(bright upbeat music) >> Well, hi everybody, John Wallace here and welcome to theCUBE, the leader in high-tech coverage. Glad to have you aboard here as we continue our coverage here at re:Invent 2022. We're out at The Venetian in Las Vegas. A lot of energy down on that exhibit floor, I promise you. We're a little bit away from the maddening crowd, but we're here with the Executive Summit sponsored by Accenture. I've got two guests I want to introduce you to. Jason Beyer who is the vice president of Data and Analytics at Bridgestone Americas. Jason, good to see you, sir. >> Hello, John. >> And Josh von Schaumburg, who is the managing director and North America lead for AWS Security at Accenture. Josh, good to see you. >> Thanks for having us. >> Yeah, first off, just quick take on the show. I know you've only been here about a day or so, but just your thoughts about what you're seeing on the floor in terms of energy, enthusiasm and, I think, turnout, right? I'm really impressed by it. We've got a lot of people down there. >> Yeah, I've been certainly impressed, John, with the turnout. But just as you say, the energy of the crowd, the excitement for the new things coming, it seems like it's a really pivotal moment for many organizations, including my own, and really excited to see what's coming over the next couple days. >> Let's jump into Bridgestone then. I kind of kidded you before we started the interview saying, all right, tires and golf balls, that's what I relate to, but you have a full array of consumer products and solution you're offering and your responsibility is managing the data and the analytics and making sure those business lines are as efficient as possible. >> Absolutely, John. So in my role, I have the privilege of being in an enterprise position. So I get to see the vast array of Bridgestone, which it is a large, highly vertically integrated company all the way from raw material sourcing of natural rubber to retail services in the automotive industry. We're at scale across those areas. The exciting thing about the company right now is we're going through this business transformation of becoming, you know, building on that heritage and that great legacy of having high quality high performance, highly focused on safety products to becoming a product and solutions company, and particular a sustainable solutions company. So what that means is we're bringing not only those great products to market, tires, golf balls, hoses, all kinds of rubber, air springs products to market, but thinking about how do we service those after they're in the market, how do we bring solutions to help fleets, vehicle owners, vehicle operators operate those in a sustainable way, in a cost effective way? So those solutions, of course, bring all new sets of data and analytics that come with it, and technology and moving to the cloud to be cloud native. So this new phase for the organization that we refer to as Bridgestone 3.0, and that business strategy is driving our cloud strategy, our technology strategy, and our data strategy and AWS and Accenture are important partners in that. >> Yeah, so we hear a lot about that these days about this transformation, this journey that people are on now. And Josh, when Bridgestone or other clients come to you and they talk about their migrations and what's their footprint going to look like and how do they get there, in the case of Bridgestone when they came to you and said, "All right, this is where we want to go with this. We're going to embark on a significant upgrade of our systems here," how do you lead 'em? How do you get 'em there? >> Yeah, I think there are a couple key cloud transformation value drivers that we've emphasized and that I've seen at Bridgestone in my time there. I mean, number one, just the rapid increase in the pace of innovation that we've seen over the last couple years. And a lot of that is also led by the scalability of all of the cloud native AWS services that we're leveraging, and in particular with the CDP platform. It really started off as a single-use case and really a single-tenant data lake. And then through the strategic vision of Jason and the leadership team, we've been able to expand that to 10 plus tenants and use cases. And a big reason behind that is the scalability of all these AWS services, right? So as we add more and more tenants, all the infrastructure just scales without any manual provisioning any tuning that we need to do. And that allows us to go really from idea, to POC, to production in really a matter of months when traditionally it might take years. >> So- >> If I can build upon that. >> Please do, yeah. >> The CDP, or central data platform, is part of a broader reference architecture that reflects that business strategy. So we looked at it and said, we could have taken a couple of different approaches to recognize the business challenges we're facing. We needed to modernize our core, our ERP, our manufacturing solutions move to smart factory and green factories, our PLM solutions. But at the same time, we're moving quickly. We have a startup mindset in our mobility solutions businesses where we're going to market on our customer and commerce solutions, and we needed to move at a different pace. And so to decouple those, we, in partnership with Accenture and AWS, built out a reference architecture that has a decoupling layer that's built around a data fabric, a data connected layer, integrated data services as well. A key part of that architecture is our central data platform built on AWS. This is a comprehensive data lake architecture using all the modern techniques within AWS to bring data together, to coalesce data, as well as recognize the multiple different modes of consumption, whether that's classic reporting, business intelligence, analytics, machine learning data science, as well as API consumption. And so we're building that out. A year ago it was a concept on a PowerPoint and just show and kind of reflect the innovation and speed. As Josh mentioned, we're up to 10 tenants, we're growing exponentially. There's high demand from the organization to leverage data at scale because of the business transformation that I mentioned and that modernization of the core ecosystem. >> That's crazy fast, right? And all of a sudden, whoa! >> Faster than I expected. >> Almost snap overnight. And you raise an interesting point too. I think when you talk about how there was a segment of your business that you wanted to get in the startup mode, whereas I don't think Bridgestone, I don't think about startup, right? I think in a much more, I wouldn't say traditional, but you've got big systems, right? And so how did you kind of inject your teams with that kind of mindset, right? That, hey, you're going to have to hit the pedal here, right? And I want you to experiment. I want you to innovate. And that might be a little bit against the grain from what they were used to. >> So just over two years ago, we built and started the organization that I have the privilege of leading, our data and analytics organization. And it's a COE. It's a center of expertise in the organization. We partner with specialized teams in product development, marketing, other places to enable data and analytics everywhere. We wanted to be pervasive, it's a team sport. But we really embraced at that moment what we refer to as a dual speed mindset. Speed one, we've got to move at the speed of the business. And that's variable. Based on the different business units and lines of lines of business and functional areas, the core modernization efforts, those are multi-year transformation programs that have multiple phases to them, and we're embedded there building the fundamentals of data governance and data management and reporting operational things. But at the same time, we needed to recognize that speed of those startup businesses where we're taking solutions and service offerings to market, doing quick minimum viable product, put it in a market, try it, learn from it adapt. Sometimes shut it down and take those learnings into the next area as well as joint ventures. We've been much more aggressive in terms of the partnerships in the marketplace, the joint ventures, the minority investments, et cetera, really to give us that edge in how we corner the market on the fleet and mobility solutions of the future. So having that dual speed approach of operating at the speed of the business, we also needed to balance that with speed two, which is building those long term capabilities and fundamentals. And that's where we've been building out those practical examples of having data governance and data management across these areas, building robust governance of how we're thinking about data science and the evolution of data science and that maturity towards machine learning. And so having that dual speed approach, it's a difficult balancing act, but it's served us well, really partnering with our key business stakeholders of where we can engage, what services they need, and where do we need to make smart choices between those two different speeds. >> Yeah, you just hit on something I want to ask Josh about, about how you said sometimes you have to shut things down, right? It's one thing to embark on I guess a new opportunity or explore, right? New avenues. And then to tell your client, "Well, might be some bumps along the way." >> Yeah. >> A lot of times people in Jason's position don't want to hear that. (laughs) It's like, I don't want to hear about bumps. >> Yeah. >> We want this to be, again, working with clients in that respect and understanding that there's going to be a learning curve and that some things might not function the way you want them to, we might have to take a right instead of a left. >> Yeah, and I think the value of AWS is you really can fail fast and try to innovate and try different use cases out. You don't have any enormous upfront capital expenditure to start building all these servers in your data center for all of your use cases. You can spin something up easily based in idea and then fail fast and move on to the next idea. And I also wanted to emphasize I think how critical top-down executive buy-in is for any cloud transformation. And you could hear it, the excitement in Jason's voice. And anytime we've seen a failed cloud transformation, the common theme is typically lack of executive buy-in and leadership and vision. And I think from day one, Bridgestone has had that buy-in from Jason throughout the whole executive team, and I think that's really evident in the success of the CDP platform. >> Absolutely. >> And what's been your experience in that regard then? Because I think that's a great point Josh raised that you might be really excited in your position, but you've got to convince the C-suite. >> Yeah. >> And there are a lot of variables there that have to be considered, that are kind of out of your sandbox, right? So for somebody else to make decisions based on a holistic approach, right? >> I could tell you, John, talking with with peers of mine, I recognize that I've probably had a little bit of privilege in that regard because the leadership at Bridgestone has recognized to move to this product and solutions organization and have sustainable solutions for the future we needed to move to the cloud. We needed to shift that technology forward. We needed to have a more data-driven approach to things. And so the selling of that was not a huge uphill a battle to be honest. It was almost more of a pull from the top, from our global group CEO, from our CEOs in our different regions, including in Bridgestone Americas. They've been pushing that forward, they've been driving it. And as Josh mentioned, that's been a really huge key to our success, is that executive alignment to move at this new pace, at this new frame of innovation, because that's what the market is demanding in the changing landscape of mobility and the movement of vehicles and things on the road. >> So how do you two work together going forward, Ben? Because you're in a great position now. You've had this tremendous acceleration in the past year, right? Talking about this tenfold increase and what the platform's enabled you to do, but as you know, you can't stand still. Right? (laughs) >> Yeah. There's so much excitement, so many use cases in the backlog now, and it's really been a snowball effect. I think one of the use cases I'm most excited about is starting to apply ML, you know, machine learning to the data sets. And I think there's an amazing IoT predictive maintenance use case there for all of the the censored data collected across all of the tires that are sold. There's an immense amount of data and ultimately we can use that data to predict failures and make our roads safer and help save lives >> Right. >> It's hard to not take a long time to explain all the things because there is a lot ahead of us. The demand curve for capabilities and the enabling things that AWS is going to support is just tremendous. As Josh mentioned, the, the AI ML use cases ahead of us, incredibly exciting. The way we're building and co-innovating things around how we make data more accessible in our data marketplace and more advanced data governance and data quality techniques. The use of, you know, creating data hubs and moving our API landscape into this environment as well is going to be incredibly empowering in terms of accessibility of data across our enterprise globally, as well as both for our internal stakeholders and our external stakeholders. So, I'll stop there because there's a lot of things in there. >> We could be here a long time. >> Yes, we could. >> But it is an exciting time and I appreciate that you're both sharing your perspectives on this because you've got a winning formula going and look forward to what's happening. And we'll see you next year right back here on the Executive Summit. >> Absolutely. >> To measure the success in 2023. How about that? >> Sounds good, thank you, Jim. >> Is that a deal? >> Awesome. >> Sounds good. >> Excellent, good deal. You've been watching AWS here at Coverage of Reinvent '22. We are the Executive Summit sponsored by Accenture and you are watching theCUBE, the leader in high tech coverage. 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>>Collibra is a company that was founded in 2008 right before the so-called modern big data era kicked into high gear. The company was one of the first to focus its business on data governance. Now, historically, data governance and data quality initiatives, they were back office functions and they were largely confined to regulatory regulated industries that had to comply with public policy mandates. But as the cloud went mainstream, the tech giants showed us how valuable data could become and the value proposition for data quality and trust. It evolved from primarily a compliance driven issue to becoming a lynchpin of competitive advantage. But data in the decade of the 2010s was largely about getting the technology to work. You had these highly centralized technical teams that were formed and they had hyper specialized skills to develop data architectures and processes to serve the myriad data needs of organizations. >>And it resulted in a lot of frustration with data initiatives for most organizations that didn't have the resources of the cloud guys and the social media giants to really attack their data problems and turn data into gold. This is why today for example, this quite a bit of momentum to rethinking monolithic data architectures. You see, you hear about initiatives like data mesh and the idea of data as a product. They're gaining traction as a way to better serve the the data needs of decentralized business Uni users, you hear a lot about data democratization. So these decentralization efforts around data, they're great, but they create a new set of problems. Specifically, how do you deliver like a self-service infrastructure to business users and domain experts? Now the cloud is definitely helping with that, but also how do you automate governance? This becomes especially tricky as protecting data privacy has become more and more important. >>In other words, while it's enticing to experiment and run fast and loose with data initiatives kinda like the Wild West, to find new veins of gold, it has to be done responsibly. As such, the idea of data governance has had to evolve to become more automated. And intelligence governance and data lineage is still fundamental to ensuring trust as data. It moves like water through an organization. No one is gonna use data that isn't trusted. Metadata has become increasingly important for data discovery and data classification. As data flows through an organization, the continuously ability to check for data flaws and automating that data quality, they become a functional requirement of any modern data management platform. And finally, data privacy has become a critical adjacency to cyber security. So you can see how data governance has evolved into a much richer set of capabilities than it was 10 or 15 years ago. >>Hello and welcome to the Cube's coverage of Data Citizens made possible by Calibra, a leader in so-called Data intelligence and the host of Data Citizens 2022, which is taking place in San Diego. My name is Dave Ante and I'm one of the hosts of our program, which is running in parallel to data citizens. Now at the Cube we like to say we extract the signal from the noise, and over the, the next couple of days, we're gonna feature some of the themes from the keynote speakers at Data Citizens and we'll hear from several of the executives. Felix Von Dala, who is the co-founder and CEO of Collibra, will join us along with one of the other founders of Collibra, Stan Christians, who's gonna join my colleague Lisa Martin. I'm gonna also sit down with Laura Sellers, she's the Chief Product Officer at Collibra. We'll talk about some of the, the announcements and innovations they're making at the event, and then we'll dig in further to data quality with Kirk Hasselbeck. >>He's the vice president of Data quality at Collibra. He's an amazingly smart dude who founded Owl dq, a company that he sold to Col to Collibra last year. Now many companies, they didn't make it through the Hado era, you know, they missed the industry waves and they became Driftwood. Collibra, on the other hand, has evolved its business. They've leveraged the cloud, expanded its product portfolio, and leaned in heavily to some major partnerships with cloud providers, as well as receiving a strategic investment from Snowflake earlier this year. So it's a really interesting story that we're thrilled to be sharing with you. Thanks for watching and I hope you enjoy the program. >>Last year, the Cube Covered Data Citizens Collibra's customer event. And the premise that we put forth prior to that event was that despite all the innovation that's gone on over the last decade or more with data, you know, starting with the Hado movement, we had data lakes, we'd spark the ascendancy of programming languages like Python, the introduction of frameworks like TensorFlow, the rise of ai, low code, no code, et cetera. Businesses still find it's too difficult to get more value from their data initiatives. And we said at the time, you know, maybe it's time to rethink data innovation. While a lot of the effort has been focused on, you know, more efficiently storing and processing data, perhaps more energy needs to go into thinking about the people and the process side of the equation, meaning making it easier for domain experts to both gain insights for data, trust the data, and begin to use that data in new ways, fueling data, products, monetization and insights data citizens 2022 is back and we're pleased to have Felix Van Dema, who is the founder and CEO of Collibra. He's on the cube or excited to have you, Felix. Good to see you again. >>Likewise Dave. Thanks for having me again. >>You bet. All right, we're gonna get the update from Felix on the current data landscape, how he sees it, why data intelligence is more important now than ever and get current on what Collibra has been up to over the past year and what's changed since Data Citizens 2021. And we may even touch on some of the product news. So Felix, we're living in a very different world today with businesses and consumers. They're struggling with things like supply chains, uncertain economic trends, and we're not just snapping back to the 2010s. That's clear, and that's really true as well in the world of data. So what's different in your mind, in the data landscape of the 2020s from the previous decade, and what challenges does that bring for your customers? >>Yeah, absolutely. And, and I think you said it well, Dave, and and the intro that that rising complexity and fragmentation in the broader data landscape, that hasn't gotten any better over the last couple of years. When when we talk to our customers, that level of fragmentation, the complexity, how do we find data that we can trust, that we know we can use has only gotten kinda more, more difficult. So that trend that's continuing, I think what is changing is that trend has become much more acute. Well, the other thing we've seen over the last couple of years is that the level of scrutiny that organizations are under respect to data, as data becomes more mission critical, as data becomes more impactful than important, the level of scrutiny with respect to privacy, security, regulatory compliance, as only increasing as well, which again, is really difficult in this environment of continuous innovation, continuous change, continuous growing complexity and fragmentation. >>So it's become much more acute. And, and to your earlier point, we do live in a different world and and the the past couple of years we could probably just kind of brute for it, right? We could focus on, on the top line. There was enough kind of investments to be, to be had. I think nowadays organizations are focused or are, are, are, are, are, are in a very different environment where there's much more focus on cost control, productivity, efficiency, How do we truly get value from that data? So again, I think it just another incentive for organization to now truly look at data and to scale it data, not just from a a technology and infrastructure perspective, but how do you actually scale data from an organizational perspective, right? You said at the the people and process, how do we do that at scale? And that's only, only only becoming much more important. And we do believe that the, the economic environment that we find ourselves in today is gonna be catalyst for organizations to really dig out more seriously if, if, if, if you will, than they maybe have in the have in the best. >>You know, I don't know when you guys founded Collibra, if, if you had a sense as to how complicated it was gonna get, but you've been on a mission to really address these problems from the beginning. How would you describe your, your, your mission and what are you doing to address these challenges? >>Yeah, absolutely. We, we started Colli in 2008. So in some sense and the, the last kind of financial crisis, and that was really the, the start of Colli where we found product market fit, working with large finance institutions to help them cope with the increasing compliance requirements that they were faced with because of the, of the financial crisis and kind of here we are again in a very different environment, of course 15 years, almost 15 years later. But data only becoming more important. But our mission to deliver trusted data for every user, every use case and across every source, frankly, has only become more important. So what has been an incredible journey over the last 14, 15 years, I think we're still relatively early in our mission to again, be able to provide everyone, and that's why we call it data citizens. We truly believe that everyone in the organization should be able to use trusted data in an easy, easy matter. That mission is is only becoming more important, more relevant. We definitely have a lot more work ahead of us because we are still relatively early in that, in that journey. >>Well, that's interesting because, you know, in my observation it takes seven to 10 years to actually build a company and then the fact that you're still in the early days is kind of interesting. I mean, you, Collibra's had a good 12 months or so since we last spoke at Data Citizens. Give us the latest update on your business. What do people need to know about your, your current momentum? >>Yeah, absolutely. Again, there's, there's a lot of tail organizations that are only maturing the data practices and we've seen it kind of transform or, or, or influence a lot of our business growth that we've seen, broader adoption of the platform. We work at some of the largest organizations in the world where it's Adobe, Heineken, Bank of America, and many more. We have now over 600 enterprise customers, all industry leaders and every single vertical. So it's, it's really exciting to see that and continue to partner with those organizations. On the partnership side, again, a lot of momentum in the org in, in the, in the markets with some of the cloud partners like Google, Amazon, Snowflake, data bricks and, and others, right? As those kind of new modern data infrastructures, modern data architectures that are definitely all moving to the cloud, a great opportunity for us, our partners and of course our customers to help them kind of transition to the cloud even faster. >>And so we see a lot of excitement and momentum there within an acquisition about 18 months ago around data quality, data observability, which we believe is an enormous opportunity. Of course, data quality isn't new, but I think there's a lot of reasons why we're so excited about quality and observability now. One is around leveraging ai, machine learning, again to drive more automation. And the second is that those data pipelines that are now being created in the cloud, in these modern data architecture arch architectures, they've become mission critical. They've become real time. And so monitoring, observing those data pipelines continuously has become absolutely critical so that they're really excited about about that as well. And on the organizational side, I'm sure you've heard a term around kind of data mesh, something that's gaining a lot of momentum, rightfully so. It's really the type of governance that we always believe. Then federated focused on domains, giving a lot of ownership to different teams. I think that's the way to scale data organizations. And so that aligns really well with our vision and, and from a product perspective, we've seen a lot of momentum with our customers there as well. >>Yeah, you know, a couple things there. I mean, the acquisition of i l dq, you know, Kirk Hasselbeck and, and their team, it's interesting, you know, the whole data quality used to be this back office function and, and really confined to highly regulated industries. It's come to the front office, it's top of mind for chief data officers, data mesh. You mentioned you guys are a connective tissue for all these different nodes on the data mesh. That's key. And of course we see you at all the shows. You're, you're a critical part of many ecosystems and you're developing your own ecosystem. So let's chat a little bit about the, the products. We're gonna go deeper in into products later on at, at Data Citizens 22, but we know you're debuting some, some new innovations, you know, whether it's, you know, the, the the under the covers in security, sort of making data more accessible for people just dealing with workflows and processes as you talked about earlier. Tell us a little bit about what you're introducing. >>Yeah, absolutely. We're super excited, a ton of innovation. And if we think about the big theme and like, like I said, we're still relatively early in this, in this journey towards kind of that mission of data intelligence that really bolts and compelling mission, either customers are still start, are just starting on that, on that journey. We wanna make it as easy as possible for the, for our organization to actually get started because we know that's important that they do. And for our organization and customers that have been with us for some time, there's still a tremendous amount of opportunity to kind of expand the platform further. And again, to make it easier for really to, to accomplish that mission and vision around that data citizen that everyone has access to trustworthy data in a very easy, easy way. So that's really the theme of a lot of the innovation that we're driving. >>A lot of kind of ease of adoption, ease of use, but also then how do we make sure that lio becomes this kind of mission critical enterprise platform from a security performance architecture scale supportability that we're truly able to deliver that kind of an enterprise mission critical platform. And so that's the big theme from an innovation perspective, From a product perspective, a lot of new innovation that we're really excited about. A couple of highlights. One is around data marketplace. Again, a lot of our customers have plans in that direction, how to make it easy. How do we make, how do we make available to true kind of shopping experience that anybody in your organization can, in a very easy search first way, find the right data product, find the right dataset, that data can then consume usage analytics. How do you, how do we help organizations drive adoption, tell them where they're working really well and where they have opportunities homepages again to, to make things easy for, for people, for anyone in your organization to kind of get started with ppia, you mentioned workflow designer, again, we have a very powerful enterprise platform. >>One of our key differentiators is the ability to really drive a lot of automation through workflows. And now we provided a new low code, no code kind of workflow designer experience. So, so really customers can take it to the next level. There's a lot more new product around K Bear Protect, which in partnership with Snowflake, which has been a strategic investor in kib, focused on how do we make access governance easier? How do we, how do we, how are we able to make sure that as you move to the cloud, things like access management, masking around sensitive data, PII data is managed as much more effective, effective rate, really excited about that product. There's more around data quality. Again, how do we, how do we get that deployed as easily and quickly and widely as we can? Moving that to the cloud has been a big part of our strategy. >>So we launch more data quality cloud product as well as making use of those, those native compute capabilities in platforms like Snowflake, Data, Bricks, Google, Amazon, and others. And so we are bettering a capability, a capability that we call push down. So actually pushing down the computer and data quality, the monitoring into the underlying platform, which again, from a scale performance and ease of use perspective is gonna make a massive difference. And then more broadly, we, we talked a little bit about the ecosystem. Again, integrations, we talk about being able to connect to every source. Integrations are absolutely critical and we're really excited to deliver new integrations with Snowflake, Azure and Google Cloud storage as well. So there's a lot coming out. The, the team has been work at work really hard and we are really, really excited about what we are coming, what we're bringing to markets. >>Yeah, a lot going on there. I wonder if you could give us your, your closing thoughts. I mean, you, you talked about, you know, the marketplace, you know, you think about data mesh, you think of data as product, one of the key principles you think about monetization. This is really different than what we've been used to in data, which is just getting the technology to work has been been so hard. So how do you see sort of the future and, you know, give us the, your closing thoughts please? >>Yeah, absolutely. And I, and I think we we're really at this pivotal moment, and I think you said it well. We, we all know the constraint and the challenges with data, how to actually do data at scale. And while we've seen a ton of innovation on the infrastructure side, we fundamentally believe that just getting a faster database is important, but it's not gonna fully solve the challenges and truly kind of deliver on the opportunity. And that's why now is really the time to deliver this data intelligence vision, this data intelligence platform. We are still early, making it as easy as we can. It's kind of, of our, it's our mission. And so I'm really, really excited to see what we, what we are gonna, how the marks gonna evolve over the next, next few quarters and years. I think the trend is clearly there when we talk about data mesh, this kind of federated approach folks on data products is just another signal that we believe that a lot of our organization are now at the time. >>The understanding need to go beyond just the technology. I really, really think about how do we actually scale data as a business function, just like we've done with it, with, with hr, with, with sales and marketing, with finance. That's how we need to think about data. I think now is the time given the economic environment that we are in much more focus on control, much more focused on productivity efficiency and now's the time. We need to look beyond just the technology and infrastructure to think of how to scale data, how to manage data at scale. >>Yeah, it's a new era. The next 10 years of data won't be like the last, as I always say. Felix, thanks so much and good luck in, in San Diego. I know you're gonna crush it out there. >>Thank you Dave. >>Yeah, it's a great spot for an in-person event and, and of course the content post event is gonna be available@collibra.com and you can of course catch the cube coverage@thecube.net and all the news@siliconangle.com. This is Dave Valante for the cube, your leader in enterprise and emerging tech coverage. >>Hi, I'm Jay from Collibra's Data Office. Today I want to talk to you about Collibra's data intelligence cloud. We often say Collibra is a single system of engagement for all of your data. Now, when I say data, I mean data in the broadest sense of the word, including reference and metadata. Think of metrics, reports, APIs, systems, policies, and even business processes that produce or consume data. Now, the beauty of this platform is that it ensures all of your users have an easy way to find, understand, trust, and access data. But how do you get started? Well, here are seven steps to help you get going. One, start with the data. What's data intelligence? Without data leverage the Collibra data catalog to automatically profile and classify your enterprise data wherever that data lives, databases, data lakes or data warehouses, whether on the cloud or on premise. >>Two, you'll then wanna organize the data and you'll do that with data communities. This can be by department, find a business or functional team, however your organization organizes work and accountability. And for that you'll establish community owners, communities, make it easy for people to navigate through the platform, find the data and will help create a sense of belonging for users. An important and related side note here, we find it's typical in many organizations that data is thought of is just an asset and IT and data offices are viewed as the owners of it and who are really the central teams performing analytics as a service provider to the enterprise. We believe data is more than an asset, it's a true product that can be converted to value. And that also means establishing business ownership of data where that strategy and ROI come together with subject matter expertise. >>Okay, three. Next, back to those communities there, the data owners should explain and define their data, not just the tables and columns, but also the related business terms, metrics and KPIs. These objects we call these assets are typically organized into business glossaries and data dictionaries. I definitely recommend starting with the topics that are most important to the business. Four, those steps that enable you and your users to have some fun with it. Linking everything together builds your knowledge graph and also known as a metadata graph by linking or relating these assets together. For example, a data set to a KPI to a report now enables your users to see what we call the lineage diagram that visualizes where the data in your dashboards actually came from and what the data means and who's responsible for it. Speaking of which, here's five. Leverage the calibra trusted business reporting solution on the marketplace, which comes with workflows for those owners to certify their reports, KPIs, and data sets. >>This helps them force their trust in their data. Six, easy to navigate dashboards or landing pages right in your platform for your company's business processes are the most effective way for everyone to better understand and take action on data. Here's a pro tip, use the dashboard design kit on the marketplace to help you build compelling dashboards. Finally, seven, promote the value of this to your users and be sure to schedule enablement office hours and new employee onboarding sessions to get folks excited about what you've built and implemented. Better yet, invite all of those community and data owners to these sessions so that they can show off the value that they've created. Those are my seven tips to get going with Collibra. I hope these have been useful. For more information, be sure to visit collibra.com. >>Welcome to the Cube's coverage of Data Citizens 2022 Collibra's customer event. My name is Dave Valante. With us is Kirk Hasselbeck, who's the vice president of Data Quality of Collibra Kirk, good to see you. Welcome. >>Thanks for having me, Dave. Excited to be here. >>You bet. Okay, we're gonna discuss data quality observability. It's a hot trend right now. You founded a data quality company, OWL dq, and it was acquired by Collibra last year. Congratulations. And now you lead data quality at Collibra. So we're hearing a lot about data quality right now. Why is it such a priority? Take us through your thoughts on that. >>Yeah, absolutely. It's, it's definitely exciting times for data quality, which you're right, has been around for a long time. So why now and why is it so much more exciting than it used to be? I think it's a bit stale, but we all know that companies use more data than ever before and the variety has changed and the volume has grown. And, and while I think that remains true, there are a couple other hidden factors at play that everyone's so interested in as, as to why this is becoming so important now. And, and I guess you could kind of break this down simply and think about if Dave, you and I were gonna build, you know, a new healthcare application and monitor the heartbeat of individuals, imagine if we get that wrong, you know, what the ramifications could be, what, what those incidents would look like, or maybe better yet, we try to build a, a new trading algorithm with a crossover strategy where the 50 day crosses the, the 10 day average. >>And imagine if the data underlying the inputs to that is incorrect. We will probably have major financial ramifications in that sense. So, you know, it kind of starts there where everybody's realizing that we're all data companies and if we are using bad data, we're likely making incorrect business decisions. But I think there's kind of two other things at play. You know, I, I bought a car not too long ago and my dad called and said, How many cylinders does it have? And I realized in that moment, you know, I might have failed him because, cause I didn't know. And, and I used to ask those types of questions about any lock brakes and cylinders and, and you know, if it's manual or, or automatic and, and I realized I now just buy a car that I hope works. And it's so complicated with all the computer chips, I, I really don't know that much about it. >>And, and that's what's happening with data. We're just loading so much of it. And it's so complex that the way companies consume them in the IT function is that they bring in a lot of data and then they syndicate it out to the business. And it turns out that the, the individuals loading and consuming all of this data for the company actually may not know that much about the data itself, and that's not even their job anymore. So we'll talk more about that in a minute, but that's really what's setting the foreground for this observability play and why everybody's so interested. It, it's because we're becoming less close to the intricacies of the data and we just expect it to always be there and be correct. >>You know, the other thing too about data quality, and for years we did the MIT CDO IQ event, we didn't do it last year, Covid messed everything up. But the observation I would make there thoughts is, is it data quality? Used to be information quality used to be this back office function, and then it became sort of front office with financial services and government and healthcare, these highly regulated industries. And then the whole chief data officer thing happened and people were realizing, well, they sort of flipped the bit from sort of a data as a, a risk to data as a, as an asset. And now as we say, we're gonna talk about observability. And so it's really become front and center just the whole quality issue because data's so fundamental, hasn't it? >>Yeah, absolutely. I mean, let's imagine we pull