really taking advantage of what object stores have to offer today. And there's several companies that have that capability and it adds a nice layer, we think it's archive, but it's not, to me it would be the intermediary. It's the pre-archive, it's kind of like, okay, put it there, and then I may archive that off on a retention schedule. >> Excellent, Edward, great analysis, thank you very much, appreciate that, so Stu, let me bring you into the conversation, put a bow on VeeamOn 2017, what are you takeaways? >> So Dave, we go to a lot of shows and love when you have a community that's excited. That term love is not one that you hear at many shows, I mean, I'm sure Edward probably-- >> Edward: I would agree. >> I love VMware bumper stickers that people have. Technology is, you know, we're down in the weeds here. I mean, here's people that are passionate about availability and backup. The thing that I was looking for coming on to this show, Dave, is what they addressed, you know, day one and the main keynote. Which is the big wave of virtualization has kind of gone past, you know, the peak of where it is. And how can they look at that next generation, can they hop on the waves? The things that I really liked, we got to talk to a lot of customers, Dave, customers, passionate, not only the enterprise where they've been getting into, but talked to a number of service providers including some interviews that we did where they like what they're doing, they keep building. Public cloud and where Veeam fits, I think it's early days. Want to see how that develops, want to see how customers use it, we did talk to one customer that was really excited about where that'll fit in. I like that Veeam has, you know, clear eyes as to where their future is and they're embracing that change. I always hear, sometimes you hear that term embrace and you're like, yeah yeah yeah, sure, you're kind of giving it lip service, but are you going to be able to move forward on that new trend, because as we talked, Dave, in a couple of segments here during our two days of interviews, usually when there's a shift in the landscape, the players change, the previous incumbent will not be the leader going forward. And Veeam has a strong team, they've put a lot of new people in place, and they know where the battles will be fought. Early days in some of this next wave, but it was exciting to be here and happy to share it with you. >> Yeah, I mean, I learned a lot about Veeam. Most of my interaction with the company have been either informal or kick in the tires, v tugs and v mugs where you've seen them for years. I came in knowing that the press releases talked about 600 million dollars in bookings, ambitions to become a billion dollar company. Very rapid growth rate, 45,000 partners. So that was quite interesting, to see that in action. This company's got real big ambitions, this idea of being sort of the availability expert for whatever use case you want, whether it's in the cloud or going to the cloud or coming from the cloud or between clouds, is very ambitious. I think that's a wide open space. I suspect it's a big market, although it's really emerging, and I suspect all the individual cloud vendors are going to be going, trying to protect their little parts of the world, companies like VMware are going to want to try to own that inter-clouding space and other startups are trying to get in there. It's a sort of jump ball in my view there, but I like the ambition. It was interesting to hear Peter McKay talk about Veeam in the context of software companies that are growing and growing fast, getting to 800 million which they're not there yet, the likes of Workday and Salesforce and ServiceNow. Of course, those are all public companies and Veeam is a private company, so it can write its own narrative. >> They've got enough revenue, Dave, that they could be public. There've been plenty of companies that have IPOed with much less revenue. I'm shocked you haven't mentioned it, Dave, profitability. I mean, in today's day and age, a company of the size that they are, and they're still growing at a rapid pace and they are profitable. So you know, kudos there. >> Yeah, and then the other thing that struck me was the pace of product announcements, I always look for that. At a lot of the shows that we go to, you hear a lot of hand waving about digital transformation, but you don't see a lot of products coming out. So there was some excitement around the products, so that's a good sign that they can turn strategy into R&D into products that sell that the partners are taking and uptaking. So it was a good sort of first experience certainly for me at VeeamOn and theCUBE, and Stu, always a pleasure working with you, we got, excuse me, get to take a break. The boys get to go home after 20 days on the road, and then, you know, we're cranking up again. We got shows every single week in June, multiple shows, US, international, so to to siliconangle.tv, check that out, check out our schedule. Go to siliconangle.com for all the news, wikibon.com is cranking some stuff out as well. Edward, thanks for sitting in. >> Oh, my pleasure. I do have one thing to interject, I've actually looked at Veeam from a totally different perspective. I've been watching them and monitoring them for about 10 years. From their technology perspective. Actually over 10 years, I started with them. So I went through the virtualization, backup wars with them and all the other companies. Their rate of innovation, their rate of change has actually been far greater than many other data protection companies. It's not just their new releases, it's their whole, they've gone through several shifts in messaging. And several shifts in what their products do. And it's been fascinating to watch. >> Well, and that's a really good point, because a lot of the traditional backup software companies are living on maintenance. And it seems like Veeam is trying to, as Pat Gelsinger says, catch the wave and not be left in the dust as driftwood. All right, we're going to leave it there, thanks for watching, everybody. We will see you next time, and take care. (upbeat electronic music)

>> From "theCube" Studios in Palo Alto in Boston bringing you data-driven insights from "theCube" and ETR. This is "Breaking Analysis" with Dave Vellante. >> As an independent pure play company, Palo Alto Networks has earned its status as the leader in security. You can measure this in a variety of ways. Revenue, market cap, execution, ethos, and most importantly, conversations with customers generally. In CISO specifically, who consistently affirm this position. The company's on track to double its revenues in fiscal year 23 relative to fiscal year 2020. Despite macro headwinds, which are likely to carry through next year, Palo Alto owes its position to a clarity of vision and strong execution on a TAM expansion strategy through acquisitions and integration into its cloud and SaaS offerings. Hello and welcome to this week's "Wikibon Cube Insights" powered by ETR and this breaking analysis and ahead of Palo Alto Ignite the company's user conference, we bring you the next chapter on top of the last week's cybersecurity update. We're going to dig into the ETR data on Palo Alto Networks as we promised and provide a glimpse of what we're going to look for at "Ignite" and posit what Palo Alto needs to do to stay on top of the hill. Now, the challenges for cybersecurity professionals. Dead simple to understand. Solving it, not so much. This is a taxonomic eye test, if you will, from Optiv. It's one of our favorite artifacts to make the point the cybersecurity landscape is a mosaic of stovepipes. Security professionals have to work with dozens of tools many legacy combined with shiny new toys to try and keep up with the relentless pace of innovation catalyzed by the incredibly capable well-funded and motivated adversaries. Cybersecurity is an anomalous market in that the leaders have low single digit market shares. Think about that. Cisco at one point held 60% market share in the networking business and it's still deep into the 40s. Oracle captures around 30% of database market revenue. EMC and storage at its peak had more than 30% of that market. Even Dell's PC market shares, you know, in the mid 20s or even over that from a revenue standpoint. So cybersecurity from a market share standpoint is even more fragmented perhaps than the software industry. Okay, you get the point. So despite its position as the number one player Palo Alto might have maybe three maybe 4% of the total market, depending on what you use as your denominator, but just a tiny slice. So how is it that we can sit here and declare Palo Alto as the undisputed leader? Well, we probably wouldn't go that far. They probably have quite a bit of competition. But this CISO from a recent ETR round table discussion with our friend Eric Bradley, summed up Palo Alto's allure. We thought pretty well. The question was why Palo Alto Networks? Here's the answer. Because of its completeness as a platform, its ability to integrate with its own products or they acquire, integrate then rebrand them as their own. We've looked at other vendors we just didn't think they were as mature and we already had implemented some of the Palo Alto tools like the firewalls and stuff and we thought why not go holistically with the vendor a single throat to choke, if you will, if stuff goes wrong. And I think that was probably the primary driver and familiarity with the tools and the resources that they provided. Now here's another stat from ETR's Eric Bradley. He gave us a glimpse of the January survey that's in the field now. The percent of IT buyers stating that they plan to consolidate redundant vendors, it went from 34% in the October survey and now stands at 44%. So we fo we feel this bodes well for consolidators like Palo Alto networks. And the same is true from Microsoft's kind of good enough approach. It should also be true for CrowdStrike although last quarter we saw softness reported on in their SMB market, whereas interestingly MongoDB actually saw consistent strength from its SMB and its self-serve. So that's something that we're watching very closely. Now, Palo Alto Networks has held up better than most of its peers in the stock market. So let's take a look at that real quick. This chart gives you a sense of how well. It's a one year comparison of Palo Alto with the bug ETF. That's the cyber basket that we like to compare often CrowdStrike, Zscaler, and Okta. Now remember Palo Alto, they didn't run up as much as CrowdStrike, ZS and Okta during the pandemic but you can see it's now down unquote only 9% for the year. Whereas the cyber basket ETF is off 27% roughly in line with the NASDAQ. We're not showing that CrowdStrike down 44%, Zscaler down 61% and Okta off a whopping 72% in the past 12 months. Now as we've indicated, Palo Alto is making a strong case for consolidating point tools and we think it will have a much harder time getting customers to switch off of big platforms like Cisco who's another leader in network security. But based on the fragmentation in the market there's plenty of room to grow in our view. We asked breaking analysis contributor Chip Simington for his take on the technicals of the stock and he said that despite Palo Alto's leadership position it doesn't seem to make much difference these days. It's all about interest rates. And even though this name has performed better than its peers, it looks like the stock wants to keep testing its 52 week lows, but he thinks Palo Alto got oversold during the last big selloff. And the fact that the company's free cash flow is so strong probably keeps it at the one 50 level or above maybe bouncing around there for a while. If it breaks through that under to the downside it's ne next test is at that low of around one 40 level. So thanks for that, Chip. Now having get that out of the way as we said on the previous chart Palo Alto has strong opinions, it's founder and CTO, Nir Zuk, is extremely clear on that point of view. So let's take a look at how Palo Alto got to where it is today and how we think you should think about his future. The company was founded around 18 years ago as a network security company focused on what they called NextGen firewalls. Now, what Palo Alto did was different. They didn't try to stuff a bunch of functionality inside of a hardware box. Rather they layered network security functions on top of its firewalls and delivered value as a service through software running at the time in its own cloud. So pretty obvious today, but forward thinking for the time and now they've moved to a more true cloud native platform and much more activity in the public cloud. In February, 2020, right before the pandemic we reported on the divergence in market values between Palo Alto and Fort Net and we cited some challenges that Palo Alto was happening having transitioning to a cloud native model. And at the time we said we were confident that Palo Alto would make it through the knot hole. And you could see from the previous chart that it has. So the company's architectural approach was to do the heavy lifting in the cloud. And this eliminates the need for customers to deploy sensors on prem or proxies on prem or sandboxes on prem sandboxes, you know for instance are vulnerable to overwhelming attacks. Think about it, if you're a sandbox is on prem you're not going to be updating that every day. No way. You're probably not going to updated even every week or every month. And if the capacity of your sandbox is let's say 20,000 files an hour you know a hacker's just going to turn up the volume, it'll overwhelm you. They'll send a hundred thousand emails attachments into your sandbox and they'll choke you out and then they'll have the run of the house while you're trying to recover. Now the cloud doesn't completely prevent that but what it does, it definitely increases the hacker's cost. So they're going to probably hit some easier targets and that's kind of the objective of security firms. You know, increase the denominator on the ROI. All right, the next thing that Palo Alto did is start acquiring aggressively, I think we counted 17 or 18 acquisitions to expand the TAM beyond network security into endpoint CASB, PaaS security, IaaS security, container security, serverless security, incident response, SD WAN, CICD pipeline security, attack service management, supply chain security. Just recently with the acquisition of Cider Security and Palo Alto by all accounts takes the time to integrate into its cloud and SaaS platform called Prisma. Unlike many acquisitive companies in the past EMC was a really good example where you ended up with a kind of a Franken portfolio. Now all this leads us to believe that Palo Alto wants to be the consolidator and is in a good position to do so. But beyond that, as multi-cloud becomes more prevalent and more of a strategy customers tell us they want a consistent experience across clouds. And is going to be the same by the way with IoT. So of the next wave here. Customers don't want another stove pipe. So we think Palo Alto is in a good position to build what we call the security super cloud that layer above the clouds that brings a common experience for devs and operational teams. So of course the obvious question is this, can Palo Alto networks continue on this path of acquire and integrate and still maintain best of breed status? Can it? Will it? Does it even have to? As Holger Mueller of Constellation Research and I talk about all the time integrated suites seem to always beat best of breed in the long run. We'll come back to that. Now, this next graphic that we're going to show you underscores this question about portfolio. Here's a picture and I don't expect you to digest it all but it's a screen grab of Palo Alto's product and solutions portfolios, network cloud, network security rather, cloud security, Sassy, CNAP, endpoint unit 42 which is their threat intelligence platform and every imaginable security service and solution for customers. Well, maybe not every, I'm sure there's more to come like supply chain with the recent Cider acquisition and maybe more IoT beyond ZingBox and earlier acquisition but we're sure there will be more in the future both organic and inorganic. Okay, let's bring in more of the ETR survey data. For those of you who don't know ETR, they are the number one enterprise data platform surveying thousands of end customers every quarter with additional drill down surveys and customer round tables just an awesome SaaS enabled platform. And here's a view that shows net score or spending momentum on the vertical axis in provision or presence within the ETR data set on the horizontal axis. You see that red dotted line at 40%. Anything at or over that indicates a highly elevated net score. And as you can see Palo Alto is right on that line just under. And I'll give you another glimpse it looks like Palo Alto despite the macro may even just edge up a bit in the next survey based on the glimpse that Eric gave us. Now those colored bars in the bottom right corner they show the breakdown of Palo Alto's net score and underscore the methodology that ETR uses. The lime green is new customer adoptions, that's 7%. The forest green at 38% represents the percent of customers that are spending 6% or more on Palo Alto solutions. The gray is at that 40 or 8% that's flat spending plus or minus 5%. The pinkish at 5% is spending is down on Palo Alto network products by 6% or worse. And the bright red at only 2% is churn or defections. Very low single digit numbers for Palo Alto, that's a real positive. What you do is you subtract the red from the green and you get a net score of 38% which is very good for a company of Palo Alto size. And we'll note this is based on just under 400 responses in the ETR survey that are Palo Alto customers out of around 1300 in the total survey. It's a really good representation of Palo Alto. And you can see the other leading companies like CrowdStrike, Okta, Zscaler, Forte, Cisco they loom large with similar aspirations. Well maybe not so much Okta. They don't necessarily rule want to rule the world. They want to rule identity and of course the ever ubiquitous Microsoft in the upper right. Now drilling deeper into the ETR data, let's look at how Palo Alto has progressed over the last three surveys in terms of market presence in the survey. This view of the data shows provision in the data going back to October, 2021, that's the gray bars. The blue is July 22 and the yellow is the latest survey from October, 2022. Remember, the January survey is currently in the field. Now the leftmost set of data there show size a company. The middle set of data shows the industry for a select number of industries in the right most shows, geographic region. Notice anything, yes, Palo Alto up across the board relative to both this past summer and last fall. So that's pretty impressive. Palo Alto network CEO, Nikesh Aurora, stressed on the last earnings call that the company is seeing somewhat elongated deal approvals and sometimes splitting up size of deals. He's stressed that certain industries like energy, government and financial services continue to spend. But we would expect even a pullback there as companies get more conservative. But the point is that Nikesh talked about how they're hiring more sales pros to work the pipeline because they understand that they have to work harder to pull deals forward 'cause they got to get more approvals and they got to increase the volume that's coming through the pipeline to account for the possibility that certain companies are going to split up the deals, you know, large deals they want to split into to smaller bite size chunks. So they're really going hard after they go to market expansion to account for that. All right, so we're going to wrap by sharing what we expect and what we're going to probe for at Palo Alto Ignite next week, Lisa Martin and I will be hosting "theCube" and here's what we'll be looking for. First, it's a four day event at the MGM with the meat of the program on days two and three. That's day two was the big keynote. That's when we'll start our broadcasting, we're going for two days. Now our understanding is we've never done Palo Alto Ignite before but our understanding it's a pretty technically oriented crowd that's going to be eager to hear what CTO and founder Nir Zuk has to say. And as well CEO Nikesh Aurora and as in addition to longtime friend of "theCube" and current president, BJ Jenkins, he's going to be speaking. Wendy Whitmore runs Unit 42 and is going to be several other high profile Palo Alto execs, as well, Thomas Kurian from Google is a featured speaker. Lee Claridge, who is Palo Alto's, chief product officer we think is going to be giving the audience heavy doses of Prisma Cloud and Cortex enhancements. Now, Cortex, you might remember, came from an acquisition and does threat detection and attack surface management. And we're going to hear a lot about we think about security automation. So we'll be listening for how Cortex has been integrated and what kind of uptake that it's getting. We've done some, you know, modeling in from the ETR. Guys have done some modeling of cortex, you know looks like it's got a lot of upside and through the Palo Alto go to market machine, you know could really pick up momentum. That's something that we'll be probing for. Now, one of the other things that we'll be watching is pricing. We want to talk to customers about their spend optimization, their spending patterns, their vendor consolidation strategies. Look, Palo Alto is a premium offering. It charges for value. It's expensive. So we also want to understand what kind of switching costs are customers willing to absorb and how onerous they are and what's the business case look like? How are they thinking about that business case. We also want to understand and really probe on how will Palo Alto maintain best of breed as it continues to acquire and integrate to expand its TAM and appeal as that one-stop shop. You know, can it do that as we talked about before. And will it do that? There's also an interesting tension going on sort of changing subjects here in security. There's a guy named Edward Hellekey who's been in "theCube" before. He hasn't been in "theCube" in a while but he's a security pro who has educated us on the nuances of protecting data privacy, public policy, how it varies by region and how complicated it is relative to security. Because securities you technically you have to show a chain of custody that proves unequivocally, for example that data has been deleted or scrubbed or that metadata does. It doesn't include any residual private data that violates the laws, the local laws. And the tension is this, you need good data and lots of it to have good security, really the more the better. But government policy is often at odds in a major blocker to sharing data and it's getting more so. So we want to understand this tension and how companies like Palo Alto are dealing with it. Our customers testing public policy in courts we think not quite yet, our government's making exceptions and policies like GDPR that favor security over data privacy. What are the trade-offs there? And finally, one theme of this breaking analysis is what does Palo Alto have to do to stay on top? And we would sum it up with three words. Ecosystem, ecosystem, ecosystem. And we said this at CrowdStrike Falcon in September that the one concern we had was the pace of ecosystem development for CrowdStrike. Is collaboration possible with competitors? Is being adopted aggressively? Is Palo Alto being adopted aggressively by global system integrators? What's the uptake there? What about developers? Look, the hallmark of a cloud company which Palo Alto is a cloud security company is a thriving ecosystem that has entries into and exits from its platform. So we'll be looking at what that ecosystem looks like how vibrant and inclusive it is where the public clouds fit and whether Palo Alto Networks can really become the security super cloud. Okay, that's a wrap stop by next week. If you're in Vegas, say hello to "theCube" team. We have an unbelievable lineup on the program. Now if you're not there, check out our coverage on theCube.net. I want to thank Eric Bradley for sharing a glimpse on short notice of the upcoming survey from ETR and his thoughts. And as always, thanks to Chip Symington for his sharp comments. Want to thank Alex Morrison, who's on production and manages the podcast Ken Schiffman as well in our Boston studio, Kristen Martin and Cheryl Knight they help get the word out on social and of course in our newsletters, Rob Hoof, is our editor in chief over at Silicon Angle who does some awesome editing, thank you to all. Remember all these episodes they're available as podcasts. Wherever you listen, all you got to do is search "Breaking Analysis" podcasts. I publish each week on wikibon.com and silicon angle.com where you can email me at david.valante@siliconangle.com or dm me at D Valante or comment on our LinkedIn post. And please do check out etr.ai. They've got the best survey data in the enterprise tech business. This is Dave Valante for "theCube" Insights powered by ETR. Thanks for watching. We'll see you next week on "Ignite" or next time on "Breaking Analysis". (upbeat music)