up our phones right now and I go to my, my favorite stock ticker app and I check out the NASDAQ market cap. I really have no idea if that's the correct number. I know it's a number, it looks large, it's in a numeric field. And, and that's kind of what's going on. There's, there's so many numbers and they're coming from all of these different sources and data providers and they're getting consumed and passed along. But there isn't really a way to tactically put controls on every number and metric across every field we plan to monitor, but with the scale that we've achieved in early days, even before calibra. And what's been so exciting is we have these types of observation techniques, these data monitors that can actually track past performance of every field at scale. And why that's so interesting and why I think the CDO is, is listening right intently nowadays to this topic is, so maybe we could surface all of these problems with the right solution of data observability and with the right scale and then just be alerted on breaking trends. So we're sort of shifting away from this world of must write a condition and then when that condition breaks, that was always known as a break record. But what about breaking trends and root cause analysis? And is it possible to do that, you know, with less human intervention? And so I think most people are seeing now that it's going to have to be a software tool and a computer system. It's, it's not ever going to be based on one or two domain experts anymore. >>So, So how does data observability relate to data quality? Are they sort of two sides of the same coin? Are they, are they cousins? What's your perspective on that? >>Yeah, it's, it's super interesting. It's an emerging market. So the language is changing a lot of the topic and areas changing the way that I like to say it or break it down because the, the lingo is constantly moving is, you know, as a target on this space is really breaking records versus breaking trends. And I could write a condition when this thing happens, it's wrong and when it doesn't it's correct. Or I could look for a trend and I'll give you a good example. You know, everybody's talking about fresh data and stale data and, and why would that matter? Well, if your data never arrived or only part of it arrived or didn't arrive on time, it's likely stale and there will not be a condition that you could write that would show you all the good in the bads. That was kind of your, your traditional approach of data quality break records. But your modern day approach is you lost a significant portion of your data, or it did not arrive on time to make that decision accurately on time. And that's a hidden concern. Some people call this freshness, we call it stale data, but it all points to the same idea of the thing that you're observing may not be a data quality condition anymore. It may be a breakdown in the data pipeline. And with thousands of data pipelines in play for every company out there there, there's more than a couple of these happening every day. >>So what's the Collibra angle on all this stuff made the acquisition, you got data quality observability coming together, you guys have a lot of expertise in, in this area, but you hear providence of data, you just talked about, you know, stale data, you know, the, the whole trend toward real time. How is Calibra approaching the problem and what's unique about your approach? >>Well, I think where we're fortunate is with our background, myself and team, we sort of lived this problem for a long time, you know, in, in the Wall Street days about a decade ago. And we saw it from many different angles. And what we came up with before it was called data observability or reliability was basically the, the underpinnings of that. So we're a little bit ahead of the curve there when most people evaluate our solution, it's more advanced than some of the observation techniques that that currently exist. But we've also always covered data quality and we believe that people want to know more, they need more insights, and they want to see break records and breaking trends together so they can correlate the root cause. And we hear that all the time. I have so many things going wrong, just show me the big picture, help me find the thing that if I were to fix it today would make the most impact. So we're really focused on root cause analysis, business impact, connecting it with lineage and catalog metadata. And as that grows, you can actually achieve total data governance at this point with the acquisition of what was a Lineage company years ago, and then my company Ldq now Collibra, Data quality Collibra may be the best positioned for total data governance and intelligence in the space. >>Well, you mentioned financial services a couple of times and some examples, remember the flash crash in 2010. Nobody had any idea what that was, you know, they just said, Oh, it's a glitch, you know, so they didn't understand the root cause of it. So this is a really interesting topic to me. So we know at Data Citizens 22 that you're announcing, you gotta announce new products, right? You're yearly event what's, what's new. Give us a sense as to what products are coming out, but specifically around data quality and observability. >>Absolutely. There's this, you know, there's always a next thing on the forefront. And the one right now is these hyperscalers in the cloud. So you have databases like Snowflake and Big Query and Data Bricks is Delta Lake and SQL Pushdown. And ultimately what that means is a lot of people are storing in loading data even faster in a SaaS like model. And we've started to hook in to these databases. And while we've always worked with the the same databases in the past, they're supported today we're doing something called Native Database pushdown, where the entire compute and data activity happens in the database. And why that is so interesting and powerful now is everyone's concerned with something called Egress. Did your, my data that I've spent all this time and money with my security team securing ever leave my hands, did it ever leave my secure VPC as they call it? >>And with these native integrations that we're building and about to unveil, here's kind of a sneak peek for, for next week at Data Citizens. We're now doing all compute and data operations in databases like Snowflake. And what that means is with no install and no configuration, you could log into the Collibra data quality app and have all of your data quality running inside the database that you've probably already picked as your your go forward team selection secured database of choice. So we're really excited about that. And I think if you look at the whole landscape of network cost, egress, cost, data storage and compute, what people are realizing is it's extremely efficient to do it in the way that we're about to release here next week. >>So this is interesting because what you just described, you know, you mentioned Snowflake, you mentioned Google, Oh actually you mentioned yeah, data bricks. You know, Snowflake has the data cloud. If you put everything in the data cloud, okay, you're cool, but then Google's got the open data cloud. If you heard, you know, Google next and now data bricks doesn't call it the data cloud, but they have like the open source data cloud. So you have all these different approaches and there's really no way up until now I'm, I'm hearing to, to really understand the relationships between all those and have confidence across, you know, it's like Jak Dani, you should just be a note on the mesh. And I don't care if it's a data warehouse or a data lake or where it comes from, but it's a point on that mesh and I need tooling to be able to have confidence that my data is governed and has the proper lineage, providence. And, and, and that's what you're bringing to the table, Is that right? Did I get that right? >>Yeah, that's right. And it's, for us, it's, it's not that we haven't been working with those great cloud databases, but it's the fact that we can send them the instructions now, we can send them the, the operating ability to crunch all of the calculations, the governance, the quality, and get the answers. And what that's doing, it's basically zero network costs, zero egress cost, zero latency of time. And so when you were to log into Big Query tomorrow using our tool or like, or say Snowflake for example, you have instant data quality metrics, instant profiling, instant lineage and access privacy controls, things of that nature that just become less onerous. What we're seeing is there's so much technology out there, just like all of the major brands that you mentioned, but how do we make it easier? The future is about less clicks, faster time to value, faster scale, and eventually lower cost. And, and we think that this positions us to be the leader there. >>I love this example because, you know, Barry talks about, wow, the cloud guys are gonna own the world and, and of course now we're seeing that the ecosystem is finding so much white space to add value, connect across cloud. Sometimes we call it super cloud and so, or inter clouding. All right, Kirk, give us your, your final thoughts and on on the trends that we've talked about and Data Citizens 22. >>Absolutely. Well, I think, you know, one big trend is discovery and classification. Seeing that across the board, people used to know it was a zip code and nowadays with the amount of data that's out there, they wanna know where everything is, where their sensitive data is. If it's redundant, tell me everything inside of three to five seconds. And with that comes, they want to know in all of these hyperscale databases how fast they can get controls and insights out of their tools. So I think we're gonna see more one click solutions, more SAS based solutions and solutions that hopefully prove faster time to value on, on all of these modern cloud platforms. >>Excellent. All right, Kurt Hasselbeck, thanks so much for coming on the Cube and previewing Data Citizens 22. Appreciate it. >>Thanks for having me, Dave. >>You're welcome. Right, and thank you for watching. Keep it right there for more coverage from the Cube. Welcome to the Cube's virtual Coverage of Data Citizens 2022. My name is Dave Valante and I'm here with Laura Sellers, who's the Chief Product Officer at Collibra, the host of Data Citizens. Laura, welcome. Good to see you. >>Thank you. Nice to be here. >>Yeah, your keynote at Data Citizens this year focused on, you know, your mission to drive ease of use and scale. Now when I think about historically fast access to the right data at the right time in a form that's really easily consumable, it's been kind of challenging, especially for business users. Can can you explain to our audience why this matters so much and what's actually different today in the data ecosystem to make this a reality? >>Yeah, definitely. So I think what we really need and what I hear from customers every single day is that we need a new approach to data management and our product teams. What inspired me to come to Calibra a little bit a over a year ago was really the fact that they're very focused on bringing trusted data to more users across more sources for more use cases. And so as we look at what we're announcing with these innovations of ease of use and scale, it's really about making teams more productive in getting started with and the ability to manage data across the entire organization. So we've been very focused on richer experiences, a broader ecosystem of partners, as well as a platform that delivers performance, scale and security that our users and teams need and demand. So as we look at, Oh, go ahead. >>I was gonna say, you know, when I look back at like the last 10 years, it was all about getting the technology to work and it was just so complicated. But, but please carry on. I'd love to hear more about this. >>Yeah, I, I really, you know, Collibra is a system of engagement for data and we really are working on bringing that entire system of engagement to life for everyone to leverage here and now. So what we're announcing from our ease of use side of the world is first our data marketplace. This is the ability for all users to discover and access data quickly and easily shop for it, if you will. The next thing that we're also introducing is the new homepage. It's really about the ability to drive adoption and have users find data more quickly. And then the two more areas of the ease of use side of the world is our world of usage analytics. And one of the big pushes and passions we have at Collibra is to help with this data driven culture that all companies are trying to create. And also helping with data literacy, with something like usage analytics, it's really about driving adoption of the CLE platform, understanding what's working, who's accessing it, what's not. And then finally we're also introducing what's called workflow designer. And we love our workflows at Libra, it's a big differentiator to be able to automate business processes. The designer is really about a way for more people to be able to create those workflows, collaborate on those workflow flows, as well as people to be able to easily interact with them. So a lot of exciting things when it comes to ease of use to make it easier for all users to find data. >>Y yes, there's definitely a lot to unpack there. I I, you know, you mentioned this idea of, of of, of shopping for the data. That's interesting to me. Why this analogy, metaphor or analogy, I always get those confused. I let's go with analogy. Why is it so important to data consumers? >>I think when you look at the world of data, and I talked about this system of engagement, it's really about making it more accessible to the masses. And what users are used to is a shopping experience like your Amazon, if you will. And so having a consumer grade experience where users can quickly go in and find the data, trust that data, understand where the data's coming from, and then be able to quickly access it, is the idea of being able to shop for it, just making it as simple as possible and really speeding the time to value for any of the business analysts, data analysts out there. >>Yeah, I think when you, you, you see a lot of discussion about rethinking data architectures, putting data in the hands of the users and business people, decentralized data and of course that's awesome. I love that. But of course then you have to have self-service infrastructure and you have to have governance. And those are really challenging. And I think so many organizations, they're facing adoption challenges, you know, when it comes to enabling teams generally, especially domain experts to adopt new data technologies, you know, like the, the tech comes fast and furious. You got all these open source projects and get really confusing. Of course it risks security, governance and all that good stuff. You got all this jargon. So where do you see, you know, the friction in adopting new data technologies? What's your point of view and how can organizations overcome these challenges? >>You're, you're dead on. There's so much technology and there's so much to stay on top of, which is part of the friction, right? It's just being able to stay ahead of, of and understand all the technologies that are coming. You also look at as there's so many more sources of data and people are migrating data to the cloud and they're migrating to new sources. Where the friction comes is really that ability to understand where the data came from, where it's moving to, and then also to be able to put the access controls on top of it. So people are only getting access to the data that they should be getting access to. So one of the other things we're announcing with, with all of the innovations that are coming is what we're doing around performance and scale. So with all of the data movement, with all of the data that's out there, the first thing we're launching in the world of performance and scale is our world of data quality. >>It's something that Collibra has been working on for the past year and a half, but we're launching the ability to have data quality in the cloud. So it's currently an on-premise offering, but we'll now be able to carry that over into the cloud for us to manage that way. We're also introducing the ability to push down data quality into Snowflake. So this is, again, one of those challenges is making sure that that data that you have is d is is high quality as you move forward. And so really another, we're just reducing friction. You already have Snowflake stood up. It's not another machine for you to manage, it's just push down capabilities into Snowflake to be able to track that quality. Another thing that we're launching with that is what we call Collibra Protect. And this is that ability for users to be able to ingest metadata, understand where the PII data is, and then set policies up on top of it. So very quickly be able to set policies and have them enforced at the data level. So anybody in the organization is only getting access to the data they should have access to. >>Here's Topica data quality is interesting. It's something that I've followed for a number of years. It used to be a back office function, you know, and really confined only to highly regulated industries like financial services and healthcare and government. You know, you look back over a decade ago, you didn't have this worry about personal information, g gdpr, and, you know, California Consumer Privacy Act all becomes, becomes so much important. The cloud is really changed things in terms of performance and scale and of course partnering for, for, with Snowflake it's all about sharing data and monetization, anything but a back office function. So it was kind of smart that you guys were early on and of course attracting them and as a, as an investor as well was very strong validation. What can you tell us about the nature of the relationship with Snowflake and specifically inter interested in sort of joint engineering or, and product innovation efforts, you know, beyond the standard go to market stuff? >>Definitely. So you mentioned there were a strategic investor in Calibra about a year ago. A little less than that I guess. We've been working with them though for over a year really tightly with their product and engineering teams to make sure that Collibra is adding real value. Our unified platform is touching pieces of our unified platform or touching all pieces of Snowflake. And when I say that, what I mean is we're first, you know, able to ingest data with Snowflake, which, which has always existed. We're able to profile and classify that data we're announcing with Calibra Protect this week that you're now able to create those policies on top of Snowflake and have them enforce. So again, people can get more value out of their snowflake more quickly as far as time to value with, with our policies for all business users to be able to create. >>We're also announcing Snowflake Lineage 2.0. So this is the ability to take stored procedures in Snowflake and understand the lineage of where did the data come from, how was it transformed with within Snowflake as well as the data quality. Pushdown, as I mentioned, data quality, you brought it up. It is a new, it is a, a big industry push and you know, one of the things I think Gartner mentioned is people are losing up to $15 million without having great data quality. So this push down capability for Snowflake really is again, a big ease of use push for us at Collibra of that ability to, to push it into snowflake, take advantage of the data, the data source, and the engine that already lives there and get the right and make sure you have the right quality. >>I mean, the nice thing about Snowflake, if you play in the Snowflake sandbox, you, you, you, you can get sort of a, you know, high degree of confidence that the data sharing can be done in a safe way. Bringing, you know, Collibra into the, into the story allows me to have that data quality and, and that governance that I, that I need. You know, we've said many times on the cube that one of the notable differences in cloud this decade versus last decade, I mean ob there are obvious differences just in terms of scale and scope, but it's shaping up to be about the strength of the ecosystems. That's really a hallmark of these big cloud players. I mean they're, it's a key factor for innovating, accelerating product delivery, filling gaps in, in the hyperscale offerings cuz you got more stack, you know, mature stack capabilities and you know, it creates this flywheel momentum as we often say. But, so my question is, how do you work with the hyperscalers? Like whether it's AWS or Google, whomever, and what do you see as your role and what's the Collibra sweet spot? >>Yeah, definitely. So, you know, one of the things I mentioned early on is the broader ecosystem of partners is what it's all about. And so we have that strong partnership with Snowflake. We also are doing more with Google around, you know, GCP and kbra protect there, but also tighter data plex integration. So similar to what you've seen with our strategic moves around Snowflake and, and really covering the broad ecosystem of what Collibra can do on top of that data source. We're extending that to the world of Google as well and the world of data plex. We also have great partners in SI's Infosys is somebody we spoke with at the conference who's done a lot of great work with Levi's as they're really important to help people with their whole data strategy and driving that data driven culture and, and Collibra being the core of it. >>Hi Laura, we're gonna, we're gonna end it there, but I wonder if you could kind of put a bow on, you know, this year, the event your, your perspectives. So just give us your closing thoughts. >>Yeah, definitely. So I, I wanna say this is one of the biggest releases Collibra's ever had. Definitely the biggest one since I've been with the company a little over a year. We have all these great new product innovations coming to really drive the ease of use to make data more valuable for users everywhere and, and companies everywhere. And so it's all about everybody being able to easily find, understand, and trust and get access to that data going forward. >>Well congratulations on all the pro progress. It was great to have you on the cube first time I believe, and really appreciate you, you taking the time with us. >>Yes, thank you for your time. >>You're very welcome. Okay, you're watching the coverage of Data Citizens 2022 on the cube, your leader in enterprise and emerging tech coverage. >>So data modernization oftentimes means moving some of your storage and computer to the cloud where you get the benefit of scale and security and so on. But ultimately it doesn't take away the silos that you have. We have more locations, more tools and more processes with which we try to get value from this data. To do that at scale in an organization, people involved in this process, they have to understand each other. So you need to unite those people across those tools, processes, and systems with a shared language. When I say customer, do you understand the same thing as you hearing customer? Are we counting them in the same way so that shared language unites us and that gives the opportunity for the organization as a whole to get the maximum value out of their data assets and then they can democratize data so everyone can properly use that shared language to find, understand, and trust the data asset that's available. >>And that's where Collibra comes in. We provide a centralized system of engagement that works across all of those locations and combines all of those different user types across the whole business. At Collibra, we say United by data and that also means that we're united by data with our customers. So here is some data about some of our customers. There was the case of an online do it yourself platform who grew their revenue almost three times from a marketing campaign that provided the right product in the right hands of the right people. In other case that comes to mind is from a financial services organization who saved over 800 K every year because they were able to reuse the same data in different kinds of reports and before there was spread out over different tools and processes and silos, and now the platform brought them together so they realized, oh, we're actually using the same data, let's find a way to make this more efficient. And the last example that comes to mind is that of a large home loan, home mortgage, mortgage loan provider where they have a very complex landscape, a very complex architecture legacy in the cloud, et cetera. And they're using our software, they're using our platform to unite all the people and those processes and tools to get a common view of data to manage their compliance at scale. >>Hey everyone, I'm Lisa Martin covering Data Citizens 22, brought to you by Collibra. This next conversation is gonna focus on the importance of data culture. One of our Cube alumni is back, Stan Christians is Collibra's co-founder and it's Chief Data citizens. Stan, it's great to have you back on the cube. >>Hey Lisa, nice to be. >>So we're gonna be talking about the importance of data culture, data intelligence, maturity, all those great things. When we think about the data revolution that every business is going through, you know, it's so much more than technology innovation. It also really re requires cultural transformation, community transformation. Those are challenging for customers to undertake. Talk to us about what you mean by data citizenship and the role that creating a data culture plays in that journey. >>Right. So as you know, our event is called Data Citizens because we believe that in the end, a data citizen is anyone who uses data to do their job. And we believe that today's organizations, you have a lot of people, most of the employees in an organization are somehow gonna to be a data citizen, right? So you need to make sure that these people are aware of it. You need that. People have skills and competencies to do with data what necessary and that's on, all right? So what does it mean to have a good data culture? It means that if you're building a beautiful dashboard to try and convince your boss, we need to make this decision that your boss is also open to and able to interpret, you know, the data presented in dashboard to actually make that decision and take that action. Right? >>And once you have that why to the organization, that's when you have a good data culture. Now that's continuous effort for most organizations because they're always moving, somehow they're hiring new people and it has to be continuous effort because we've seen that on the hand. Organizations continue challenged their data sources and where all the data is flowing, right? Which in itself creates a lot of risk. But also on the other set hand of the equation, you have the benefit. You know, you might look at regulatory drivers like, we have to do this, right? But it's, it's much better right now to consider the competitive drivers, for example, and we did an IDC study earlier this year, quite interesting. I can recommend anyone to it. And one of the conclusions they found as they surveyed over a thousand people across organizations worldwide is that the ones who are higher in maturity. >>So the, the organizations that really look at data as an asset, look at data as a product and actively try to be better at it, don't have three times as good a business outcome as the ones who are lower on the maturity scale, right? So you can say, ok, I'm doing this, you know, data culture for everyone, awakening them up as data citizens. I'm doing this for competitive reasons, I'm doing this re reasons you're trying to bring both of those together and the ones that get data intelligence right, are successful and competitive. That's, and that's what we're seeing out there in the market. >>Absolutely. We know that just generally stand right, the organizations that are, are really creating a, a data culture and enabling everybody within the organization to become data citizens are, We know that in theory they're more competitive, they're more successful. But the IDC study that you just mentioned demonstrates they're three times more successful and competitive than their peers. Talk about how Collibra advises customers to create that community, that culture of data when it might be challenging for an organization to adapt culturally. >>Of course, of course it's difficult for an organization to adapt but it's also necessary, as you just said, imagine that, you know, you're a modern day organization, laptops, what have you, you're not using those, right? Or you know, you're delivering them throughout organization, but not enabling your colleagues to actually do something with that asset. Same thing as through with data today, right? If you're not properly using the data asset and competitors are, they're gonna to get more advantage. So as to how you get this done, establish this. There's angles to look at, Lisa. So one angle is obviously the leadership whereby whoever is the boss of data in the organization, you typically have multiple bosses there, like achieve data officers. Sometimes there's, there's multiple, but they may have a different title, right? So I'm just gonna summarize it as a data leader for a second. >>So whoever that is, they need to make sure that there's a clear vision, a clear strategy for data. And that strategy needs to include the monetization aspect. How are you going to get value from data? Yes. Now that's one part because then you can leadership in the organization and also the business value. And that's important. Cause those people, their job in essence really is to make everyone in the organization think about data as an asset. And I think that's the second part of the equation of getting that right, is it's not enough to just have that leadership out there, but you also have to get the hearts and minds of the data champions across the organization. You, I really have to win them over. And if you have those two combined and obviously a good technology to, you know, connect those people and have them execute on their responsibilities such as a data intelligence platform like s then the in place to really start upgrading that culture inch by inch if you'll, >>Yes, I like that. The recipe for success. So you are the co-founder of Collibra. You've worn many different hats along this journey. Now you're building Collibra's own data office. I like how before we went live, we were talking about Calibra is drinking its own champagne. I always loved to hear stories about that. You're speaking at Data Citizens 2022. Talk to us about how you are building a data culture within Collibra and what maybe some of the specific projects are that Collibra's data office is working on. >>Yes, and it is indeed data citizens. There are a ton of speaks here, are very excited. You know, we have Barb from m MIT speaking about data monetization. We have Dilla at the last minute. So really exciting agen agenda. Can't wait to get back out there essentially. So over the years at, we've doing this since two and eight, so a good years and I think we have another decade of work ahead in the market, just to be very clear. Data is here to stick around as are we. And myself, you know, when you start a company, we were for people in a, if you, so everybody's wearing all sorts of hat at time. But over the years I've run, you know, presales that sales partnerships, product cetera. And as our company got a little bit biggish, we're now thousand two. Something like people in the company. >>I believe systems and processes become a lot important. So we said you CBRA isn't the size our customers we're getting there in of organization structure, process systems, et cetera. So we said it's really time for us to put our money where is and to our own data office, which is what we were seeing customers', organizations worldwide. And they organizations have HR units, they have a finance unit and over time they'll all have a department if you'll, that is responsible somehow for the data. So we said, ok, let's try to set an examples that other people can take away with it, right? Can take away from it. So we set up a data strategy, we started building data products, took care of the data infrastructure. That's sort of good stuff. And in doing all of that, ISA exactly as you said, we said, okay, we need to also use our product and our own practices and from that use, learn how we can make the product better, learn how we make, can make the practice better and share that learning with all the, and on, on the Monday mornings, we sometimes refer to eating our dog foods on Friday evenings. >>We referred to that drinking our own champagne. I like it. So we, we had a, we had the driver to do this. You know, there's a clear business reason. So we involved, we included that in the data strategy and that's a little bit of our origin. Now how, how do we organize this? We have three pillars, and by no means is this a template that everyone should, this is just the organization that works at our company, but it can serve as an inspiration. So we have a pillar, which is data science. The data product builders, if you'll or the people who help the business build data products. We have the data engineers who help keep the lights on for that data platform to make sure that the products, the data products can run, the data can flow and you know, the quality can be checked. >>And then we have a data intelligence or data governance builders where we have those data governance, data intelligence stakeholders who help the business as a sort of data partner to the business stakeholders. So that's how we've organized it. And then we started following the CBRA approach, which is, well, what are the challenges that our business stakeholders have in hr, finance, sales, marketing all over? And how can data help overcome those challenges? And from those use cases, we then just started to build a map and started execution use of the use case. And a important ones are very simple. We them with our, our customers as well, people talking about the cata, right? The catalog for the data scientists to know what's in their data lake, for example, and for the people in and privacy. So they have their process registry and they can see how the data flows. >>So that's a starting place and that turns into a marketplace so that if new analysts and data citizens join kbra, they immediately have a place to go to, to look at, see, ok, what data is out there for me as an analyst or a data scientist or whatever to do my job, right? So they can immediately get access data. And another one that we is around trusted business. We're seeing that since, you know, self-service BI allowed everyone to make beautiful dashboards, you know, pie, pie charts. I always, my pet pee is the pie chart because I love buy and you shouldn't always be using pie charts. But essentially there's become proliferation of those reports. And now executives don't really know, okay, should I trust this report or that report the reporting on the same thing. But the numbers seem different, right? So that's why we have trusted this reporting. So we know if a, the dashboard, a data product essentially is built, we not that all the right steps are being followed and that whoever is consuming that can be quite confident in the result either, Right. And that silver browser, right? Absolutely >>Decay. >>Exactly. Yes, >>Absolutely. Talk a little bit about some of the, the key performance indicators that you're using to measure the success of the data office. What are some of those KPIs? >>KPIs and measuring is a big topic in the, in the data chief data officer profession, I would say, and again, it always varies with to your organization, but there's a few that we use that might be of interest. Use those pillars, right? And we have metrics across those pillars. So for example, a pillar on the data engineering side is gonna be more related to that uptime, right? Are the, is the data platform up and running? Are the data products up and running? Is the quality in them good enough? Is it going up? Is it going down? What's the usage? But also, and especially if you're in the cloud and if consumption's a big thing, you have metrics around cost, for example, right? So that's one set of examples. Another one is around the data sciences and products. Are people using them? Are they getting value from it? >>Can we calculate that value in ay perspective, right? Yeah. So that we can to the rest of the business continue to say we're tracking all those numbers and those numbers indicate that value is generated and how much value estimated in that region. And then you have some data intelligence, data governance metrics, which is, for example, you have a number of domains in a data mesh. People talk about being the owner of a data domain, for example, like product or, or customer. So how many of those domains do you have covered? How many of them are already part of the program? How many of them have owners assigned? How well are these owners organized, executing on their responsibilities? How many tickets are open closed? How many data products are built according to process? And so and so forth. So these are an set of examples of, of KPIs. There's a, there's a lot more, but hopefully those can already inspire the audience. >>Absolutely. So we've, we've talked about the rise cheap data offices, it's only accelerating. You mentioned this is like a 10 year journey. So if you were to look into a crystal ball, what do you see in terms of the maturation of data offices over the next decade? >>So we, we've seen indeed the, the role sort of grow up, I think in, in thousand 10 there may have been like 10 achieve data officers or something. Gartner has exact numbers on them, but then they grew, you know, industries and the number is estimated to be about 20,000 right now. Wow. And they evolved in a sort of stack of competencies, defensive data strategy, because the first chief data officers were more regulatory driven, offensive data strategy support for the digital program. And now all about data products, right? So as a data leader, you now need all of those competences and need to include them in, in your strategy. >>How is that going to evolve for the next couple of years? I wish I had one of those balls, right? But essentially I think for the next couple of years there's gonna be a lot of people, you know, still moving along with those four levels of the stack. A lot of people I see are still in version one and version two of the chief data. So you'll see over the years that's gonna evolve more digital and more data products. So for next years, my, my prediction is it's all products because it's an immediate link between data and, and the essentially, right? Right. So that's gonna be important and quite likely a new, some new things will be added on, which nobody can predict yet. But we'll see those pop up in a few years. I think there's gonna be a continued challenge for the chief officer role to become a real executive role as opposed to, you know, somebody who claims that they're executive, but then they're not, right? >>So the real reporting level into the board, into the CEO for example, will continue to be a challenging point. But the ones who do get that done will be the ones that are successful and the ones who get that will the ones that do it on the basis of data monetization, right? Connecting value to the data and making that value clear to all the data citizens in the organization, right? And in that sense, they'll need to have both, you know, technical audiences and non-technical audiences aligned of course. And they'll need to focus on adoption. Again, it's not enough to just have your data office be involved in this. It's really important that you're waking up data citizens across the organization and you make everyone in the organization think about data as an asset. >>Absolutely. Because there's so much value that can be extracted. Organizations really strategically build that data office and democratize access across all those data citizens. Stan, this is an exciting arena. We're definitely gonna keep our eyes on this. Sounds like a lot of evolution and maturation coming from the data office perspective. From the data citizen perspective. And as the data show that you mentioned in that IDC study, you mentioned Gartner as well, organizations have so much more likelihood of being successful and being competitive. So we're gonna watch this space. Stan, thank you so much for joining me on the cube at Data Citizens 22. We appreciate it. >>Thanks for having me over >>From Data Citizens 22, I'm Lisa Martin, you're watching The Cube, the leader in live tech coverage. >>Okay, this concludes our coverage of Data Citizens 2022, brought to you by Collibra. Remember, all these videos are available on demand@thecube.net. And don't forget to check out silicon angle.com for all the news and wiki bod.com for our weekly breaking analysis series where we cover many data topics and share survey research from our partner ETR Enterprise Technology Research. If you want more information on the products announced at Data Citizens, go to collibra.com. There are tons of resources there. You'll find analyst reports, product demos. It's really worthwhile to check those out. Thanks for watching our program and digging into Data Citizens 2022 on the Cube, your leader in enterprise and emerging tech coverage. We'll see you soon.

>>We're back with the Cube's coverage of Von 2022 from the aria in Las Vegas, we're talking pure data protection and nobody better to talk you about that than pure storage. You can't miss these guys when they're around because the orange crush is here. Dave ante for Dave Nicholson, Michael Sonic is here. He is the vice president of global alliances at pure storage. Michael. Good to see you again. Thanks for the little golf. Appreciate joy Lee. Yeah, appreciate that. Hopefully you get out there my back and, uh, be seen. So how you doing, man? I'm doing face to face. >>It's wonderful to be face to face with the cube. It's, uh, always a pleasure to have the opportunity to spend some time with you. Good to meet you. Good to meet. You have the opportunity to get, spend some time together. You guys, um, it's just great being at a show my first one back. And so I'm, uh, you know, just feeling the energy from the room and, uh, just great to come in here and see the cube all lit >>Up. Yeah. Accelerate 2019 in Austin was an awesome event. And, and one of the last ones that we did before, you know, the pandemic for all of us, um, we did some obviously support for, for virtual. You guys are having another show finally face to face in June. So look forward to that. Got it. >>20 days, 21 days, >>We'll see you there. Right. So tell us about what's going on with Veeam. Give us the update. Yeah, >>Look, we're thrilled to be here as a sponsor for Veeam and for Veeam on, uh, this is a longstanding partnership, you know, us, right. So found in 2009 start shipping product in 2012, um, really disrupted the block storage space with an all flash solution. Yeah. And you know, it's, it's a success story in terms of company going from single product to multi-product to portfolio, to solution. And along that way, the data protection use case and workload has really come into the, you know, kind of center focus for us first with flash blade in the market, which is our unified fast file and object solution. And more recently with flash array C, which is our capacity optimized flash array for block storage, which is a great relationship with Veeam and an area where we've done some, um, significant, you know, joint engineering and the FAC, which is what we refer to it as. >>And the Veeam selling motion is extremely strong. Um, and you know, it's, it's solving a real problem and that is, you know, customers are increasingly being faced with these, um, tighter and tighter SLAs to ensure the availability of their data is there. And then there's also, you know, the, the security element. And I think a term that VES using here was cyber resiliency, which I like, right. I mean, you know, the, um, safe mode integration, which is our solution for IM mutability and, and for, um, anti ransomware or, or one step to take, to, to safeguard yourself in a, against a ransomware event. Um, you know, that those are great complimentary parts of us. And indeed, >>You know, Michael, I, I, I want to ask you about your shared vision with, with Veeam. I remember I was talking to cause on the cube. Um, it might have been a 2019. I can't remember. Might have been the year before that. No, I >>Think shorts or pants. >>Sorry. >>Was he in shorts or pants? He was in pants. >>Ah, okay. So I was pushing him on, well, why don't you do it this way? Why don't you do that? Why don't you do tiering all this stuff? And it just always came back to simplicity. He said, we optimize for simplicity over all this complexity and you know, we'll get the, the function through the ecosystem partnership. So is that the shared vision with Veeam? I mean, that, it's kind of, it's just work. It just works is their mantra. But, but talk about that shared vision as particularly as it relates to data protection and cyber resiliency. >>Yeah. Thanks so much for, for recalling that Dave, cuz it, it, we hear it constantly. It's it's in the, now that we're coming back to the office, it's in the hallways, it's out in front of conference rooms, you know, the, the elegance and, and the, and the, um, value and simplicity is everywhere inside of pure. Um, I would say it's part of our shared vision. I think it's customer centricity is at the core of what Veeam and pure, you know, has really fused us together. We're both global, you know, their history is European based and grew up out of there and then have succeeded in north America. Ours is absolutely north America based first on the west coast, then across the country. And then finally into Europe, more recently globally and, and, and a lot of growth internationally, including APJ. So it's customer centricity, it's global, it's the way we go to the customer. So a partner centric go to market motion is live and well in both organizations, uh, solution providers, MSPs, GSIs, you know, range of different ways to get to that customer. Um, and without a doubt, the customer experience is, is part of the, is part of the piece. And, and that's where our simplicity is, um, front and center. And, and I know vem is the same >>Dig, dig it into it. Go ahead. >>Yeah. Yeah, no. So, so out in the real world, are the conversations still about flash for backup and recovery convincing people that that makes sense or, or have we moved on to where now it's the pure flash value proposition BEC because people accept that flash makes sense. Where, where are we in the real world? >>Yeah, I, I think it's, it's different in different industries, different use cases, different workloads, different environments, and it's, um, part of a bigger story. But I think what, what is happening now is, um, we were before the inevitability of flash as the data center, primary storage solution, but now, like, I don't think anyone would debate that. Right. And, and I think now in data protection flash as a component to a robust, secure data protection, both as a target for backup and as a source of recovery is an inevitability to be part of that conversation. Flash is >>There, you guys like to be first at a lot of things, you know, gives you bragging rights, but it also gives you market momentum. Again, I'll pull it. My, my bag of pure memories. I remember meeting Scott Deason, who was the first CEO of, of pure, it's only been two to my knowledge, right. Scott was first Charlie G Carlo now, um, in, in, it was early days, it was 2009, like in an Oracle open world or something. And he was telling me about this startup that he's doing. And, and one of the things that struck me is the vision around the API economy, which was new at the time. It was like, well, okay, what's that? And that's really, what's, what's happened here. It's part of simplicity. It's part about ecosystem. We were talking about products versus platforms. You can't really have a platform unless you have an ecosystem. So where are we at today? How does that relate to your partnership with, with Veeam? Yeah. >>It, it's such a great recall on your part, you know, cause I think, um, we are a storage company. We do provide a raise in the wild, you know, over 10,000 customer, tens of thousands of arrays now. And you know, but at the core, it's the software that matters and, and that's really what drives the user experience. And we're proud to be, you know, the development partner on the universal storage API, the us API for Veeam, that is a essential ingredient to success for the joint pure and vem customer experience. It gives them that single pane of glass, that administrative view, where they're able to get the information they need on what's happening within their environment and be able to take corrective action. And, you know, we're very proud of all the tools that we provide our storage customers, but in a da in a data protection use case and workload, they want to put, you know, they want to go right to Veeam and, and have that be the source of truth. And that's where that API is so important. >>What, what's the story to customers, Michael, in terms of particularly cyber resilience, you've got obviously got a TCO play, simple equals lower cost. Um, you got really much tighter service level agreements and requirements now, um, the security, the storage and data protection and security space are kind of coming together. So what's the narrative for customers. Give me the pitch. Yeah, >>Look, I think, I think every customer today has an obligation to include security as a must have within their solution anywhere in the data center. And for us, it's, you know, simply put the combination of Veeam for data protection, with pure for FlashRay C or flash blade with safe mode, you know, which provides that imutability provides that customer with a safeguarded copy against bad actors externally to their organization, or was jointly developed with a customer to prevent the risk of bad actors inside of the organization. Um, city of new Orleans is one of the customer references that's up on, you know, the pure storage website, just a, a great, um, you know, story in terms of the city's ability to defend against ransomware attack, continue, you know, with continuity of essential services, police, ambulances, fire departments, um, all on the combination of pure and deem. And so, you know, a good, you know, example to pull that thread all the way through in terms of what the value proposition is. And then what's the experience for the customer when they are find themselves on the other side of that event. >>What's the nature of the partnership, um, with, with Veeam, obviously there's a go to market, um, are there, you know, solutions that you guys are doing together, engineering work that you're doing together? Can you explain that? Yeah, >>You bet. I mean, you know, these are two of, uh, I think high profile adjacencies in the data center, you've got your primary storage and then secondary tertiary, and you've got your data protection use case and workload. Um, with Veeam, we've got dedicated engineering to the Veeam partnership on the pure side, as a development partner for the us API, um, you know, is a, is a key piece we're integrated into what the support experience is like for the customer. And really trying, starting to challenge ourselves now with some of the leadership changes that beam's taken on and the opportunity to sit down and, and spend some time, you know, with the non and, and John, and really say, Hey, like we're at the core here, we've got an opportunity. Let's, let's open up some strategic doors and see what could be next. >>Well, Veeam Ising, there's no question it's kind of early Veeam was the wild west that's right. Course big parties are still, you know, the reputational, but, but as you think about these joint engineering and joint go to market and you talk to, to joint customers, where do you see sort of the future? I mean, I, I, you know, the ransomware stuff, obviously the pandemic was impossible to predict. I, I shouldn't say that a lot of people did predict it, but now that we see it, but now that you have some visibility on these permanent changes that are affecting CSO, buying strategies, data protection, storage, buying strategies, how do you see the future of this relationship? >>Yeah, look, I think, I think the, um, at the core we do what we do and we're focused on continuing to innovate and do it with excellence in everything that we do. Um, we measure ourselves rigorously against a net promoter score. It's a certified net promoter score. We're at 85.2 top 1% of all B2B. So >>Head of V even >>At the core, >>Barely at the >>Core it's, it's about that customer experience and customer satisfaction. Um, and, and so that's a, maybe a, a different way of saying we trust that our partners do what they do with excellence. And in the case of Veeam, you know, partnering around the data protection, use case and workload, looking at how that's evolving into holistic data management and hybrid cloud environment. Um, we see rich opportunity for us to continue the partnerships, strengthen it, learn and listen from our customers and our partners. And, uh, and maybe challenge ourselves to, to do some things a little differently uniquely along the way I talked >>To them. Oh, good. >>Yeah, no, yeah. You, you mentioned, uh, you mentioned something at the outset that lends a lot of cred, credibility to the pure story anywhere you seek to play. Um, you mentioned that he, uh, you know, founded in 2009 product shipping in 2012. Um, I remember that Dave's not old enough to remember that period of time <laugh>, but, uh, if you remember, um, violent memory was the king, they, they were, they were the ones to be. Yep. And you guys were quietly toiling in a bit of obscurity and people were asking, well, come on, come on, come on, come on, give us something, but you didn't until you were ready. So I've seen that methodical approach in every, in every step of the way as you've transformed from being a product into solution focus and partnership focus. Um, so what does that look like? Moving forward? You, you mentioned kind of getting ahead of the game in terms of all backups and recovery, uh, volumes being on flash. What does that addressable market look like to you guys in the future? How, how are you looking at that? Yeah. Is this just the beginning of a new thing that's gonna develop over time? >>Yeah, I think, I think it's a, is a great question. It's an insightful question. It's also a great way for me to plug accelerate in, in 20, you know, 20 days or so. Um, it's a great backdrop for pure to make some announcements in terms of what's next and, and, you know, and when we're ready to make them, you know, it's a good example. Um, but, but in direct answer to your question, you know, without a doubt, you know, the adjacencies between data protection, primary storage, secondary storage, the blurring that's happening within that, you know, based on the ransomware threats, based on, you know, other environments around cloud and, and how customers have learned from cloud experiences early on and applying those learnings, not just to demanding simplicity in their solutions, but demanding the ability for, you know, kind of the storage is code and, and to have that cloud operating model across everything that they do. And so, you know, I think those are at the core, some of the things that we think about in terms of what's next and, and, uh, and to do it with partners like beam at the forefront, as well as the voice of our customer at >>The forefront. And that's why I wanted to ask you that's great setup. Thank you, David. Um, so the port works acquisition was really interesting. We're at, um, in Valencia Spain, the cube is, uh, our, our colleagues are over there. Unfortunately, John furier couldn't make the trip, the vid hit him. Uh, but one of the conversations, the topic of conversations over there is, you know, shift left with the solar winds, hack the sensitivity around the software supply chain. We certainly talked about it last week at red hat summit. I haven't heard a lot about DevOps here, but it's sort of intrinsic that, that whole shift left component, that idea of not bolting on data protection at the tail end, actually shifting left means doing it in the development cycle, not throwing it over the fence, you know, to, to the operations people. What's that conversation like subsequent to the port works acquisition, which was very interesting. A small lever can go a long way. Can you give us the update there? >>Yeah. And first and foremost, I hope John's okay. Right? >>He is. He's doing well. Good, Mr. John, >>We do. And so, you know, I think the, um, the, the future of applications is really on center stage when you put port works into the conversation mm-hmm <affirmative>. And so as companies move like no, one's gonna develop applications today without a container strategy right related to that. And that's gonna allow for the applications to move and data gravity to really play a bigger role and pure feels confident in our ability to play a big role in that. And as those applications mature up the containerized curve, they're definitely gonna have data protection, data management, other fundamental things built into it in that shift left context that we're gonna be prepared to take advantage of based on the assets. We have >>The two hardcore engineering cultures, uh, that, that have momentum, uh, pure and, and Veeam. Michael. It's great to see you again. Thanks so much for coming to the cube. >>Uh, it's always a pleasure to be with you gentlemen, and, uh, great to meet you for the first time. Good to meet you, Michael. Look forward to seeing you the next time and, and thanks again. >>All right. You bet. All right, keep it right there, everybody. Thanks for watching. This is the Cube's coverage of vem on 2022. We're at the area in Las Vegas, and we'll be right back right after the short break.

>>Hello, everybody. Welcome to Von 2022, the live version. Yes, we're finally back live. Last time we did Von was 2019 live. Of course we did two subsequent years, uh, virtual. My name is Dave Valante and we've got two days of wall to wall coverage of VEON. As usual Veeam has brought together a number of customers, but it's really doing something different this year. Like many, uh, companies that you see, they have a big hybrid event. It's close to 40,000 people online and that's sort of driving the actual program where the content is actually different for the, the, the virtual viewers versus the onsite onsite. There's the, the V I P event going on, they got the keynotes. VM is a company who's a ancy occurred during the, the VMware rise. They brought in a new way of doing data protection. They didn't use agents. They, they protected at the hypervisor level. >>That changed the way that people did things. They're now doing it again in cloud, in SAS, in containers and ransomware. And so we're gonna dig into that. My cohost is Dave Nicholson this week, and we've got a special guest Zs Carava who is the principal at ZK research. He's an extraordinary analyst Zs. Great to see you, David. Thanks for coming out. Absolutely good to see you Beon. Great to be here. Yeah, we've done. Von act, live things have changed so dramatically. Uh, I mean the focus ransomware, it's now a whole new Tam, uh, the adjacency to security data protection. It's just a Zs. It's a whole new ballgame, isn't it? >>Well, it is. And, and in fact, um, during the keynote, they, they mentioned that they've, they're now tied at number one in, for, you know, back of a recovery, which is, I think it's safe to say Veeam. Does that really well? >>I think from a that's tied with Dell. Yes. Right. They didn't, I don't think they met Dell as >>Keto. And, uh, but I, you know, they've been rising Dell, EMC's been falling. And so I think >>It's somebody said 10 points that Dell lost and sharing the I data. >>It's not a big surprise. I mean, they haven't really invested a whole lot, >>I think anyway, >>Anyways, but I think from a Veeam perspective, the question is now that they've kind of hit that number one spot or close to it, what do they do next? This company, they mentioned, I was talking the CTO yesterday. You mentioned they're holding X bite of customer data. That is a lot of data. Right. And so they, they do back recovery really well. They do it arguably better than anybody. And so how do they take that data and then move into other adjacent markets to go create, not just a back recovery company, but a true data management platform company that has relevancy in cyber and analytics and artificial intelligence and data warehousing. Right? All those other areas I think are, are really open territory for this company right now. >>You know, Dave, you were a CTO at, at EMC when you, when you saw a lot of the acquisitions that the company made, uh, you, you know, they really never had a singular focus on data protection. They had a big data protection business, but that's the differentiator with Veeam. That's all it does. And you see that shine through from a, from a CTO's perspective. How do you see this market changing, evolving? And what's your sense as to how Vema is doing here? >>I think a lot of it's being driven by kind of, uh, unfortunately evil genius, uh, out in the market space. Yeah. I know we're gonna be hearing a lot about ransomware, uh, a lot about some concepts that we didn't really talk about outside of maybe the defense industry, air gaping, logical air gaping, um, Zs, you mentioned, you know, this, this, this question of what do you do when you have so many petabytes of data under management exabytes now exabytes, I'm sorry. Yeah, I see there I'm I'm already falling behind. One thing you could do is you could encrypt it all and then ask for Bitcoin in exchange for access to that data. >>Yes. That is what happens a >>Lot of them. So we're, we're getting, we're getting so much of the evil genius stuff headed our way. You start, you start thinking in those ways, but yet to, to your point, uh, dedicated backup products, don't address the scale and scope and variety of threats, not just from operational, uh, uh, you know, mishaps, uh, but now from so many bad actors coming in from the outside, it it's a whole new world. >>See us as analysts. We get inundated with ransomware solutions. Everybody's talking about it across the spectrum. The thing that interested me about what's happening here at VEON is they're, they're sort of trotting out this study that they do Veeam does some serious research, you know, thousands of customers that got hit by ransomware that they dug into. And then a, a larger study of all companies, many of whom didn't realize or said they hadn't been hit by ransomware, but they're really trying to inject thought leadership into the equation. You saw some of that in the analyst session this morning, it's now public. Uh, so we could talk about it. What were your thoughts on that data? >>Yeah, that was, uh, really fascinating data cuz it shows the ransomware industry, the response to it is largely reactive, right? We wait to get breach. We wait to, to uh, to get held at ransom I suppose. And then we, a lot of companies paid out. In fact, I thought there's one hospital in Florida, they're buying lots and lots of Bitcoin simply to pay out ransomware attacks. They didn't even really argue with them. They just pay it out. And I think Veeam's trying to change that mentality a little bit. You know, if you have the right strategy in place to be more preventative, you can do that. You can protect your data and then restore it right when you want to. So you don't have to be in that big bucket of companies that frankly pay and actually don't get their data back. Right. >>And like a third, I think roughly >>It's shocking amount of companies that get hit by that. And for a lot of companies, that's the end of their business. >>You know, a lot of the recovery process is manual is again a technologist. You understand that that's not the ideal way to go. In fact, it's probably a, a way to fail. >>Well, recovery's always the problem when I was in corporate, it used to joke that we were the best at backup, terrible at recovery. Well, you know, that's not atypical. >>My Fred Fred Moore, who was the vice president of strategy at a company called storage tech storage technology, corpor of storage tech. He had a great, uh, saying, he said, backup is one thing. Recovery is everything. And he started, he said that 30 years ago, but, but orchestration and automating that orchestration is, is really vital. We saw in the study, a lot of organizations are using scripts and scripts are fragile here they break. Right? >>Yeah, no, absolutely. Absolutely. Um, unfortunately the idea of the red run book on the shelf is still with us. Uh, uh, you know, scripting does not equal automation necessarily in every case, there's still gonna be a lot of manual steps in the process. Um, but you know, what I hope we get to talk about during the next couple of days is, you know, some of the factors that go into this, we've got day zero exploits that have already been uncovered that are stockpiled, uh, and tucked away. And it's inevitable that they're gonna hit. Yeah. So whether it's a manual recovery process or some level of automation, um, if you don't have something that is air gapped and cut off from the rest of the world in a physical or logical way, you can't guarantee >>That the, the problem with manual processes and scripting is even if you can set it up today, the environment changes so fast, right? With shadow it and business units buying their own services and users storing things and you know, wherever, um, you, you can't keep up with scripts in manual. Automation must be the way and I've been, and I don't care what part of it. You work in, whether it's this area in networking, communications, whatever automation must be the way I think prior to the pandemic, I saw a lot of resistance from it pros in the area of mission. Since the pandemic, I've seen a lot of warming up to it because I think it pros, I just realized they can't do their job without it. So, so you >>Don't, you don't think that edge devices, uh, lend themselves to manual >>Recovery, no process. In fact, I think that's one of the things they didn't talk about. What's that is, is edge. Edge is gonna be huge. More, every retailer, I talk to oil and gas, company's been using it for a long time. I've, you know, manufacturing organizations are looking at edge as a way to put more data in more places to improve experiences. Cuz you're moving the data closer, but we're creating a world where the fragmentation of data, you think it's bad now just wait a couple of years until the edge is a little more, you know, uh, to life here. And I think you ain't see nothing yet. This is this world of data. Everywhere is truly becoming that. And the thing with edge is there's no one definition, edge, you got IOT edge cellular edge, campus edge, right? Um, you know, you look at hotels, they have their own edge. I talked to major league baseball, right? They have every, stadium's got its own edge server in it. So we're moving into a world. We're putting more data in more places it's more fragmented than ever. And we need better ways of managing Of securing that data. But then also being able to recover for when >>Things happen. I was having that Danny Allen, he used the term that we coined called super cloud. He used that in the analyst meeting today. And, and that's a metaphor for this new layer of cloud. That's developing to your point, whether it's on-prem in a hybrid across clouds, not just running on the cloud, but actually abstracting away the complexity of the underlying primitives and APIs. And then eventually to your point, going out to the edge, I don't know if anyone who has an aggressive edge strategy Veeam to its credit, you know, has gone well beyond just virtualization and gone to bare metal into cloud. They were the containers. There was first at SAS. They acquired Caston who was a partner of theirs and they tried to acquire them earlier, but there was some government things and you know, that whole thing that got cleaned up and now they've, they own Caston. And I think the edge is next. I mean, it's gotta be, there's gonna be so much data at the edge. I guess the question is where is it today? How much of that is actually persisted? How much goes back to the cloud? I don't think people really have a good answer for that yet. >>No. In fact, a lot of edge services will be very ephemeral in nature. So it's not like with cloud where we'll take data and we'll store it there forever with the edge, we're gonna take data, we'll store it there for the time, point in time we need it. But I think one of the interesting things about Veeam is because they're decoupled from the airline hardware, they can run virtual machines and containers, porting Veeam to whatever platform you have next actually isn't all that difficult. Right? And so then if you need to be able to go back to a certain point in time, they can do that instantly. It's, it's a fascinating way to do backup. Are >>You you' point about it? I mean, you remember the signs up and down, you know, near the EMC facility, right outside of Southborough no hardware agenda that that was Jeremy Burton when he was running Verto of course they've got a little hardware agenda. So, but Veeam doesn't Veeam is, you know, they they're friendly with all the hardware players of pure play software, couple other stats on them. So they're a billion dollar company. They've now started to talk about their ARR growth. They grew, uh, 27% last year in, in, in annual recurring revenue, uh, 25%, uh, in the most recent quarter. And so they're in, in the vast majority of their business is subscription. I think they said, uh, 73% is now subscription based. So they really trans transitioned that business. The other thing about vem is they they've come up with a licensing model that's very friendly. >>Um, and they sort of removed that friction early on in the process. I remember talking to TIR about this. He said, we are gonna incent our partners and make it transparent to them, whether it's, you know, that when we shift from, you know, the, the, the, the crack of, of perpetual license to a subscription model, we're gonna make that transparent to partners. We'll take care of that. Essentially. They funded that transition. So that's worked very well. So they do stand out, I think from some of the larger companies at these big portfolios, although the big portfolio companies, you know, they get board level contacts and they can elbow their ways in your thoughts on that sort of selling dynamic. >>So navigating that transition to a subscription model is always fraught with danger. Everybody wants you to be there, but they want you to be there now. Mm-hmm <affirmative>, they don't like the transition that happens over 1824 months to get there. Um, >>As a private company, they're somewhat shielded from what they would've been if they were appli. Sure, >>Exactly. But, but that, but that bodes well from a, from a, a Veeam perspective. Um, the other interesting thing is that they sit where customers sit today in the real world, a hybrid world, not everything is in the cloud or a single cloud, uh, still a lot of on-prem things to take care of. And, >>And there will be for >>A long time exactly. Back to this idea. Yeah. There's a very long tail on that. So it's, it's, it's well enough to have a niche product that addresses a certain segment of the market, but to be able to go in and say all data everywhere, it doesn't matter where it lives. We have you covered. Um, that's a powerful message. And we were talking earlier. I think they, they stand a really good shot at taking market share, you know, on an ongoing basis. >>Yeah. The interesting thing about this market, Dave is they're, you know, although, you know, they're tied to number one with Dell now, they're, it's 12%, right? This reminds me of the security industry five, six years ago, where it's so fragmented. There's so many vendors, no one really stood out right. Then what happened in security? It's a little company called Palo Alto networks came around, they created a platform story. They moved into adjacent markets like SDWAN, they did a lot of smart acquisitions and they took off. I think vem is at that similar point where they've now, you know, that 12% number they've got some capital. Now they could go do some acquisitions that they want do. There's lots of adjacent markets as they talk about this company could be the Palo Alto of the data management market, if you know, and based on good execution. But there's certainly the opportunities there with all the data that they're holding. >>That's a really interesting point. I wanna stay that in a second. So there's obviously, there's, there's backup, there's recovery, there's data protection, there's ransomware protection, there's SAS data protection. And now all of a sudden you're seeing even a company like Rubrik is kind of repositioning as a security play. Yeah. Which I'm not sure that's the right move for a company that's really been focused on, on backup to really dive into that fragmented market. But it's clearly an adjacency and we heard Anan the new CEO today in the analyst segment, you know, we asked him, what's your kinda legacy gonna look like? And he said, I want to, I want to, defragment this market he's looking at. Yeah. He wants 25 to 45% of the market, which I think is really ambitious. I love that goal now to your point, agree, he, he sure. But that doubles yeah. >>From today or more, and he gets there to your point, possibly through acquisitions, they've made some really interesting tuck-ins with Castin. They certainly bought an AWS, uh, cloud play years ago. But my, my so, uh, Veeam was purchased by, uh, private equity inside capital inside capital in January of 2020, just before COVID for 5 billion. And at the time, then COVID hit right after you were like uhoh. And then of course the market took off so great acquisition by insight. But I think an IPO is in their future and that's, uh, Zs when they can start picking up some of these adjacent markets through every day. >>And I think one of the challenges for them is now that the Holden XAB bited data, they need to be able to tell customers things they, the customer doesn't know. Right. And that's where a lot of the work they're doing in artificial intelligence machine learning comes into play. Right. And, and nobody does that better than AWS, right? AWS is always looking at your data and telling you things you don't know, which makes you buy more. And so I think from a Veeam perspective, they need to now take all this, this huge asset they have and, and find a way to monetize it. And that's by revealing these key insights to customers that the customers don't even know they have. And >>They've got that monitor monitoring layer. Um, it's if you called it, Danny, didn't like to use the term, but he called it an AI. It's really machine learning that monitors. And then I think makes recommendations. I want to dig into that a little bit with it. >>Well, you can see the platform story starting to build here. Right. And >>Here's a really good point. Yeah. Because they really have been historically a point product company. This notion of super cloud is really a platform play. >>Right. And if you look in the software industry, look across any, any segment of the software industry, those companies that were niche that became big became platforms, Salesforce, SAP, Oracle. Right. And, and they find a way to allow others to build on their platform. You know, companies, they think like a Citrix, they never did that. Yeah. And they kind of taped, you know, petered out at a certain level of growth and had to, you know, change. They're still changing their business model, in fact. But I think that's Veeam's at that inflection point, right. They either build a platform story, enable others to do more on their platform or they stagnate >>HP software is another good example. They never were able to get that platform. And we're not able bunch of spoke with it, a non used to work there. Why is it so important Dave, to have a platform over a product? >>Well, cynical, Dave says, uh, you have a platform because it attracts investment and it makes you look cooler than maybe you really are. Um, but, uh, but really for longevity, you have, you, you, you have to be a platform. So what's >>The difference. How do you know when you have platform versus it? APIs? Is it, yeah. Brett, is it ecosystem? >>Some of it is. Some of it is semantics. Look at when, when I'm worried about my critical assets, my data, um, I think of a platform, a portfolio of point solutions for backing up edge data stuff. That's in the cloud stuff that exists in SAS. I see that holistically. And I think guys, you're doing enough. This is good. Don't, don't dilute your efforts. Just keep focusing on making sure that you can back up my data wherever it lives and we'll both win together. So whenever I hear a platform, I get a little bit, a little bit sketchy, >>Well platform, beats products, doesn't >>It? Yeah. To me, it's a last word. You said ecosystem. Yes. When you think of the big platform players, everybody B in the customer, uh, experience space builds to build for Salesforce. First, if you're a small security vendor, you build for Palo Alto first, right? Right. If you're in the database, you build for Oracle first and when you're that de facto platform, you create an ecosystem around you that you no longer have to fund and build yourself. It just becomes self-fulfilling. And that drives a level of stickiness that can't be replicated through product. >>Well, look at the ecosystem that, that these guys are forming. I mean, it's clear. Yeah. So are they becoming in your view >>Of platform? I think they are becoming a platform and I think that's one of the reasons they brought on and in, I think he's got some good experience doing that. You could argue that ring kind of became that. Right. The, when, you know, when he was ring central. >>Yeah. >>Yeah. And, uh, so I think some, some of his experiences and then moving into adjacencies, I think is really the reason they brought him in to lead this company to the next level. >>Excellent guys, thanks so much for setting up VEON 20, 22, 2 days of coverage on the cube. We're here at the area. It's a, it's a great venue. I >>Love the area. >>Yeah. It's nice. It's a nice intimate spot. A lot of customers here. Of course, there's gonna be a big Veeam party. They're famous for their parties, but, uh, we'll, we'll be here to cover it and, uh, keep it right there. We'll be back with the next segment. You're watching the cube VEON 20, 22 from Las Vegas.