from around the globe it's thecube with digital coverage of exascale day made possible by hewlett packard enterprise welcome everyone to the cube celebration of exascale day ben bennett is here he's an hpc strategist and evangelist at hewlett-packard enterprise ben welcome good to see you good to see you too son hey well let's evangelize exascale a little bit you know what's exciting you uh in regards to the coming of exoskilled computing um well there's a couple of things really uh for me historically i've worked in super computing for many years and i have seen the coming of several milestones from you know actually i'm old enough to remember gigaflops uh coming through and teraflops and petaflops exascale is has been harder than many of us anticipated many years ago the sheer amount of technology that has been required to deliver machines of this performance has been has been us utterly staggering but the exascale era brings with it real solutions it gives us opportunities to do things that we've not been able to do before if you look at some of the the most powerful computers around today they've they've really helped with um the pandemic kovid but we're still you know orders of magnitude away from being able to design drugs in situ test them in memory and release them to the public you know we still have lots and lots of lab work to do and exascale machines are going to help with that we are going to be able to to do more um which ultimately will will aid humanity and they used to be called the grand challenges and i still think of them as that i still think of these challenges for scientists that exascale class machines will be able to help but also i'm a realist is that in 10 20 30 years time you know i should be able to look back at this hopefully touch wood look back at it and look at much faster machines and say do you remember the days when we thought exascale was faster yeah well you mentioned the pandemic and you know the present united states was tweeting this morning that he was upset that you know the the fda in the u.s is not allowing the the vaccine to proceed as fast as you'd like it in fact it the fda is loosening some of its uh restrictions and i wonder if you know high performance computing in part is helping with the simulations and maybe predicting because a lot of this is about probabilities um and concerns is is is that work that is going on today or are you saying that that exascale actually you know would be what we need to accelerate that what's the role of hpc that you see today in regards to sort of solving for that vaccine and any other sort of pandemic related drugs so so first a disclaimer i am not a geneticist i am not a biochemist um my son is he tries to explain it to me and it tends to go in one ear and out the other um um i just merely build the machines he uses so we're sort of even on that front um if you read if you had read the press there was a lot of people offering up systems and computational resources for scientists a lot of the work that has been done understanding the mechanisms of covid19 um have been you know uncovered by the use of very very powerful computers would exascale have helped well clearly the faster the computers the more simulations we can do i think if you look back historically no vaccine has come to fruition as fast ever under modern rules okay admittedly the first vaccine was you know edward jenner sat quietly um you know smearing a few people and hoping it worked um i think we're slightly beyond that the fda has rules and regulations for a reason and we you don't have to go back far in our history to understand the nature of uh drugs that work for 99 of the population you know and i think exascale widely available exoscale and much faster computers are going to assist with that imagine having a genetic map of very large numbers of people on the earth and being able to test your drug against that breadth of person and you know that 99 of the time it works fine under fda rules you could never sell it you could never do that but if you're confident in your testing if you can demonstrate that you can keep the one percent away for whom that drug doesn't work bingo you now have a drug for the majority of the people and so many drugs that have so many benefits are not released and drugs are expensive because they fail at the last few moments you know the more testing you can do the more testing in memory the better it's going to be for everybody uh personally are we at a point where we still need human trials yes do we still need due diligence yes um we're not there yet exascale is you know it's coming it's not there yet yeah well to your point the faster the computer the more simulations and the higher the the chance that we're actually going to going to going to get it right and maybe compress that time to market but talk about some of the problems that you're working on uh and and the challenges for you know for example with the uk government and maybe maybe others that you can you can share with us help us understand kind of what you're hoping to accomplish so um within the united kingdom there was a report published um for the um for the uk research institute i think it's the uk research institute it might be epsrc however it's the body of people responsible for funding um science and there was a case a science case done for exascale i'm not a scientist um a lot of the work that was in this documentation said that a number of things that can be done today aren't good enough that we need to look further out we need to look at machines that will do much more there's been a program funded called asimov and this is a sort of a commercial problem that the uk government is working with rolls royce and they're trying to research how you build a full engine model and by full engine model i mean one that takes into account both the flow of gases through it and how those flow of gases and temperatures change the physical dynamics of the engine and of course as you change the physical dynamics of the engine you change the flow so you need a closely coupled model as air travel becomes more and more under the microscope we need to make sure that the air travel we do is as efficient as possible and currently there aren't supercomputers that have the performance one of the things i'm going to be doing as part of this sequence of conversations is i'm going to be having an in detailed uh sorry an in-depth but it will be very detailed an in-depth conversation with professor mark parsons from the edinburgh parallel computing center he's the director there and the dean of research at edinburgh university and i'm going to be talking to him about the azimoth program and and mark's experience as the person responsible for looking at exascale within the uk to try and determine what are the sort of science problems that we can solve as we move into the exoscale era and what that means for humanity what are the benefits for humans yeah and that's what i wanted to ask you about the the rolls-royce example that you gave it wasn't i if i understood it wasn't so much safety as it was you said efficiency and so that's that's what fuel consumption um it's it's partly fuel consumption it is of course safety there is a um there is a very specific test called an extreme event or the fan blade off what happens is they build an engine and they put it in a cowling and then they run the engine at full speed and then they literally explode uh they fire off a little explosive and they fire a fan belt uh a fan blade off to make sure that it doesn't go through the cowling and the reason they do that is there has been in the past uh a uh a failure of a fan blade and it came through the cowling and came into the aircraft depressurized the aircraft i think somebody was killed as a result of that and the aircraft went down i don't think it was a total loss one death being one too many but as a result you now have to build a jet engine instrument it balance the blades put an explosive in it and then blow the fan blade off now you only really want to do that once it's like car crash testing you want to build a model of the car you want to demonstrate with the dummy that it is safe you don't want to have to build lots of cars and keep going back to the drawing board so you do it in computers memory right we're okay with cars we have computational power to resolve to the level to determine whether or not the accident would hurt a human being still a long way to go to make them more efficient uh new materials how you can get away with lighter structures but we haven't got there with aircraft yet i mean we can build a simulation and we can do that and we can be pretty sure we're right um we still need to build an engine which costs in excess of 10 million dollars and blow the fan blade off it so okay so you're talking about some pretty complex simulations obviously what are some of the the barriers and and the breakthroughs that are kind of required you know to to do some of these things that you're talking about that exascale is going to enable i mean presumably there are obviously technical barriers but maybe you can shed some light on that well some of them are very prosaic so for example power exoscale machines consume a lot of power um so you have to be able to design systems that consume less power and that goes into making sure they're cooled efficiently if you use water can you reuse the water i mean the if you take a laptop and sit it on your lap and you type away for four hours you'll notice it gets quite warm um an exascale computer is going to generate a lot more heat several megawatts actually um and it sounds prosaic but it's actually very important to people you've got to make sure that the systems can be cooled and that we can power them yeah so there's that another issue is the software the software models how do you take a software model and distribute the data over many tens of thousands of nodes how do you do that efficiently if you look at you know gigaflop machines they had hundreds of nodes and each node had effectively a processor a core a thread of application we're looking at many many tens of thousands of nodes cores parallel threads running how do you make that efficient so is the software ready i think the majority of people will tell you that it's the software that's the problem not the hardware of course my friends in hardware would tell you ah software is easy it's the hardware that's the problem i think for the universities and the users the challenge is going to be the software i think um it's going to have to evolve you you're just you want to look at your machine and you just want to be able to dump work onto it easily we're not there yet not by a long stretch of the imagination yeah consequently you know we one of the things that we're doing is that we have a lot of centers of excellence is we will provide well i hate say the word provide we we sell super computers and once the machine has gone in we work very closely with the establishments create centers of excellence to get the best out of the machines to improve the software um and if a machine's expensive you want to get the most out of it that you can you don't just want to run a synthetic benchmark and say look i'm the fastest supercomputer on the planet you know your users who want access to it are the people that really decide how useful it is and the work they get out of it yeah the economics is definitely a factor in fact the fastest supercomputer in the planet but you can't if you can't afford to use it what good is it uh you mentioned power uh and then the flip side of that coin is of course cooling you can reduce the power consumption but but how challenging is it to cool these systems um it's an engineering problem yeah we we have you know uh data centers in iceland where it gets um you know it doesn't get too warm we have a big air cooled data center in in the united kingdom where it never gets above 30 degrees centigrade so if you put in water at 40 degrees centigrade and it comes out at 50 degrees centigrade you can cool it by just pumping it round the air you know just putting it outside the building because the building will you know never gets above 30 so it'll easily drop it back to 40 to enable you to put it back into the machine um right other ways to do it um you know is to take the heat and use it commercially there's a there's a lovely story of they take the hot water out of the supercomputer in the nordics um and then they pump it into a brewery to keep the mash tuns warm you know that's that's the sort of engineering i can get behind yeah indeed that's a great application talk a little bit more about your conversation with professor parsons maybe we could double click into that what are some of the things that you're going to you're going to probe there what are you hoping to learn so i think some of the things that that are going to be interesting to uncover is just the breadth of science that can be uh that could take advantage of exascale you know there are there are many things going on that uh that people hear about you know we people are interested in um you know the nobel prize they might have no idea what it means but the nobel prize for physics was awarded um to do with research into black holes you know fascinating and truly insightful physics um could it benefit from exascale i have no idea uh i i really don't um you know one of the most profound pieces of knowledge in in the last few hundred years has been the theory of relativity you know an austrian patent clerk wrote e equals m c squared on the back of an envelope and and voila i i don't believe any form of exascale computing would have helped him get there any faster right that's maybe flippant but i think the point is is that there are areas in terms of weather prediction climate prediction drug discovery um material knowledge engineering uh problems that are going to be unlocked with the use of exascale class systems we are going to be able to provide more tools more insight [Music] and that's the purpose of computing you know it's not that it's not the data that that comes out and it's the insight we get from it yeah i often say data is plentiful insights are not um ben you're a bit of an industry historian so i've got to ask you you mentioned you mentioned mentioned gigaflop gigaflops before which i think goes back to the early 1970s uh but the history actually the 80s is it the 80s okay well the history of computing goes back even before that you know yes i thought i thought seymour cray was you know kind of father of super computing but perhaps you have another point of view as to the origination of high performance computing [Music] oh yes this is um this is this is one for all my colleagues globally um you know arguably he says getting ready to be attacked from all sides arguably you know um computing uh the parallel work and the research done during the war by alan turing is the father of high performance computing i think one of the problems we have is that so much of that work was classified so much of that work was kept away from commercial people that commercial computing evolved without that knowledge i uh i have done in in in a previous life i have done some work for the british science museum and i have had the great pleasure in walking through the the british science museum archives um to look at how computing has evolved from things like the the pascaline from blaise pascal you know napier's bones the babbage's machines uh to to look all the way through the analog machines you know what conrad zeus was doing on a desktop um i think i think what's important is it doesn't matter where you are is that it is the problem that drives the technology and it's having the problems that requires the you know the human race to look at solutions and be these kicks started by you know the terrible problem that the us has with its nuclear stockpile stewardship now you've invented them how do you keep them safe originally done through the ascii program that's driven a lot of computational advances ultimately it's our quest for knowledge that drives these machines and i think as long as we are interested as long as we want to find things out there will always be advances in computing to meet that need yeah and you know it was a great conversation uh you're a brilliant guest i i love this this this talk and uh and of course as the saying goes success has many fathers so there's probably a few polish mathematicians that would stake a claim in the uh the original enigma project as well i think i think they drove the algorithm i think the problem is is that the work of tommy flowers is the person who took the algorithms and the work that um that was being done and actually had to build the poor machine he's the guy that actually had to sit there and go how do i turn this into a machine that does that and and so you know people always remember touring very few people remember tommy flowers who actually had to turn the great work um into a working machine yeah super computer team sport well ben it's great to have you on thanks so much for your perspectives best of luck with your conversation with professor parsons we'll be looking forward to that and uh and thanks so much for coming on thecube a complete pleasure thank you and thank you everybody for watching this is dave vellante we're celebrating exascale day you're watching the cube [Music]

>>C G technology is focused on data where we have long believed that data is in our DNA. We help maximize humanity's potential by delivering world class, precision engineered data solutions developed through sustainable and profitable partnerships. Included in our offerings are hard disk drives. As I'm sure many of you know, ah, hard drive consists of a slider also known as a drive head or transducer attached to a head gimbal assembly. I had stack assembly made up of multiple head gimbal assemblies and a drive enclosure with one or more platters, or just that the head stacked assembles into. And while the concept hasn't changed, hard drive technology has progressed well beyond the initial five megabytes, 500 quarter inch drives that Seagate first produced. And, I think 1983. We have just announced in 18 terabytes 3.5 inch drive with nine flatters on a single head stack assembly with dual head stack assemblies this calendar year, the complexity of these drives further than need to incorporate Edge analytics at operation sites, so G Edward stemming established the concept of continual improvement and everything that we do, especially in product development and operations and at the end of World War Two, he embarked on a mission with support from the US government to help Japan recover from its four time losses. He established the concept of continual improvement and statistical process control to the leaders of prominent organizations within Japan. And because of this, he was honored by the Japanese emperor with the second order of the sacred treasure for his teachings, the only non Japanese to receive this honor in hundreds of years. Japan's quality control is now world famous, as many of you may know, and based on my own experience and product development, it is clear that they made a major impact on Japan's recovery after the war at Sea Gate. The work that we've been doing and adopting new technologies has been our mantra at continual improvement. As part of this effort, we embarked on the adoption of new technologies in our global operations, which includes establishing machine learning and artificial intelligence at the edge and in doing so, continue to adopt our technical capabilities within data science and data engineering. >>So I'm a principal engineer and member of the Operations and Technology Advanced Analytics Group. We are a service organization for those organizations who need to make sense of the data that they have and in doing so, perhaps introduce a different way to create an analyzed new data. Making sense of the data that organizations have is a key aspect of the work that data scientist and engineers do. So I'm a project manager for an initiative adopting artificial intelligence methodologies for C Gate manufacturing, which is the reason why I'm talking to you today. I thought I'd start by first talking about what we do at Sea Gate and follow that with a brief on artificial intelligence and its role in manufacturing. And I'd like them to discuss how AI and machine Learning is being used at Sea Gate in developing Edge analytics, where Dr Enterprise and Cooper Netease automates deployment, scaling and management of container raised applications. So finally, I like to discuss where we are headed with this initiative and where Mirant is has a major role in case some of you are not conversant in machine learning, artificial intelligence and difference outside some definitions. To cite one source, machine learning is the scientific study of algorithms and statistical bottles without computer systems use to effectively perform a specific task without using explicit instructions, relying on patterns and inference Instead, thus, being seen as a subset of narrow artificial intelligence were analytics and decision making take place. The intent of machine learning is to use basic algorithms to perform different functions, such as classify images to type classified emails into spam and not spam, and predict weather. The idea and this is where the concept of narrow artificial intelligence comes in, is to make decisions of a preset type basically let a machine learn from itself. These types of machine learning includes supervised learning, unsupervised learning and reinforcement learning and in supervised learning. The system learns from previous examples that are provided, such as images of dogs that are labeled by type in unsupervised learning. The algorithms are left to themselves to find answers. For example, a Siris of images of dogs can be used to group them into categories by association that's color, length of coat, length of snout and so on. So in the last slide, I mentioned narrow a I a few times, and to explain it is common to describe in terms of two categories general and narrow or weak. So Many of us were first exposed to General Ai in popular science fiction movies like 2000 and One, A Space Odyssey and Terminator General Ai is a I that can successfully perform any intellectual task that a human can. And if you ask you Lawn Musk or Stephen Hawking, this is how they view the future with General Ai. If we're not careful on how it is implemented, so most of us hope that is more like this is friendly and helpful. Um, like Wally. The reality is that machines today are not only capable of weak or narrow, a I AI that is focused on a narrow, specific task like understanding, speech or finding objects and images. Alexa and Google Home are becoming very popular, and they can be found in many homes. Their narrow task is to recognize human speech and answer limited questions or perform simple tasks like raising the temperature in your home or ordering a pizza as long as you have already defined the order. Narrow. AI is also very useful for recognizing objects in images and even counting people as they go in and out of stores. As you can see in this example, so artificial intelligence supplies, machine learning analytics inference and other techniques which can be used to solve actual problems. The two examples here particle detection, an image anomaly detection have the potential to adopt edge analytics during the manufacturing process. Ah, common problem in clean rooms is spikes in particle count from particle detectors. With this application, we can provide context to particle events by monitoring the area around the machine and detecting when foreign objects like gloves enter areas where they should not. Image Anomaly detection historically has been accomplished at sea gate by operators in clean rooms, viewing each image one at a time for anomalies, creating models of various anomalies through machine learning. Methodologies can be used to run comparative analyses in a production environment where outliers can be detected through influence in an automated real Time analytics scenario. So anomaly detection is also frequently used in machine learning to find patterns or unusual events in our data. How do you know what you don't know? It's really what you ask, and the first step in anomaly detection is to use an algorithm to find patterns or relationships in your data. In this case, we're looking at hundreds of variables and finding relationships between them. We can then look at a subset of variables and determine how they are behaving in relation to each other. We use this baseline to define normal behavior and generate a model of it. In this case, we're building a model with three variables. We can then run this model against new data. Observations that do not fit in the model are defined as anomalies, and anomalies can be good or bad. It takes a subject matter expert to determine how to classify the anomalies on classify classification could be scrapped or okay to use. For example, the subject matter expert is assisting the machine to learn the rules. We then update the model with the classifications anomalies and start running again, and we can see that there are few that generate these models. Now. Secret factories generate hundreds of thousands of images every day. Many of these require human toe, look at them and make a decision. This is dull and steak prone work that is ideal for artificial intelligence. The initiative that I am project managing is intended to offer a solution that matches the continual increased complexity of the products we manufacture and that minimizes the need for manual inspection. The Edge Rx Smart manufacturing reference architecture er, is the initiative both how meat and I are working on and sorry to say that Hamid isn't here today. But as I said, you may have guessed. Our goal is to introduce early defect detection in every stage of our manufacturing process through a machine learning and real time analytics through inference. And in doing so, we will improve overall product quality, enjoy higher yields with lesser defects and produce higher Ma Jin's. Because this was entirely new. We established partnerships with H B within video and with Docker and Amaranthus two years ago to develop the capability that we now have as we deploy edge Rx to our operation sites in four continents from a hardware. Since H P. E. And in video has been an able partner in helping us develop an architecture that we have standardized on and on the software stack side doctor has been instrumental in helping us manage a very complex project with a steep learning curve for all concerned. To further clarify efforts to enable more a i N M l in factories. Theobald active was to determine an economical edge Compute that would access the latest AI NML technology using a standardized platform across all factories. This objective included providing an upgrade path that scales while minimizing disruption to existing factory systems and burden on factory information systems. Resource is the two parts to the compute solution are shown in the diagram, and the gateway device connects to see gates, existing factory information systems, architecture ER and does inference calculations. The second part is a training device for creating and updating models. All factories will need the Gateway device and the Compute Cluster on site, and to this day it remains to be seen if the training devices needed in other locations. But we do know that one devices capable of supporting multiple factories simultaneously there are also options for training on cloud based Resource is the stream storing appliance consists of a kubernetes cluster with GPU and CPU worker notes, as well as master notes and docker trusted registries. The GPU nodes are hardware based using H B E l 4000 edge lines, the balance our virtual machines and for machine learning. We've standardized on both the H B E. Apollo 6500 and the NVIDIA G X one, each with eight in video V 100 GP use. And, incidentally, the same technology enables augmented and virtual reality. Hardware is only one part of the equation. Our software stack consists of Docker Enterprise and Cooper Netease. As I mentioned previously, we've deployed these clusters at all of our operations sites with specific use. Case is planned for each site. Moran Tous has had a major impact on our ability to develop this capability by offering a stable platform in universal control plane that provides us, with the necessary metrics to determine the health of the Kubernetes cluster and the use of Dr Trusted Registry to maintain a secure repository for containers. And they have been an exceptional partner in our efforts to deploy clusters at multiple sites. At this point in our deployment efforts, we are on prem, but we are exploring cloud service options that include Miranda's next generation Docker enterprise offering that includes stack light in conjunction with multi cluster management. And to me, the concept of federation of multi cluster management is a requirement in our case because of the global nature of our business where our operation sites are on four continents. So Stack Light provides the hook of each cluster that banks multi cluster management and effective solution. Open source has been a major part of Project Athena, and there has been a debate about using Dr CE versus Dr Enterprise. And that decision was actually easy, given the advantages that Dr Enterprise would offer, especially during a nearly phase of development. Cooper Netease was a natural addition to the software stack and has been widely accepted. But we have also been a work to adopt such open source as rabbit and to messaging tensorflow and tensor rt, to name three good lab for developments and a number of others. As you see here, is well, and most of our programming programming has been in python. The results of our efforts so far have been excellent. We are seeing a six month return on investment from just one of seven clusters where the hardware and software cost approached close to $1 million. The performance on this cluster is now over three million images processed per day for their adoption has been growing, but the biggest challenge we've seen has been handling a steep learning curve. Installing and maintaining complex Cooper needs clusters in data centers that are not used to managing the unique aspect of clusters like this. And because of this, we have been considering adopting a control plane in the cloud with Kubernetes as the service supported by Miranda's. Even without considering, Kubernetes is a service. The concept of federation or multi cluster management has to be on her road map, especially considering the global nature of our company. Thank you.