[Music] hello and welcome to this power panel where we go deep with three storage industry vets two from infinidat in an analyst view to find out what's happening in the high-end storage business and what's new with infinidat which has recently added significant depth to its executive ranks and we're going to review the progress on infinidat's infinibox ssa a low-latency all-solid state system designed for the most intensive enterprise workloads to do that we're joined by phil bullinger the chief executive officer of it finidet ken steinhardt is the field cto at infinidat and we bring in the analyst view with eric bergener who's the vice president of research infrastructure systems platforms and technologies group at idc all three cube alums gents welcome back to the cube good to see you thanks very much dave good to be here thanks david as always a pleasure phil let me start with you as i mentioned up top you've been top grading your team we covered the herzog news beefing up your marketing and also upping your game and emea and apj go to market recently give us the business update on the company since you became ceo earlier this year yeah dave i'd be happy to you know the uh i joined the company in january and it's been a it's been a fast 11 months uh exciting exciting times at infinidad as you know really beginning last fall the company has gone through quite a renaissance a change in the executive leadership team uh i was really excited to join the company we brought on you know a new cfo new chief human resources officer new chief legal officer operations head of operations and most recently as has been you know widely reported we brought in eric to head up our marketing organization as a cmo and then last week richard bradbury in in london to head up international sales so very excited about the team we brought together it's uh it's resulted in or it's been the culmination of a lot of work this year to accelerate the growth of infinidat and that's exactly what we've done it's the company has posted quarter after quarter of significant revenue growth we've been accelerating our rate and pace of adding large new fortune 500 global 2000 accounts and the results show it definitely the one of the most exciting things i think this year has been infinidat has pretty rapidly evolved from a single product line uh company around the infinibox architecture which is what made us unique at the start and still makes us very unique as a company and we've really expanded out from there on that same common software-defined architecture to the ssa the solid state array which we're going to talk about in some in some depth today and then our backup appliance our data protection appliance as well all running the same software and what we see now in the field uh many customers are expanding quickly beyond you know the traditional infinibox business uh to the other parts of our portfolio and our sales teams in turn are expanding their selling motion from kind of an infinibox approach to a portfolio approach and it's it's really helping accelerate the growth of the company yeah that's great to hear you really got a deep bench and of course you you know a lot of people in the industry so you're tapping a lot of your your colleagues okay let's get into the market i want to bring in uh the analyst perspective eric can you give us some context when we talk about things like ultra low latency storage what's the market look like to you help us understand the profile of the customer the workloads the market segment if you would well you bet so i'll start off with a macro trend which is clearly there's more real-time data being captured every year in fact by 2024 24 of all of the data captured and stored will be real-time and that puts very different performance requirements on the storage infrastructure than what we've seen in years past a lot of this is driven by digital transformation we've seen new workload types come in big data analytics real-time big data analytics and obviously we've got legacy workloads that need to be handled as well one other trend i'll mention that is really pointing up this need for low latency consistent low latency is workload consolidation we're seeing a lot of enterprises look to move to fewer storage platforms consolidate more storage workloads onto fewer systems and to do that they really need low latency consistent low latency platforms to be able to achieve that and continue to meet their service level agreements great thank you for that all right ken let's bring you into the conversation steiny what are the business impacts of of latency i want you to help us understand when and why is high latency a problem what are the positive impacts of having a consistent low latency uh opportunity or option and what kind of workloads and customers need that right the world has really changed i mean when when dinosaurs like me started in this industry the only people that really knew about performance were the people in the data center and then as things moved into online computing over the years then people within your own organization would care about performance if things weren't going well and it was really the erp revolution the 1990s that sort of opened uh people's eyes to the need for performance particularly for storage performance where now it's not just your internal users but your suppliers are now seeing what your systems look like fast forward to today in a web-based internet world everyone can see with customer facing applications whether you're delivering what they want or not and to answer your question it really comes down to competitive differentiation for the users that can deliver a better user customer experience if you and i'm sure everybody can relate if you go online and try to place an order especially with the holiday season coming up if there's one particular site that is able to give you instantaneous response you're more likely to do business there than somebody where you're going to be waiting and it literally is that simple it used to be that we cared about bandwidth and we used to care about ios per second and the third attribute latency really has become the only one that really matters going forward we found that most customers tell us that these days almost anyone can meet their requirements for bandwidth and ios per second with very few outlying cases where that's not true but the ever unachievable zero latency instantaneous response that's always going to be able to give people competitive differentiation in everything that they do and whoever can provide that is going to be in a very good position to help them serve their customers better yeah eric that stat you threw out of 24 real time uh and that that sort of underscores the need but phil i wonder how how this fits if you could talk about how that fits into your tam expansion strategy i think that's the job of of every ceo is to think about the expanding the tam it seems like you know a lot of people might say it's not necessarily the largest market but it's strategic and maybe opens up some downstream opportunities is that how you're thinking about it or based on what ken just said you expect this to to grow over time oh we definitely expect it to grow uh dave you know the the history of infinidat has been around our infinibox product targeting the primary storage market at the at the higher end of that market you know it's we've enjoyed operating in a eight nine 10 billion dollar tan through the years and that it continues to grow and we continue to outpace market growth within that tam which is exciting what this uh what the ssa really does is it opens up a tier of workload performance that we see more and more emerging in the primary data center the infinibox classic infinibox architecture we have very very fast as we say it typically outperforms most of our all-flash uh array competitors but clearly there there are a tier of workloads that are growing in the data center that require very very tight tail latencies and and that segment is certainly growing it's where some of the most demanding workloads are on the infinibox ssa was really built to expand our participation in those segments of the market and as i mentioned up front at the same time also taking that that software architecture and moving it into the the data protection space as well which is a whole nother market space that we're opening up for the company so we really see our tam this year with more of the this portfolio approach expanding quite a bit eric how how do you see it well those real-time applications that you talked about that require that consistent ultra-low latency grow kind of in in parallel with that that time curve you know will they become a bigger part of that the the overall storage team and and the workload mix how does idc see it yeah so so they actually are going to be growing over time and a lot of that's driven by the fact of the expectations that um steinhart mentioned a little bit earlier just on the part of customers right what they expect when they interact with your i.t infrastructure so we see that absolutely growing going forward i will make a quick comment about you know when all flash arrays first hit back in 2012 um in the 10 years since they started shipping they now generate over 80 of the primary revenues out there in in the primary storage arena so clearly they've taken over an interesting aspect of what's going on here is that a lot of companies now write rfps specifically requiring an all-flash array and what's going to be interesting for infinidat is despite the fact that they could deliver better performance than many of those systems in the past they couldn't really go after the business where that rfp was written for an afa spec well now they'll certainly have the opportunity to do that in my estimation that's going to give them access to about an additional 5 billion in tam by 2025 so this is big for them as a company yeah that's a 50 increase in tamp so okay well eric you just set up my my follow-up question to you ken was going to be the tougher questions uh which we've you and i have had some healthy debates about this but i know you'll have answers so so for years you've argued that your cached architecture and magic sauce algorithms if i caught that could outperform all flash arrays we're using spinning disks so eric talked about the sort of check off item but are there other reasons for the change of heart why and why does the world need another afa doesn't this cut against your petabyte scale messaging i wonder if you could sort of add some color to that sure a great question and the good news is infinibox still does typically outperform all flash arrays but usually that's for average of latency performance and we're tending to get because we're a a caching architecture not a tiered architecture and we're caching to dram which is an order of magnitude faster than flash or even storage class memory technologies it's our software magic and that software defined storage approach that we've had that now effectively is extended to solid state arrays and some customers told us that you know we love your performance it's incredible but if you could let us effectively be confident that we're seeing you know some millisecond sub half millisecond performance consistently for every single io you're going to give us competitive differentiation and this is one of the reasons why we chose to call the product a solid state array as opposed to merely an all-flash array the more common ubiquitous term and it's because we're not dependent on a specific technology we're using dram we can use virtually any technology on the back end and in this case we've chosen to use flash but it's the software that is able to provide that caching to the front end dram that makes things different so that's one aspect is it's the software that really makes the difference it's been the software all along and still on this architecture still mentions going to across the multiple products it's still the software it's also that in that class of ultra high performance architecturally because it is based on the infinibox architecture we're able to deliver 100 availability which is another aspect that the market has evolved to come to expect and it's not rocket science or magic how we do it the godfather of computer science john von neumann all the way back in the 1950s theorized all the way back then that the right way to do ultra high availability and integrity in i.t systems of any type is in threes triple redundancy and in our case amazingly we're the only architecture that uses triple redundant active active components for every single mission critical component on the system and that gives a level of confidence to people from an availability perspective to go with that performance that is just unmatched in the market and then bring all of that together with a set it and forget it mentality for ease of use and simplicity of management and as phil mentioned being able to have a single architecture that can address now not only the ultra high performance but across the entire swath of as eric mentioned consolidation which is a key aspect as well driving this in addition to those real-time applications that he mentioned and even being able to take it down into our our infiniguard data protection device but all with the same common base of software common interface common user experience and unmatched availability and we've got something that we really think people are going to like and they've certainly been proving that of late well i was going to ask you you know what makes the the infinibox ssa different but i think you just laid it out but your contention is this is totally unique in the marketplace is that right ken yes indeed this is a unique architecture and i i literally as a computer scientist myself truly am genuinely surprised that no other vendor in the market has taken the wisdom of the godfather of computer science john von neumann and put it into practice except in the storage world for this particular architecture which transcends our entire realm all the way from the performance down to the data protection phil i mean you have a very wide observation space in this industry and a good strong historical perspective do you think the expectations for performance and this notion of ultra low latencies you know becoming more demanding is is there a parallel so first of all why is that we've talked about a little bit but is there a parallel to the way availability remember you could have escalated over the years um because it was such a problem and now it's really become table stakes and that last mile is so hard but what are your thoughts on that i i think i think absolutely dave you know the the hallmark of infinidat is this white glove concierge level customer experience that we deliver and it's it's affirmed uh year after year in unsolicited enterprise customer feedback uh above every other competitor in our space uh infinidat sets itself apart for this um and i think that's a big part of what continues to drive and fuel the growth and success of the company i just want to touch on a couple things that ken and and eric mentioned the ssa absolutely opens up our tan because we get to we get a lot more at bats now but i think a lot of the industry looks at infinidat as well those guys are are hard drive zealots right they've their architecture is all based on rotating disk that's what they believe in and it's a hybrid versus afa world out there and they were increasingly not on the right bus and that's just absolutely not true in that our our neural cache and what ken talked about what made us unique at the start i think actually only increasingly differentiates us going forward in terms of the the set it and forget it the intelligence of our architecture the ability of that dram based cache to adapt so dynamically without any knobs and and configuration changes to massive changes in workload scale and user scale and it does it with no drama in fact most of our customers the most common feedback we get is that your platform just kind of disappears into our data infrastructure we don't think about it we don't worry about it when we install an infiniti an infinidat rack our intentions are never to come back you know we're not there showing up with trays of disk under our arms trying to upgrade a mission-critical platform that's just not our model what the ssa does is it gives our customers choice it's not about infinidat saying that used to be the shiny object now this is our new shiny object please everybody now go buy that what where where we position our ssa is it's a it's a tco latency sla choice that they can make between exactly identical customer experiences so instead of an old hybrid and a new afa we've got that same software architecture set it and forget it the neural cache and customers can choose what back-end persistent store they want based on the tco and the sla that they want to deliver to a given set of applications so probably the most significant thing that i've seen happen in the last six months at infinidat is a lot of our largest customers the the fortune 15s the fortune 50s the fortune 100s who have been long-standing infinidat customers are now on almost every sort of re-tranche of or trancha purchase orders into us we're now seeing a mix we're seeing a mix of some ssa and some classic infinibox because they're mixing and matching in a given data center down a given row these applications need this sla these applications need this la and we're able to give them that choice and frankly we don't we don't intentionally try to steer them one direction or the other they they're smart they do the math they can pick and choose what experience they want knowing that irrespective of what front door they go through into the infinidat portfolio they're going to get that same experience so i'm hearing it's not just a an rfp check off item it's more than that the market is heading in that direction eric's data on on real time and we're certainly seeing that the data-driven applications the injection of ai and you know systems making decisions in in real time um and i i'm also hearing phil that you're building on your core principles i'm hearing the white glove service the media agnostic the set it and forget it sort of principles that you guys were founded on is you're carrying that through to this this opportunity we absolutely are in the reason and you ask a good question before and i want to more completely answer it i think availability and customer experience are incredibly important today more so than ever because data center economics and data center efficiency um are more important than ever before is as customers evaluate what workloads belong in the public cloud what workloads do i want on-prem irrespective of those decisions they're trying to optimize their their operational expenses their capex expenses and so one thing that infinidat has always excelled at is consolidation bringing multiple users multiple workloads into the same common platform in the data center it says floor space and watts and and uh you know storage administration resources but to do consolidation well you've got to be incredibly reliable and incredibly predictable without a lot of fuss and drama associated with it and so i think the thing that has made infinidat really strong through the years with being a very good consolidation platform is more important now than ever before in in the enterprise storage space because it is really about data center efficiency and uh administration efficiency associated with that yeah thank you for that phil now actually ken let me come back to you i want to ask you a question about consolidation and you and i and and doc our business friend rest his soul have had some some great conversations about this over time but but as you consolidate people are sometimes worried about the blast radius could you address that concern sure well um phil alluded to software and uh it is the cornerstone of everything we bring to the table and it's not just that deep learning that transcends all the intelligence phil talked about in terms of that full wide range of product it's also protection of data across multiple sites and in multiple ways so we were very fortunate in that when we started to create this product since it is a modern product we got to start with a clean sheet of paper and basically look at everything that had been done before and even with some of the very people who created some of the original software for replication in the market were able to then say if i could do it again how would i do it today and how would it be better so we started with local replication and snapshot technology which is the foundation for being able to do full active active replication across two sites today where you can have true zero rpo no data loss even in the face of any kind of failure of a site of a server of a network of a storage device of a connection as well as zero rto immediate consistent operation with no human intervention and we can extend from that out to remote sites literally anywhere in the world in multiples where you can have additional copies of information and at any of them you can be using not only for protection against natural disasters and floods and things like that but from a cyber security perspective immutable snapshots being able to provide data that you know the bad actors can't compromise in multiple locations so we can protect today against virtually any kind of failure scenario across the swath of infinibox or infinibox ssa you can even connect infinite boxes and infinibox ssas because they are the same architecture exactly as phil said what we're seeing is people deploying mostly infinibox because it addresses the wide swath from a consolidation perspective and usually just infinibox ssa for those ultra high performance environments but the beauty of it is it looks feels runs and operates as that one single simple environment that's set it and forget it and just let it run okay so you can consolidate with with confidence uh let's end with the the independent analyst perspective eric you know how do you see this offering what do you think it means for the market is this a new category is it an extension to an existing space how do you look at that uh so i don't see it as a new category i mean it clearly falls into the current definition of afas i think it's more important from the point of view of the customer base that likes this architecture likes the availability the functionality the flexibility that it brings to the table and they can leverage it with tier zero workloads which was something that in the past they didn't have that latency consistency to do that you know i'll just make one one final comment on the software side as well so the reason software is eating the world mark andreessen is basically because of the flexibility the ease of use and the economics and if you take a look at how this particular vendor infinidat designed their product with a software-based definition they were able to swap out underneath and create a different set of characteristics with this new platform because of the flexibility in the software design and that's critical one if you think about how software is dominating so today for 2021 68 of the revenue in the external storage market that's the size of the software defined storage market that's going to be going to almost 80 by 2024 so clearly things are moving in the direction of systems that are defined in a software-defined manner yeah and data is eating software which is why you're going to need ultra low latency um okay we got to wrap it eric you've just published a piece uh this summer called enterprise storage vendor infinidat expands total available market opportunities with all flash system introduction i'm sure they can get that on your website here's a little graphic that shows you how to get that but so guys thanks so much for coming on the cube congratulations on the progress and uh we'll be watching thanks steve thanks very much dave thank you as always a pleasure all right thank you for watching this cube conversation everybody this is dave vellante and we'll see you next time [Music] you

>>from around the globe. It's the Cube presenting innovation for good, brought to you by on shape. >>Hello, everyone, and welcome to Innovation for Good Program, hosted by the Cuban. Brought to You by on Shape, which is a PTC company. My name is Dave Valentin. I'm coming to you from our studios outside of Boston. I'll be directing the conversations today. It's a very exciting, all live program. We're gonna look at how product innovation has evolved and where it's going and how engineers, entrepreneurs and educators are applying cutting edge, cutting edge product development techniques and technology to change our world. You know, the pandemic is, of course, profoundly impacted society and altered how individuals and organizations they're gonna be thinking about an approaching the coming decade. Leading technologists, engineers, product developers and educators have responded to the new challenges that we're facing from creating lifesaving products to helping students learn from home toe how to apply the latest product development techniques and solve the world's hardest problems. And in this program, you'll hear from some of the world's leading experts and practitioners on how product development and continuous innovation has evolved, how it's being applied toe positive positively affect society and importantly where it's going in the coming decades. So let's get started with our first session fueling Tech for good. And with me is John Hirschbeck, who is the president of the Suffers, a service division of PTC, which acquired on shape just over a year ago, where John was the CEO and co founder, and Dana Grayson is here. She is the co founder and general partner at Construct Capital, a new venture capital firm. Folks, welcome to the program. Thanks so much for coming on. >>Great to be here, Dave. >>All right, John. >>You're very welcome. Dana. Look, John, let's get into it for first Belated congratulations on the acquisition of Von Shape. That was an awesome seven year journey for your company. Tell our audience a little bit about the story of on shape, but take us back to Day zero. Why did you and your co founders start on shape? Well, >>actually, start before on shaping the You know, David, I've been in this business for almost 40 years. The business of building software tools for product developers and I had been part of some previous products in the industry and companies that had been in their era. Big changes in this market and about, you know, a little Before founding on shape, we started to see the problems product development teams were having with the traditional tools of that era years ago, and we saw the opportunity presented by Cloud Web and Mobile Technology. And we said, Hey, we could use Cloud Web and Mobile to solve the problems of product developers make their Their business is run better. But we have to build an entirely new system, an entirely new company, to do it. And that's what on shapes about. >>Well, so notwithstanding the challenges of co vid and difficulties this year, how is the first year been as, Ah, division of PTC for you guys? How's business? Anything you can share with us? >>Yeah, our first year of PTC has been awesome. It's been, you know, when you get acquired, Dave, you never You know, you have great optimism, but you never know what life will really be like. It's sort of like getting married or something, you know, until you're really doing it, you don't know. And so I'm happy to say that one year into our acquisition, um, PTC on shape is thriving. It's worked out better than I could have imagined a year ago. Along always, I mean sales are up. In Q four, our new sales rate grew 80% vs Excuse me, our fiscal Q four Q three. In the calendar year, it grew 80% compared to the year before. Our educational uses skyrocketing with around 400% growth, most recently year to year of students and teachers and co vid. And we've launched a major cloud platform using the core of on shape technology called Atlas. So, um, just tons of exciting things going on a TTC. >>That's awesome. But thank you for sharing some of those metrics. And of course, you're very humble individual. You know, people should know a little bit more about you mentioned, you know, we founded Solid Works, co founded Solid where I actually found it solid works. You had a great exit in the in the late nineties. But what I really appreciate is, you know, you're an entrepreneur. You've got a passion for the babies that you you helped birth. You stayed with the salt systems for a number of years. The company that quiet, solid works well over a decade. And and, of course, you and I have talked about how you participated in the the M I T. Blackjack team. You know, back in the day, a zai say you're very understated, for somebody was so accomplished. Well, >>that's kind of you, but I tend to I tend Thio always keep my eye more on what's ahead. You know what's next, then? And you know, I look back Sure to enjoy it and learn from it about what I can put to work making new memories, making new successes. >>Love it. Okay, let's bring Dana into the conversation. Hello, Dana. You look you're a fairly early investor in in on shape when you were with any A And and I think it was like it was a serious B, but it was very right close after the A raise. And and you were and still are a big believer in industrial transformation. So take us back. What did you see about on shape back then? That excited you. >>Thanks. Thanks for that. Yeah. I was lucky to be a early investment in shape. You know, the things that actually attracted me. Don shape were largely around John and, uh, the team. They're really setting out to do something, as John says humbly, something totally new, but really building off of their background was a large part of it. Um, but, you know, I was really intrigued by the design collaboration side of the product. Um, I would say that's frankly what originally attracted me to it. What kept me in the room, you know, in terms of the industrial world was seeing just if you start with collaboration around design what that does to the overall industrial product lifecycle accelerating manufacturing just, you know, modernizing all the manufacturing, just starting with design. So I'm really thankful to the on shape guys, because it was one of the first investments I've made that turned me on to the whole sector. And while just such a great pleasure to work with with John and the whole team there. Now see what they're doing inside PTC. >>And you just launched construct capital this year, right in the middle of a pandemic and which is awesome. I love it. And you're focused on early stage investing. Maybe tell us a little bit about construct capital. What your investment thesis is and you know, one of the big waves that you're hoping to ride. >>Sure, it construct it is literally lifting out of any what I was doing there. Um uh, for on shape, I went on to invest in companies such as desktop metal and Tulip, to name a couple of them form labs, another one in and around the manufacturing space. But our thesis that construct is broader than just, you know, manufacturing and industrial. It really incorporates all of what we'd call foundational industries that have let yet to be fully tech enabled or digitized. Manufacturing is a big piece of it. Supply chain, logistics, transportation of mobility or not, or other big pieces of it. And together they really drive, you know, half of the GDP in the US and have been very under invested. And frankly, they haven't attracted really great founders like they're on in droves. And I think that's going to change. We're seeing, um, entrepreneurs coming out of the tech world orthe Agnelli into these industries and then bringing them back into the tech world, which is which is something that needs to happen. So John and team were certainly early pioneers, and I think, you know, frankly, obviously, that voting with my feet that the next set, a really strong companies are going to come out of the space over the next decade. >>I think it's a huge opportunity to digitize the sort of traditionally non digital organizations. But Dana, you focused. I think it's it's accurate to say you're focused on even Mawr early stage investing now. And I want to understand why you feel it's important to be early. I mean, it's obviously riskier and reward e er, but what do you look for in companies and and founders like John >>Mhm, Um, you know, I think they're different styles of investing all the way up to public market investing. I've always been early stage investors, so I like to work with founders and teams when they're, you know, just starting out. Um, I happened to also think that we were just really early in the whole digital transformation of this world. You know, John and team have been, you know, back from solid works, etcetera around the space for a long time. But again, the downstream impact of what they're doing really changes the whole industry. And and so we're pretty early and in digitally transforming that market. Um, so that's another reason why I wanna invest early now, because I do really firmly believe that the next set of strong companies and strong returns for my own investors will be in the spaces. Um, you know, what I look for in Founders are people that really see the world in a different way. And, you know, sometimes some people think of founders or entrepreneurs is being very risk seeking. You know, if you asked John probably and another successful entrepreneurs, they would call themselves sort of risk averse, because by the time they start the company, they really have isolated all the risk out of it and think that they have given their expertise or what they're seeing their just so compelled to go change something, eh? So I look for that type of attitude experience a Z. You can also tell from John. He's fairly humble. So humility and just focus is also really important. Um, that there's a That's a lot of it. Frankly, >>Excellent. Thank you, John. You got such a rich history in the space. Uh, and one of you could sort of connect the dots over time. I mean, when you look back, what were the major forces that you saw in the market in in the early days? Particularly days of on shape on? And how is that evolved? And what are you seeing today? Well, >>I think I touched on it earlier. Actually, could I just reflect on what Dana said about risk taking for just a quick one and say, throughout my life, from blackjack to starting solid works on shape, it's about taking calculated risks. Yes, you try to eliminate the risk Sa's much as you can, but I always say, I don't mind taking a risk that I'm aware of, and I've calculated through as best I can. I don't like taking risks that I don't know I'm taking. That's right. You >>like to bet on >>sure things as much as you sure things, or at least where you feel you. You've done the research and you see them and you know they're there and you know, you, you you keep that in mind in the room, and I think that's great. And Dana did so much for us. Dana, I want to thank you again. For all that, you did it every step of the way, from where we started to to, you know, your journey with us ended formally but continues informally. Now back to you, Dave, I think, question about the opportunity and how it's shaped up. Well, I think I touched on it earlier when I said It's about helping product developers. You know, our customers of the people build the future off manufactured goods. Anything you think of that would be manufacturing factory. You know, the chair you're sitting in machine that made your coffee. You know, the computer you're using, the trucks that drive by on the street, all the covert product research, the equipment being used to make vaccines. All that stuff is designed by someone, and our job is given the tools to do it better. And I could see the problems that those product developers had that we're slowing them down with using the computing systems of the time. When we built solid works, that was almost 30 years ago. If people don't realize that it was in the early >>nineties and you know, we did the >>best we could for the early nineties, but what we did. We didn't anticipate the world of today. And so people were having problems with just installing the systems. Dave, you wouldn't believe how hard it is to install these systems. You need toe speck up a special windows computer, you know, and make sure you've got all the memory and graphics you need and getting to get that set up. You need to make sure the device drivers air, right, install a big piece of software. Ah, license key. I'm not making this up. They're still around. You may not even know what those are. You know, Dennis laughing because, you know, zero cool people do things like this anymore. Um, and it only runs some windows. You want a second user to use it? They need a copy. They need a code. Are they on the same version? It's a nightmare. The teams change, you know? You just say, Well, get everyone on the software. Well, who's everyone? You know, you got a new vendor today? A new customer tomorrow, a new employee. People come on and off the team. The other problem is the data stored in files, thousands of files. This isn't like a spreadsheet or word processor, where there's one file to pass around these air thousands of files to make one, even a simple product. People were tearing their hair out. John, what do we do? I've got copies everywhere. I don't know where the latest version is. We tried like, you know, locking people out so that only one person can change it At the time that works against speed, it works against innovation. We saw what was happening with Cloud Web and mobile. So what's happened in the years since is every one of the forces that product developers experience the need for speed, the need