(upbeat electronic music) >> Narrator: From theCUBE studios in Palo Alto and Boston, connecting with thought leaders all around the world, this is a CUBE conversation. >> Okay, hello everyone. I'm John Furrier with theCUBE. We're here with Meet the Analysts segment Sunday morning. We've got everyone around the world here to discuss a bit of the news around the EU killing the privacy deal, striking it down, among other topics around, you know, data privacy and global commerce. We got great guests here, Ray Wang, CEO of Constellation Research. Bill Mew, founder and CEO of Cyber Crisis Management from the Firm Crisis Team. And JD, CEO of Spearhead Management. JD, I can let you say your name because I really can't pronounce it. How do I (laughs) pronounce it, doctor? >> I wouldn't even try it unless you are Dutch, otherwise it will seriously hurt your throat. (Ray laughing) So, JD works perfect for me. >> Doctor Drooghaag. >> And Sarbjeet Johal, who's obviously an influencer, a cloud awesome native expert. Great, guys. Great to have you on, appreciate it, thanks for comin' on. And Bill, thank you for initiating this, I appreciate all your tweets. >> Happy Sunday. (Bill laughing) >> You guys have been really tweeting up a storm, I want to get everyone together, kind of as an analyst, Meet the Analyst segment. Let's go through with it. The news is the EU and U.S. Privacy Shield for data struck down by the court, that's the BBC headline. Variety of news, different perspectives, you've got an American perspective and you've got an international perspective. Bill, we'll start with you. What does this news mean? I mean, basically half the people in the world probably don't know what the Privacy Shield means, so why is this ruling so important, and why should it be discussed? >> Well, thanks to sharing between Europe and America, it's based on a two-way promise that when data goes from Europe to America, the Americans promise to respect our privacy, and when data goes form America to Europe, the Europeans promise to respect the American privacy. Unfortunately, there are big cultural differences between the two blocks. The Europeans have a massive orientation around privacy as a human right. And in the U.S., there's somewhat more of a prioritization on national security, and therefore for some time there's been a mismatch here, and it could be argued that the Americans haven't been living up to their promise because they've had various different laws, and look how much talk about FISA and the Cloud Act that actually contravene European privacy and are incompatible with the promise Americans have given. That promise, first of all, was in the form of a treaty called Safe Harbor. This went to court and was struck down. It was replaced by Privacy Shield, which was pretty much the same thing really, and that has recently been to the court as well, and that has been struck down. There now is no other means of legally sharing data between Europe and America other than what are being called standard contractual clauses. This isn't a broad treaty between two nations, these are drawn by each individual country. But also in the ruling, they said that standard contractual clauses could not be used by any companies that were subject to mass surveillance. And actually in the U.S., the FISA courts enforce a level of mass surveillance through all of the major IT firms, of all major U.S. telcos, cloud firms, or indeed, social media firms. So, this means that for all of the companies out there and their clients, business should be carrying on as usual apart from if you're one of those major U.S. IT firms, or one of their clients. >> So, why did this come about? Was there like a major incident? Why now, was it in the court, stuck in the courts? Were people bitchin' and moanin' about it? Why did this go down, what's the real issue? >> For those of us who have been following this attentively, things have been getting more and more precarious for a number of years now. We've had a situation where there are different measures being taken in the U.S., that have continued to erode the different protections that there were for Europeans. FISA is an example that I've given, and that is the sort of secret courts and secret warrants that are issued to seize data without anyone's knowledge. There's the Cloud Act, which is a sort of extrajudicial law that means that warrants can be served in America to U.S. organizations, and they have to hand over data wherever that data resides, anywhere in the world. So, data could exist on a European server, if it was under the control of an American company, they'd have to hand that over. So, whilst FISA is in direct conflict with the promises that the Americans made, things like the Cloud Act are not only in controversion with the promise they've made, there's conflicting law here, because if you're a U.S. subsidiary of a big U.S. firm, and you're based in Europe, who do you obey, the European law that says you can't hand it over because of GDPR, or the American laws that says they've got extrajudicial control, and that you've got to hand it over. So, it's made things a complete mess. And to say has this stuff, hasn't really happened? No, there's been a gradual erosion, and this has been going through the courts for a number of years. And many of us have seen it coming, and now it just hit us. >> So, if I get you right in what you're saying, it's basically all this mishmash of different laws, and there's no coherency, and consistency, is that the core issue? >> On the European side you could argue there's quite a lot of consistency, because we uphold people's privacy, in theory. But there have been incidents which we could talk about with that, but in theory, we hold your rights dear, and also the rights of Europeans, so everyone's data should be safe here from the sort of mass surveillance we're seeing. In the U.S., there's more of a direct conflict between everything, including there's been a, in his first week in the White House, Donald Trump signed an executive order saying that the Privacy Act in the U.S., which had been the main protection for people in the U.S., no longer applied to non-U.S. citizens. Which was, if you wanted try and cause a storm, and if you wanted to try and undermine the treaty, there's no better way of doing it than that. >> A lot of ways, Ray, I mean simplify this for me, because I'm a startup, I'm hustlin', or I'm a big company, I don't even know who runs the servers anymore, and I've got data stored in multiple clouds, I got in regions, and Oracle just announced more regions, you got Amazon, a gazillion regions, I could be on-premise. I mean bottom line, what is this about? I mean, and -- >> Bill's right, I mean when Max Schrems, the Austrian. Bill's right, when Max Schrems the Austrian activist actually filed his case against Facebook for where data was being stored, data residency wasn't as popular. And you know, what it means for companies that are in the cloud is that you have to make sure your data's being stored in the region, and following those specific region rules, you can't skirt those rules anymore. And I think the cloud companies know that this has been coming for some time, and that's why there's been announced in a lot of regions, a lot of areas that are actually happening, so I think that's the important part. But going back to Bill's earlier point, which is important, is America is basically the Canary Islands of privacy, right? Privacy is there, but it isn't there in a very, very explicit sense, and I think we've been skirting the rules for quite some time, because a lot of our economy depends on that data, and the marketing of the data. And so we often confuse privacy with consent, and also with value exchange, and I think that's part of the problem of what's going on here. Companies that have been building their business models on free data, free private data, free personally identifiable data information are the ones that are at risk! And I think that's what's going on here. >> It's the classic Facebook issue, you're the product, and the data is your product. Well, I want to get into what this means, 'cause my personal take away, not knowing the specifics, and just following say, cyber security for instance, one of the tenets there is that data sharing is an invaluable, important ethos in the community. Now, everyone has their own privacy, or security data, they don't want to let everyone know about their exploits but, but it's well known in the security world that sharing data with each other, different companies and countries is actually a good thing. So, the question that comes in my mind, is this really about data sharing or data privacy, or both? >> I think it's about both. And actually what the ruling is saying here is, all we're asking from the European side is please stop spying on us and please give us a level of equal protection that you give to your own citizens. Because data comes from America to Europe, whatever that data belongs to, a U.S. citizen or a European citizen, it's given equal protection. It is only if data goes in the other direction, where you have secret courts, secret warrants, seizure of data on this massive scale, and also a level of lack of equivalence that has been imposed. And we're just asking that once you've sorted out a few of those things, we'd say everything's back on the table, away we go again! >> Why don't we merge the EU with the United States? Wouldn't that solve the problem? (Bill laughing) >> We just left Europe! (laughs heartily) >> Actually I always -- >> A hostile takeover of the UK maybe, the 52nd state. (Bill laughing loudly) >> I always pick on Bill, like Bill, you got all screaming loud and clear about all these concerns, but UKs trying to get out of that economic union. It is a union at the end of the day, and I think the problem is the institutional mismatch between the EU and U.S., U.S. is old democracy, bigger country, population wise, bigger economy. Whereas Europe is several countries trying to put together, band together as one entity, and the institutions are new, like you know, they're 15 years old, right? They're maturing. I think that's where the big mismatch is and -- >> Well, Ray, I want to get your thoughts on this, Ray wrote a book, I forget what year it was, this digital disruption, basically it was digital transformation before it was actually a trend. I mean to me it's like, do you do the process first and then figure out where the value extraction is, and this may be a Silicon Valley or an American thing, but go create value, then figure out how to create process or understand regulations. So, if data and entrepreneurship is going to be a new modern era of value, why wouldn't we want to create a rule based system that's open and enabling, and not restrictive? >> So, that's a great point, right? And the innovation culture means you go do it first, and you figure out the rules later, and that's been a very American way of getting things done, and very Silicon Valley in our perspective, not everyone, but I think in general that's kind of the trend. I think the challenge here is that we are trading privacy for security, privacy for convenience, privacy for personalization, right? And on the security level, it's a very different conversation than what it is on the consumer end, you know, personalization side. On the security side I think most Americans are okay with a little bit of "spying," at least on your own side, you know, to keep the country safe. We're not okay with a China level type of spying, which we're not sure exactly what that means or what's enforceable in the courts. We look like China to the Europeans in the way we treat privacy, and I think that's the perspective we need to understand because Europeans are very explicit about how privacy is being protected. And so this really comes back to a point where we actually have to get to a consent model on privacy, as to knowing what data is being shared, you have the right to say no, and when you have the right to say no. And then if you have a value exchange on that data, then it's really like sometimes it's monetary, sometimes it's non-monetary, sometimes there's other areas around consensus where you can actually put that into place. And I think that's what's missing at this point, saying, you know, "Do we pay for your data? Do we explicitly get your consent first before we use it?" And we haven't had that in place, and I think that's where we're headed towards. And you know sometimes we actually say privacy should be a human right, it is in the UN Charter, but we haven't figured out how to enforce it or talk about it in the digital age. And so I think that's the challenge. >> Okay, people, until they lose it, they don't really understand what it means. I mean, look at Americans. I have to say that we're idiots on this front, (Bill chuckling) but you know, the thing is most people don't even understand how much value's getting sucked out of their digital exhaust. Like, our kids, TikTok and whatnot. So I mean, I get that, I think there's some, there's going to be blow back for America for sure. I just worry it's going to increase the cost of doing business, and take away from the innovation for citizen value, the people, because at the end of the day, it's for the people right? I mean, at the end of the day it's like, what's my privacy mean if I lose value? >> Even before we start talking about the value of the data and the innovation that we can do through data use, you have to understand the European perspective here. For the European there's a level of double standards and an erosion of trust. There's double standards in the fact that in California you have new privacy regulations that are slightly different to GDPR, but they're very much GDPR like. And if the boot was on the other foot, to say if we were spying on Californians and looking at their personal data, and contravening CCPA, the Californians would be up in arms! Likewise if we having promised to have a level of equality, had enacted a local rule in Europe that said that when data from America's over here, actually the privacy of Americans counts for nothing, we're only going to prioritize the privacy of Europeans. Again, the Americans would be up in arms! And therefore you can see that there are real double standards here that are a massive issue, and until those addressed, we're not going to trust the Americans. And likewise, the very fact that on a number of occasions Americans have signed up to treaties and promised to protect our data as they did with Safe Harbor, as they did with Privacy Shield, and then have blatantly, blatantly failed to do so means that actually to get back to even a level playing field, where we were, you have a great deal of trust to overcome! And the thing from the perspective of the big IT firms, they've seen this coming for a long time, as Ray was saying, and they sought to try and have a presence in Europe and other things. But the way this ruling has gone is that, I'm sorry, that isn't going to be sufficient! These big IT firms based in the U.S. that have been happy to hand over data, well some of them maybe more happy than others, but they all need to hand over data to the NSA or the CIA. They've been doing this for some time now without actually respecting this data privacy agreement that has existed between the two trading blocks. And now they've been called out, and the position now is that the U.S. is no longer trusted, and neither are any of these large American technology firms. And until the snooping stops and equality is introduced, they can now no longer, even from their European operations, they can no longer use standard contractual clauses to transfer data, which is going to be a massive restriction on their business. And if they had any sense, they'd be lobbying very, very hard right now to the Senate, to the House, to try and persuade U.S. lawmakers actually to stick to some these treaties! To stop introducing really mad laws that ride roughshod over other people's privacy, and have a certain amount of respect. >> Let's let JD weigh in, 'cause he just got in, sorry on the video, I made him back on a host 'cause he dropped off. Just, Bill, real quick, I mean I think it's like when, you know, I go to Europe there's the line for Americans, there's the line for EU. Or EU and everybody else. I mean we might be there, but ultimately this has to be solved. So, JD, I want to let you weigh in, Germany has been at the beginning forefront of privacy, and they've been hardcore, and how's this all playing out in your perspective? >> Well, the first thing that we have to understand is that in Germany, there is a very strong law for regulation. Germans panic as soon as they know regulation, so they need to understand what am I allowed to do, and what am I not allowed to do. And they expect the same from the others. For the record I'm not German, but I live in Germany for some 20 years, so I got a bit of a feeling for them. And that sense of need for regulation has spread very fast throughout the European Union, because most of the European member states of the European Union consider this, that it makes sense, and then we found that Britain had already a very good framework for privacy, so GDPR itself is very largely based on what the United Kingdom already had in place with their privacy act. Moving forward, we try to find agreement and consensus with other countries, especially the United States because that's where most of the tech providers are, only to find out, and that is where it started to go really, really bad, 2014, when the mass production by Edward Snowden came out, to find out it's not data from citizens, it's surveillance programs which include companies. I joined a purchasing conference a few weeks ago where the purchase of a large European multinational, where the purchasing director explicitly stated that usage of U.S. based tech providers for sensitive data is prohibited as a result of them finding out that they have been under surveillance. So, it's not just the citizens, there's mass -- >> There you have it, guys! We did trust you! We did have agreements there that you could have abided by, but you chose not to, you chose to abuse our trust! And you're now in a position where you are no longer trusted, and unless you can lobby your own elected representatives to actually recreate a level playing field, we're not going to continue trusting you. >> So, I think really I -- >> Well I mean that, you know, innovation has to come from somewhere, and you know, has to come from America if that's the case, you guys have to get on board, right? Is that what it -- >> Innovation without trust? >> Is that the perspective? >> I don't think it's a country thing, I mean like, it's not you or them, I think everybody -- >> I'm just bustin' Bill's chops there. >> No, but I think everybody, everybody is looking for what the privacy rules are, and that's important. And you can have that innovation with consent, and I think that's really where we're going to get to. And this is why I keep pushing that issue. I mean, privacy should be a fundamental right, and how you get paid for that privacy is interesting, or how you get compensated for that privacy if you know what the explicit value exchange is. What you're talking about here is the surveillance that's going on by companies, which shouldn't be happening, right? That shouldn't be happening at the company level. At the government level I can understand that that is happening, and I think those are treaties that the governments have to agree upon as to how much they're going to impinge on our personal privacy for the trade off for security, and I don't think they've had those discussions either. Or they decided and didn't tell any of their citizens, and I think that's probably more likely the case. >> I mean, I think what's happening here, Bill, you guys were pointing out, and Ray, you articulated there on the other side, and my kind of colorful joke aside, is that we're living a first generation modern sociology problem. I mean, this is a policy challenge that extends across multiple industries, cyber security, citizen's rights, geopolitical. I mean when would look, and even when we were doing CUBE events overseas in Europe, in North American companies we'd call it abroad, we'd just recycle the American program, and we found there's so much localization value. So, Ray, this is the digital disruption, it's the virtualization of physical for digital worlds, and it's a lot of network theory, which is computer science, a lot of sociology. This is a modern challenge, and I don't think it so much has a silver bullet, it's just that we need smart people working on this. That's my take away! >> I think we can describe the ideal endpoint being somewhere we have meaningful protection alongside the maximization of economic and social value through innovation. So, that should be what we would all agree would be the ideal endpoint. But we need both, we need meaningful protection, and we need the maximization of economic and social value through innovation! >> Can I add another axis? Another axis, security as well. >> Well, I could -- >> I put meaningful protection as becoming both security and privacy. >> Well, I'll speak for the American perspective here, and I won't speak, 'cause I'm not the President of the United States, but I will say as someone who's been from Silicon Valley and the east coast as a technical person, not a political person, our lawmakers are idiots when it comes to tech, just generally. (Ray laughing) They're not really -- (Bill laughing loudly) >> They really don't understand. They really don't understand the tech at all! >> So, the problem is -- >> I'm not claiming ours are a great deal better. (laughs) >> Well, this is why I think this is a modern problem. Like, the young people I talk to are like, "Why do we have this rules?" They're all lawyers that got into these positions of Congress on the American side, and so with the American JEDI Contract you guys have been following very closely is, it's been like the old school Oracle, IBM, and then Amazon is leading with an innovative solution, and Microsoft has come in and re-pivoted. And so what you have is a fight for the digital future of citizenship! And I think what's happening is that we're in a massive societal transition, where the people in charge don't know what the hell they're talkin' about, technically. And they don't know who to tap to solve the problems, or even shape or frame the problems. Now, there's pockets of people that are workin' on it, but to me as someone who looks at this saying, it's a pretty simple solution, no one's ever seen this before. So, there's a metaphor you can draw, but it's a completely different problem space because it's, this is all digital, data's involved. >> We've got a lobbyists out there, and we've got some tech firms spending an enormous amount of lobbying. If those lobbyists aren't trying to steer their representatives in the right direction to come up with law that aren't going to massively undermine trade and data sharing between Europe and America, then they're making a big mistake, because we got here through some really dumb lawmaking in the U.S., I mean, there are none of the laws in Europe that are a problem here. 'Cause GDPR isn't a great difference, a great deal different from some of the laws that we have already in California and elsewhere. >> Bill, Bill. >> The laws that are at issue here -- >> Bill, Bill! You have to like, back up a little bit from that rhetoric that EU is perfect and U.S. is not, that's not true actually. >> I'm not saying we're perfect! >> No, no, you say that all the time. >> But I'm saying there's a massive lack of innovation. Yeah, yeah. >> I don't, I've never said it! >> Arm wrestle! >> Yes, yes. >> When I'm being critical of some of the dumb laws in the U.S, (Sarbjeet laughing) I'm not saying Europe is perfect. What we're trying to say is that in this particular instance, I said there was an equal balance here between meaningful protection and the maximization of economic and social value. On the meaningful protection side, America's got it very wrong in terms of the meaningful protection it provides to civil European data. On the maximization of economic and social value, I think Europe's got it wrong. I think there are a lot of things we could do in Europe to actually have far more innovation. >> Yeah. >> It's a cultural issue. The Germans want rules, that's what they crave for. America's the other way, we don't want rules, I mean, pretty much is a rebel society. And that's kind of the ethos of most tech companies. But I think you know, to me the media, there's two things that go on with this tech business. The company's themselves have to be checked by say, government, and I believe in not a lot of regulation, but enough to check the power of bad actors. Media so called "checking power", both of these major roles, they don't really know what they're talking about, and this is back to the education piece. The people who are in the media so called "checking power" and the government checking power assume that the companies are bad. Right, so yeah, because eight out of ten companies like Amazon, actually try to do good things. If you don't know what good is, you don't really, (laughs) you know, you're in the wrong game. So, I think media and government have a huge education opportunity to look at this because they don't even know what they're measuring. >> I support the level of innovation -- >> I think we're unreeling from the globalization. Like, we are undoing the globalization, and that these are the side effects, these conflicts are a side effect of that. >> Yeah, so all I'm saying is I support the focus on innovation in America, and that has driven an enormous amount of wealth and value. What I'm questioning here is do you really need to spy on us, your allies, in order to help that innovation? And I'm starting to, I mean, do you need mass surveillance of your allies? I mean, I can see you may want to have some surveillance of people who are a threat to you, but wait, guys, we're meant to be on your side, and you haven't been treating our privacy with a great deal of respect! >> You know, Saudi Arabia was our ally. You know, 9/11 happened because of them, their people, right? There is no ally here, and there is no enemy, in a way. We don't know where the rogue actors are sitting, like they don't know, they can be within the walls -- >> It's well understood I think, I agree, sorry. it's well understood that nation states are enabling terrorist groups to take out cyber attacks. That's well known, the source enables it. So, I think there's the privacy versus -- >> I'm not sure it's true in your case that it's Europeans that's doing this though. >> No, no, well you know, they share -- >> I'm a former officer in the Royal Navy, I've stood shoulder to shoulder with my U.S. counterparts. I put my life on the line on NATO exercises in real war zones, and I'm now a disabled ex-serviceman as a result of that. I mean, if I put my line on the line shoulder to shoulder with Americans, why is my privacy not respected? >> Hold on -- >> I feel it's, I was going to say actually that it's not that, like even the U.S., right? Part of the spying internally is we have internal actors that are behaving poorly. >> Yeah. >> Right, we have Marxist organizations posing as, you know, whatever it is, I'll leave it at that. But my point being is we've got a lot of that, every country has that, every country has actors and citizens and people in the system that are destined to try to overthrow the system. And I think that's what that surveillance is about. The question is, we don't have treaties, or we didn't have your explicit agreements. And that's why I'm pushing really hard here, like, they're separating privacy versus security, which is the national security, and privacy versus us as citizens in terms of our data being basically taken over for free, being used for free. >> John: I agree with that. >> That I think we have some agreement on. I just think that our governments haven't really had that conversation about what surveillance means. Maybe someone agreed and said, "Okay, that's fine. You guys can go do that, we won't tell anybody." And that's what it feels like. And I don't think we deliberately are saying, "Hey, we wanted to spy on your citizens." I think someone said, "Hey, there's a benefit here too." Otherwise I don't think the EU would have let this happen for that long unless Max had made that case and started this ball rolling, so, and Edward Snowden and other folks. >> Yeah, and I totally support the need for security. >> I want to enter the -- >> I mean we need to, where there are domestic terrorists, we need to stop them, and we need to have local action in UK to stop it happening here, and in America to stop it happening there. But if we're doing that, there is absolutely no need for the Americans to be spying on us. And there's absolutely no need for the Americans to say that privacy applies to U.S. citizens only, and not to Europeans, these are daft, it's just daft! >> That's a fair point. I'm sure GCHQ and everyone else has this covered, I mean I'm sure they do. (laughs) >> Oh, Bill, I know, I've been involved, I've been involved, and I know for a fact the U.S. and the UK are discussing I know a company called IronNet, which is run by General Keith Alexander, funded by C5 Capital. There's a lot of collaboration, because again, they're tryin' to get their arms around how to frame it. And they all agree that sharing data for the security side is super important, right? And I think IronNet has this thing called Iron Dome, which is essentially like they're saying, hey, we'll just consistency around the rules of shared data, and we can both, everyone can have their own little data. So, I think there's recognition at the highest levels of some smart people on both countries. (laughs) "Hey, let's work together!" The issue I have is just policy, and I think there's a lot of clustering going on. Clustered here around just getting out of their own way. That's my take on that. >> Are we a PG show? Wait, are we a PG show? I just got to remember that. (laughs) (Bill laughing) >> It's the internet, there's no regulation, there's no rules! >> There's no regulation! >> The European rules or is it the American rules? (Ray laughing) >> I would like to jump back quickly to the purpose of the surveillance, and especially when mass surveillance is done under the cover of national security and terror prevention. I worked with five clients in the past decade who all have been targeted under mass surveillance, which was revealed by Edward Snowden, and when they did their own investigation, and partially was confirmed by Edward Snowden in person, they found out that their purchasing department, their engineering department, big parts of their pricing data was targeted in mass surveillance. There's no way that anyone can explain me that that has anything to do with preventing terror attacks, or finding the bad guys. That is economical espionage, you cannot call it in any other way. And that was authorized by the same legislation that authorizes the surveillance for the right purposes. I'm all for fighting terror, and anything that can help us prevent terror from happening, I would be the first person to welcome it. But I do not welcome when that regulation is abused for a lot of other things under the cover of national interest. I understand -- >> Back to the lawmakers again. And again, America's been victim to the Chinese some of the individual properties, well documented, well known in tech circles. >> Yeah, but just 'cause the Chinese have targeted you doesn't give you free right to target us. >> I'm not saying that, but its abuse of power -- >> If the U.S. can sort out a little bit of reform, in the Senate and the House, I think that would go a long way to solving the issues that Europeans have right now, and a long way to sort of reaching a far better place from which we can all innovate and cooperate. >> Here's the challenge that I see. If you want to be instrumenting everything, you need a closed society, because if you have a free country like America and the UK, a democracy, you're open. If you're open, you can't stop everything, right? So, there has to be a trust, to your point, Bill. As to me that I'm just, I just can't get my arms around that idea of complete lockdown and data surveillance because I don't think it's gettable in the United States, like it's a free world, it's like, open. It should be open. But here we've got the grids, and we've got the critical infrastructure that should be protected. So, that's one hand. I just can't get around that, 'cause once you start getting to locking down stuff and measuring everything, that's just a series of walled gardens. >> So, to JD's point on the procurement data and pricing data, I have been involved in some of those kind of operations, and I think it's financial espionage that they're looking at, financial security, trying to figure out a way to track down capital flows and what was purchased. I hope that was it in your client's case, but I think it's trying to figure out where the money flow is going, more so than trying to understand the pricing data from competitive purposes. If it is the latter, where they're stealing the competitive information on pricing, and data's getting back to a competitor, that is definitely a no-no! But if it's really to figure out where the money trail went, which is what I think most of those financial analysts are doing, especially in the CIA, or in the FBI, that's really what that probably would have been. >> Yeah, I don't think that the CIA is selling the data to your competitors, as a company, to Microsoft or to Google, they're not selling it to each other, right? They're not giving it to each other, right? So, I think the one big problem I studied with FISA is that they get the data, but how long they can keep the data and how long they can mine the data. So, they should use that data as exhaust. Means like, they use it and just throw it away. But they don't, they keep mining that data at a later date, and FISA is only good for five years. Like, I learned that every five years we revisit that, and that's what happened this time, that we renewed it for six years this time, not five, for some reason one extra year. So, I think we revisit all these laws -- >> Could be an election cycle. >> Huh? >> Could be an election cycle maybe. (laughs) >> Yes, exactly! So, we revisit all these laws with Congress and Senate here periodically just to make sure that they are up to date, and that they're not infringing on human rights, or citizen's rights, or stuff like that. >> When you say you update to check they're not conflicting with anything, did you not support that it was conflicting with Privacy Shield and some of the promises you made to Europeans? At what point did that fail to become obvious? >> It does, because there's heightened urgency. Every big incident happens, 9/11 caused a lot of new sort of like regulations and laws coming into the picture. And then the last time, that the Russian interference in our election, that created some sort of heightened urgency. Like, "We need to do something guys here, like if some country can topple our elections, right, that's not acceptable." So, yeah -- >> And what was it that your allies did that caused you to spy on us and to downgrade our privacy? >> I'm not expert on the political systems here. I think our allies are, okay, loose on their, okay, I call it village politics. Like, world is like a village. Like it's so only few countries, it's not millions of countries, right? That's how I see it, a city versus a village, and that's how I see the countries, like village politics. Like there are two camps, like there's Russia and China camp, and then there's U.S. camp on the other side. Like, we used to have Russia and U.S., two forces, big guys, and they managed the whole world balance somehow, right? Like some people with one camp, the other with the other, right? That's how they used to work. Now that Russia has gone, hold on, let me finish, let me finish. >> Yeah. >> Russia's gone, there's this void, right? And China's trying to fill the void. Chinese are not like, acting diplomatic enough to fill that void, and there's, it's all like we're on this imbalance, I believe. And then Russia becomes a rogue actor kind of in a way, that's how I see it, and then they are funding all these bad people. You see that all along, like what happened in the Middle East and all that stuff. >> You said there are different camps. We thought we were in your camp! We didn't expect to be spied on by you, or to have our rights downgraded by you. >> No, I understand but -- >> We thought we were on your side! >> But, but you have to guys to trust us also, like in a village. Let me tell you, I come from a village, that's why I use the villager as a hashtag in my twitter also. Like in village, there are usually one or two families which keep the village intact, that's our roles. >> Right. >> Like, I don't know if you have lived in a village or not -- >> Well, Bill, you're making some great statements. Where's the evidence on the surveillance, where can people find more information on this? Can you share? >> I think there's plenty of evidence, and I can send some stuff on, and I'm a little bit shocked given the awareness of the FISA Act, the Cloud Act, the fact that these things are in existence and they're not exactly unknown. And many people have been complaining about them for years. I mean, we've had Safe Harbor overturned, we've had Privacy Shield overturned, and these weren't just on a whim! >> Yeah, what does JD have in his hand? I want to know. >> The Edward Snowden book! (laughs) >> By Edward Snowden, which gives you plenty. But it wasn't enough, and it's something that we have to keep in mind, because we can always claim that whatever Edward Snowden wrote, that he made it up. Every publication by Edward Snowden is an avalanche of technical confirmation. One of the things that he described about the Cisco switches, which Bill prefers to quote every time, which is a proven case, there were bundles of researchers saying, "I told you guys!" Nobody paid attention to those researchers, and Edward Snowden was smart enough to get the mass media representation in there. But there's one thing, a question I have for Sabjeet, because in the two parties strategy, it is interesting that you always take out the European Union as part. And the European Union is a big player, and it will continue to grow. It has a growing amount of trade agreements with a growing amount of countries, and I still hope, and I think think Bill -- >> Well, I think the number of countries is reducing, you've just lost one! >> Only one. (Bill laughing loudly) Actually though, those are four countries under one kingdom, but that's another point. (Bill chortling heartily) >> Guys, final topic, 5G impact, 'cause you mentioned Cisco, couldn't help think about -- >> Let me finish please my question, John. >> Okay, go ahead. How would you the United States respond if the European Union would now legalize to spy on everybody and every company, and every governmental institution within the United States and say, "No, no, it's our privilege, we need that." How would the United States respond? >> You can try that and see economically what happens to you, that's how the village politics work, you have to listen to the mightier than you, and we are economically mightier, that's the fact. Actually it's hard to swallow fact for, even for anybody else. >> If you guys built a great app, I would use it, and surveil all you want. >> Yeah, but so this is going to be driven by the economics. (John laughing) But the -- >> That's exactly what John said. >> This is going to be driven by the economics here. The big U.S. cloud firms are got to find this ruling enormously difficult for them, and they are inevitably going to lobby for a level of reform. And I think a level of a reform is needed. Nobody on your side is actually arguing very vociferously that the Cloud Act and the discrimination against Europeans is actually a particularly good idea. The problem is that once you've done the reform, are we going to believe you when you say, "Oh, it's all good now, we've stopped it!" Because with Crypto AG scandal in Switzerland you weren't exactly honest about what you were doing. With the FISA courts, so I mean FISA secret courts, the secret warrants, how do we know and what proof can we have that you've stopped doing all these bad things? And I think one of the challenges, A, going to be the reform, and then B, got to be able to show that you actually got your act together and you're now clean. And until you can solve those two, many of your big tech companies are going to be at a competitive disadvantage, and they're going to be screaming for this reform. >> Well, I think that, you know, General Mattis said in his book about Trump and the United states, is that you need alliances, and I think your point about trust and executing together, without alliances, it really doesn't work. So, unless there's some sort of real alliance, (laughs) like understanding that there's going to be some teamwork here, (Bill laughing) I don't think it's going to go anywhere. So, otherwise it'll continue to be siloed and network based, right? So to the village point, if TikTok can become a massively successful app, and they're surveilling, so and then we have to decide that we're going to put up with that, I mean, that's not my decision, but that's what's goin' on here. It's like, what is TikTok, is it good or bad? Amazon sent out an email, and they've retracted it, that's because it went public. I guarantee you that they're talkin' about that at Amazon, like, "Why would we want infiltration by the Chinese?" And I'm speculating, I have no data, I'm just saying, you know. They email those out, then they pull it back, "Oh, we didn't mean to send that." Really, hmm? (laughs) You know, so this kind of -- >> But the TRA Balin's good, you always want to get TRA Balin out there. >> Yeah, exactly. There's some spying going on! So, this is the reality. >> So, John, you were talking about 5G, and I think you know, the role of 5G, you know, the battle between Cisco and Huawei, you just have to look at it this way, would you rather have the U.S. spy on you, or would you rather have China? And that's really your binary choice at this moment. And you know both is happening, and so the question is which one is better. Like, the one that you're in alliance with? The one that you're not in alliance with, the one that wants to bury you, and decimate your country, and steal all your secrets and then commercialize 'em? Or the one kind of does it, but doesn't really do it explicitly? So, you've got to choose. (laughs) >> It's supposed to be -- >> Or you can say no, we're going to create our own standard for 5G and kick both out, that's an option. >> It's probably not as straightforward a question as, or an answer to that question as you say, because if we were to fast-forward 50 years, I would argue that China is going to be the largest trading nation in the world. I believe that China is going to have the upper hand on many of these technologies, and therefore why would we not want to use some of their innovation, some of their technology, why would we not actually be more orientated around trading with them than we might be with the U.S.? I think the U.S. is throwing its weight around at this moment in time, but if we were to fast-forward I think looking in the longterm, if I had to put my money on Huawei or some of its competitors, I think given its level of investments in research and whatever, I think the better longterm bet is Huawei. >> No, no, actually you guys need to pick a camp. It's a village again. You have to pick a camp, you can't be with both guys. >> Global village. >> Oh, right, so we have to go with the guys that have been spying on us? >> How do you know the Chinese haven't been spying on you? (Ray and John laughing loudly) >> I think I'm very happy, you find a backdoor in the Huawei equipment and you show it to us, we'll take them to task on it. But don't start bullying us into making decisions based on what-ifs. >> I don't think I'm, I'm not qualified to represent the U.S., but what we would want to say is that if you look at the dynamics of what's going on, China, we've been studying that as well in terms of the geopolitical aspects of what happens in technology, they have to do what they're doing right now. Because in 20 years our population dynamics go like this, right? You've got the one child policy, and they won't have the ability to go out and fight for those same resources where they are, so what they're doing makes sense from a country perspective and country policy. But I think they're going to look like Japan in 20 years, right? Because the xenophobia, the lack of immigration, the lack of inside stuff coming in, an aging population. I mean, those are all factors that slow down your economy in the long run. And the lack of bringing new people in for ideas, I mean that's part of it, they're a closed system. And so I think the longterm dynamics of every closed system is that they tend to fail versus open