for innovation, the need to be more efficient with their people in their capital. Resource is every one of those trends have been amplified since we started on shape by a lot of forces in the world. And covert is amplified all those the need for agility and remote work cove it is amplified all that the same time, The acceptance of cloud. You know, a few years ago, people were like cloud, you know, how is that gonna work now They're saying to me, You know, increasingly, how would you ever even have done this without the cloud. How do you make solid works work without the cloud? How would that even happen? You know, once people understand what on shapes about >>and we're the >>Onley full SAS solution software >>as a service, >>full SAS solution in our industry. So what's happened in those years? Same problems we saw earlier, but turn up the gain, their bigger problems. And with cloud, we've seen skepticism of years ago turn into acceptance. And now even embracement in the cova driven new normal. >>Yeah. So a lot of friction in the previous environments cloud obviously a huge factor on, I guess. I guess Dana John could see it coming, you know, in the early days of solid works with, you know, had Salesforce, which is kind of the first major independent SAS player. Well, I guess that was late nineties. So his post solid works, but pre in shape and their work day was, you know, pre on shape in the mid two thousands. And and but But, you know, the bet was on the SAS model was right for Crick had and and product development, you know, which maybe the time wasn't a no brainer. Or maybe it was, I don't know, but Dana is there. Is there anything that you would invest in today? That's not Cloud based? >>Um, that's a great question. I mean, I think we still see things all the time in the manufacturing world that are not cloud based. I think you know, the closer you get to the shop floor in the production environment. Um e think John and the PTC folks would agree with this, too, but that it's, you know, there's reliability requirements, performance requirements. There's still this attitude of, you know, don't touch the printing press. So the cloud is still a little bit scary sometimes. And I think hybrid cloud is a real thing for those or on premise. Solutions, in some cases is still a real thing. What what we're more focused on. And, um, despite whether it's on premise or hybrid or or SAS and Cloud is a frictionless go to market model, um, in the companies we invest in so sass and cloud, or really make that easy to adopt for new users, you know, you sign up, started using a product, um, but whether it's hosted in the cloud, whether it's as you can still distribute buying power. And, um, I would I'm just encouraging customers in the customer world and the more industrial environment to entrust some of their lower level engineers with more budget discretionary spending so they can try more products and unlock innovation. >>Right? The unit economics are so compelling. So let's bring it, you know, toe today's you know, situation. John, you decided to exit about a year ago. You know? What did you see in PTC? Other than the obvious money? What was the strategic fit? >>Yeah, Well, David, I wanna be clear. I didn't exit anything. Really? You >>know, I love you and I don't like that term exit. I >>mean, Dana had exit is a shareholder on and so it's not It's not exit for me. It's just a step in the journey. What we saw in PTC was a partner. First of all, that shared our vision from the top down at PTC. Jim Hempleman, the CEO. He had a great vision for for the impact that SAS can make based on cloud technology and really is Dana of highlighted so much. It's not just the technology is how you go to market and the whole business being run and how you support and make the customers successful. So Jim shared a vision for the potential. And really, really, um said Hey, come join us and we can do this bigger, Better, faster. We expanded the vision really to include this Atlas platform for hosting other SAS applications. That P D. C. I mean, David Day arrived at PTC. I met the head of the academic program. He came over to me and I said, You know, and and how many people on your team? I thought he'd say 5 40 people on the PTC academic team. It was amazing to me because, you know, we were we were just near about 100 people were required are total company. We didn't even have a dedicated academic team and we had ah, lot of students signing up, you know, thousands and thousands. Well, now we have hundreds of thousands of students were approaching a million users and that shows you the power of this team that PTC had combined with our product and technology whom you get a big success for us and for the teachers and students to the world. We're giving them great tools. So so many good things were also putting some PTC technology from other parts of PTC back into on shape. One area, a little spoiler, little sneak peek. Working on taking generative design. Dana knows all about generative design. We couldn't acquire that technology were start up, you know, just to too much to do. But PTC owns one of the best in the business. This frustrated technology we're working on putting that into on shaping our customers. Um, will be happy to see it, hopefully in the coming year sometime. >>It's great to see that two way exchange. Now, you both know very well when you start a company, of course, a very exciting time. You know, a lot of baggage, you know, our customers pulling you in a lot of different directions and asking you for specials. You have this kind of clean slate, so to speak in it. I would think in many ways, John, despite you know, your install base, you have a bit of that dynamic occurring today especially, you know, driven by the forced march to digital transformation that cove it caused. So when you sit down with the team PTC and talk strategy. You now have more global resource is you got cohorts selling opportunities. What's the conversation like in terms of where you want to take the division? >>Well, Dave, you actually you sounds like we should have you coming in and talking about strategy because you've got the strategy down. I mean, we're doing everything said global expansion were able to reach across selling. We got some excellent PTC customers that we can reach reach now and they're finding uses for on shape. I think the plan is to, you know, just go, go, go and grow, grow, grow where we're looking for this year, priorities are expand the product. I mentioned the breath of the product with new things PTC did recently. Another technology that they acquired for on shape. We did an acquisition. It was it was small, wasn't widely announced. It, um, in an area related to interfacing with electrical cad systems. So So we're doing We're expanding the breath of on shape. We're going Maura, depth in the areas were already in. We have enormous opportunity to add more features and functions that's in the product. Go to market. You mentioned it global global presence. That's something we were a little light on a year ago. Now we have a team. Dana may not even know what we have. A non shape, dedicated team in Barcelona, based in Barcelona but throughout Europe were doing multiple languages. Um, the academic program just introduced a new product into that space that z even fueling more success and growth there. Um, and of course, continuing to to invest in customer success and this Atlas platform story I keep mentioning, we're going to soon have We're gonna soon have four other major PTC brands shipping products on our Atlas Saas platform. And so we're really excited about that. That's good for the other PTC products. It's also good for on shape because now there's there's. There's other interesting products that are on shape customers can use take advantage of very easily using, say, a common log in conventions about user experience there, used to invest of all they're SAS based, so they that makes it easier to begin with. So that's some of the exciting things going on. I think you'll see PTC, um, expanding our lead in SAS based applications for this sector for our our target, uh, sectors not just in, um, in cat and data management, but another area. PTC's Big and his augmented reality with of euphoria, product line leader and industrial uses of a R. That's a whole other story we should do. A whole nother show augmented reality. But these products are amazing. You can you can help factory workers people on, uh, people who are left out of the digital transformation. Sometimes we're standing from machine >>all day. >>They can't be sitting like we are doing Zoom. They can wear a R headset in our tools, let them create great content. This is an area Dana is invested in other companies. But what I wanted to note is the new releases of our authoring software. For this, our content getting released this month, used through the Atlas platform, the SAS components of on shape for things like revision management and collaboration on duh workflow activity. All that those are tools that we're able to share leverage. We get a lot of synergy. It's just really good. It's really fun to have a good time. That's >>awesome. And then we're gonna be talking to John MacLean later about that. Let's do a little deeper Dive on that. And, Dana, what is your involvement today with with on shape? But you're looking for you know, which of their customers air actually adopting. And they're gonna disrupt their industries. And you get good pipeline from that. How do you collaborate today? >>That sounds like a great idea. Um, Aziz, John will tell you I'm constantly just asking him for advice and impressions of other entrepreneurs and picking his brain on ideas. No formal relationship clearly, but continue to count John and and John and other people in on shaping in the circle of experts that I rely on for their opinions. >>All right, so we have some questions from the crowd here. Uh, one of the questions is for the dream team. You know, John and Dana. What's your next next collective venture? I don't think we're there yet, are we? No. >>I just say, as Dana said, we love talking to her about. You know, Dana, you just returned the compliment. We would try and give you advice and the deals you're looking at, and I'm sort of casually mentoring at least one of your portfolio entrepreneurs, and that's been a lot of fun for May on, hopefully a value to them. But also Dana. We uran important pipeline to us in the world of some new things that are happening that we wouldn't see if you know you've shown us some things that you've said. What do you think of this business? And for us, it's like, Wow, it's cool to see that's going on And that's what's supposed to work in an ecosystem like this. So we we deeply value the ongoing relationship. And no, we're not starting something new. I got a lot of work left to do with what I'm doing and really happy. But we can We can collaborate in this way on other ventures. >>I like this question to somebody asking With the cloud options like on shape, Wilmore students have stem opportunities s Oh, that's a great question. Are you because of sass and cloud? Are you able to reach? You know, more students? Much more cost effectively. >>Yeah, Dave, I'm so glad that that that I was asked about this because Yes, and it's extremely gratified us. Yes, we are because of cloud, because on shape is the only full cloud full SAS system or industry were able to reach. Stem education brings able to be part of bringing step education to students who couldn't get it otherwise. And one of most gratifying gratifying things to me is the emails were getting from teachers, um, that that really, um, on the phone calls that were they really pour their heart out and say We're able to get to students in areas that have very limited compute resource is that don't have an I T staff where they don't know what computer that the students can have at home, and they probably don't even have a computer. We're talking about being able to teach them on a phone to have an android phone a low end android phone. You can do three D modeling on there with on shape. Now you can't do it any other system, but with on shape, you could do it. And so the teacher can say to the students, They have to have Internet access, and I know there's a huge community that doesn't even have Internet access, and we're not able, unfortunately to help that. But if you have Internet and you have even an android phone, we can enable the educator to teach them. And so we have case after case of saving a stem program or expanding it into the students that need it most is the ones we're helping here. So really excited about that. And we're also able to let in addition to the run on run on whatever computing devices they have, we also offer them the tools they need for remote teaching with a much richer experience. Could you teach solid works remotely? Well, maybe if the student ran it had a windows workstation. You know, big, big, high end workstation. Maybe it could, but it would be like the difference between collaborating with on shape and collaborate with solid works. Like the difference between a zoom video call and talking on the landline phone. You know, it's a much richer experience, and that's what you need. And stem teaching stem is hard, So yeah, we're super super. Um, I'm excited about bringing stem to more students because of cloud yond >>we're talking about innovation for good, and then the discussion, John, you just had it. Really? There could be a whole another vector here. We could discuss on diversity, and I wanna end with just pointing out. So, Dana, your new firm, it's a woman led firm, too. Two women leaders, you know, going forward. So that's awesome to see, so really? Yeah, thumbs up on that. Congratulations on getting that off the ground. >>Thank you. Thank you. >>Okay, so thank you guys. Really appreciate It was a great discussion. I learned a lot and I'm sure the audience did a swell in a moment. We're gonna talk with on shaped customers to see how they're applying tech for good and some of the products that they're building. So keep it right there. I'm Dave Volonte. You're watching innovation for good on the Cube, the global leader in digital tech event coverage. Stay right there. >>Oh, yeah, it's >>yeah, yeah, around >>the globe. It's the Cube presenting innovation for good. Brought to you by on shape. >>Okay, we're back. This is Dave Volonte and you're watching innovation for good. A program on Cuba 3 65 made possible by on shape of PTC company. We're live today really live tv, which is the heritage of the Cube. And now we're gonna go to the sources and talkto on shape customers to find out how they're applying technology to create real world innovations that are changing the world. So let me introduce our panel members. Rafael Gomez Furberg is with the Chan Zuckerberg bio hub. A very big idea. And collaborative nonprofit was initiative that was funded by Mark Zuckerberg and his wife, Priscilla Chan, and really around diagnosing and curing and better managing infectious diseases. So really timely topic. Philip Tabor is also joining us. He's with silver side detectors, which develops neutron detective detection systems. Yet you want to know if early, if neutrons and radiation or in places where you don't want them, So this should be really interesting. And last but not least, Matthew Shields is with the Charlottesville schools and is gonna educate us on how he and his team are educating students in the use of modern engineering tools and techniques. Gentlemen, welcome to the Cuban to the program. This should be really interesting. Thanks for coming on. >>Hi. Or pleasure >>for having us. >>You're very welcome. Okay, let me ask each of you because you're all doing such interesting and compelling work. Let's start with Rafael. Tell us more about the bio hub and your role there, please. >>Okay. Yeah. So you said that I hope is a nonprofit research institution, um, funded by Mark Zuckerberg and his wife, Priscilla Chan. Um, and our main mission is to develop new technologies to help advance medicine and help, hopefully cure and manage diseases. Um, we also have very close collaborations with Universe California, San Francisco, Stanford University and the University California Berkeley on. We tried to bring those universities together, so they collaborate more of biomedical topics. And I manage a team of engineers. They by joining platform. Um, and we're tasked with creating instruments for the laboratory to help the scientist boats inside the organization and also in the partner universities Do their experiments in better ways in ways that they couldn't do before >>in this edition was launched Well, five years ago, >>it was announced at the end of 2016, and we actually started operation with at the beginning of 2017, which is when I joined, um, So this is our third year. >>And how's how's it going? How does it work? I mean, these things take time. >>It's been a fantastic experience. Uh, the organization works beautifully. Um, it was amazing to see it grow From the beginning, I was employee number 12, I think eso When I came in, it was just a nem P office building and empty labs. And very quickly we had something running about. It's amazing eso I'm very proud of the work that we have done to make that possible. Um And then, of course, that's you mentioned now with co vid, um, we've been able to do a lot of very cool work attire being of the pandemic in March, when there was a deficit of testing, uh, capacity in California, we spun up a testing laboratory in record time in about a week. It was crazy. It was a crazy project, Um, but but incredibly satisfying. And we ended up running all the way until the beginning of November, when the lab was finally shut down. We could process about 3000 samples a day. I think at the end of it all, we were able to test about 100 on the order of 100 and 50,000 samples from all over the state. We were providing free testing toe all of the Department of Public Health Department of Public Health in California, which at the media pandemic, had no way to do testing affordably and fast. So I think that was a great service to the state. Now the state has created that testing system that would serve those departments. So then we decided that it was unnecessary to keep going with testing in the other biopsy that would shut down. >>All right. Thank you for that. Now, Now, Philip, you What you do is mind melting. You basically helped keep the world safe. Maybe describe a little bit more about silver sod detectors and what your role is there and how it all works. >>Tour. So we make a nuclear bomb detectors and we also make water detectors. So we try and do our part thio keep the world from blowing up and make it a better place at the same time. Both of these applications use neutron radiation detectors. That's what we make. Put them out by import border crossing places like that. They can help make sure that people aren't smuggling. Shall we say very bad things. Um, there's also a burgeoning field of research and application where you can use neutrons with some pretty cool physics to find water so you could do things. Like what? A detector up in the mountains and measure snowpack. Put it out in the middle of the field and measure soil moisture content. And as you might imagine, there's some really cool applications in, uh, research and agronomy and public policy for this. >>All right, so it's OK, so it's a It's much more than, you know, whatever fighting terrorism, it's there's a riel edge or I kind of i o t application for what you guys >>do. We do both its's to plowshares. You might >>say a mat. I I look at your role is kind of scaling the brain power for for the future. Maybe tell us more about Charlottesville schools and in the mission that you're pursuing and what you do. >>Thank you. Um, I've been in Charlottesville City schools for about 11 or 12 years. I started their teaching, um, a handful of classes, math and science and things like that. But Thescore board and my administration had the crazy idea of starting an engineering program about seven years ago. My background is an engineering is an engineering. My masters is in mechanical and aerospace engineering and um, I basically spent a summer kind of coming up with what might be a fun engineering curriculum for our students. And it started with just me and 30 students about seven years ago, Um, kind of a home spun from scratch curriculum. One of my goals from the outset was to be a completely project based curriculum, and it's now grown. We probably have about six or 700 students, five or six full time teachers. We now have pre engineering going on at the 5th and 6th grade level. I now have students graduating. Uh, you know, graduating after senior year with, like, seven years of engineering under their belt and heading off to doing some pretty cool stuff. So it's It's been a lot of fun building a program and, um, and learning a lot in the process. >>That's awesome. I mean, you know, Cuba's. We've been passionate about things like women in tech, uh, diversity stem. You know, not only do we need more, more students and stem, we need mawr underrepresented women, minorities, etcetera. We were just talking to John Herstek and integrate gration about this is Do you do you feel is though you're I mean, first of all, the work that you do is awesome, but but I'll go one step further. Do you feel as though it's reaching, um, or diverse base? And how is that going? >>That's a great question. I think research shows that a lot of people get funneled into one kind of track or career path or set of interests really early on in their educational career, and sometimes that that funnel is kind of artificial. And so that's one of the reasons we keep pushing back. Um, so our school systems introducing kindergartners to programming on DSO We're trying to push back how we expose students to engineering and to stem fields as early as possible. And we've definitely seen the first of that in my program. In fact, my engineering program, uh, sprung out of an after school in Extracurricular Science Club that actually three girls started at our school. So I think that actually has helped that three girls started the club that eventually is what led to our engineering programs that sort of baked into the DNA and also our eyes a big public school. And we have about 50% of the students are under the poverty line and we e in Charlottesville, which is a big refugee town. And so I've been adamant from Day one that there are no barriers to entry into the program. There's no test you have to take. You don't have to have be taking a certain level of math or anything like that. That's been a lot of fun. To have a really diverse set of kids enter the program and be successful, >>that's final. That's great to hear. So, Philip, I wanna come back to you. You know, I think about maybe some day we'll be able to go back to a sporting events, and I know when I when I'm in there, there's somebody up on the roof looking out for me, you know, watching the crowd, and they have my back. And I think in many ways, the products that you build, you know, our similar. I may not know they're there, but they're keeping us safe or they're measuring things that that that I don't necessarily see. But I wonder if you could talk about a little bit more detail about the products you build and how they're impacting society. >>Sure, so There are certainly a lot of people who are who are watching, trying to make sure things were going well in keeping you safe that you may or may not be aware of. And we try and support ah lot of them. So we have detectors that are that are deployed in a variety of variety of uses, with a number of agencies and governments that dio like I was saying, ports and border crossing some other interesting applications that are looking for looking for signals that should not be there and working closely to fit into the operations these folks do. Onda. We also have a lot of outreach to researchers and scientists trying to help them support the work they're doing. Um, using neutron detection for soil moisture monitoring is a some really cool opportunities for doing it at large scale and with much less, um, expense or complication than would have been done. Previous technologies. Um, you know, they were talking about collaboration in the previous segment. We've been able to join a number of conferences for that, virtually including one that was supposed to be held in Boston, but another one that was held out of the University of Heidelberg in Germany. And, uh, this is sort of things that in some ways, the pandemic is pushing people towards greater collaboration than they would have been able to do. Had it all but in person. >>Yeah, we did. Uh, the cube did live works a couple years ago in Boston. It was awesome show. And I think, you know, with this whole trend toward digit, I call it the Force march to digital. Thanks to cove it I think that's just gonna continue. Thio grow. Rafael. What if you could describe the process that you use to better understand diseases? And what's your organization's involvement? Been in more detail, addressing the cove in pandemic. >>Um, so so we have the bio be structured in, Um um in a way that foster so the combination of technology and science. So we have to scientific tracks, one about infectious diseases and the other one about understanding just basic human biology, how the human body functions, and especially how the cells in the human body function on how they're organized to create tissues in the body. On Ben, it has this set of platforms. Um, mind is one of them by engineering that are all technology rated. So we have data science platform, all about data analysis, machine learning, things like that. Um, we have a mass spectrometry platform is all about mass spectrometry technologies to, um, exploit those ones in service for the scientist on. We have a genomics platform that it's all about sequencing DNA and are gonna, um and then an advanced microscopy. It's all about developing technologies, uh, to look at things with advanced microscopes and developed technologies to marry computation on microscopy. So, um, the scientists set the agenda and the platforms, we just serve their needs, support their needs, and hopefully develop technologies that help them do their experiments better, faster, or allow them to the experiment that they couldn't do in any other way before. Um And so with cove, it because we have that very strong group of scientists that work on have been working on infectious disease before, and especially in viruses, we've been able to very quickly pivot to working on that s O. For example, my team was able to build pretty quickly a machine to automatically purified proteins on is being used to purify all these different important proteins in the cove. It virus the SARS cov to virus Onda. We're sending some of those purified proteins all over the world. Two scientists that are researching the virus and trying to figure out how to develop vaccines, understand how the virus affects the body and all that. Um, so some of the machines we built are having a very direct impact on this. Um, Also for the copy testing lab, we were able to very quickly develop some very simple machines that allowed the lab to function sort of faster and more efficiently. Sort of had a little bit of automation in places where we couldn't find commercial machines that would do it. >>Um, eso Matt. I mean, you gotta be listening to this and thinking about Okay, So someday your students are gonna be working at organizations like like, like Bio Hub and Silver Side. And you know, a lot of young people they're just don't know about you guys, but like my kids, they're really passionate about changing the world. You know, there's way more important than you know, the financial angles and it z e. I gotta believe you're seeing that you're right in the front lines there. >>Really? Um, in fact, when I started the curriculum six or seven years ago, one of the first bits of feedback I got from my students is they said Okay, this is a lot of fun. So I had my students designing projects and programming microcontrollers raspberry, PiS and order we nose and things like that. The first bit of feedback I got from students was they said Okay, when do we get to impact the world? I've heard engineering >>is about >>making the world a better place, and robots are fun and all, but, you know, where is the real impact? And so um, dude, yeah, thanks to the guidance of my students, I'm baking that Maurin. Now I'm like day one of engineering one. We talk about how the things that the tools they're learning and the skills they're gaining, uh, eventually, you know, very soon could be could be used to make the world a better place. >>You know, we all probably heard that famous line by Jeff Hammer Barker. The greatest minds of my generation are trying to figure out how to get people to click on ads. I think we're really generally generationally, finally, at the point where young students and engineering a really, you know, a passionate about affecting society. I wanna get into the product, you know, side and understand how each of you are using on shape and and the value that that it brings. Maybe Raphael, you could start how long you've been using it. You know, what's your experience with it? Let's let's start there. >>I begin for about two years, and I switched to it with some trepidation. You know, I was used to always using the traditional product that you have to install on your computer, that everybody uses that. So I was kind of locked into that. But I started being very frustrated with the way it worked, um, and decided to give on ship chance. Which reputation? Because any change always, you know, causes anxiety. Um, but very quickly my engineers started loving it, Uh, just because it's it's first of all, the learning curve wasn't very difficult at all. You can transfer from one from the traditional product to entree very quickly and easily. You can learn all the concepts very, very fast. It has all the functionality that we needed and and what's best is that it allows to do things that we couldn't do before or we couldn't do easily. Now we can access the our cat documents from anywhere in the world. Um, so when we're in the lab fabricating something or testing a machine, any computer we have next to us or a tablet or on iPhone, we can pull it up and look at the cad and check things or make changes. That's something that couldn't do before because before you had to pay for every installation off the software for the computer, and I couldn't afford to have 20 installations to have some computers with the cat ready to use them like once every six months would have been very inefficient. So we love that part. And the collaboration features are fantastic, especially now with Kobe, that we have to have all the remote meetings eyes fantastic, that you can have another person drive the cad while the whole team is watching that person change the model and do things and point to things that is absolutely revolutionary. We love it. The fact that you have very, very sophisticated version control before it was always a challenge asking people, please, if you create anniversary and apart, how do we name it so that people find it? And then you end up with all these collection of files with names that nobody ever remembers, what they are, the person left. And now nobody knows which version is the right one. A mess with on shape on the version ING system it has, and the fact that you can go back in history off the document and go back to previous version so easily and then go back to the press and version and explore the history of the part that is truly, um, just world changing for us, that we can do that so easily on for me as a manager to manage this collection of information that is critical for our operations. It makes it so much easier because everything is in one place. I don't have to worry about file servers that go down that I have to administer that have to have I t taken care off that have to figure how to keep access to people to those servers when they're at home, and they need a virtual private network and all of that mess disappears. I just simply give give a person in accounting on shape and then magically, they have access to everything in the way I want. And we can manage the lower documents and everything in a way that is absolutely fantastic. >>Feel what was your what? What were some of the concerns you had mentioned? You had some trepidation. Was it a performance? Was it security? You know some of the traditional cloud stuff, and I'm curious as to how, How, whether any of those act manifested really that you had to manage. What were your concerns? >>Look, the main concern is how long is it going to take for everybody in the team to learn to use the system like it and buy into it? Because I don't want to have my engineers using tools against their will write. I want everybody to be happy because that's how they're productive. They're happy, and they enjoyed the tools they have. That was my main concern. I was a little bit worried about the whole concept of not having the files in a place where I couldn't quote unquote seat in some server and on site, but that That's kind of an outdated concept, right? So that took a little bit of a mind shift, but very quickly. Then I started thinking, Look, I have a lot of documents on Google Drive. Like, I don't worry about that. Why would I worry about my cat on on shape, right? Is the same thing. So I just needed to sort of put things in perspective that way. Um, the other, um, you know, the concern was the learning curve, right? Is like, how is he Will be for everybody to and for me to learn it on whether it had all of the features that we needed. And there were a few features that I actually discussed with, um uh, Cody at on shape on, they were actually awesome about using their scripting language in on shape to sort of mimic some of the features of the old cat, uh, in on, shaped in a way that actually works even better than the old system. So it was It was amazing. Yeah, >>Great. Thank you for that, Philip. What's your experience been? Maybe you could take us through your journey within shape. >>Sure. So we've been we've been using on shaped silver side for coming up on about four years now, and we love it. We're very happy with it. We have a very modular product line, so we make anything from detectors that would go into backpacks. Two vehicles, two very large things that a shipping container would go through and saw. Excuse me. Shape helps us to track and collaborate faster on the design. Have multiple people working a same time on a project. And it also helps us to figure out if somebody else comes to us and say, Hey, I want something new how we congrats modules from things that we already have put them together and then keep track of the design development and the different branches and ideas that we have, how they all fit together. A za design comes together, and it's just been fantastic from a mechanical engineering background. I will also say that having used a number of different systems and solid works was the greatest thing since sliced bread. Before I got using on shape, I went, Wow, this is amazing and I really don't want to design in any other platform. After after getting on Lee, a little bit familiar with it. >>You know, it's funny, right? I'll have the speed of technology progression. I was explaining to some young guns the other day how I used to have a daytime er and that was my life. And if I lost that daytime, er I was dead. And I don't know how we weigh existed without, you know, Google maps eso we get anywhere, I don't know, but, uh but so So, Matt, you know, it's interesting to think about, you know, some of the concerns that Raphael brought up, you hear? For instance, you know, all the time. Wow. You know, I get my Amazon bill at the end of the month that zip through the roof in, But the reality is that Yeah, well, maybe you are doing more, but you're doing things that you couldn't have done before. And I think about your experience in teaching and educating. I mean, you so much more limited in terms of the resource is that you would have had to be able to educate people. So what's your experience been with With on shape and what is it enabled? >>Um, yeah, it was actually talking before we went with on shape. We had a previous CAD program, and I was talking to my vendor about it, and he let me know that we were actually one of the biggest CAD shops in the state. Because if you think about it a really big program, you know, really big company might employ. 