systems. So, I'm not sure, they may have better technology along the way. But I think a lot of us are probably in the camp now thinking that we're not going to aid and abet them, in that sense to get there. >> You're competing a country with a company, I didn't say that China had necessarily everything rosy in its future, it'll be a bigger economy, and it'll be a bigger trading partner, but it's got its problems, the one child policy and the repercussions of that. But that is not one of the things, Huawei, I think Huawei's a massively unlimited company that has got a massive lead, certainly in 5G technology, and may continue to maintain a lead into 6G and beyond. >> Oh yeah, yeah, Huawei's done a great job on the 5G side, and I don't disagree with that. And they're ahead in many aspects compared to the U.S., and they're already working on the 6G technologies as well, and the roll outs have been further ahead. So, that's definitely -- >> And they've got a great backer too, the financer, the country China. Okay guys, (Ray laughing) let's wrap up the segment. Thanks for everyone's time. Final thoughts, just each of you on this core issue of the news that we discussed and the impact that was the conversation. What's the core issue? What should people think about? What's your solution? What's your opinion of how this plays out? Just final statements. We'll start with Bill, Ray, Sarbjeet and JD. >> All I'm going to ask you is stop spying on us, treat us equally, treat us like the allies that we are, and then I think we've got to a bright future together! >> John: Ray? >> I would say that Bill's right in that aspect in terms of how security agreements work, I think that we've needed to be more explicit about those. I can't represent the U.S. government, but I think the larger issue is really how do we view privacy, and how we do trade offs between security and convenience, and you know, what's required for personalization, and companies that are built on data. So, the sooner we get to those kind of rules, an understanding of what's possible, what's a consensus between different countries and companies, I think the better off we will all be a society. >> Yeah, I believe the most important kind of independence is the economic independence. Like, economically sound parties dictate the terms, that's what U.S. is doing. And the smaller countries have to live with it or pick the other bigger player, number two in this case is China. John said earlier, I think, also what JD said is the fine balance between national security and the privacy. You can't have, you have to strike that balance, because the rogue actors are sitting in your country, and across the boundaries of the countries, right? So, it's not that FISA is being fought by Europeans only. Our internal people are fighting that too, like how when you are mining our data, like what are you using it for? Like, I get concerned too, when you can use that data against me, that you have some data against me, right? So, I think it's the fine balance between security and privacy, we have to strike that. Awesome. JD? I'll include a little fake check, fact check, at the moment China is the largest economy, the European Union is the second largest economy, followed directly by the USA, it's a very small difference, and I recommend that these two big parties behind the largest economy start to collaborate and start to do that eye to eye, because if you want to balance the economical and manufacturing power of China, you cannot do that as being number two and number three. You have to join up forces, and that starts with sticking with the treaties that you signed, and that has not happened in the past, almost four years. So, let's go back to the table, let's work on rules where from both sides the rights and the privileges are properly reflected, and then do the most important thing, stick to them! >> Yep, I think that's awesome. I think I would say that these young kids in high school and college, they need to come up and solve the problems, this is going to be a new generational shift where the geopolitical landscape will change radically, you mentioned the top three there. And new alliances, new kinds of re-imagination has to be there, and from America's standpoint I'll just say that I'd like to see lawmakers have, instead of a LinkedIn handle, a GitHub handle. You know, when they all go out on campaign talk about what code they've written. So, I think having a technical background or some sort of knowledge of computer science and how the internet works with sociology and societal impact will be critical for our citizenships to advance. So, you know rather a lawyer, right so? (laughs) Maybe get some law involved in that, I mean the critical lawyers, but today most people are lawyers in American politics, but show me a GitHub handle of that congressman, that senator, I'd be impressed. So, that's what we need. >> Thanks, good night! >> Ray, you want to say something? >> I wanted to say something, because I thought the U.S. economy was 21 trillion, the EU is sittin' at about 16, and China was sitting about 14, but okay, I don't know. >> You need to do math man. >> Hey, we went over our 30 minutes time, we can do an hour with you guys, so you're still good. (laughs) >> Can't take anymore. >> No go on, get in there, go at it when you've got something to say. >> I don't think it's immaterial the exact size of the economy, I think that we're better off collaborating on even and fair terms, we are -- >> We're all better off collaborating. >> Yeah. >> Gentlemen -- >> But the collaboration has to be on equal and fair terms, you know. (laughs) >> How do you define fair, good point. Fair and balanced, you know, we've got the new -- >> We did define fair, we struck a treaty! We absolutely defined it, absolutely! >> Yeah. >> And then one side didn't stick to it. >> We will leave it right there, and we'll follow up (Bill laughing) in a later conversation. Gentlemen, you guys are good. Thank you. (relaxing electronic music)

(upbeat techno music) >> Announcer: From New York City, it's theCUBE, covering New Relic FutureStack 2019, brought to you by the New Relic. >> Hi, I'm Stu Miniman and this is theCUBE's exclusive coverage of New Relic's Futurestack 2019 here in New York City, seventh year of the show. Our first year here, about 600 or so in attendance, and real excited, because we've had some of the users here to help kick off our coverage. And joining us, first time guest on the program, Josh Biggely is a senior engineer of Enterprise Monitoring, with Cardinal Health coming to us from a little bit further north and east than I do, Prince Edward Island, thank you so much for coming here to New York City and joining me on the program. >> Yeah, thanks for having me Stu, I'm excited to be here. I haven't been in New York, it's probably been more two decades. So it's nice to be back in a big city, I live in a very small place. >> Yeah, so if you go to Times Square, it's now Disneyland, is what we call it. It's not the 42nd street that it might've been a couple of decades ago. I grew up about 45 minutes from here, so it's gone through a lot, love the city, especially gorgeous weather we're having here in the fall. >> I'm excited for it. >> All right, so Josh, Cardinal Health, health is in the name so we think we understand a little bit about it, but tell us a little bit about the organization itself and how it's going through changes these days. >> Sure, so Cardinal Health is a global healthcare solutions provider. We are essential to care, which means we deliver the products and solutions that your healthcare providers need to literally cure disease, keep people healthy. So we're in 85% of the hospitals in the United States, 26,000 pharmacies, about 3,000,000 different home healthcare users receive products from us. Again we're global, so we're based in Dublin, Ohio, just outside of Columbus. But obviously, I live in Canada so I work for the Cardinal Health Canada Division. We've got acquisitions around the world. So yeah, it's an exciting company. We've recently gone through a transformation not only as a company, but from a technology side where we've shifted one of our data centers entirely into the cloud. >> All right, and Josh, your role inside the company, tell us a little bit about, you said it's global, what's under your purview? >> So my team is responsible for Enterprise Monitoring, and that means that we develop, deploy, support and integrate solutions for monitoring both infrastructure applications and digital experience for our customers. We have a number of tools, including New Relic, that we use. But it's a broad scope for a small team. >> Stu: Okay, and you've talked about that transformation. Walk us through a little bit about that, what led to, as you said, some big moves into public cloud? >> Yeah, our team is part of an overall effort to allow Cardinal Health to be more adaptive, to be more agile. The move to cloud allows teams that are developing applications and platforms to make a decision how to respond to the needs of their customers more rapidly. Gone are the days of, "I need a new server, "I need to predict six months from now "that I'm going to need a new server, "put the order in, get it delivered, "get it racked, get it wired." We watch a lot of people, the provision on demand. I mean, our senior vice president, or my senior vice president, likes to say, "I want you to fail fast, fail cheap." He does not say fail often. Although sometimes I do that, but that's okay. As long as you recognize that you're failing and can roll that back, redeploy, It's been really transformative for my team in particular, who was very infrastructure focused when I started with the company five years ago. >> Stu: All right, and can you bring us inside from your application portfolio, was it a set of applications, was it an entire data center? What moved over, how long did it take, and can you share what cloud you're using? >> Sure, so it's been about a two year journey. We're actually a multicloud company. We've got a small footprint in Azure, small footprint in AWS, but we're primarily in Google Cloud. We are shutting down one data center, we are minimizing another data center, and we've moved everything. We've moved everything from small bespoke applications that are targeted on team to entire ecommerce platforms and we've done everything from lift and shift, which I know you don't like to hear. But we've done lift and shift, we've done rehosting, we've done refactoring and we have re-architected entire platforms. >> Yeah, so if you could expand a little bit when we say lift and shift, I'm fine with lift and shift as long as there's another word or plan after that which I'm expecting you do have. >> Josh: Yeah, absolutely. So the lift and shift was, "Hey, let's move from our data centers into GCP. "Let's give teams the visibility, the observability "that they need so that they can make the decisions on "what they need to do best." In a lot of cases, or in fact, in 15% of the 6,500 severs that we touch, we actually full out decommed the instance. Teams had them, they were running at our data centers but they weren't actually providing any value to the company. >> So you said your team before was mostly concerned about infrastructure and a lot of what you did is now on GCP so you fired the entire team and you hired a bunch of PhDs to be able to manage Google environments? >> Absolutely not. (laughter) The principals of enterprise monitoring as a practice still apply in a cloud. We are, at heart, data geeks. And I would fair say that we're actually data story tellers. Our job is to give tools and methodologies to application teams who know what the data means in context, but we give the tools to provide that data to them. >> Stu: All right, love that. I believe I've actually seen data geek shirts at the the New Relic shows itself. But data story tellers, that was kind of thing that you heard, "I have a data scientist "that's going to help us to do this." Is that data scientist in New York or are you actually enabling who is able to tell those data stories today? >> So that is the unique part. Data story telling is not a data science. I wish that I could be a data scientist, I like math, but I'm not nearly that good at it. A data story teller takes the data and the narrative of the business, and weaves them together. When you tell someone, "Here's some data." They will look at it and they will develop their own narrative around it. But as a story teller you help craft that narrative for them. They're going to look at that data and they're going to feel it, They're going to understand it and it's going to motivate them to act in a way that is aligned with what the business objectives are. So data story tellers come in all forms. They come as monitoring engineers, they're app engineers, but they're also people who are facing the customer, they're business leaders, they're people in our distribution centers who are trying to understand the impacts of orders in their order flow, in their personnel that they have. It is a discipline that anyone can engage in if we're willing to give them the right tools. >> All right, so Josh, you got rid of a data center, you're minimizing a data center, you're shifting to cloud, you're making a lot of changes and now being able to tell data stories. Can you tell us organizationally everything goes smoothly or are their anythings that you learned along the way that maybe you could share with your peers to help them along that journey? And any rough spots, with hindsight being what it is, that you might be able to learn from? >> Yeah, so hindsight definitely 20/20. The one thing that I would say to folks is get your data right. Metadata, trusting your data is key, it's absolutely vital. We talk a lot about automation and automation is one of those things that the cloud enables very nicely. If you automate on garbage data, you are going to automate garbage generation. That was one of our struggles but I think that every organization struggles with data fidelity. But teams need to spend more time in making sure that their data, specifically their metadata, around, "Hey is this prod, is it non-prod, "what stack is this running, who built it?" Those things definitely need to be sorted out. >> Okay, talk about the observability and the monitoring that you do, how long have you been using New Relic and what products? And tell us a little about that journey. >> Sure, so we've been using New Relic for about two years. It was a bit of a slow run up to its adoption. We are a multi-tool company so we have a number of tools. Some of them are focused primarily on our network infrastructure, our on-prem storage. Although Cardinal had moved predominantly to the cloud, we have distribution centers, nuclear pharmacies all around the world. And those facilities have not gone into the cloud. So you've got network connectivity. New Relic for us has filled our cloud niche and observability, as Lou announced, is going to give us context to things that we're after. You hear the term dark data, we call them obs logs. It's data that we want to have, we only need it for a very short period of time to help us do post-op or RCAs as well as to look at, overall in our organization, the performance of the applications. For us, New Relic is going to give us an option to put data for observability. Observability is really about high fidelity data. In its world of cloud, everyone wants everything right now. And they also want it down to the millisecond. A platform that can pull that off, that's a remarkable thing. >> Yeah, Veruca Salt had it right, "I want it now." So are you using New Relic One yet? >> We have been using New Relic One for at least a couple of months going back into March this year. It's exciting, we're one of those companies that Lou talked about in his key note, we have hundreds of sub accounts. And we did so very intentfully, but it was a bit of a nightmare before we got to New Relic One. That ability for a platform team to see across multiple sub accounts, really powerful. >> Okay, so you saw a lot of announcements this morning. Anything particular that jumped out, you were excited? Because Lou kept saying over and over, and if you're using New Relic One, "This is free, this is free, this is free." That platform where it's all available for you now. >> I think the programmability is one of the things that really got me excited. One of the engineers on my team had a chance to go and sit with Lou and team, two weeks ago, and was part of that initial Hackathon. Made some really interesting things. That's exciting so shout out to Zack and the work he did. Logging, for me, is something that is huge. I know we've got data that we should have in context. So that Lou announced five terabytes of ingestion for free, all I could do was tap my fingers together and think, "Oh, okay. You're asking for it, Lou. Challenge accepted." (laughter) >> Stu: That's exciting, right. So you feel that you're going to be building apps, it sounds like already, at the FutureHack. That you're starting to move down that path. >> Definitely, and I'm really excited. Not to necessarily give it to my team. We build the patterns for teams that needs patterns, but there are so many talented individuals at Cardinal Health who, if we give them the patterns to follow, they're just going to go execute. Open sourcing that is a brilliant idea and really crowd sourcing development is the way to go. >> Yeah, I think you bring up a really interesting point. So even though your team might be the one that provides the platform, you're giving that programmability, sensibility to a broader audience inside the team and democratizing the data that you have in there. >> Yes, you keyed in on one of the things I love to talk about which is democratized access to data. Over and over again you'll hear me preach that, "I know what I know but I also know what I don't know "and more particular I don't know what I don't know. "I need other people to help me recognize that." >> We've really talked about that buzzword out there about digital transformation. When it is actually being happened, it goes from, "Oh, somebody had an opinion," to, "Wait, I actually now can actually get to the data, "and show you the data and leverage the data "to be able to take good actions on that." >> That's right, data driven decision making is not just just an idiom. It's not something that is a buzzword, it is a practice that we all need to follow. >> Stu: All right, so Josh, you're speaking here at the show. Give our audience just a quick taste, if you will, about what you're going to be sharing with your peers here at the show. >> We've actually talked about a lot of it already so I hope that people are not going to watch this session before my session later. But it really is around the power of additional transformation, the power of observability, what happens when you do things right, and the way the cloud makes teams more nimble. I won't give you it all because then people won't watch my session on Replay but, yeah, it'll be good. >> Well, definitely they should check that out. I'm hoping New Relic has that available on Replay. Give the final word here, what you're really hoping to come out of this week. Sounds like your team's deeply engaged, you've done the Hackathon, you're working with the executive teams. So FutureStack 2019, what are you hoping to walk away with? >> For me, it's about developing patterns. My team, in addition to our enterprise architecture team, is responsible for mapping out what we're going to do and how we're going to do it. Teams want to go fast and if we're not going to lay down the foundation for them to move quickly, especially in the realm of enterprise monitoring, they're going to try do it themselves. Which may or may not work. We don't want to turn teams away from using specific tools if it fits, but if there's a platform that will allow them to execute and to keep all that data centralized, that is really the key to observability. Having that high fidelity data, but then being able to ask questions, not just of the data you put in, but the data that put in maybe by a platform team or by a team that supported Kubernetes or PCF. >> All right, well, Josh Biggely, thank you so much for sharing all that you've been going through in Cardinal Health's transformation. Great to talk to you. >> Thanks so much, Stu. >> All right, lots more here at New Relic's FutureStack 2019. I'm Stu Miniman and as always, thank you for watching theCUBE. (light techno music)

>> From the SiliconANGLE Media office in Boston, Massachesetts, it's theCUBE. Now here's your host, Stu Miniman. >> Hi I'm Stu Miniman and this is a CUBE conversation from our Boston area studios. The ecosystem around data and analytics definitely isn't becoming any simpler today. Joining me for this segment is Drew Clarke who's the chief strategy officer at Qlik. And Drew let's start there, we talk about the wave of big data, a lot of them have wrapped themselves around the cloke of AI today, you've got machine learning in there. So help kinda give us a little bit about where Qlik fits into that ecosystem and differentiates itself from this very diverse ecosystem. >> Yeah, sure and I get that question a lot Stu is, who is Qlik and what makes us unique. And as a strategy, individual and professional, I spend a lot of time talking, working with customers that are looking at companies and I always come back to it like, what is that core kinda part? Every company comes from something and then how does it fit into the landscape, so I use actually our history to explain a little bit about who we are. So we're 25 years ago, or 25 years old and our very first customer was Tetrapak which make cardboard boxes, of all different sizes, so if you think about Amazon when you order something and you get it showed up at your, it shows up at your desktop or your door, it's in a different size box. Well Tetrapak had a problem of their sales people were selling inventory they didn't have. And they needed to be able to sell what they had, but they also wanted to make sure they showed what they did not have. So they signed on and had a project with Qlik. And this is in Sweden, and they developed a product which is really a product configurator tied with a visualization to it. So what they had the answer on a business question was, tell me what products are and are not available and be able to dynamically make selections as sales reps were answering the questions. So that was the genesis of our own kinda product, so we had a choice back then to say, do we stay in a product configurator space, or do we move into the visualization analytics? And so we took that unique kinda package, what we call the associative engine with the visual kinda piece and we went and started on the business intelligence or the analytics journey. And where we've kinda evolved that as a company is we took that, and another great example is another customer a couple of years ago there was the tsunami in Japan, do you remember that Stu? >> Of course. >> When that happened. So one of our customers was in the consumer products and they had a lot of supply or ingredients that came out of Japan. And they also knew that, okay, the tsunami hit, big impact on there supply chain, and they had to actually make an announcement, they had earnings on Wall Street, and they needed to be able to outline to their investors within the week to say, well is this a big impact, is this not a big impact on our forward looking revenues? And they tried answering the question using traditional analytics, you know, show me what products were impacted by the tsunami, and that's a first order question, as you know it's an easy question to ask. Well now you're going down into the ingredients, you're looking at where the data is in the supply chain and you come back with an answer that says these are the ones that are impacted. The next question that the business asks was okay, tell me what products were not affected. And now think about that is not question going through every single row. Oh and tell me what the inventory is, and can we run campaigns and sales where we know we're either A gonna miss our revenue numbers or we're gonna hit 'em. And they used the Qlik, they tried a different kinda traditional way of answering a question, they couldn't answer it 'cause they get stuck at that first. It was Qlik that actually entered and helped them answer the second question, show what products were not affected and do we have inventory, and they would be able to make that decision. And so that's where we start, what we makes us unique is this combination of analytics and visual kinda interface. And that's been kinda our core differentiator in the market from 25 years ago to where we are today. >> Yeah, and boy that history has changed quite a lot. Think about data visualization, we used to do infographics many years ago, just how do I tell a story with that data? There's the creative things you can do with it but as well as us as humans we look at all of those data points out there and most of the times it's not static, I love people when they're sharing, it's like okay, let me give you charts for something over a 100 year period, and you can watch it ebb and flow and change in the like, so there's so many technology. 25 years ago, cloud had many different terms, I can argue I've worked with plenty of people that we had the XSP back in the 90s and the pre-cloud things. But there's some challenges that we've been trying to solve and then some major breakthroughs we've had with some of these journeys and these technology waves, so bring us up to today as to, we talk about things like speed and scale and agility impacting what we're doing, it's got to be, you've got the why and the core, but the how and the what has changed dramatically. >> Stu you really are kind of a technical kinda guy at heart, right, so one of the things you said at the beginning there where you talked about looking at an infographic and the human kinda component of, how do you look at this information, how do you understand it? It's getting bigger and harder to understand. One of the things that we firmly believe in is the human being is an integral part of the decision making process. And so you think about a scatter plot with 30,000 data points, how do you actually make sense of it? And we spend a lot of time about the human brain and how it looks at information on this kinda big data scale and we're a predator as a human, we're binocular and we look for certain things, and so we spend a lot of time around that kinda visual interface. And I think Steven Few writes about this, Edward Tufte and his documentation around kinda how do you present information in a great way. Well, you take that 30,000 data points on a scatterplot, and well bringing it forward in our technology we show density in heat because that's what we look for. And we look for patterns, and we look for outliers as a predator as kind of an individual. And so we present the information in a way that a human is kinda wired to receive it, but underneath, and this is where I think you're second part was going, underneath is like how do you keep that elegance and responding to a kind of now compute and infrastructure and all the sides. >> Yeah and I guess I always worried is we talk about garbage in, garbage out sometimes. How do I make sure I've got good data, how do I make sure the algorithm is learning? There was a tool that was, oh let me train this AI on Twitter and what they got back they had to turn it off really quick because it became a troll and then much worse and the language was awful, so sometimes if you just let the data run wild the algorithm doesn't understand what's going on. How do you balance that and make sure we're getting good decisions and good information? And we say, if you automate a bad process you haven't done a good thing. >> Right, right. Well that comes through a number of layers from automation there's kinda the data, getting it from the raw source, getting it ready for the analytical consumption, and is it a machine, is it a human, is it a human augmented with kinda the intelligence? And as you progress through this data journey of bringing the data into now the common terms are data lakes and data swamps. How do you find the right information and where do you put the right kinda governance? And governance, not being a bad word, but governance being a, I'm confident that information is correct. And so you see the introduction of data catalogs, so much like a card catalog in a library if you're old enough to actually remember that. >> I know the Dewey Decimal System. >> Okay, there you go so I was a page, that was one of my first paying job was to put books back in the library. And you want to be able to find the right information and know that it's been curated, been set up, but it doesn't have to be written all out. You want to have that progressive kind of bringing of that information for the user to be able to do that. And as you kind of fan out from the central that raw data out to kinda where the analytics users are kinda engaging and working with it. That governance allows for that confidence, but then you need to know that you're scaling and the speed. You don't want to wait if you had a request. The decision just like, even what happened to that customer, tsunami happened, I have earnings on a set day in days from an event. I can't wait a month to come up with the answer. I need that speed, I need that faster. >> Alright, so who's the one inside the customer that work's on this, you know, we've all heard that there's skill gaps out there. Years ago it was like, okay we're going to build this giant army of data scientists. It's not like we're saying we don't need data scientists but we don't have enough time to train enough PhD's to fill the jobs. So where are we today, where do the customers fit organizationally, and if you can get into a little bit of where the product touches them? >> Sure, so what you bring up is the. Great interviewer, broad question, so many different ways we can go with this. And I come back to the idea of what a lot of people come and talk about is this citizen data scientist, but it's really about data literacy. And these are individuals who need to be comfortable working with data, and how do you actually have that confidence level of when I'm looking at it do I know is it real? Am I having the right conversation? Just recently I had the opportunity to see a number of presentations by college seniors who were presenting their senior thesis' on how they're working on a particular theme. And I was in this behavioral sciences and leadership department, it was at the United States Military Academy at Westpoint. And when you think about leadership and you think about behavioral sciences and you think about a lot of the softer side of it, but everyone of these cadets had data and you can see them looking at the empirical data, looking at the R coefficients, is this noise, is this signal, what's causation versus correlation. What you see is this language of data literacy in the curriculum and you flash forward and you look at every department in a company and you see people are coming in who understand there's data that can be used to be informing my decision so I don't need to wait for this white lab coat PhD on data science. It's like well, is there causation is there correlation? So marketing, finance, sales, we're seeing this at that data citizen at the edges in a company and it's coming out of the universities. >> Yeah I was at a conference recently and the analysts up on the keynote stage says, you want to teach your team machine learning? Get a summer intern that's taken the courses and have them spend a week training you up on it. So excellent, so sounds like if someone wants to get started with Qlik, relatively low bar. I don't have to go through some six month training class to be able to start getting some business value and rolling this out. >> Yeah, exactly. Stu, you can go right on our website and you can sign up and start to use our product right in the cloud. If you want to put it on a desktop you can do that. And you just drag in your first data files and I encourage you to actually bring in a complicated dataset. Don't go with a simple excel file, a lot of companies can do bars, charts, and graphs. But what you really want to do is bring in two different datasets and bring it into, and remember the associative engine of bringing different data together? And it's the second and third question that you're really looking for those insights. And so you can very quickly assemble the information. You don't need to go back and learn what a left outer joint is because our engine takes care of that for you. You want to understand what's going on? It's transparent. And then you start finding insights within minutes of being able to use that. >> Yeah well if you go back to the Hitchhikers Guide to the Galaxy, sometimes the answer's easy, I have to know the right questions to be able to ask. Alright, Drew I want to give you the final takeaway for this piece. >> Okay, so if you're thinking about dealing with any data and you want to answer not just the question, but it's usually the second and third, and you want to have a speed of use. You can do that with our platform, but think about it really in that concept of data literacy and you want that right information for the individuals to read and write, that's okay and it's easy. It's analyzing and arguing and that's where the competitive advantage so take a look at that. >> Alright, well Drew Clarke really appreciate the updates on Qlik and be sure to check out theCUBE.net. There's a nice little search bar on top, you can search by company, search by person, actually a lot of the key metadata you can search for in there. Thousands of videos in there. Never a registration to be able to get it. So I'm Stu Miniman and thanks as always for watching theCUBE. (upbeat 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

>> Live from Stanford University. It's the Cube covering global Women in Data Science conference brought to you by Silicon Angle media. >> Welcome back to the key. We air live at Stanford University for the fourth annual Women in Data Science Conference. The Cube has had the pleasure of being here all four years on I'm welcoming Back to the Cube, one of our distinguished alumni Janet George, the fellow chief data officer, scientists, big data and cognitive computing at Western Digital. Janet, it's great to see you. Thank you. Thank you so much. So I mentioned yes. Fourth, Annie will women in data science. And it's been, I think I met you here a couple of years ago, and we look at the impact. It had a chance to speak with Margo Garrett's in a about an hour ago, one of the co founders of Woods saying, We're expecting twenty thousand people to be engaging today with the Livestream. There are wigs events in one hundred and fifty locations this year, fifty plus countries expecting about one hundred thousand people to engage the attention. The focus that they have on data science and the opportunities that it has is really palpable. Tell us a little bit about Western Digital's continued sponsorship and what makes this important to you? >> So Western distal has recently transformed itself as a company, and we are a data driven company, so we are very much data infrastructure company, and I think that this momentum off A is phenomenal. It's just it's a foundational shift in the way we do business, and this foundational shift is just gaining tremendous momentum. Businesses are realizing that they're going to be in two categories the have and have not. And in order to be in the half category, you have started to embrace a You've got to start to embrace data. You've got to start to embrace scale and you've got to be in the transformation process. You have to transform yourself to put yourself in a competitive position. And that's why Vest Initial is here, where the leaders in storage worldwide and we'd like to be at the heart of their data is. >> So how has Western Digital transform? Because if we look at the evolution of a I and I know you're give you're on a panel tan, you're also giving a breakout on deep learning. But some of the importance it's not just the technical expertise. There's other really important skills. Communication, collaboration, empathy. How has Western digital transformed to really, I guess, maybe transform the human capital to be able to really become broad enough to be ableto tow harness. Aye, aye, for good. >> So we're not just a company that focuses on business for a We're doing a number of initiatives One of the initiatives were doing is a I for good, and we're doing data for good. This is related to working with the U. N. We've been focusing on trying to figure out how climate change the data that impacts climate change, collecting data and providing infrastructure to store massive amounts of species data in the environment that we've never actually collected before. So climate change is a huge area for us. Education is a huge area for us. Diversity is a huge area for us. We're using all of these areas as launching pad for data for good and trying to use data to better mankind and use a eye to better mankind. >> One of the things that is going on at this year's with second annual data fun. And when you talk about data for good, I think this year's Predictive Analytics Challenge was to look at satellite imagery to train the model to evaluate which images air likely tohave oil palm plantations. And we know that there's a tremendous social impact that palm oil and oil palm plantations in that can can impact, such as I think in Borneo and eighty percent reduction in the Oregon ten population. So it's interesting that they're also taking this opportunity to look at data for good. And how can they look at predictive Analytics to understand how to reduce deforestation like you talked about climate and the impact in the potential that a I and data for good have is astronomical? >> That's right. We could not build predictive models. We didn't have the data to put predictive boats predictive models. Now we have the data to put put out massively predictive models that can help us understand what change would look like twenty five years from now and then take corrective action. So we know carbon emissions are causing very significant damage to our environment. And there's something we can do about it. Data is helping us do that. We have the infrastructure, economies of scale. We can build massive platforms that can store this data, and then we can. Alan, it's the state at scale. We have enough technology now to adapt to our ecosystem, to look at disappearing grillers, you know, to look at disappearing insects, to look at just equal system that be living, how, how the ecosystem is going to survive and be better in the next ten years. There's a >> tremendous amount of power that data for good has, when often times whether the Cube is that technology conferences or events like this. The word trust issues yes, a lot in some pretty significant ways. And we often hear that data is not just the life blood of an organization, whether it's in just industry or academia. To have that trust is essential without it. That's right. No, go. >> That's right. So the data we have to be able to be discriminated. That's where the trust comes into factor, right? Because you can create a very good eh? I'm odder, or you can create a bad air more so a lot depends on who is creating the modern. The authorship of the model the creator of the modern is pretty significant to what the model actually does. Now we're getting a lot of this new area ofthe eyes coming in, which is the adversarial neural networks. And these areas are really just springing up because it can be creators to stop and block bad that's being done in the world next. So, for example, if you have malicious attacks on your website or hear militias, data collection on that data is being used against you. These adversarial networks and had built the trust in the data and in the so that is a whole new effort that has started in the latest world, which is >> critical because you mentioned everybody. I think, regardless of what generation you're in that's on. The planet today is aware of cybersecurity issues, whether it's H vac systems with DDOS attacks or it's ah baby boomer, who was part of the fifty million Facebook users whose data was used without their knowledge. It's becoming, I won't say accepted, but very much commonplace, Yes, so training the A I to be used for good is one thing. But I'm curious in terms of the potential that individuals have. What are your thoughts on some of these practices or concepts that we're hearing about data scientists taking something like a Hippocratic oath to start owning accountability for the data that they're working with. I'm just curious. What's >> more, I have a strong opinion on this because I think that data scientists are hugely responsible for what they are creating. We need a diversity of data scientists to have multiple models that are completely divorce, and we have to be very responsible when we start to create. Creators are by default, have to be responsible for their creation. Now where we get into tricky areas off, then you are the human auto or the creator ofthe Anay I model. And now the marshal has self created because it a self learned who owns the patent, who owns the copyright to those when I becomes the creator and whether it's malicious or non malicious right. And that's also ownership for the data scientist. So the group of people that are responsible for creating the environment, creating the morals the question comes into how do we protect the authors, the uses, the producers and the new creators off the original piece of art? Because at the end of the day, when you think about algorithms and I, it's just art its creation and you can use the creation for good or bad. And as the creation recreates itself like a learning on its own with massive amounts of data after an original data scientist has created the model well, how we how to be a confident. So that's a very interesting area that we haven't even touched upon because now the laws have to change. Policies have to change, but we can't stop innovation. Innovation has to go, and at the same time we have to be responsible about what we innovate >> and where do you think we are? Is a society in terms of catching As you mentioned, we can't. We have to continue innovation. Where are we A society and society and starting to understand the different principles of practices that have to be implemented in order for proper management of data, too. Enable innovation to continue at the pace that it needs. >> June. I would say that UK and other countries that kind of better than us, US is still catching up. But we're having great conversations. This is very important, right? We're debating the issues. We're coming together as a community. We're having so many discussions with experts. I'm sitting in so many panels contributing as an Aye aye expert in what we're creating. What? We see its scale when we deploy an aye aye, modern in production. What have we seen as the longevity of that? A marker in a business setting in a non business setting. How does the I perform and were now able to see sustained performance of the model? So let's say you deploy and am are in production. You're able inform yourself watching the sustained performance of that a model and how it is behaving, how it is learning how it's growing, what is its track record. And this knowledge is to come back and be part of discussions and part of being informed so we can change the regulations and be prepared for where this is going. Otherwise will be surprised. And I think that we have started a lot of discussions. The community's air coming together. The experts are coming together. So this is very good news. >> Theologian is's there? The moment of Edward is building. These conversations are happening. >> Yes, and policy makers are actively participating. This is very good for us because we don't want innovators to innovate without the participation of policymakers. We want the policymakers hand in hand with the innovators to lead the charter. So we have the checks and balances in place, and we feel safe because safety is so important. We need psychological safety for anything we do even to have a conversation. We need psychological safety. So imagine having a >> I >> systems run our lives without having that psychological safety. That's bad news for all of us, right? And so we really need to focus on the trust. And we need to focus on our ability to trust the data or a right to help us trust the data or surface the issues that are causing the trust. >> Janet, what a pleasure to have you back on the Cube. I wish we had more time to keep talking, but it's I can't wait till we talk to you next year because what you guys are doing and also your pact, true passion for data science for trust and a I for good is palpable. So thank you so much for carving out some time to stop by the program. Thank you. It's my pleasure. We want to thank you for watching the Cuba and Lisa Martin live at Stanford for the fourth annual Women in Data Science conference. We back after a short break.