5, 10, 15, 20 cad guys, right? I mean, when I worked for a large defense contractor, I think there were probably 20 of us as the cad guys. I now have about 300 students doing cat. So there's probably more students with more hours of cat under their belt in my building than there were when I worked for the big defense contractor. Um, but like you mentioned, uh, probably our biggest hurdle is just re sources. And so we want We want one of things I've always prided myself and trying to do in this. Programs provide students with access two tools and skills that they're going to see either in college or in the real world. So it's one of the reason we went with a big professional cad program. There are, you know, sort of K 12 oriented software and programs and things. But, you know, I want my kids coding and python and using slack and using professional type of tools on DSO when it comes to cat. That's just that That was a really hurt. I mean, you know, you could spend $30,000 on one seat of, you know, professional level cad program, and then you need a $30,000 computer to run it on if you're doing a heavy assemblies, Um and so one of my dreams And it was always just a crazy dream. And I was the way I would always pitcher in my school system and say, someday I'm gonna have a kid on a school issued chromebook in subsidized housing, on public WiFi doing professional level bad and that that was a crazy statement until a couple of years ago. So we're really excited that I literally and you know, March and you said the forced march, the forced march into, you know, modernity, March 13th kids sitting in my engineering lab that we spent a lot of money on doing cad March 14th. Those kids were at home on their school issued chromebooks on public WiFi, uh, keeping their designs going and collaborating. And then, yeah, I could go on and on about some of the things you know, the features that we've learned since then they're even better. So it's not like this is some inferior, diminished version of Academy. There's so much about it. Well, I >>wanna I wanna ask you that I may be over my skis on this, but we're seeing we're starting to see the early days of the democratization of CAD and product design. It is the the citizen engineer, I mean, maybe insulting to the engineers in the room, But but is that we're beginning to see that >>I have to believe that everything moves into the cloud. Part of that is democratization that I don't need. I can whether you know, I think artists, you know, I could have a music studio in my basement with a nice enough software package. And Aiken, I could be a professional for now. My wife's a photographer. I'm not allowed to say that I could be a professional photographer with, you know, some cloud based software, and so, yeah, I do think that's part of what we're seeing is more and more technology is moving to the cloud. >>Philip. Rafael Anything you Dad, >>I think I mean, yeah, that that that combination of cloud based cat and then three d printing that is becoming more and more affordable on ubiquitous It's truly transformative, and I think for education is fantastic. I wish when I was a kid I had the opportunity to play with those kinds of things because I was always the late things. But, you know, the in a very primitive way. So, um, I think this is a dream for kids. Teoh be able to do this. And, um, yeah, there's so many other technologies coming on, like Arduino on all of these electronic things that live kids play at home very cheaply with things that back in my day would have been unthinkable. >>So we know there's a go ahead. Philip, please. >>We had a pandemic and silver site moved to a new manufacturing facility this year. I was just on the shop floor, talking with contractors, standing 6 ft apart, pointing at things. But through it all, our CAD system was completely unruffled. Nothing stopped in our development work. Nothing stopped in our support for existing systems in the field. We didn't have to think about it. We had other server issues, but none with our, you know, engineering cad, platform and product development in support world right ahead, which was cool, but also a in that's point. I think it's just really cool what you're doing with the kids. The most interesting secondary and college level engineering work that I did was project based, taken important problem to the world. Go solve it and that is what we do here. That is what my entire career has been. And I'm super excited to see. See what your students are going to be doing, uh, in there home classrooms on their chromebooks now and what they do building on that. >>Yeah, I'm super excited to see your kids coming out of college with engineering degrees because, yeah, I think that Project based experience is so much better than just sitting in a classroom, taking notes and doing math problems on day. I think it will give the kids a much better flavor. What engineering is really about Think a lot of kids get turned off by engineering because they think it's kind of dry because it's just about the math for some very abstract abstract concept on they are there. But I think the most important thing is just that hands on a building and the creativity off, making things that you can touch that you can see that you can see functioning. >>Great. So, you know, we all know the relentless pace of technology progression. So when you think about when you're sitting down with the folks that on shape and there the customer advisor for one of the things that that you want on shape to do that it doesn't do today >>I could start by saying, I just love some of the things that does do because it's such a modern platform. And I think some of these, uh, some some platforms that have a lot of legacy and a lot of history behind them. I think we're dragging some of that behind them. So it's cool to see a platform that seemed to be developed in the modern era, and so that Z it is the Google docks. And so the fact that collaboration and version ing and link sharing is and like platform agnostic abilities, the fact that that seems to be just built into the nature of the thing so far, That's super exciting. As far as things that, uh, to go from there, Um, I don't know, >>Other than price. >>You can't say >>I >>can't say lower price. >>Yeah, so far on P. D. C. S that work with us. Really? Well, so I'm not complaining. There you there, >>right? Yeah. Yeah. No gaps, guys. Whitespace, Come on. >>We've been really enjoying the three week update. Cadence. You know, there's a new version every three weeks and we don't have to install it. We just get all the latest and greatest goodies. One of the trends that we've been following and enjoying is the the help with a revision management and release work flows. Um, and I know that there's more than on shape is working on that we're very excited for, because that's a big important part about making real hardware and supporting it in the field. Something that was cool. They just integrated Cem markup capability. In the last release that took, we were doing that anyway, but we were doing it outside of on shapes. And now we get to streamline our workflow and put it in the CAD system where We're making those changes anyway when we're reviewing drawings and doing this kind of collaboration. And so I think from our perspective, we continue to look forward. Toa further progress on that. There's a lot of capability in the cloud that I think they're just kind of scratching the surface on you, >>right? I would. I mean, you're you're asking to knit. Pick. I would say one of the things that I would like to see is is faster regeneration speed. There are a few times with convicts, necessities that regenerating the document takes a little longer than I would like. It's not a serious issue, but anyway, I I'm being spoiled, >>you know? That's good. I've been doing this a long time, and I like toe ask that question of practitioners and to me, it It's a signal like when you're nit picking and that's what you're struggling to knit. Pick that to me is a sign of a successful product, and and I wonder, I don't know, uh, have the deep dive into the architecture. But are things like alternative processors. You're seeing them hit the market in a big way. Uh, you know, maybe helping address the challenge, But I'm gonna ask you the big, chewy question now. Then we maybe go to some audience questions when you think about the world's biggest problems. I mean, we're global pandemics, obviously top of mind. You think about nutrition, you know, feeding the global community. We've actually done a pretty good job of that. But it's not necessarily with the greatest nutrition, climate change, alternative energy, the economic divides. You've got geopolitical threats and social unrest. Health care is a continuing problem. What's your vision for changing the world and how product innovation for good and be applied to some of the the problems that that you all are passionate about? Big question. Who wants toe start? >>Not biased. But for years I've been saying that if you want to solve the economy, the environment, uh, global unrest, pandemics, education is the case. If you wanna. If you want to, um, make progress in those in those realms, I think funding funding education is probably gonna pay off pretty well. >>Absolutely. And I think Stam is key to that. I mean, all of the ah lot of the well being that we have today and then industrialized countries. Thanks to science and technology, right improvements in health care, improvements in communication, transportation, air conditioning. Um, every aspect of life is touched by science and technology. So I think having more kids studying and understanding that is absolutely key. Yeah, I agree, >>Philip, you got anything to add? >>I think there's some big technical problems in the world today, Raphael and ourselves there certainly working on a couple of them. Think they're also collaboration problems and getting everybody to be able to pull together instead of pulling separately and to be able to spur the ideas on words. So that's where I think the education side is really exciting. What Matt is doing and it just kind of collaboration in general when we could do provide tools to help people do good work. Uh, that is, I think, valuable. >>Yeah, I think that's a very good point. And along those lines, we have some projects that are about creating very low cost instruments for low research settings, places in Africa, Southeast Asia, South America, so that they can do, um, um, biomedical research that it's difficult to do in those place because they don't have the money to buy the fancy lab machines that cost $30,000 an hour. Um, so we're trying to sort of democratize some of those instruments. And I think thanks to tools like Kahn shape then is easier, for example, to have a conversation with somebody in Africa and show them the design that we have and discuss the details of it with them on. But it's amazing, right to have somebody, you know, 10 time zones away, Um, looking really life in real time with you about your design and discussing the details or teaching them how to build a machine, right? Because, um, you know, they have a three D printer. You can you can just give them the design and say like, you build it yourself, uh, even cheaper than and, you know, also billing and shipping it there. Um, so all that that that aspect of it is also super important. I think for any of these efforts to improve some of the hardest part was in the world for climate change. Do you say, as you say, poverty, nutrition issues? Um, you know, availability of water. You have that project at about finding water. Um, if we can also help deploy technologies that teach people remotely how to create their own technologies or how to build their own systems that will help them solve those forms locally. I think that's very powerful. >>Yeah, the point about education is right on. I think some people in the audience may be familiar with the work of Erik Brynjolfsson and Andrew McAfee, the second machine age where they sort of put forth the premise that, uh, is it laid it out. Look, for the first time in history, machines air replacing humans from a cognitive perspective. Machines have always replaced humans, but that's gonna have an impact on jobs. But the answer is not toe protect the past from the future. The answer is education and public policy that really supports that. So I couldn't agree more. I think it's a really great point. Um, we have We do have some questions from the audience. If if we could If I can ask you guys, um, you know, this one kind of stands out. How do you see artificial intelligence? I was just talking about machine intelligence. Um, how do you see that? Impacting the design space guys trying to infuse a I into your product development. Can you tell me? >>Um, absolutely, like, we're using AI for some things, including some of these very low cost instruments that will hopefully help us diagnose certain diseases, especially this is that are very prevalent in the Third World. Um, and some of those diagnostics are these days done by thes armies of technicians that are trained to look under the microscope. But, um, that's a very slow process. Is very error prone and having machine learning systems that can to the same diagnosis faster, cheaper and also little machines that can be taken to very remote places to these villages that have no access to a fancy microscope. To look at a sample from a patient that's very powerful. And I we don't do this, but I have read quite a bit about how certain places air using a Tribune attorneys to actually help them optimize designs for parts. So you get these very interesting looking parts that you would have never thought off a person would have never thought off, but that are incredibly light ink. Earlier, strong and I have all sort of properties that are interesting thanks to artificial intelligence machine learning in particular >>yet another. The advantage you get when when your work is in the cloud I've seen. I mean, there's just so many applications that so if the radiology scan is in the cloud and the radiologist is goes to bed at night, Radiologist could come in in the morning and and say, Oh, the machine while you were sleeping was using artificial intelligence to scan these 40,000 images. And here's the five that we picked out that we think you should take a closer look at. Or like Raphael said, I can design my part. My, my, my, my, my you know, mount or bracket or whatever and go to sleep. And then I wake up in the morning. The machine has improved. It for me has made it strider strider stronger and lighter. Um And so just when your when your work is in the cloud, that's just that's a really cool advantage that you get that you can have machines doing some of your design work for you. >>Yeah, we've been watching, uh, you know, this week is this month, I guess is AWS re invent and it's just amazing to see how much effort is coming around machine learning machine intelligence. You know Amazon has sage maker Google's got, you know, embedded you no ML and big query. Uh, certainly Microsoft with Azure is doing tons of stuff and machine learning. I think the point there is that that these things will be infused in tow R and D and in tow software product by the vendor community. And you all will apply that to your business and and build value through the unique data that your collecting, you know, in your ecosystems. And and that's how you add value. You don't have to be necessarily, you know, developers of artificial intelligence, but you have to be practitioners to apply that. Does that make sense to you, Philip? >>Yeah, absolutely. And I think your point about value is really well chosen. We see AI involved from the physics simulations all the way up to interpreting radiation data, and that's where the value question, I think, is really important because it's is the output of the AI giving helpful information that the people that need to be looking at it. So if it's curating a serious of radiation alert, saying, Hey, like these air the anomalies. You need to look at eyes it, doing that in a way that's going to help a good response on. In some cases, the II is only as good as the people. That sort of gave it a direction and turn it loose. And you want to make sure that you don't have biases or things like that underlying your AI that they're going to result in less than helpful outcomes coming from it. So we spend quite a lot of time thinking about how do we provide the right outcomes to people who are who are relying on our systems? >>That's a great point, right? Humans air biased and humans build models, so models are inherently biased. But then the software is hitting the market. That's gonna help us identify those biases and help us, you know? Of course. Correct. So we're entering Cem some very exciting times, guys. Great conversation. I can't thank you enough for spending the time with us and sharing with our audience the innovations that you're bringing to help the world. So thanks again. >>Thank you so much. >>Thank you. >>Okay. Welcome. Okay. When we come back, John McElheny is gonna join me. He's on shape. Co founder. And he's currently the VP of strategy at PTC. He's gonna join the program. We're gonna take a look at what's next and product innovation. I'm Dave Volonte and you're watching innovation for good on the Cube, the global leader. Digital technology event coverage. We'll be right back. >>Okay? Okay. Yeah. Okay. >>From around >>the globe, it's the Cube. Presenting innovation for good. Brought to you by on shape. >>Okay, welcome back to innovation. For good. With me is John McElheny, who is one of the co founders of On Shape and is now the VP of strategy at PTC. John, it's good to see you. Thanks for making the time to come on the program. Thanks, Dave. So we heard earlier some of the accomplishments that you've made since the acquisition. How has the acquisition affected your strategy? Maybe you could talk about what resource is PTC brought to the table that allowed you toe sort of rethink or evolve your strategy? What can you share with us? >>Sure. You know, a year ago, when when John and myself met with Jim Pepperman early on is we're we're pondering. Started joining PTC one of things became very clear is that we had a very clear shared vision about how we could take the on shape platform and really extended for, for all of the PTC products, particular sort of their augmented reality as well as their their thing works or the i o. T business and their product. And so from the very beginning there was a clear strategy about taking on shape, extending the platform and really investing, um, pretty significantly in the product development as well as go to market side of things, uh, toe to bring on shape out to not only the PTC based but sort of the broader community at large. So So So PTC has been a terrific, terrific, um, sort of partner as we've we've gonna go on after this market together. Eso We've added a lot of resource and product development side of things. Ah, lot of resource and they go to market and customer success and support. So, really, on many fronts, that's been both. Resource is as well a sort of support at the corporate level from from a strategic standpoint and then in the field, we've had wonderful interactions with many large enterprise customers as well as the PTC channels. So it's been really a great a great year. >>Well, and you think about the challenges of in your business going to SAS, which you guys, you know, took on that journey. You know, 78 years ago. Uh, it's not trivial for a lot of companies to make that transition, especially a company that's been around as long as PTC. So So I'm wondering how much you know, I was just asking you How about what PCP TC brought to the table? E gotta believe you're bringing a lot to the table to in terms of the mindset, uh, even things is, is mundane is not the right word, but things like how you compensate salespeople, how you interact with customers, the notion of a service versus a product. I wonder if you could address >>that. Yeah, it's a it's a really great point. In fact, after we had met Jim last year, John and I one of the things we walked out in the seaport area in Boston, one of things we sort of said is, you know, Jim really gets what we're trying to do here and and part of let me bring you into the thinking early on. Part of what Jim talked about is there's lots of, you know, installed base sort of software that's inside of PTC base. That's helped literally thousands of customers around the world. But the idea of moving to sass and all that it entails both from a technology standpoint but also a cultural standpoint. Like How do you not not just compensate the sales people as an example? But how do you think about customer success? In the past, it might have been that you had professional services that you bring out to a customer, help them deploy your solutions. Well, when you're thinking about a SAS based offering, it's really critical that you get customers successful with it. Otherwise, you may have turned, and you know it will be very expensive in terms of your business long term. So you've got to get customers success with software in the very beginning. So you know, Jim really looked at on shape and he said that John and I, from a cultural standpoint, you know, a lot of times companies get acquired and they've acquired technology in the past that they integrate directly into into PTC and then sort of roll it out through their products, are there just reached channel, he said. In some respects, John John, think about it as we're gonna take PTC and we want to integrate it into on shape because we want you to share with us both on the sales side and customer success on marketing on operations. You know all the things because long term, we believe the world is a SAS world, that the whole industry is gonna move too. So really, it was sort of an inverse in terms of the thought process related to normal transactions >>on That makes a lot of sense to me. You mentioned Sharon turns the silent killer of a SAS company, and you know, there's a lot of discussion, you know, in the entrepreneurial community because you live this, you know what's the best path? I mean today, You see, you know, if you watch Silicon Valley double, double, triple triple, but but there's a lot of people who believe, and I wonder, if you come in there is the best path to, you know, in the X Y axis. If if it's if it's uh, growth on one and retention on the other axis. What's the best way to get to the upper right on? Really? The the best path is probably make sure you've nailed obviously the product market fit, But make sure that you can retain customers and then throw gas on the fire. You see a lot of companies they burn out trying to grow too fast, but they haven't figured out, you know that. But there's too much churn. They haven't figured out those metrics. I mean, obviously on shape. You know, you were sort of a pioneer in here. I gotta believe you've figured out that customer retention before you really, You know, put the pedal to the >>metal. Yeah, and you know, growth growth can mask a lot of things, but getting getting customers, especially the engineering space. Nobody goes and sits there and says, Tomorrow we're gonna go and and, you know, put 100 users on this and and immediately swap out all of our existing tools. These tools are very rich and deep in terms of capability, and they become part of the operational process of how a company designs and builds products. So any time anybody is actually going through the purchasing process. Typically, they will run a try along or they'll run a project where they look at. Kind of What? What is this new solution gonna help them dio. How are we gonna orient ourselves for success? Longer term. So for us, you know, getting new customers and customer acquisition is really critical. But getting those customers to actually deploy the solution to be successful with it. You know, we like to sort of, say, the marketing or the lead generation and even some of the initial sales. That's sort of like the Kindle ing. But the fire really starts when customers deploy it and get successful. The solution because they bring other customers into the fold. And then, of course, if they're successful with it, you know, then in fact, you have negative turn which, ironically, means growth in terms of your inside of your install. Bates. >>Right? And you've seen that with some of the emerging, you know, SAS companies, where you're you're actually you know, when you calculate whatever its net retention or renew ALS, it's actually from a dollar standpoint. It's up in the high nineties or even over 100%. >>So >>and that's a trend we're gonna continue. See, I >>wonder >>if we could sort of go back. Uh, and when you guys were starting on shape, some of the things that you saw that you were trying to strategically leverage and what's changed, you know, today we were talking. I was talking to John earlier about in a way, you kinda you kinda got a blank slate is like doing another startup. >>You're >>not. Obviously you've got installed base and customers to service, but But it's a new beginning for you guys. So one of the things that you saw then you know, cloud and and sas and okay, but that's we've been there, done that. What are you seeing? You know today? >>Well, you know, So So this is a journey, of course, that that on shape on its own has gone through it had I'll sort of say, you know, several iterations, both in terms of of of, you know, how do you How do you get customers? How do you How do you get them successful? How do you grow those customers? And now that we've been part of PTC, the question becomes okay. One, There is certainly a higher level of credibility that helps us in terms of our our megaphone is much bigger than it was when we're standalone company. But on top of that now, figuring out how to work with their channel with their direct sales force, you know, they have, um, for example, you know, very large enterprises. Well, many of those customers are not gonna go in forklift out their existing solution to replace it with with on shape. However, many of them do have challenges in their supply chain and communications with contractors and vendors across the globe. And so, you know, finding our fit inside of those large enterprises as they extend out with their their customers is a very interesting area that we've really been sort of incremental to to PTC. And then, you know, they they have access to lots of other technology, like the i o. T business. And now, of course, the augmented reality business that that we can bring things to bear. For example, in the augmented reality world, they've they've got something called expert capture. And this is essentially imagine, you know, in a are ah, headset that allows you to be ableto to speak to it, but also capture images still images in video. And you could take somebody who's doing their task and capture literally the steps that they're taking its geo location and from their builds steps for new employees to be, we'll learn and understand how todo use that technology to help them do their job better. Well, when they do that, if there is replacement products or variation of of some of the tools that that they built the original design instruction set for they now have another version. Well, they have to manage multiple versions. Well, that's what on shape is really great at doing and so taking our technology and helping their solutions as well. So it's not only expanding our customer footprint, it's expanding the application footprint in terms of how we can help them and help customers. >>So that leads me to the tam discussion and again, as part of your strategist role. How do you think about that? Was just talking to some of your customers earlier about the democratization of cat and engineering? You know, I kind of joked, sort of like citizen engineering, but but so that you know, the demographics are changing the number of users potentially that can access the products because the it's so much more of a facile experience. How are you thinking about the total available market? >>It really is a great question, You know, it used to be when you when you sold boxes of software, it was how many engineers were out there. And that's the size of the market. The fact that matter is now when, When you think about access to that information, that data is simply a pane of glass. Whether it's a computer, whether it's a laptop, UH, a a cell phone or whether it's a tablet, the ability to to use different vehicles, access information and data expands the capabilities and power of a system to allow feedback and iteration. I mean, one of the one of the very interesting things is in technology is when you can take something and really unleash it to a larger audience and builds, you know, purpose built applications. You can start to iterate, get better feedback. You know there's a classic case in the clothing industry where Zara, you know, is a fast sort of turnaround. Agile manufacturer. And there was a great New York Times article written a couple years ago. My wife's a fan of Zara, and I think she justifies any purchases by saying, You know, Zara, you gotta purchase it now. Otherwise it may not be there the next time. Yet you go back to the store. They had some people in a store in New York that had this woman's throw kind of covering Shaw. And they said, Well, it would be great if we could have this little clip here so we can hook it through or something. And they sent a note back toe to the factory in Spain, and literally two weeks later they had, you know, 4000 of these things in store, and they sold out because they had a closed loop and iterative process. And so if we could take information and allow people access in multiple ways through different devices and different screens, that could be very specific information that, you know, we remove a lot of the engineering data book, bring the end user products conceptually to somebody that would have had to wait months to get the actual physical prototype, and we could get feedback well, Weaken have a better chance of making sure whatever product we're building is the right product when it ultimately gets delivered to a customer. So it's really it's a much larger market that has to be thought of rather than just the kind of selling A boxes software to an engineer. >>That's a great story. And again, it's gonna be exciting for you guys to see that with. The added resource is that you have a PTC, Um, so let's talk. I promise people we wanna talk about Atlas. Let's talk about the platform. A little bit of Atlas was announced last year. Atlas. For those who don't know it's a SAS space platform, it purports to go beyond product lifecycle management and you You're talking cloud like agility and scale to CAD and product design. But John, you could do a better job than I. What do >>we need to know about Atlas? Well, I think Atlas is a great description because it really is metaphorically sort of holding up all of the PTC applications themselves. But from the very beginning, when John and I met with Jim, part of what we were intrigued about was that he shared a vision that on shape was more than just going to be a cad authoring tool that, in fact, you know, in the past these engineering tools were very powerful, but they were very narrow in their purpose and focus. And we had specialty applications to manage the versions, etcetera. What we did in on shape is we kind of inverted that thinking. We built this collaboration and sharing engine at the core and then kind of wrap the CAD system around it. But that collaboration sharing and version ING engine is really powerful. And it was that vision that Jim had that he shared that we had from the beginning, which was, how do we take this thing to make a platform that could be used for many other applications inside of inside of any company? And so not only do we have a partner application area that is is much like the APP store or Google play store. Uh, that was sort of our first Stan Shih ation of this. This this platform. But now we're extending out to broader applications and much meatier applications. And internally, that's the thing works in the in the augmented reality. But there'll be other applications that ultimately find its way on top of this platform. And so they'll get all the benefits of of the collaboration, sharing the version ing the multi platform, multi device. And that's an extremely extremely, um, strategic leverage point for the company. >>You know, it's interesting, John, you mentioned the seaport before. So PTC, for those who don't know, built a beautiful facility down at the Seaport in Boston. And, of course, when PTC started, you know, back in the mid 19 eighties, there was nothing at the seaport s. >>So it's >>kind of kind of ironic, you know, we were way seeing the transformation of the seaport. We're seeing the transformation of industry and of course, PTC. And I'm sure someday you'll get back into that beautiful office, you know? Wait. Yeah, I'll bet. And, uh and but I wanna bring this up because I want I want you to talk about the future. How you how you see that our industry and you've observed this has moved from very product centric, uh, plat platform centric with sass and cloud. And now we're seeing ecosystems form around those products and platforms and data flowing through the ecosystem powering, you know, new innovation. I wonder if you could paint a picture for us of what the future looks like to you from your vantage point. >>Yeah, I think one of the key words you said there is data because up until now, data for companies really was sort of trapped in different applications. And it wasn't because people were nefarious and they want to keep it limited. It was just the way in which things were built. And, you know, when people use an application like on shape, what ends up happening is there their day to day interaction and everything that they do is actually captured by the platform. And, you know, we don't have access to that data. Of course it's it's the customer's data. But as as an artifact of them using the system than doing their day to day job, what's happening is they're creating huge amounts of information that can then be accessed and analyzed to help them both improve their design process, improve their efficiencies, improve their actual schedules in terms of making sure they can hit delivery times and be able to understand where there might be roadblocks in the future. So the way I see it is companies now are deploying SAS based tools like on shape and an artifact of them. Using that platform is that they have now analytics and tools to better understand and an instrument and manage their business. And then from there, I think you're going to see, because these systems are all you know extremely well. Architected allow through, you know, very structured AP. I calls to connect other SAS based applications. You're gonna start seeing closed loop sort of system. So, for example, people design using on shape, they end up going and deploying their system or installing it, or people use the end using products. People then may call back into the customers support line and report issues, problems, challenges. They'll be able to do traceability back to the underlying design. They'll be able to do trend analysis and defect analysis from the support lines and tie it back and closed loop the product design, manufacture, deployment in the field sort of cycles. In addition, you can imagine there's many things that air sort of as designed. But then when people go on site and they have to install it. There's some alterations modifications. Think about think about like a large air conditioning units for buildings. You go and you go to train and you get a large air conditioning unit that put up on top of building with a crane. They have to build all kinds of adaptors to make sure that that will fit inside of the particulars of that building. You know, with on shape and tools like this, you'll be able to not only take the design of what the air conditioning system might be, but also the all the adapter plates, but also how they installed it. So it sort of as designed as manufactured as stalled. And all these things can be traced, just like if you think about the transformation of customer service or customer contacts. In the early days, you used to have tools that were PC based tools called contact management solution, you know, kind of act or gold mine. And these were basically glorified Elektronik role in Texas. It had a customer names and they had phone numbers and whatever else. And Salesforce and Siebel, you know, these types of systems really broadened out the perspective of what a customer relationship? Waas. So it wasn't just the contact information it was, you know, How did they come to find out about you as a company? So all of the pre sort of marketing and then kind of what happens after they become a customer and it really was a 3 60 view. I think that 3 60 view gets extended to not just to the customers, but also tools and the products they use. And then, of course, the performance information that could come back to the manufacturer. So, you know, as an engineer, one of the things you learn about with systems is the following. And if you remember, when the CD first came out CDs that used to talk about four times over sampling or eight times over sampling and it was really kind of, you know, the fidelity the system. And we know from systems theory that the best way to improve the performance of a system is to actually have more feedback. The more feedback you have, the better system could be. And so that's why you get 16 60 for example, etcetera. Same thing here. The more feedback we have of different parts of a company that a better performance, The company will be better customer relationships. Better, uh, overall financial performance as well. So that's that's the view I have of how these systems all tied together. >>It's a great vision in your point about the data is I think right on. It used to be so fragmented in silos, and in order to take a system view, you've gotta have a system view of the data. Now, for years, we've optimized maybe on one little component of the system and that sometimes we lose sight of the overall outcome. And so what you just described, I think is, I think sets up. You know very well as we exit. Hopefully soon we exit this this covert era on John. I hope that you and I can sit down face to face at a PTC on shape event in the near term >>in the seaport in the >>seaport would tell you that great facility toe have have an event for sure. It >>z wonderful >>there. So So John McElhinney. Thanks so much for for participating in the program. It was really great to have you on, >>right? Thanks, Dave. >>Okay. And I want to thank everyone for participating. Today we have some great guest speakers. And remember, this is a live program. So give us a little bit of time. We're gonna flip this site over toe on demand mode so you can share it with your colleagues and you, or you can come back and and watch the sessions that you heard today. Uh, this is Dave Volonte for the Cube and on shape PTC. Thank you so much for watching innovation for good. Be well, Have a great holiday. And we'll see you next time. Yeah.

>>from around the globe. It's the Cube presenting innovation for good, brought to you by on shape. >>Hello, everyone, and welcome to Innovation for Good Program, hosted by the Cuban. Brought to You by on Shape, which is a PTC company. My name is Dave Valentin. I'm coming to you from our studios outside of Boston. I'll be directing the conversations today. It's a very exciting, all live program. We're gonna look at how product innovation has evolved, where it's going and how engineers, entrepreneurs and educators are applying cutting edge, cutting edge product development techniques and technology to change our world. You know, the pandemic is, of course, profoundly impacted society and altered how individuals and organizations they're gonna be thinking about and approaching the coming decade. Leading technologists, engineers, product developers and educators have responded to the new challenges that we're facing from creating lifesaving products to helping students learn from home toe how to apply the latest product development techniques and solve the world's hardest problems. And in this program, you'll hear from some of the world's leading experts and practitioners on how product development and continuous innovation has evolved, how it's being applied toe positive, positively affect society and importantly where it's going in the coming decades. So let's get started with our first session fueling Tech for good. And with me is John Herstek, who is the president of the Suffers, a service division of PTC, which required on shape just over a year ago, where John was the CEO and co founder. And Dana Grayson is here. She is the co founder and general partner at Construct Capital, a new venture capital firm. Folks, welcome to the program. Thanks so much for coming on. Great >>to be here, Dave. >>All right, John. You're very welcome. Dana. Look, John, let's get into it for first. A belated congratulations on the acquisition of Von Shape. That was an awesome seven year journey for your company. Tell our audience a little bit about the story of on shape, but take us back to Day zero. Why did you and your co founders start on shape? Well, >>actually, start before on shaping the You know, David, I've been in this business for almost 40 years. The business of building software tools for product developers and I had been part of some previous products in the industry and companies that had been in their era. Big changes in this market and about, you know, a little Before founding on shape, we started to see the problems product development teams were having with the traditional tools of that era years ago, and we saw the opportunity presented by Cloud Web and Mobile Technology. And we said, Hey, we could use Cloud Web and Mobile to solve the problems of product developers make their Their business is run better. But we have to build an entirely new system, an entirely new company, to do it. And that's what on shapes about. >>Well, so notwithstanding the challenges of co vid and difficulties this year, how is the first year been as, Ah, division of PTC for you guys? How's business? Anything you can share with us? >>Yeah, our first year of PTC has been awesome. It's been, you know, when you get acquired, Dave, you never You know, you have great optimism, but you never know what life will really be like. It's sort of like getting married or something, you know, until you're really doing it, you don't know. And so I'm happy to say that one year into our acquisition, a TPI TC on shape is thriving. It's worked out better than I could have imagined a year ago. Along always, I mean sales are up. In Q four, our new sales rate grew 80% vs Excuse me, our fiscal Q four Q three. In the calendar year, it grew 80% compared to the year before. Our educational uses skyrocketing with around 400% growth, most recently year to year of students and teachers and co vid. And we've launched a major cloud platform using the core of on shape technology called Atlas. So, um, just tons of exciting things going on a TTC. >>That's awesome. But thank you for sharing some of those metrics. And of course, you're very humble individual. You know, people should know a little bit more about you mentioned, you know, we founded solid works, go founded solid, where I actually found it solid works. You had a great exit in the late nineties. But what I really appreciate is, you know, you're an entrepreneur. You've got a passion for the babies that you helped birth. You stayed with the salt systems for a number of years. The company that quiet, solid works well over a decade. And and, of course, you and I have talked about how you participated in the M I t blackjack team. You know, back in the day a Z I say you're very understated, for somebody was so accomplished. So well, >>that's kind of you. But I tend to I tend Thio always keep my eye more on what's ahead. You know what's next then? And you know, I look back Sure to enjoy it and learn from it about what I can put toe work, making new memories, making new successes. >>I love it. Okay, let's bring Dana into the conversation. Hello, Dana. And you Look, you were fairly early investor in on shape when you were with any A. And I think it was like it was a Siri's B. But it was very right close after the A raise. And and you were and still are a big believer in industrial transformation. So take us back. What did you see about on shape back then? That that excited you? >>Thanks. Thanks for that. Yeah. I was lucky to be a early investment in shape. You know, the things that actually attracted me. Don shape were largely around John and, uh, the team. They're really setting out to do something, as John says humbly, something totally new, but really building off of their background was a large part of it. Um, but, you know, I was really intrigued by the design collaboration side of the product. Um, I would say that's frankly what originally attracted me to it. What kept me in the room, you know, in terms of the industrial world was seeing just if you start with collaboration around design what that does to the overall industrial product lifecycle accelerating manufacturing just, you know, modernizing, manufacturing, just starting with design. So I'm really thankful to the on shape guys, because it was one of the first investments I've made that turned me on to the whole sector. And, wow, just such a great pleasure to work with with John and the whole team there. Now see what they're doing inside PTC, >>and you just launched construct capital this year, right in the middle of a pandemic and which is awesome. I love it. And you're focused on early stage investing. Maybe tell us a little bit about construct capital. What? Your investment thesis is and you know, one of the big waves that you're hoping to ride. >>Sure, it construct it is literally lifting out of any what I was doing there, um uh, you're on shape. I went on to invest in companies such as desktop metal and Tulip, to name a couple of them form labs, another one in and around the manufacturing space. But our thesis it construct is broader than just, you know, manufacturing and industrial. It really incorporates all of what we'd call foundational industries that have let yet to be fully tech enabled or digitized. Manufacturing is a big piece of it. Supply chain, logistics, transportation and mobility or not, or other big pieces of it. And together they really drive, you know, half of the GDP in the US and have been very under invested. And frankly, they haven't attracted really great founders like Iran in droves. And I think that's going to change. We're seeing, um, entrepreneurs coming out of the tech world or staggolee into these industries and then bringing them back into the tech world, which is which is something that needs to happen. So John and team were certainly early pioneers and I think, you know, frankly, obviously, that voting with my feet that the next set, a really strong companies are going to come out of this space over the next decade. >>I think there's a huge opportunity to digitize the sort of traditionally non digital organizations. But Dana, you focused. I think it's it's accurate to say you're focused on even Mawr early stage investing now. And I want to understand why you feel it's important to be early. I mean, it's obviously riskier and reward e er, but what do you look for in companies and and founders like John >>Mhm, Um, you know, I think they're different styles of investing all the way up to public market investing. I've always been early stage investors, so I like to work with founders and teams when they're, you know, just starting out. Um, I happened to also think that we were just really early in the whole digital transformation of this world. You know, John and team have been, you know, back from solid works, etcetera around the space for a long time. But again, the downstream impact of what they're doing really changes the whole industry and and so we're pretty early and in digitally transforming that market. Um, so that's another reason why I wanna invest early now, because I do really firmly believe that the next set of strong companies and strong returns for my own investors will be in the spaces. Um, you know, what I look for in Founders are people that really see the world in a different way. And, you know, sometimes some people think of founders or entrepreneurs is being very risk seeking. You know, if you asked John probably and another successful entrepreneurs, they would call themselves sort of risk averse, because by the time they start the company, they really have isolated all the risk out of it and think that they have given their expertise or what they're seeing their just so compelled to go change something, eh? So I look for that type of attitude experience a Z. You can also tell from John. He's fairly humble. So humility and just focus is also really important. Um, that there's a that's a lot of it. Frankly, >>excellent. Thank you. And John, you got such a rich history in the space in one of you could sort of connect the dots over time. I mean, when you look back, what were the major forces that you saw in the market in in the early days? Uh, particularly days of on shape on how is that evolved? And what are you seeing today? Well, I >>think I touched on it earlier. Actually, could I just reflect on what Dana said about risk taking for just a quick one and say, throughout my life, from blackjack to starting solid works on shape, it's about taking calculated risks. Yes, you try to eliminate the risk sa's much as you can, but I always say, I don't mind taking a risk that I'm aware of, and I've calculated through as best I can. I don't like taking risks that I don't know I'm taking. >>That's right. You like to bet on >>sure things as much sure things, or at least where you feel you. You've done the research and you see them and you know they're there and you know, you, you you keep that in mind in the room, and I think that's great. And Dana did so much for us. Dana, I want to thank you again for all that you did it every step of the way from where we started. Thio, Thio You know your journey with us ended formally but continues informally. Now back to you. Um, Dave, I think question about the opportunity and how it's shaped up. Well, I think I touched on it earlier when I said It's about helping product developers. You know, our customers of the people build the future of manufactured goods. Anything you think of that would be manufacturing factory. You know, the chair you're sitting in machine that made your coffee. You know, the computer you're using that trucks that drive by on the street, all the covert product research, the equipment being used to make vaccines. All that stuff is designed by someone, and our job is given the tools to do it better. And I could see the problems that those product developers had that we're slowing them down with using the computing systems of the time. When we built solid works, that was almost 30 years ago. People don't realize that it was in the early >>nineties, and, you know, we did the >>best we could for the early nineties, but what we did, we didn't anticipate the world of today. And so people were having problems with just installing the systems. Dave, you wouldn't believe how hard it is to install these systems. You need a spec up a special windows computer, you know, and make sure you've got all the memory and graphics you need and getting to get that set up. You need to make sure the device drivers air, right, install a big piece of software. Ah, license key. I'm not making this up. They're still around. You may not even know what those are. You know, Dennis laughing because, you know, zero cool people do things like this anymore on but only runs some windows. You want a second user to use it? They need a copy. They need a code. Are they on the same version? It's a nightmare. The teams change. You know? You just say, Well, get everyone on the software. Well, who's everyone? You know? You got a new vendor today? A new customer tomorrow, a new employee. People come on and off the team. The other problem is the data stored in files, thousands of files. This isn't like a spreadsheet or word processor where there's one file to pass around these air thousands of files to make one, even a simple product. People were tearing their hair out. John, what do we do? I've got copies everywhere. I don't know where the latest version is. We tried like, you know, locking people out so that only one person can change it at the time that works against speed. It works against innovation. We saw what was happening with Cloud Web and mobile. So what's happened in the years since is every one of the forces that product developers experience the need for speed, the need for innovation, the need to be more efficient with their people in their capital. Resource is every one of those trends have been amplified since we started on shape by a lot of forces in the world. And covert is amplified all those the need for agility and remote work cove it is amplified all that the same time, The acceptance of cloud. You know, a few years ago, people were like cloud, you know, how is that gonna work now They're saying to me, you know, increasingly, how would you ever even have done this without the cloud? How do you make solid works Work without the cloud? How would that even happen? You know, And once people understand what on shapes about >>and we're the >>Onley full SAS solution software as a service, full SAS solution in our industry. So what's happened in those years? Same problems we saw earlier, but turn up the gain, their bigger problems. And with cloud, we've seen skepticism of years ago turn into acceptance. And now even embracement in the cova driven new normal. >>Yeah. So a lot of friction in the previous environments cloud obviously a huge factor on, I guess. I guess Dana John could see it coming, you know, in the early days of solid works with Salesforce, which is kind of the first major independent SAS player. Well, I guess that was late nineties. So it was post solid works, but pre in shape and their work day was, you know, pre on shape in the mid two thousands. And and but But, you know, the bet was on the SAS model was right for Crick had and and product development, you know, which Maybe the time wasn't a no brainer. Or maybe it was I don't know, but Dana is there. Is there anything that you would invest in today that's not Cloud based? >>Um, that's a great question. I mean, I think we still see things all the time in the manufacturing world that are not cloud based. I think you know, the closer you get to the shop floor in the production environment. Um, e think John and the PTC folks would agree with this, too, but that it's, you know, there's reliability requirements. There's performance requirements. There's still this attitude of, you know, don't touch the printing press. So the cloud is still a little bit scary sometimes. And I think hybrid cloud is a real thing for those or on premise. Solutions, in some cases is still a real thing. What, what were more focused on. And, um, despite whether it's on premise or hybrid or or SAS and Cloud is a frictionless go to market model, um, in the companies we invest in so sass and cloud, or really make that easy to adopt for new users, you know, you sign up, start using a product, um, but whether it's hosted in the cloud, whether it's as you can still distribute buying power. And, um, I would I'm just encouraging customers in the customer world and the more industrial environment to entrust some of their lower level engineers with more budget discretionary spending so they can try more products and unlock innovation. >>Right? The unit economics are so compelling. So let's bring it, you know, toe today's you know, situation. John, you decided to exit about a year ago. You know? What did you see in PTC? Other than the obvious money? What was the strategic fit? >>Yeah, Well, David, I wanna be clear. I didn't exit anything. Really? You >>know, I love you and I don't like that term exit. I >>mean, Dana had exit is a shareholder on and so it's not It's not exit for me. It's just a step in the journey. Um, what we saw in PTC was a partner. First of all, that shared our vision from the top down at PTC. Jim Hempleman, the CEO. He had a great vision for for the impact that SAS can make based on cloud technology. And really is Dana of highlighted so much. It's not just the technology is how you go to market and the whole business being run and how you support and make the customers successful. So Jim shared a vision for the potential. And really, really, um said Hey, come join us and we can do this bigger, Better, faster. We expanded the vision really to include this Atlas platform for hosting other SAS applications. That P D. C. I mean, David Day arrived at PTC. I met the head of the academic program. He came over to me and I said, You know, and and how many people on your team? I thought he'd say 5 40 people on the PTC academic team. It was amazing to me because, you know, we were we were just near about 100 people were required are total company. We didn't even have a dedicated academic team and we had ah, lot of students signing up, you know, thousands and thousands. Well, now we have hundreds of thousands of students were approaching a million users, and that shows you the power of this team that PTC had combined with our product and technology whom you get a big success for us and for the teachers and students to the world. We're giving them great tools. So so many good things were also putting some PTC technology from other parts of PTC back into on shape. One area, a little spoiler, little sneak peek. Working on taking generative design. Dana knows all about generative design. We couldn't acquire that technology were start up, you know, just to too much to do. But PTC owns one of the best in the business. This frustrated technology we're working on putting that into on shaping our customers. Um, will be happy to see it, hopefully in the coming year sometime. >>It's great to see that two way exchange. Now, you both know very well when you start a company, of course, a very exciting time. You know, a lot of baggage, you know, our customers pulling you in a lot of different directions and asking you for specials. You have this kind of clean slate, so to speak in it. I would think in many ways, John, despite you know, your install base, you have a bit of that dynamic occurring today especially, you know, driven by the forced march to digital transformation that cove it caused. So when you sit down with the team PTC and talk strategy, you now have more global resource is you got cohorts selling opportunities. What's the conversation like in terms of where you want to take the division? >>Well, Dave, you actually you sounds like we should have you coming in and talking about strategy because you've got the strategy down. I mean, we're doing everything said global expansion were able to reach across selling. We've got some excellent PTC customers that we can reach reach now and they're finding uses for on shape. I think the plan is to, you know, just go, go, go and grow, grow, grow where we're looking for this year, priorities are expand the product. I mentioned the breath of the product with new things PTC did recently. Another technology that they acquired for on shape. We did an acquisition. It was it was small, wasn't widely announced. It, um, in an area related to interfacing with electrical cad systems. So? So we're doing We're expanding the breath of on shape. We're going Maura. Depth in the areas were already in. We have enormous opportunity. Add more features and functions that's in the product. Go to market. You mentioned it global global presence. That's something we were a little light on a year ago. Now we have a team. Dana may not even know what we have a non shape, dedicated team in Barcelona, based in Barcelona but throughout Europe were doing multiple languages. Um, the academic program just introduced a new product into that space. That's that's even fueling more success and growth there, Um, and of course, continuing to to invest in customer success. And this Atlas platform story I keep mentioning, we're going to soon have We're gonna soon have four other major PTC brands shipping products on our Atlas Saas platform. And so we're really excited about that. That's good for the other PTC products. It's also good for on shape because now there's there's. There's other interesting products that are on shape customers can use take advantage of very easily using, say, a common log in conventions about user experience there used to invest of all their SAS based, so they that makes it easier to begin with. So that's some of the exciting things going on. I think you'll see P. D. C. Um expanding our lead in saas based applications for this sector for our target sectors, not just in in cat and data management. But another area, PTC's Big and his augmented reality with of euphoria, product line leader and industrial uses of a R. That's a whole other story we should do. A whole nother show augmented reality. But these products are amazing. You can You can help factory workers people on, uh, people who are left out of the digital transformation. Sometimes we're standing from machine >>all day. >>They can't be sitting like we are doing Zoom. They could wear a R headset in our tools. Let them create great content. This is an area Dana is invested in in other companies, but what I wanted to note is the new releases of our authoring software. For this, our content getting released this month, used through the Atlas platform, the SAS components of on shape for things like revision management and collaboration on duh workflow activity. All that those are tools that we're able to share leverage. We get a lot of synergy. It's just really good. It's really fun to We'll have a good time, >>that's awesome. And then we're gonna be talking to John MacLean later about Atlas and do a little deeper dive on that. And, Dana, what is your involvement today with with on shape? But you're looking for you know, which of their customers air actually adopting, and they're gonna disrupt their industries. You get good pipeline from that. How do you collaborate today? >>That sounds like a great idea. Um, a Z John will tell you I'm constantly just ask him for advice and impressions of other entrepreneurs and picking his brain on ideas. No formal relationship clearly, but continue to count John and and John and other people in on shaping in the circle of experts that I rely on for their opinions. >>All right, so we have some questions from the crowd here. Uh, one of the questions is for the dream team. You know, John and Dana. What's your next next collective venture? I don't think we're there yet, are we? No. I >>just say, as Dana said, we love talking to her about. You know, Dana, you just returned the compliment. We would try and give you advice and the deals you're looking at, and I'm sort of casually mentoring at least one of your portfolio entrepreneurs, and that's been a lot of fun for May on hopefully a value to them. But also Dana, We uran important pipeline to us in the world of some new things that are happening that we wouldn't see if you know you've shown us some things that you've said. What do you think of this business? And for us, it's like, Wow, it's cool to see that's going on And that's what's supposed to work in an ecosystem like this. So we we deeply value the ongoing relationship. And no, we're not starting something new. I got a lot of work left to do with what I'm doing and really happy. But we can We can collaborate in this way on other ventures. >>I like this question to somebody asking with the cloud options like on shape, Wilmore students have stem opportunities s Oh, that's a great question. Are you because of sass and cloud? Are you able to reach? You know, more students? Much more cost effectively. >>Yeah, Dave, I'm so glad that that that I was asked about this because Yes, and it's extremely gratifying us. Yes, we are because of cloud, because on shape is the only full cloud full SAS system. Our industry were able to reach stem education brings able to be part of bringing step education to students who couldn't get it otherwise. And one of most gratifying gratifying things to me is the emails were getting from teachers, um, that that really, um, on the phone calls that were they really pour their heart out and say We're able to get to students in areas that have very limited compute resource is that don't have an I T staff where they don't know what computer that the students can have at home, and they probably don't even have a computer. We're talking about being able to teach them on a phone to have an android phone a low end android phone. You could do three D modeling on there with on shape. Now you can't do it any other system, but with on shape, you could do it. And so the teacher can say to the students, They have to have Internet access, and I know there's a huge community that doesn't even have Internet access, and we're not able, unfortunately to help that. But if you have Internet and you have even an android phone, we can enable the educator to teach them. And so we have case after case of saving a stem program or expanding it into the students that need it most is the ones we're helping here. So really excited about that. And we're also able to let in addition to the run on run on whatever computing devices they have, we also offer them the tools they need for remote teaching with a much richer experience. You know, could you teach solid works remotely? Well, maybe if the student ran it had a windows workstation, you know, big, big, high and workstation. Maybe it could, but it would be like the difference between collaborating with on shape and collaborate with solid works. Like the difference between a zoom video call and talking on the landline phone. You know, it's a much richer experience, and that's what you need in stem teaching. Stem is hard. So, yeah, we're super super excited about bringing stem to more students because of clouds. >>Yeah, we're talking about innovation for good, and then the discussion, John, you just had it. Really? There could be a whole another vector here. We could discuss on diversity, and I wanna end with just pointing out So, Dana, your new firm. It's a woman led firm, too. Two women leaders, you know, going forward. So that's awesome to see, so really? Yeah, thumbs up on that. Congratulations on getting that off the ground. Yeah. Thank you. Okay. So thank you guys. Really appreciate It was a great discussion. I learned a lot, and I'm sure the audience did a swell in a moment. We're gonna talk with on shape customers to see how they're applying tech for good and some of the products that they're building. So keep it right there. I'm Dave Volonte. You're watching innovation for good on the Cube, the global leader in digital tech event coverage. Stay right there. Yeah.