(energetic music) >> Narrator: Live from San Juan, Puerto Rico, it's theCUBE, covering CoinAgenda. Brought to you by SiliconANGLE. >> Hello and welcome to our exclusive Puerto Rico coverage of CoinAgenda, I'm John Furrier with theCUBE. We're here covering all the action at Restart, we've got a ton of events, all the thoughts leaders, influencers, decision makers, you name it, in the industry, pioneers making it happen. My next guest is Toni Lane, who's the founder of CoinGraph. She's a true influencer with a lot of impact in this market. Welcome to theCUBE. >> Thank you for having me. >> We're so glad to have you on. Like the little joke at the beginning about being an influencer, you actually are an influencer. You've done such great work in the industry, well regarded in the community. You have publication and you do a lot of great content. Thanks for coming on. >> Oh, for sure, yeah, thanks for having me. >> So being the influencer, what does that mean these days? Because we were just talking before the camera on, we came on camera, influence changes. You can't be an influencer all the time. You can be super or expert at something, but your expertise could change, you move to a new topic, learn something. And there's a lot of people in the digital marketing world saying I'm an influencer. It's kind of half baked, and really, I mean, it's not about the followers, your thoughts? >> Well, I mean, most of those followers are purchased. So there's a big difference between being an influencer and having actual influence. Because if you're, you know, if you have a million followers on Twitter, that's nice. How much engagement do you have? And that's actually what you look for, it's like when you look at someone's, whether it's, you know, social media, their digital presence, it's not about followers, it's all about engagement. You know, I don't even have that many, like I don't spend a lot of time doing that, at least I haven't so far, it's something I'm getting more into. But I have people that are really engaged, and so I look at people that have 15 million followers and I'm like, you have just as many likes on your things as I do, right. Because these people aren't real people. And it's less about, having influence in general is in many ways about having authenticity. And so influence is your ability to get something done. Being an influencer is your ability to hold someone's attention for a fragment of time. But being an influencer is not the same as having influence. >> And this community here, certainly, with decentralization here, you get the decentralized applications coming up blockchain, you got ICOs booming. It's all about the network effect, if you look at network effect, that is a new concept that ad technology does not know because you can't cookie a network connection. The only way to measure someone's true network is through malware today, and that's not good, no one does that. Well, they do, they're-- >> Toni: Unfortunately, yeah. >> But you can't you do it at business price, not sustainable. So the point is, it's not about how many followers you have. It could be that one follower, maybe 200 or 2,000, that opens up more. This is the network effect. This is what this community is all about, so I want to get your thoughts on this community's vibe. A lot of mission-driven, impact-oriented, merged with tech. So you have a fusion of technology, artistry, craftsmanship and mission-driven societal change in one melting pot. This is your wheelhouse. Share your thoughts on this. >> Well, so all of the different digital currencies have different value systems and they attract a different breed. And there are different incentives for each of these based on how the technology is designed, each protocol, right? So if you look at Bitcoin, in Bitcoin, the incentives are, you know, mining is done by computers, so your only incentive is like having social influence? And this is, I think, why we've seen a lot of kind of I would call it a scarcity mentality in terms of the way, why we see even more trolls in Bitcoin is because social influence is a huge way that success is measured, because as a developer, you can't have, you can't achieve a level of status any other way as a developer or as an influencer in Bitcoin, because the Bitcoin network is so far removed from that. And that's actually a perverse incentive in and of itself, and not only that, but early days in Bitcoin, there were major organizations who would hire people to man 100 Reddit and Twitter accounts and go into the Bitcoin community and actually fragment the public opinion using a technique grassroots psychological insurgency. So buying Reddit accounts that had been active for the last 10 years and going through and, you know, essentially just stabbing at people and creating, even having conversations with themselves to empower the voice of trolls. And what happens is you start bringing out what we call, actually, what the former Assad called, after Henry Kissinger, there was a big move that happened in the Middle East, where Kissinger realized the Middle East was becoming too powerful, and he saw it as a threat to American democracy. And so Kissinger organized a deal that fragmented the Middle East. And Assad said to Kissinger that his actions would be, he played Assad, basically. And Assad said to Kissinger, "Your actions "will bring up demons hidden underneath "the surface of the Arab world." And that strategy is actually something used in the Bitcoin community to leverage the incentives that are created, which is why we have seen previously so much, even from our industry leaders, so much fragmentation and so much tension. But the network is the most secure and the least corruptible, hands down, fundamentally. It's real cryptography. >> But let's talk about that, I love this conversation, because with networks, you have the concept of self-heal, and this gets nerdy on the packets, how packets move, at that level, self-healing networks has been a paradigm that's been proven. So that's out there, that's got to go to a societal level. The other one is the incentive system, if you have an immune system, if you will, in a network, this is a cultural thing. So actions, the Reddit's obvious, right. Weaponizing content has been well-documented, it's coming now mainstream, people are getting it that this outcome was actually manufactured by bad behavior. Now, I argue that there's an exact opposite effect. You can actually weaponize for good, 'cause everything has a polar opposite. So what is your view on that, because this is something that we've been teasing out for the first time. How do you weaponize content for good, (mumbles) not the right word, but look for the opposite value? >> Right, yeah, I mean, it is in so many ways, right. So I think it's about, there's a professor at Stanford whose name is BJ Fogg, and he's a behavioral researcher and he talks about essentially, you know, he writes a lot about habits. But something that's even more interesting about his understanding of propaganda is I studied a lot of Edward Bernays, he's responsible, he created the theory of propaganda, right. And he's the nephew of Sigmund Freud, he's responsible for essentially every consumptive theory in like leading up to the last century, he's actually, I would say he's responsible for the state of advertising and the economy today, almost really single handedly. And what's fascinating about this theory is that you can use propaganda to get women to smoke by unearthing what it is unconsciously in men that makes them not want to smoke. You can also use propaganda to get people to invest in health and wellness. You can also use propaganda to get people to stop their bad habits. So it's understanding that a technique works in a cognitive capacity in a way that affects a large amount of people. And it's really about the intention behind why a person who has influence, as we were saying, is leveraging that relationship. So I would say it's more about-- >> So we have to reimagine influence. Because the signalings that are igniting the cognitive brain can be tweaked. So that's what you're getting at here, right, so that's what we have to do. >> And it's an illusion from almost every angle. It's even the idea that, in the United States, the level of influence the president has and who's running, you know, and who, yeah, and who's at the wheel, right. So it's, we live in a world that is built on manufactured consent, and manufactured consent is enabled through thinkers like Bernays and through what I call the illusion of things like our former construct of even American democracy. That these things we've imagined to be so, the foundation and the structure for the way that we live. All of those things have become so far removed from their theory that they're no longer serving the principles under which they were founded, and that disconnect is actually a huge, it's a gap, it's an inertia gap for exploitation or it's an inertia gap for growth, and usually what happens is you have the exploitation first. Someone says oh, here's a big gap of information asymmetry, so I'm going to exploit the information asymmetry. And then once people start realizing that that information asymmetry is being exploited, you experience a huge inversion of that and you have enough kind of, you have enough inertia behind that slingshot to launch it into something totally different. >> Yeah, this is a great concept, I interviewed the founder of the Halcyon HAL in Washington, DC, and she's an amazing woman. And she had a great conscious about this, and what she postulated was, bubbles that burst, exploitation's always, we've seen it in all trends. The underbelly, 'cause it's motivated, no dogma. They don't care about structural incentives, they just want to make cash. But she had an interesting theory, she was talking about you can let the air out of the bubble with community and data. So all the societal entrepreneurship activities now that are mission-driven, now getting back to mission-driven is interesting. There might be a way to actually avoid the pop. Because, depending upon what the backlash might be on the exploitation side, as we saw in the dotcom bubble, you can actually let the air out a little bit through things like data. I mean, how do you see, in your mind, just thinking out loud, how do you see that playing out, because we have community now. We have access to open data. Blockchain is all about immutability. It's all about power to the user's data. This is a mega trend. Your thoughts? >> So interdependence is huge in the blockchain community, and that's actually to touch back on the incentives in Bitcoin, I think that that's actually one of Bitcoin's, it's not that it's a wrong or a right, it just is, right, like sidechains will be launched eventually, but the idea that Ethereum created something that was adaptable and empowered people to be creative, and yet they're creating incentives for her people to launch products that are, I believe, 'causing, in some ways, could cause some serious harm to the ecosystem once the air is let out of that bubble. >> John: The data. >> The data, so data, yes yes yes. >> How do you let the air out of the bubble, because the pop will be massively implosion, it'll leave a crater. >> So data is a non-scarce resource. This is actually how I describe blockchain to people. And this is actually, I think, one of the, the challenge, if you want to look at it from the perspective of challenge, and then I'll talk about for the benefit, just between Bitcoin and Ethereum, there are obviously other blockchains, EOS is like coming out super soon, Holochain. There are tons, Steem has actually its own infrastructure, tons of other blockchains to speak about. But just to take these two main blockchains, which are not competitors. In Bitcoin, you have, it's really cryptography. Cryptography is not about, you know, like let's do some rapid prototyping, cryptography is about let's like put a lot of thought into this thing and have mathematical certainty that this is not exploitatable. And Ethereum is just kind of like, well, let's build a framework and then let people play as much as they can. And so there are challenges and benefits to both of those models, the challenge of Ethereum being that you've let all of this capital into the industry which is not actually, 46% of ICOs have already failed. Already failed. And then if you look at Bitcoin-- >> And a person with your industry (mumbles) at 1,200, so it's a 50% discount. >> Oh yeah, oh yeah. And then if you do the same thing and you're looking at the Bitcoin blockchain, we've seen that the capacity for innovation, Bitcoin could have done what, they could've been the first to market for what Ethereum is doing. And they chose a different route, and I think there are some pros and cons to both of those things, but I think there is an intentionality behind why the world played out in the way that it did. And I think it's the right strategy for both products. So the way I describe applications using blockchain technology to people and what I call the future of an infinite economy is that, if you think about why are Facebook and Google these multi billion dollars companies, it's really simple. It's because what do they own, right? The data, the data. And they're some of the last companies that are still stewarding these things in a way that is taking vast amount of aggregated ownership over an asset that people are generating every day that's extremely valuable to companies in the private sector. So the way that I describe blockchain is that, if we being to own our self-sovereign identity, then when we're owning our data, that's the foundation for universal basic income. If we take a non-scarce resource like data that's being generated every day, not just from us, right, but the data in the health of the ocean, right. The stewardship of the ocean, the health of the fish, actually saying okay, fish are thriving in this area, and so there's a healthy ecosystem, and so this coin is trading higher because we're stewarding this area of the ocean so we don't overfish. The quality of the air so that, when we're actually de-polluting the air collectively, everyone around us is creating and generating data to say we're making the air better. The air, actually, the health of our bodies, of our Earth, of our minds, of our planet, of even the health of our innovation. Right, what are the incentives behind our innovation, those are all forms of data. And that's a non-scarce resource, so if we take all of these different applications and make many different blockchains. Which I fundamentally believe that there's a powerful theory in having blockchains that are economically scarce, because I believe you're going to empower more diverse spectrums and also have a level of difficulty in creating the coin. You're going to have more innovation. And so-- >> Well, this is a key area. I mean, this is super important. Well, I mean, you step back for a second, you zoom out, you say okay, we have data, data's super valuable, if you take it to the individual's levels, which has not been, quite frankly, the individual's been exploited. Facebooks of the world, these siloed platforms, have been using the data for advertising. That's just what everyone knows, but there's other examples. The point is, when you put the data in the hands of the users, combine that with cloud computing and the Internet of Things when you can have an edge of the network high powered computer, the use cases have never been pushed before. The envelope that we're pushing now has never been in this configuration. You could never have a decentralized network, immutable, storing users' data, you've never had the ability to write the kind of software you can today, you've never had cloud computing, you've never had compute at the edge, which is where the users live, they are the edge. You have the ability where the user's role can enable a new kind of collective intelligence. This is like mind blowing. So I mean, just how would you explain that to a common person? I mean, 'cause this is the challenge, 'cause collective intelligence has been well documented in data science. User generated content is kind of the beginning of what we see in user wearables. But if you can control the data streaming into the network, with all the self-healing and all the geek stuff we're talking about, it's going to change structural things. How do you explain that to a normal person? >> You don't, you don't, right. So you show them. Because I can sit here all day and I can talk to you about, you know, I could talk to you about all of these things, but at the end of the day, with normal people, it's not something you want to explain. You want to show them, because with my, actually, my grandma gets Bitcoin. My grandma hit me up in like 2012 and she was like, "Do you know what that Bitcoin thing is?" I'm like, "Mimi," I'm like, "How do you know "what Bitcoin is, Mimi?" And she's just like, "I don't know, I read." You know, I was like, "This is, so what are you reading? "Like, are you hanging out on like libertarian forums, "like what's up?" And so-- >> What's going on in the club there, I mean, are they playing-- >> Yeah, but she is a really unique lady. So I would say that, for most people, they are not going to, when you explain things to people-- >> What would you show them, I mean, what's an example? >> The way that, so when I was, so I got into Bitcoin in 2011, and the way that I would explain Bitcoin to people is I would just send it to them. I would be like, "Here's Bitcoin, like take this Bitcoin, "here's some Bitcoin for you." And that was, people got it, because they were like, I have five dollars now in my hands that was not there. And this person just sent it to me. And for some people even still, you know, to be honest, even then, I remember how much energy it took for me to do that. Everywhere I go, I'd be like, in cabs, I'd be checking out grocery stores and I would try, I would essentially pitch Bitcoin to every person that I met. >> John: You were evangelizing a lot of it. >> It took so much energy though, and even after that, there was a period-- >> It was hard for people to receive it, they would have to do what at that time? Think about what the process was back then. >> Oh yeah. There were very few people who, even after doing that, really got it. But you know what happened. This is so much perspective for me, I remember doing that in 2013 and I remember, in 2018, actually, I think it was the end of 2017. I went to a gas station, it's the only gas station in San Francisco with a Bitcoin ATM. And I was like, I need to get some cash and I'm running on Bitcoin. >> John: You guys want a mountain view now. >> Yeah, yeah. And so I go in and these guys, I'm like frustrated, I'm like oh, the ATM is like the worst user experience ever, I'm like (groans). That's literally, I'm like, it's just, it was like eyes rolling in the back of my head, like just so frustrated because I'm a super privacy freak. And so it was just a super complex process, but the guys that, the guy's (mumbles) he looks at me and he goes, "Yo." And I was like, "What's up, man?" And he goes, "Are you trying to buy some Bitcoin?" I was like, "I'm trying to sell some Bitcoin right now." (John laughs) >> You're dispensing it, they're like yeah. >> Yeah, he's like, "Oh, word." And he's like, "How much are you trying to sell?" And I'm like, "I don't know, like 2K." And so he goes, "Aight." And he's like, "Let me hit up my friends," he literally calls three of his friends who come down and they just like, they're like, "Do you want to sell more?" They're like, all they just peer to peer. It's like we bypass the ATM and it was actually a peer to peer exchange. And I didn't have to explain anything. You know what made people get it? You showed them the money, you showed them the money. And sometimes people don't, you can explain these concepts that are world-changing, super high level or whatever. People are not actually going to get it until it's useful to them. And that's why a user interface is so important. Like, if you even look at the Internet. Who made the money on the Internet, right, it was the people who understood how to own the user interface. >> I had a conversation with Fred Kruger from WorkCoin, he's been around the block for a long time, great guy. We were riffing on the old days. But we talked about the killer app for the mini computer and the mainframe, the mini computer and then the PC, it was email, for 20 years, the killer app was email. We were like, what's the killer app for blockchain? It's money, the killer app is money. And it's going to be 50 year killer app. Now, the marketplace is certainly maybe tier two killer app, but the killer app is money. >> For sure, that's amazing. >> That's the killer app. Okay, so we're talking about money, let's talk about wallets and whatnot. There's a lot of people that I know personally that had been, wallets had been hacked. Double authentication (mumbles) news articles on this, but even early on, you got to protect yourself. It's something that you're an advocate of, I know recently, you've been sharing some stuff on Telegram. Share your thoughts on newbies coming in, be careful. Your wallet can be hacked, and you got to take care of yourself online. Is there a best practice, can you share some color commentary on when you get into the system, when you get Bitcoin or crypto, what are some of the best practices? >> It's not even, I think you need to remember a key principle of cryptography when you're dealing with digital currency, which was like don't really trust anything unless you call someone, you have like first hand verification from a person that you trust. Because these things are, I mean, I've had, literally last week, I had seven friends contact me, actually more than that once I posted about it, and they were like, "Is this you?" And I was like what, like people would literally just go online, they would scrape my Facebook photo, they'd go on Telegram and they would make, my name is @ToniLaneC, T-O-N-I-L-A-N-E-C, and so is my Twitter, and people would scrape my photos from my Twitter or my Telegram or my Facebook and they would create fake accounts. And they would start messaging people and say "Hey, like "what's up, how are you, that's cool, great, awesome. "So like, I need like 20 BTC for a loan. "Can you help me?" And all my friends were like, "I was just talking to you, is this you?" And I'm like no. And so I think that there's, the other thing you have to, it's not just security in terms of, and this is actually a problem Blockchain has to solve, right. It's not just security in terms of protecting your wallet and, you know, getting like a Ledger or a Trezor and making sure that you're keeping things like in cold storage, that you're going, there are so many, keeping your money in a hard wallet, not keeping your private keys on your computer, like keeping everything, storing your passwords in multiple places that you know are safe. Both handwritten, like in lock boxes, putting it in your safe deposit box or, you know, there are so many different ways that we can get into like the complexities of protecting yourself and security. Not using centralized cell networks is one of the big ways that I do this. Because if you are using two factor-- >> John: What's a centralized cell network? >> AT&T, Verizon, T-Mobile. Because you are putting yourself in a situation where, if you're using a centralized system, those centralized systems are really easily exploitable. I know because my mom, when I was a kid one time, she put a password on my account so I couldn't buy games. I was not happy about it, it was my money that I was using, it was my money I was using to buy games, she was like, "You should just spend your money on better things." And so I remember going in when I was a kid, and I was like, this is my money, I totally want to buy this upgrade on this game. And so I went in and I essentially figured out how to hack into my own phone to be able to use my own money to buy the games that I wanted to buy-- >> Highly motivated learning opportunity there (laughs). >> But I realized that, in the same way we were talking about things that can be used for good can be used for bad, in the same way that someone can do something like that, you can also say, well, I'm in a call and say that I'm this person and take their phone and then get their two factor auth. So I don't use centralized cell networks, I don't use cell networks at all. >> John: What do you use? >> So, I mean, I have different kinds of like strategies or different things that mostly-- >> You might not want to say it here, okay, all right. >> Yeah yeah yeah, they're different, I'm happy to talk about those privately. The way that I've kind of handled that situation, and then the other thing that I would say is like, we really need hardcore reputation systems in our industry and for the world. And not social reputation systems like what is happening in China right now, where you can have someone leave you, like let's say I get into an Uber and I'm 30 seconds late. I can end up in a situation where I'm like not able to be admitted into a hospital or I'm not able to take a public train. Because someone rates me lower on this reputation system, I think that's a huge human rights issue. >> John: Yeah, that's a huge problem. >> And so not reputation systems like this, but reputations like the one we're working on at CULTU.RE that are really based more on the idea of restoration and humanization, rather than continued social exploitation to create some kind of collective norm, I think that kind of model is, it's not only a-- >> Well, the network should reject that by-- >> Toni: Exactly, exactly. >> All right, so let's talk about digital nations, we have China, so there's some bad behavior going on there. I mean, some will argue that there's really no R&D over there, and now they're trying to export the R&D that they stole into other countries, again, that's my personal rant. But the innovation there is clear, we chat and other things are happening. They finally turned the corner where they're driving a lot of, you know, mainly because of the mobile. But there's other nations out there that are kind of left behind. The UK just signed this week with Coinbase a pretty instrumental landmark licensing deal, which is a signal, 'cause I know Estonia, Armenia, you name every country wants to, Bahrain's got, you know, Dubai envy. So I mean, every country wants to be the crypto country. Every country wants to be the smart cities digital nation. I know this is something that you liked, and you and I were talking about 'cause we both are interested in. Your reaction, your thoughts on where that's going, I see, it's a good sign. What are the thresholds there, what are some of the keys things that they need to do to be a real digital nation? >> Well, I think it's less about digital nations in terms of like a nation is a series of borders, and more about first nations that we are, this is what we work on at CULTU.RE, that we are actually a nation of people and a lot of those nations have overlap and we should be able to participate in many different nations who have many different economies that are all really cooperating interdependently to create the best possible life for all human good, rather than just saying like I care about me and mine, because that strategy, the way government works now, it's a closed network with low trust that is extremely inefficient in management of resources. And the only way you can really-- >> That's the opposite, by the way, of what this movement's about. >> Yeah, exactly. And the only way you can have influence in government is to go in government and to work through government. All right. So it's the idea that, look at how much food we waste in the United States. If we took the food we wasted in the United States and repurposed it, we could literally cure world hunger. That is how bad it has gotten, right. And there are people starving in the US. There are people on food stamps in the US. >> Well, I mean, every institution, education, healthcare, you name it, it's all, you know, FUBAR, big time. >> Yeah, but we're throwing away tons of lettuce and all of this different kinds of produce because it like looks funky. Like this peach looks a little too much like a bottom. So we're like not able to sell it. >> Or lettuce got a little brown on it, throw the whole thing away. >> Yes, exactly, exactly, and that waste is unacceptable. So what we need to move toward is a model of open networks of governance where we have peer to peer distribution of finance and of resources in a way that allows people to aggregate around the marketplaces that are actually benefiting the way that they believe the world should work. So it's about creating a collective strategy of collective non-violence and eliminating harm, so obviously, you know, having a society that has enough proper incentives so that people are well off and that people are provided for, and I think blockchain will-- >> I noticed you're wearing a United Nations pin. >> Woo-hoo, yeah. And blockchain, I think, will also create this. >> John: I have one too. >> Let's up top. (slap) Yeah, I think blockchain will also help create universal basic income, but in addition to that, it's the idea that, if I'm living next door, I'll give two examples. So one is about the legality of the way that we contribute to the society. So let's say I have a next door neighbor. And let's say that this next door neighbor and I feel literally, we totally get along on everything, there's just one issue we feel we're like, I totally disagree with this, I totally disagree. And that issue is the use of, and I hope this isn't controversial to say, but anyway. So the use of medical marijuana, right. And it shouldn't be, because we can have two different opinions and the world can still work and that's the point. >> Well, in California, it's now legal to own marijuana. >> Yeah, for sure, it's legal here as well. So it's the idea that, if I, so let's say I'm a woman who, you know, I have someone in my life who was injured by a driver who was driving under the influence of marijuana. And so that's all I know about marijuana because I don't really do drugs, I've never been around drugs. So when I hear that word, I immediately think about the person in my life who was harmed because of, yes, and so immediately triggered, and I'm like, I don't want to support anything, I don't want to support anything to do with marijuana, I think marijuana is like the Devil's lettuce. And I have no interest in supporting marijuana. She never has to support marijuana, she doesn't have to. But her next door neighbor is a veteran with Parkinson's disease, her, me, whatever, is a veteran with Parkinson's disease, okay. And the only way that this man can move is, he's literally shaking, but when he smokes medical marijuana, he's actually able to, you watch and literally 30-45 minutes, he's upright, he looks like a normal healthy man. And so he says, "I believe that every, "after I fought in this, I believe every person "should have access to medical marijuana, "because this is the only way I'm able "to even operate my life." >> The different context. >> And I'm so, yes, exactly. And so what culture is really about is about understanding each other's context, that's even how reputation works. It's contextual awareness that provides greater understanding of who we are as individuals and the way we work together to make society work. So maybe they can mutually agree that he is not going to smoke while he's driving and he can pay to support everyone to have access who needs access to medical marijuana. >> Or he could finance Uber rides for them. You know, or whatever, I mean, these are mechanisms. >> Yes, yes, but it's the, yes, exactly, exactly. It's the idea that we are all, we're coming together to share context is a way that's not aggressive and not accusatory, so two people can believe two totally different things and still develop enough mutual respect to live together peacefully in a society. >> You know, the other too I'm riffing on that is that now KYC is a concept (mumbles) kicked around here, know your customer. I've been riffing on the notion of KYC for know your neighbor. And what we're seeing in these communities, even the analog world, people don't know who their neighbors are. Like, they don't actually even like care about them. >> Toni: For sure. >> You know, maybe I grew up in, you know, a different culture where, you know, everyone played freely, the parents were on the porch having their cocktail or socializing and watching the kids from the porch play on the lawn. Now I call that Snapchat, right. So I can see my kids Snapchat, so I'm not involved, but I have peripheral view. >> Toni: For sure. >> But we took care of each other. That doesn't happen much anymore, and I think one of the things that's interesting in some of these community dynamics that's been successful is this empathy about respect. They kind of get to know people in a non-judgmental way. And I think that is something that you see in some of these fragmented communities, where it's just like, if they just did things a little bit different. Do you agree, I see you're shaking your head, your thoughts on this? This super interesting social science thing that's, now you can measure it with digital or you can measure that kind of-- >> We can incentivize it. We can incentivize it. And that's the difference, measurement is one thing. Incentive is a behavior changer. Incentive is a behavior changer. And that is what we actually have to do in the way we think about the foundation of these systems, is it's not incentivizing competitive marketplaces that are like my way of thinking about this is right and your way of thinking about this thing is wrong, and like ah, it's not about that. At the end of the day like, I think we forget or misquote so much of, so many of the great thinkers of the last generation, like if you think about Darwin. What does everyone know about Darwin, right, it's like survival of the fittest. It's not what Darwin said, okay. It's misquoted and it's used, it's like one of those things where people who want to exploit-- >> It's a meme, basically. >> Yeah, people who want to exploit someone else's knowledge for their own ends will use that to, in some way, uplift the kind of like strategy of, you know, incentives of the time. What Darwin actually said was that human beings with the highest capacity for sympathy, qualities we now identify as altruism, compassion, empathy, reciprocity, will be the most likely to survive during hardship. Fundamentally, I mean, look at the state of the world today. It doesn't look good, it's like, you look at the way people interact with each other, it's like a virus that's attacking itself in an ecosystem that is our planet Earth, and we need to be, you know what is the antibody, our own sense of consideration for our fellow man. That is the antibody to violence. And so we can incentivize this, and we're going to have to because we're going to, AI, automation, these will fundamentally transform the way we think about jobs in a way that will liberate us like we've never known before. And once given the freedom, I think that we'll see the world start to change. >> Toni, I really appreciate you spending the time in this thought leadership conversation, riffing back and forth. Feels great and it's a great productive conversation. I got to ask you, how did you get there? I mean, who are you? I mean, you're amazing. Like, how did you get here, you obviously, Coin Telegraph's one of the projects you're running, great content. You're wearing the UN pin, I'm aligning with that. Got a great perspective. What's your story? Where did you come from originally, I mean... How did you get here? >> I think, you know, I don't know. I'm really connected to Saturn, I don't know where my home planet is. >> Which spaceship did you come in on? No, I mean, seriously, what's your background? How did you weave into this? 'Cause you have a holistic view on things, it's impressive. But you also can get down and dirty on the tech, and you have a good, strong network. Did you kind of back into this by accident on purpose, or was it something that you studied? What's the evolution that you have? >> Yeah, you know. I studied performance art and I was an artist all of my life. And I had a really big existential crisis, because I realized, as I was looking around, that technology was replacing every form. I remember the first time I watched an AI generate, this was maybe in like, I don't remember how, this was a long time ago, but I was essentially watching, before like the deep dream stuff, maybe like 2009 or 10. And I remember watching computers generate art. And I just was like, I was like mic drop, I was like anything that could ever be created can and will be created by computers, because these are, you are looking at this data, you can scan every art piece in the world and create an amalgamation of this in a way that extends so far beyond team and capacity that the form that we have used to express artistic integrity, all forms will, in some way, become obsolete as a form of creative expression. And I had this huge existential crisis as a performer, realizing that the value of my work was essentially, like, how long would the value of my work live on if no one is, I am not alive to continue singing the song. You don't remember the people who played Carmen, you remember Bizet who wrote the opera, you remember Carmen the character, but the life of the performer is like that of a butterfly. It's like you emerge from the cocoon, you fly around the world beautifully for a very short amount of time. And then you just, you know, stardust again. And so I had this huge existential moment, and it was a really big awakening call. It was as though the gravity of the universe came into the entire dimension of my being and said these, what you have learned has given you a skill, but this is not your path. So I went okay, I just need some time to like process that and so, 'cause this is my entire life, it's the only thing I ever imagined I would ever do. And so I ended up spending three months in silence meditating. And people are like whoa, like how did you do that? And I don't think people, I don't know, not that people don't understand, but I'm not certain that a lot of people have the level of this kind of existential moment that I experienced. And I couldn't have done anything else, I really just needed to take that time to process that I was actually reformulating every construct at the foundation of my own reality. And that was going to take, that's not something you just do overnight, right, like some people can do it more fluidly, but this was a real shift, a conscious shift. And so I asked myself three questions in that meditation, it was what is my purpose, what is the paradigm shift and where is my love. And so I just meditated on these three questions and started to, I don't know how deeply you've studied lucid dreaming or out of body experiences, but that's another, a conversation we can get into in another time, that was my area of study during that period. And so I ended up leaving the three months in silence and I just kind of, I started following my intuition. So I would just, essentially, sometimes I'd walk into a library and I would just shut my eyes and I would just walk around and I would touch books. And I would just feel what they felt like to me, like the density of their knowledge. And I would just feel something that I felt called to, and I would just pull it out of the shelf and just read it. And I don't know how to explain it-- >> (mumbles) Energy, basically-- >> I was guided, I was guided to this. This was in 2011. And so what I started getting into was propaganda theory, the dissolution of Aristotelian politics as an idea of citizen and state when we're really all consumers in a Keynesian economy structured by Edward Bernays, the inventor of propaganda, who essentially based our entire attitude of economic health on, you know, a dissolving human well being. Like, the evolution of our economic well being and our human well being were fundamentally at odds, and not only was that system non-sustainable, but it was a complete illusion. At every touch, point and turn, that the systems we lived in were illusions. And so is all of the world, right, like this whole world is an illusion, but these illusions in particular have some serious implications in terms of people who don't have the capacity, or not the capacity, everyone has the capacity, but who have not explored that deeply, right, who haven't gone that deep with themselves. >> And one of those books was like a tech book or was like-- >> It was just multiple, no, it was multiple books. And it's not that I would even read all of the books all of the way through. Sometimes I would just pick up a book and I would just open it to a certain page and I would read like a passage or a couple pages, and I'd just feel like that's all I need to read out of that book. It's, you just tune into it. >> When was your first trade on Bitcoin, first buy, 2011? >> You want to know something nuts? People always, people are like, "When did you first buy Bitcoin?" I was not, I didn't. So after I started, once you know, all this knowledge came to me, I just started talking about it, I was like, I've been given some wisdom, I just have to share it. So I started going out into the world and finding podiums and sharing. And that was when someone put a USB full of Bitcoin into my hands. I very rarely, I don't necessarily buy, I've just been gifted a lot. >> Good gifts. >> Toni: They've been great gifts, yeah. >> And then when did you start Coin Telegraph, when did that come online? >> So that was in 2013. I joined, the property had been operable for I think like three or four months. And some guys called me and they said, "We're just really impressed with you "and we want to work with you." And I said, "Well, that's nice," I was like, "But you don't have a business, right?" And they were like, "What do you mean?" And I was like, "Well, you have a blog, right?" And so I went in and I said, essentially like, here's, to scale the property, I was like, "Here's a plan for the next three years. "If we really want to get this property to where "it needs to be." I'm like, "Here are the programs that we need "to institute, here's like this entire, "countries we can be operable in "and then other acquisitions of other properties." I essentially went in and said like, "Here's the business model and the plan at scale," and they were just like, I think they were a little like, the first call that we had, I think they were just like, "We just called you to," it was a bold move, like, "We just called you to offer you something, "and you countered our offer by saying "we don't have a business?" It was one of those things, but they-- >> Well, it was the labor of love for them, right, I mean-- >> Well, for all of us, yeah, for all of us. >> When all you do is you're blogging, you're just sharing. And then you start thinking about, you know, how to grow, and you got to nurture it, you need cash. >> Yes, and so I essentially came in and then started, I was both editor in chief and CEO and co-founder of the property who helped bring in a lot of the network, build the reputation for the brand, create a scaling strategy. A lot of mergers and acquisitions, a lot of franchises and-- >> How many properties did you buy roughly, handful, six, less than six? >> So I would also say that-- >> Little blogs and kind of (mumbles) them together, bring people together, was that the thinking? >> Yeah, you know, what's interesting is media from all shapes and sizes, 15 to 20 offices in 25 different countries. I always say this when I talk about this, a very important lesson that I learned. How do you manage a team of 40 anarchists? You don't, you don't, that's the answer, you don't, you don't even like, you're like oh. I remember when I was like, "We're a team!" And someone was like, "No, we're not, "I don't believe in teams, I work for myself "and I don't need," I was like oh, wow. I was like oh-- >> John: The power of we, no. >> I was just like, all right, but it was a good learning experience, because I was like well, this is the way, these are your needs. So if that's your, I was like, well, let's embrace that, let's embrace the idea-- >> But that's the culture, you can't change it. >> And let's create the economy around that, let's actually do direct incentive for it, if you think that you're, if you want to be in this on your own, then let's say okay, we're going to make this fully free market economics and we're going to have a matter of consensus on whether or not someone who's exploiting the system, you write an article, you send it out, the number of views and shares that it gets from accounts that are, you know, proven verified, that is how much you get out of the bounty that's created from our ad sales, and if the community comes together in a consensus and says that someone wrote an article that was basically exploiting the system, like beer, guns, tits and weed plus Bitcoin and then they just shared it with everyone, then obviously, they would be weighted differently because the community would reach consensus so-- >> Change the incentive system. >> We just, I started, yeah, I started redesigning, essentially, once I had that moment, I was like okay, I was like, well, we really got to change the incentives here then because the incentives are not going to work like that. If that's the, if there's a consensus that that is the way you guys want to do things, then I got to change things around that. All right, cool, and so yeah, it was a really interesting awesome learning experience from like, you know, a team of like, maybe like 20 to 40 into, probably took it up 40, and then with all of the other, you know, companies and franchises, to about 435 people. And then just took the revenue from, yeah, just took, it was like skating revenue and then rocketing revenue. So that was really my role in the growth of the business and we're all, you know, it's amazing to see how these kind of blockchain holacracies work, you know, at a micro scale and at a macro scale. And what it really takes to build a movement, right. And then, in some ways, I guess it'd either become or create a meme. >> Well, I really appreciate the movement you've been supporting, we're here to bring theCUBE to the movement, our second show, third show we've been doing. And getting a lot more this year, as the ecosystem is coming together, the norms are forming, they're storming, they're forming, it's great stuff. You've been a great thought leader, and thanks for sharing the awesome range of topics here for theCUBE. >> For sure. >> Toni Lane here inside theCUBE, I'm John Furrier. Thanks for watching our exclusive Puerto Rico coverage of CoinAgenda, we'll be right back. (energetic music)