>>From around the globe. It's the queue cover >>Space and cyber security >>Symposium 2020 hosted by Cal poly. >>Hello and welcome to the space and cybersecurity symposium 2020 hosted by Cal poly and the cube I'm chilling for a, your host. We have a great session here. Space, cyber security, the department of defense perspective. We have bond Google hall, director of C four ISR directorate office of the undersecretary of defense for acquisition and sustainment for the DOD and Chris Henson, technical director space and weapons, cybersecurity solutions for the national security agency. Gentlemen, thank you for taking the time for this awesome session. Thank you, John. Thank you. So we're gonna talk about the perspective of the DOD relative to space cybersecurity, a lot, going on congestion, contention, freedom, evolution innovation. So Paul, I'd like to have you start with your opening statement on how you see the space cybersecurity perspective, Don, thanks for the intro. Really appreciate it. First, let me give my thanks to Cal poly for a convening, the space and cybersecurity symposium this year, you know, and despite the pandemic, the organization and the content delivery spreading impressive, I really foot stomping. >>What can possibly be done with a number of these virtual platforms? This has been awesome. Thanks for the opportunity. I also want to recognize my colleague, Chris Nissen from NSA was actually assigned to our staff that LSD, but he brings both policy and technical perspective in this whole area. So I think you'll, you'll find his commentary, uh, and positions on things very refreshing or for today's seminar. Now space cyber security is a pretty interesting terminology for us all. Uh, cyber security means protecting against cyber threats and it's really more than just computers here on earth, right? Uh, space is the newest war fighting domain, and cybersecurity's perhaps even more of a challenge in this domain that and others. Uh, I'm sure it'll turn journal Thompson and major journals Shaw discuss the criticality of this new dorm space force. It's the newest military service in the earlier sessions and they're at the risk of repeating what they already addressed. >>Let me start by talking about what space means to DOD and what we're doing directly from my vantage point as part of the acquisition and sustainment arm of the Pentagon. Uh, what I want to share with you today is how the current space strategy ties into the national defense strategy and supports the department's operational objectives. As the director of CFRI SAR. I have come to understand how the integration of CFRI Sarcic. Billy is a powerful asset to enhance the lethality of the joint war fighter. Secretary Lord, our boss, the sec, the undersecretary for acquisition and sustainment is diligent in her pursuit to adapt and modernize acquisition processes, to influence the strategy and to focus our efforts domain are to make our objectives a reality. I think first and foremost, we are building a more lethal force. This joint force will project low Valley and custom contested environments and across all domains through an operationally integrated and resiliency for ISR infrastructure. >>We are also called debating our alliances, deepening interoperability, which is very important in a future fight and collab, collaboratively planning with those partner with us in the fight most significantly for our work in acquisition and sustainment, we continue to optimize the department for greater performance and affordability through reform of the acquisition process. Now space is our newest war fighting domain. And while it is indeed unique, it shares many common traits with the others land, air and sea all are important to the defense of the U S in conflict. No doubt about this. They will be contested and they must be defended. One domain will not win future conflicts in a joint operation in a future fight in the future conflict. They must all succeed. I see three areas being key to a DOD strategic success in space, one, developing our whole of government approach in close partnership with the private sector and our allies to prioritizing our investments in resiliency, innovation, and adaptive operations, and third responding rapidly and effectively to leverage emerging technologies and seize opportunities to advance your strengths, partnerships and alliances. >>Let me emphasize that space is increasingly congested and tested and demanded as essential delete Valley operational effectiveness and the security of our nation. Now the commercialization of space offers a broad set of investments in satellite technology, potential opportunities to leverage those investments and pathways to develop cost efficient space architecture, where the department and the nation. It's funny, there's a new race, a race for space. If you will, between commercial companies buying for dominance of space. Now the joint staff within DOD is currently building an operational construct to employ and engage as a unified force, coordinated across all domains. We call it the joint, all domain command and control. It is the framework that is under development to allow us to conduct integrated operations in the future. The objective of Jesse too is to provide the war fighter access to the decision making information while providing mission assurance of the information and resilience of the underlying terrestrial air in space networks that support them operationally. >>six to maintain seamless integration, adaptation, and employment of our capability. To sense signal connect, transmit, process control, direct, and deliver lethal capabilities against the enemy. We gain a strategic advantage through the integration of these capabilities across all the domains, by providing balance bowel space, awareness, horse protection, and weapons controlled and deployment capabilities. Now successfully any ratings, the systems and capabilities will provide our war fighters overwhelming superiority on the battlefield environment, challenged by near peer adversaries, as well as non state actors in space. The character of its employment is changing, driven by increasing demands, not just by DOD, but by the commercial sector as well. You know, more and more, uh, we see greater use of small satellite systems to address a myriad of emerging questions, ubiquitous communications, awareness, sensor diversity, and many more. Uh, as I said before, the commercial world is pioneering high rate production of small satellites in our efforts to deploy hundreds, if not thousands of nodes space X, Darlene constellation is one example. >>Another one is Amazon's Kiper, uh, Kuyper just received FCC approval to deploy like over 3000 of these different notes. While a number of these companies continue to grow. Some have struggled. They some pointed as one web, uh, nevertheless, the appetite remains strong and DOD is taking advantage of these advances to support our missions. We are currently exploring how to better integrate the DOD activities involving small satellites under the small satellite coordinating activity, scholarly call it. We want to ensure collaboration and interoperability to maximize efficiency in acquisition and operation. When we started this activity on over a year and a half ago, we documented over 70 plus separate small, small sat programs within DOD. And now we've developed a very vibrant community of interest surrounding a small satellites. Now, part of the work we have identified nine focus areas for further development. These are common areas to all systems and by continuing to expand on these, our plan is they enable a standard of practice that can be applied across all of the domains. >>This includes lawn services, ground processing distribution, and of course, a topic of interest to the symposium space security and Chris we'll, we'll talk more about that being the Houston expert, uh, in this area. Uh, one challenge that we can definitely start working on today is workforce development. Cybersecurity's unique as it straddles STEM and security and policy, the trade craft is different. And unfortunately I've seen estimates recently, so suggesting a workforce gap in the next several years, much like the STEM fields, uh, during the next session, I am a part of a panel with precedent, Armstrong, Cal poly, and Steve Jake's the founder of the national security space association to address workforce development. But for this panel, I'll look forward to having further dialogue surrounding space, opera security with Chris and John. Thank you, John >>Bob, thank you for that whole thing, Steven. Yes. Workforce gaps. We need the new skill space is here. Thank you very much. Chris Henson, technical director of space and weapons, cybersecurity solutions for the national security agency. Your statement, >>Thank you for having me. Uh, I'm one of several technical leaders in space at the national security agency. And I'm currently on a joint duty assignment at the office of under secretary of defense for acquisition and sustainment. I work under mr. GUMA hot in the C four ISR area, but almost 63 years ago on the 4th of October, 1957, Sputnik was the first artificial satellite launched by the Soviet union in space. History was made in each of you can continue to write future space history in your careers. And just like in 1957, the U S isn't alone in space to include our close partnerships and longterm activities with organizations like the Japanese space agency, the European space agency, and, uh, the Canadian space agency, just to name a few. And when we tackle cybersecurity per space, we have to address, address the idea that the communications command and control, uh, and those mission datas will transverse networks owned and operated by a variety of partners, not only.go.mil.com.edu, et cetera. We need to have all the partners address the cyber effects of those systems because the risk excepted by one is shared by all and sharing cyber best practices, lessons learned, uh, data vulnerabilities, threat data, mitigation, mitigation procedures, all our valuable takeaways, uh, in expanding this space community, improving overall conditions for healthy environment. So thank you for having me, and I appreciate the opportunity to speak to you and your audience. And I look forward to the discussion questions. Thank you. >>Thank you, Chris. Thank you, Bob. Okay. I mean open innovation, the internet, you see plenty of examples. The theme here is partners, commercial government. It's going to take a lot of people and tech companies and technologies to make space work. So we asked my first question, Bonnie, we'll start with you is what do you see as the DOD his role in addressing cybersecurity in space? Uh, it's real, uh, it's a new frontier. Um, it's not going away. It's only going to get more innovative, more open, more contested. It seems like a lot to do there. So what's your role in addressing cyber security in space? >>I think our role is to be the leader in developing and only is it the strategy, but the, uh, the implementation plan is to ensure a full of cybersecurity. If you look at the national cyber cyber strategy, I think publishing 2018 calls for like-minded countries, industry academia, and civil society. Once you mentioned John, the support technology development, uh, digital safety policy advocacy, and research you here today, and those listening are fulfilling their strategy. When you, when you develop, enable use cyber hygiene products, as examples of capabilities, you're pushing the goal to fruition. When you know, what's on your network patron network backup, you're in encrypt your network, you're hardening and preventing cyber attacks. And we in government academia in the case of Cal poly civil networks and in commercial companies, we all benefit from doing that cyber security. Uh, and I think Chris will, we'll, we'll definitely back me up on this more than passwords encryption or pharma. It's truly a mindset and a culture of enabling missions to succeed in assured in a resilient fashion. >>Chris, you're taking reaction to, to the cybersecurity challenge involved here, >>That's it, it's starting really at the highest level of governments. We have, uh, you know, the, the recent security policy directive five that just came out just a couple of days ago, recognize all the factors of cybersecurity that need to come into play. And probably the most important outcome of that as mr said, is the leadership role and that leadership, uh, blends out very well into partnership. So partnership with industry partnership with academia partnership, with, uh, other people that are exploring space. And those partnerships lend itself very naturally to sharing cybersecurity issues, topics as we come up with best practices as we come up with mitigation strategies. And as we come up with vulnerabilities and share that information, the, uh, we're not going to go alone in space, just like we're probably not going to go alone in many other industries or areas, uh, that the DOD has to be, uh, involved in many spectrums of deploying to space. >>And that deployment involves as Mr. Guzman said, encryption authentication, knowing what's on the network, knowing the, the fabric of that network. And if nothing else, this, uh, this, uh, internet of things and work from home environment that we've, uh, partaken of these last few months has even explored and expanded that notion even more dramatically as we have people dial in from all over the different, uh, locations, well space will be that natural node that, uh, natural, uh, next network and mesh involvement that we'll have to protect and explore on not just from a terrestrial involvement, but all segments of it. Th the comm segment, the space vehicle and the ground portion, >>No bond. We talked about this in our other segment, um, around with the president of Cal poly, but the operating models of the space force and the DOD and getting space. It's a software defined world, right? So cybersecurity is a real big issue. Cause you have an operating model that's requiring software to power, these low hanging satellites. That's just an extension to the network. It's distributed computing, know what this is. If you understand what technology we do in space, it's no different, it's just a different environment. So it's software defined that just lends itself well to hacking. I mean, if I'm a hacker I'm going, Hey, why not just take out a satellite and crash it down or make the GPS do something different? I mean, it's definitely an attack vector. This is a big deal. It's not just like getting credentials that are cashed on a server. You gotta really protect, >>Right? Because in one hand it space will carry not only, uh, uh, you know, for local national security information. Uh, but the, uh, I feel like at the economic wellbeing, the financial state of allowed a lot of countries and institutions, you know, more and more John lb, they'll be using space assets to, uh, uh, to make, uh, make, make all that happen. Right. So, and if you look at the, you talk, you mentioned the attack vectors in space, you know, it's not just the computers in the ground, but if you look at the whole life cycle for satellite systems in space, you know, that the, the, the tasking that you need to do that the command, the controlling of the vehicle, the data that comes down in the ground, even when you launch the, the birds, the satellites, you know, they only need to be protected because they're all somewhat vulnerable to, uh, to hacking, uh, to cyber attacks. Especially as we grow into commercialization space, it's going to be a lot more people out there playing in this world. It's going to be a lot more companies out there. And, you know, it's hard to track, uh, uh, you know, the, the potential of, of, of foreign influences as an example, and therefore the potential of being vulnerable in terms of the cyber threat. >>Gentlemen, I like you guys said to move on to this leadership role, you mentioned that you want to be a leader. I get it. The DOD is department of defense. That's a new frontier to defend war time zone. You mentioned war time opportunity potentially, but how do you guys assist that's term hat to getting done? Because there's public and private space operations happening, um, there's security challenge. What does being a leader mean? And how does the DOD department of defense assist driving the public and private? Do you lead from a project standpoint, you lead from a funding standpoint? Is it architectural? I mean, you're talking about now a new end to end architecture. It's not just cloud it's on premise. It's in devices, it's offloaded with new AI technology and Nicks and devices. It's IOT, it's all, this is all new, this is all new. What does it mean for the DOD to be a leader and how do you assist others to get involved? And what does that mean? >>Yeah, I think, uh, the one hand, you know, DOD used to lead, uh, in terms of, uh, uh, being the only source of funding for a lot of, uh, highly developmental efforts. Uh, we're seeing a different story in space. Again, I keep going back to the commercialization of space. We're seeing a lot more players, right? So in many ways >>Ally's commercial companies are actually legally leading the R and D uh, of a lot of different technologies. So we want to take, we certainly want to take advantage of that. So from a leadership standpoint, I think we, we, Lucia can come in, you know, by partnering a lot more with, with the commercial companies, uh, in 2022, the DOD released the defense, uh, uh, space strategy as an example that highlights the threats, the challenges and opportunities the United States has faced by, by sending a example of how we, how we, uh, how we counter, uh, the threats that are out there, not just the DOD, but, but the disability and the commercial sector as well. Our current conditions are strong, but we want to use four lines of effort to meet our challenges and capitalize on our desire state space, uh, lines of effort include building a comprehensive military badges space, integrating space into a national joint and combined operations. Like I mentioned before, shaping that strategic environment and cooperating with allies, partners, and industry and other U S governmental agencies, departments, and agencies to advance the cost of space to take full advantage of what space can provide us, uh, in DOD, uh, and the nation. Chris has a domain. Now, what's your take on all that? >>That's because again, it's going to take more people, >>More diverse, potentially more security >>Halls. What's your view on it? >>Well, let's, let's look at how innovation and new technologies can help us in these areas. So, uh, and, and mentioned it a couple of topics that you hit on already. One of the areas that we can improve on is certainly in the, uh, the architecture, uh, where we look at a zero trust architecture, one of the NIST standards that's come about where it talks about the authentication, uh, the need to know a granular approach, this idea of being able to protect, not just data, but the resources and how people can get access to those, whether they're coming in through an identification, authentication Prudential, or, uh, other aspects of, uh, the, the idea of not just anybody should be able to have access to data or anybody should have access once they're on the inside of the network. So that zero trust architecture is, is one approach where we can show some leadership and guidance. >>Another area is in, uh, a topic that you touched on as well was in the software area. So some innovations are coming on very rapidly and strong in this artificial intelligence and machine learning. So if we can take this AI and ML and apply it to our software development areas, they can parse so much information very quickly. And, uh, you know, this vast array of code that's going into system nowadays, and then that frees up our human, uh, explicit talent and developers that can then look at other areas and not focus on minor bawling to Beverly fix a vulnerability. Uh, they, they can really use their unique skills and talents to come up with a better process, a better way, and let the artificial intelligence and machine learning, find those common problems, those, those unknown, hidden lines of code that, uh, get put into a software alarm Prairie, and then pull down over and over again from system to system. So I think between, uh, an architecture leadership role and employee innovation are two areas that we can show, uh, some benefits and process improvement to this whole system. >>That's a great point, Chris, and you think about just the architectural computer architecture, you know, S you know, network attached storage is an advantage software defined there. You could have flash all flash arrays for storage. You could have multiple cores on a device and this new architecture, offloads things, and it's a whole new way to gain efficiencies. I mean, you got Intel, you got Nvidia, you've got armed all the processors all built in. Um, so there's definitely been commercial best practices and benefits to a new kind of architecture that takes advantage of these new things. It's just, just efficiencies. Um, but this brings up the whole supply chain conversation. I want to get your thoughts on this, because there is talk about predatory investments and access and tactics to gain supply chain access to space systems, your thoughts. >>Yeah. It's a serious threat and not just for, uh, the U S uh, space. So supply chain, if you will, is the supply chain. And I says, you know, writ large, I think, uh, I think it's a, it's a, it's a threat that's, that's real, we're we're seeing today. I just saw an example recently, uh, involving, uh, our, I think our launch services were, there was a, uh, a foreign, uh, threat that was those trying to get into a true through with predatory investments. Uh, so, uh, it is something that we need to, uh, be aware of it it's happening, uh, and is continuing to happen. Uh, it's an easy way to gain access, to, uh, do our IP. Uh, and, uh, so it's something that we, uh, are serious about in terms of, uh, awareness and, and countering >>Chris, your thoughts. I mean, we've see, I mean, I'm an open source guy. I was seen it when I grew up in the industry in the eighties, open source became a revolution, but with that, it enabled new tactics for, um, state sponsored attacks on it that became a domain in of itself. Um, that's well-documented and people talk about that all the time in cyber. Now you have open innovation with hardware, software connected systems. This is going to bring supply chain nightmare. How do you track it all? Who's got what software and what device, where the chip come from, who made it, this is the potential is everywhere. How do you see the, these tactics, whether it's a VC firm from another country or this, that, and the other thing startup. >>Yeah. So when we see, when we see coal companies being purchased by foreign investors, and, you know, we can get blocked out of those, whether it's in the food industry, or if it's in a microchip, then that microchip could be used in a cell phone or a satellite or an automobile. So all of our industries that have these companies that are being purchased, or a large born investment influx into those, you know, that could be suspect. And we, we have to be very careful with those, uh, and, and do the tracking of those, especially when those, uh, some of those parts of mechanisms are coming from off shore. And then going again, going back to, uh, the space policy directive five, it calls out for better supply chain, resource management, the tracking, the knowing the pedigree and the, the quantitative of ability of knowing where those software libraries came from, where the parts came from and the tracking and delivery of that from an end to end system. >>And typically when we have a really large vendor, they can, they can do that really well. But when we have a subcontractor to a subcontractor, to a subcontractor, their resources may not be such that they can do that. Try tracking in mitigation for counterfeits or fraudulent materials going into our systems. So it's a very difficult challenge, and we want to ensure as best we can that as we ingest those parts, as we ingest those software libraries and technologies into the system, that, uh, before we employ them, we have to do some robust testing. And I don't want to say that the last line of defense, but that certainly is a mechanism for finding out, do the systems perform as they stated, uh, on a test bench or a flat set, whatever the case may be before we actually deploy it. And then we're relying on the output or the data that comes from that, that system that may have some corrupt or suspect parts in it. >>Great point, this federal grant, >>The problem with space systems is kind of, you know, is once you, once you launch the bird or the sunlight, uh, your access to it is, is diminished significantly, right? Unless you, you go up there and take it down. Uh, so, you know, kind of to Chris's point, we need to be able to test all the different parts of insurer that is performing as, as described there ass, I spent as specified, uh, with, with good knowledge that it's, uh, it's, uh, it's trustworthy. Uh, and, uh, so we that all on the ground before we, we take it up to launch it. >>It's funny. You want agility, you want speed and you want security, and you want reliability and risk management all aggressive, and it's a technical problem. It says it's a business model problem. I'd love to get real quick. Before we jump into some of the more workforce and gap issues on the personnel side, have you guys should just take a minute to explain quickly what's the federal view. If you had to kind of summarize the federal view of the DOD and the roll with it wants to take, so all the people out there on the commercial side or students out there who are, you know, wanting to jump in, what is the current modern federal view of space cybersecurity. >>Chris, why don't you take that on I'll follow up. Okay. Uh, I don't know that I can give you the federal view, but I can certainly give you the department of defense. That cybersecurity is extremely important. And as our vendors and our suppliers, uh, take on a very, very large and important role, one area that we're looking at improving on is a cyber certification maturity model, where we, where we look at the vendors and how they implement an employee cyber hygiene. So that guidance in and of itself shows the emphasis of cyber security that when we want to write a contract or a vendor, uh, for, for a purchase, that's going to go into a space system. We'd like to know from a third party audit capability, can that vendor, uh, protect and defend to some extent the amount that that part or piece or software system is going to have a cyber protection already built into it from that vendor, from the ground floor up before it even gets put into a larger system. >>So that shows a level of the CMMC process that we've thought about and, uh, started to employ, uh, beginning in 2021 and will be further built on in, in the out years. How, how important the DOD takes that. And other parts of the government are looking at this, in fact, other nations are looking at the CMMC model. So I think it shows a concern in very many areas, uh, not just in the department of defense that they're going to adopt an approach like this. Uh, so it shows the, the pluses and the benefits of a cybersecurity model that, uh, all can build on boggy reaction. Yeah, I'll just, uh, I'll just add to that, John, you, you, you, you asked earlier about, you know, how do we, uh, track, uh, commercial entities or, or people in the space and cyber security domains? Uh, I can tell you that, uh, at least my view of it, you know, space and cyber security are new, it's exciting, it's challenging a lot technical challenges there. So I think in >>Terms of attracting the right people, personnel to work those areas, uh, I think it's, it's not only intellectually challenging, uh, but it's important for, for the dependency that NASA States, uh, and it's important for, for, for economic security, uh, writ large for, for us as well. So I think, uh, in terms of a workforce and trying to get people interested in, in those domains, uh, I hope that they see the same thing we do in terms of, of the challenges and the opportunities it presents itself in the future. >>Awesome. I love your talk on intro track there falling. You mentioned, uh, the three key areas of DOD sec success, developing a government whole government approach to partnership with the private sector. I think that's critical and the allies prioritizing the right investments on resilience, innovation, adaptive operations, and responding to rapidly to effectively emerging technology. So you can be fast, all think are all things. I all, all those things are relevant. So given that, I want to get your thoughts on the defense space strategy in 2020, the DOD released dispense defense space, strategy, highlighting threats, and challenges and opportunities. How would you summarize those threats and those challenges and opportunities? What are the, what are those things that you're watching in the defense space area? Right. >>Well, I think, I think I saw, as I said before, of course, as well, you know, uh, or, or seeing that a space will be highly contested, uh, because it's a critical element in our, in our war fighting construct, uh, Dwayne, a future conflict, I think we need to, to win space as well. So when you, when you look at our near peer adversaries, there's a lot of efforts, uh, in trying to, to, to take that advantage away from the United States. So, so the threat is real, uh, and I think it's going to continue to evolve and grow. Uh, and the more we use space, both commercial and government, I think you're going to see a lot more when these threads some AFAs itself, uh, in, in forms of cyber, cyber attacks, or even kinetic attacks in some cases as needed. Uh, so yeah, so with the, the, the threat is need growing, uh, space is congested, as we talked about, it will continually be contested in the future as well. So we need to have, uh, like we do now in, in, in all the other domains, a way to defend it. And that's what we're working on with India, with the, how do we pilot with tech, our assets in space, and how do we make sure that the data information that traverses through space assets are trust 40, um, and, uh, and, and, and free of any, uh, uh, interference >>Chris, exciting time. I'm your, if you're in technology, um, this is crossing many lines here, tech society will war time, defense, new areas, new tech. I mean, it's security, it's intoxicating at many levels, because if you think about it, it's not one thing. It's not one thing anymore. It spans a broader spectrum, these opportunities. >>Yeah. And I, and I think that expansion is, is a natural outgrowth from, as our microprocessors and chips and technology continue to shrink smaller and smaller. You know, we, we think of our, our cell phones and our handheld devices and tablets, and so on that have just continued to, uh, get embedded in our everyday society, our everyday way of life. And that's a natural extension when we start applying those to space systems. When we think of smallsats and cube sets and the technology that's, uh, can be repurposed into, uh, a small vehicle and the cost has come down so dramatically that, you know, we, we can afford to get a rapid experiments, rapid, um, exploitations and, and different approaches in space and learn from those and repeat them very quickly and very rapidly. And that applies itself very well to an agile development process, dev sec ops, and this notion of spins and cycles and refreshing and re uh, addressing priorities very quickly so that when we do put a new technology up, that the technology is very lean and cutting edge, and hasn't been years and years in the making, but it's, uh, relevant and new, and the, uh, the cybersecurity and the vulnerabilities of that have to be addressed because of, and allow that DevSecOps process to take place so that we can look at those vulnerabilities and get that new technology and those new, new experiments and demonstrations in space and get lessons learned from them over and over again. >>Well, that brings us to the next big topic I want to spend the remainder of our time on that is workforce this next generation. If I wasn't so old, I would quit my job and I would join medially. It's so much, it's a fun, it's exciting. And it's important. And this is what I think is a key point is that cybersecurity in and of itself has got a big gap of shortage of workers, nevermind, adding space to it. So this is, uh, the intersection of space and cybersecurity. There is a workforce opportunity for this next generation, a young person to person re-skilling, this is a big deal. Bong, you have thoughts on this. It's not just STEM, it's everything. >>Yeah. It's everything, you know, uh, the opportunities would have in space it's significant and tremendous. And I think, uh, if I were young, again, as you pointed out, John, uh, you know, I'm, I'm, I'm lucky that I'm in this domain in this world and I started years ago. Uh, but it continues to be exciting, uh, lots of, lots of opportunities, you know, and when you, when you look at, uh, some of the commercial space, uh, systems that are being, being put up, uh, if you look at, I mentioned Starlink before, and, and, uh, Amazon's Kuyper constellation. These guys are talking about couple of thousand satellites in space to provide ubiquitous communications for internet globally and that sort of thing. Uh, and they're not the only ones that are out there producing capability. Uh, we're seeing a lot more commercial imagery products being developed by bike, by companies, both within the U S and, and, uh, foreign foreign elements as well. So I think it's an exciting time to be in space. Certainly lots of opportunities, there's technical challenges, uh, galore in terms of, you know, not only the overcoming the physics of space, but being able to operate, uh, flexibly, uh, in, uh, get the most you can out of the capabilities we have, uh, uh, operating up as high as being cool. I mean, everyone looks at launch. >>She gets millions of views on live streams, the on demand, reruns get millions and millions of views. Um, it's, there's a lot of things there. Um, so Chris, what specifically could you share are things that people would work on? Um, jobs skills, what are some, what's the aperture, what's it look like if you zoom out and look at all the opportunities from a scale standpoint, what's out there, >>We'll talk to the aperture, but I want to give a shout out to our space force. And I mean, their, their job is to train and equip, uh, future space and, uh, that, that space talent. And I think that's going to be a huge plus up, uh, to have, uh, uh, a space force that's dedicated to training equipping, uh, the, an acquisition and a deployment model that, uh, will benefit not just the other services, but all of our national defense and our, uh, you know, our, our strategic way of, uh, how, how this company, country, employees space, uh, altogether. So having, having a space for us, I think, as a, is a huge, uh, a huge issue. And then to get to that aperture aspect of, of what you're, what you're asking and, you know, that addresses a larger workforce. Uh, we need so many different talents in, in this area. >>Uh, we can, we can have, we can employ a variety of people, uh, from technical writers to people who write, uh, write in developed software to those who, uh, are bending metal and actually, uh, working in a hardware environment. And, uh, those that do planning and launch operations and all of those spectrums and issues of jobs, or are directly related to a workforce that can contribute to, to space. And then once that data gets to the ground and employed out to a user, whether it's a data or we're looking at, uh, from a sensor recent, uh, recent events on, uh, shipping lanes, those types of things. So space has such a wide and diverse swath that the aperture's really wide open, uh, for a variety of backgrounds. And, and those that, uh, really just want to take an opportunity, take a, take a technical degree or a degree that, uh, can apply itself to a tough problem, uh, because they certainly exist in space. And we can, we can use that mindset of problem solving, whether you come at it from a hacker mindset, an ethical, a white hat approach to testing and vulnerability exploration, or somebody who knows how to actually, um, make, uh, operations, uh, safer, better, uh, through space situation awareness. So there's a, there's a huge swath of opportunity for us >>Bon talk about the, um, the cyber security enabled environment, the use cases that are possible when you have cybersecurity in play with space systems, um, which is in and of itself, a huge range of jobs, codings supply chain. We just talked about a bunch of them. There's still more connected use cases that go beyond that, that, that are enabled by it. If you think about it, and this is what the students at Cal poly and every other college and university community college, you name it, or watching videos on YouTube, anyone with a brain can jump in. If they, if they see the future, it's an all net new space force is driving awareness, but there's a whole slew of these new use cases that I call space enabled by cybersecurity systems. Your thoughts. >>Absolutely. I, you know, I was, uh, had planned on attending the, uh, uh, the cyber challenge that's Cal poly had planned in June, of course, a pandemic, uh, uh, took care of that plan. But, but I was intrigued by, by the approach that the Cal poly was taking with, with, uh, middle school and high school kids of, of, of, of exposing him to a problem set here. You have a, a satellite that came down from space, uh, and, uh, part of the challenge was to do Porensic analysis on the debris, uh, the remaining pieces of the sound like to figure out what happened. Uh, it had a, uh, a cybersecurity connotation. It was hacked. It was attacked by, by cyber threat nation, took it down. And the beauty of having these kids kind of play with, with the remaining parts of the satellite figure out what happened. >>So I was pretty exciting. I was really looking forward to participating in that, but again, the pandemic kind of blew that up, but I, I look forward to future events like that to, to get our young people intrigued and interested in, uh, in this new field of space. Now, you know, Chris was talking earlier about opportunities, the opportunity that you talk about, you know, while I would like to have people come to the government, right. To help us out. It's not, it's not just focused on government, right? There's not lots of opportunities in commercial space. I, if you will, uh, for, for a lot of talent to, uh, uh, to have, uh, to participate in. So the challenge is a man's government and the commercial sector, John, >>I mean, you get the hardcore, you know, I want to work for the DOD. I want to work for NSA. I want to work for the government. You clearly got people who want to have that kind of mission, but for the folks out there, Chris and bong that are like, I'll do I qualify it? It's like the black box of the DOD. It's like a secret thing. You got any clearance, you've got to get all these certifications. And you've got to take all kinds of tests and background checks. And, um, is it like that? And will that continue? Cause some people might say, Hey, can I even get involved? What do I do? So I know there's some private partnerships going on with companies out there in the private sector. So this is now a new, you guys seem to be partnering and going outside the comfort zone of the old kind of tactical things. What are some of those opportunities that people could get involved that they might not know about >>PR for NSA, there's a variety of workforce, uh, initiatives that, uh, uh, for anybody from a high school work study can take advantage of to, uh, those that would like have to have internships. And those that are in a traditional academic environment, there's, uh, several NSA schools across the country that have a academic and cyber acts, uh, sites of excellence that participate in projects that are shepherded and mentored by those at NSA that can get those tough problems that don't have maybe a classified or super sensitive, uh, nature that that can be worked in and in an academia environment. So, so those are two or three examples of how somebody can break into, uh, the, uh, an intelligence organization and the, and the other agencies have those, uh, opportunities as well across the intelligence community and the, the partnership between and collaborative collaboration between private industry and the agencies and the department of defense just continue to grow over and over again. And even myself being able to take care advantage of a joint duty assignment between my home organization and the Pentagon just shows another venue of somebody that's in one organization can partner and leverage with another organization as well. So I'm an example of, of that partnering that's going on today. >>So there's some innovation, bong, non traditional pathways to find talent. What are out there? What are new, what are these new nontraditional ways >>I was going to add to what Chris was, was mentioning John? Yeah. Even within view and under the purview of our chief information officer, back in 2013, the deputy surfed dirty defense signed the, uh, what we call the DOD cyberspace workforce strategy, uh, into effect. And that included a program called the cyber information technology exchange program. It's an exchange program in which a, uh, you know, private sector employee and worked for the DOD in cyber security positions, uh, span across multiple mission critical areas. So this is one opportunity to learn, uh, you know, in inside the DOD what's happening as a private sector person, if you will, uh, going back to what we talked about, you know, kinda, uh, opportunities, uh, within the government for, for somebody who might be interested, uh, you know, you don't have to be super smart, Bork and space. Uh, there's a lot of like, like Chris pointed out, there's a lot of different areas that we need to have people down within people to do, uh, to conduct the mission space. So you don't have to be mathematician mathematician. You don't have to be an engineer to succeed in this business. I think there's plenty of opportunities for, for any types of, of talent, any type of academic disciplines that, that, that, that they're out there. >>And I think, you know, Chris is shout out to the space force is really worth calling out again, because I think to me, that's a big deal. It's a huge deal. It's going to change the face of our nation and society. So super, super important. And that's going to rise the tide. I think it's gonna create, uh, some activation, uh, for a younger generation, certainly, and kind of new opportunities, new problems to solve new threats to take on and, and move it on. So really super conversation space in cybersecurity, the department of defense perspective, Von and Chris, thank you for taking the time. I'd love you guys just to close out. We'll start with you bong. And then Chris summarize for the folks watching, whether it's a student at Cal poly or other university or someone in industry and government, what is the department of defense perspective for space cybersecurity? >>Chris, won't go and take that on. I started, thank you. Uh, cyber security applies to much more than just the launch and download of mission data or human led exploration and the planning, testing, and experiments in the lab prior to launch require that cyber protection, just as much as any other space link, ground segment, trust rail network, or user data, and any of that loss of intellectual property or proprietary data is an extremely valuable and important, and really warrants, cybersecurity safeguards in any economic espionage or data exfiltration or denied access to that data I E ransomware or some other, uh, attack that can cripple any business or government endeavor. Uh, no matter how small or large, if it's left in our economic backbone, uh, clearly depends on space and GPS is more than just a direction finding our banking needs that a T and timing from P and T or whether it says systems that protect our shipping and airline industry of whether they can navigate and go through a particular storm or not, uh, even fighting forest fires picked up by a remote sensor. >>All those space-based assets, uh, require protection from spoofing date, uh, data denial or total asset loss. An example would be if a satellite sensitive optics were intentionally pointed at the sun and damaged, or if a command, uh, to avoid collision with another space vehicle was delayed or disrupted or a ground termination command. As we just saw just a few days ago at T minus three seconds prior to liftoff, if those all don't go as planned, uh, those losses are real and can be catastrophic. So the threat to space is pervasive real and genuine, and your active work across all those platforms is a necessary and appreciated. And your work in this area is critical, uh, going forward going forward. Uh, thank you for this opportunity to speak with you and, uh, talking on this important topic. >>Thank you, Chris Henson, goodbye. >>Closing remarks. Yeah. Likewise, John, uh, again, uh, as, as Chris said, thank you for, for the opportunity to discuss this very important, uh, around space, cyber security, as well as addressing, uh, at the end there, we were talking about workforce development and the need to have, uh, people, uh, in the mix for four features. We discussed with you. We need to start that recruiting early, uh, as we're doing to address, uh, the STEM gap today, we need to apply the same thing for cybersecurity. We, we absolutely need smart, innovative people to protect both Iraq. Anomic wellbeings a nation as well as our national defense. So this is the right conversation to have at this time, John and I, again, thank you and our Cal poly hose for, or, uh, having a symposium and, and having this opportunity to have this dialogue. Thank you, >>Gentlemen. Thank you for your time and great insights. We couldn't be there in person. We're here virtual for the space and cybersecurity symposium, 2020, the Cal poly I'm Jennifer with Silicon angle and the cube, your host. Thank you for watching.

>> Hello everyone. My name is Zoltan Toroczkai. I am from University of Notre Dame, Physics department, and I'd like to thank the organizers for their kind invitation to participate in this very interesting and promising workshop. Also like to say that I look forward to collaborations with the Redefine Lab and Yoshian collaborators on the topics of this work. So today I'll briefly talk about, our attempt to understand, the fundamental limits of analog, continuous-time computing at least from the point of view of Boolean Satisfiability problem-solving using ordinary differential equations. But I think the issues that we raise during this occasion actually apply to other approaches, analog approaches as well, until to other problems as well. I think everyone here, knows what Boolean Satisfiability problems are. You have N Boolean variables, you have M clauses. Each a disjunction of K literals. Literal is a variable or it's negation. And the goal is to find an assignment to the variable such that all the clauses are true. This is a decision type problem from the NP class, which means you can check in polynomial time for satisfiability of any assignment. And the 3-SAT is NP-complete with K, 3 or larger, which means an efficient 3-SAT solver, (clears throat) implies an efficient solver for all the problems in the NP clause because all the problems in the NP clause can be reduced in polynomial time to 3-SAT. As a matter of fact you can, reduce the NP-complete problems into each other. You can go from 3-SAT to Set Packing or to Maximum Independent Set which is the set packing in graph theoretic notions or terms, to the ising graph SAT problem decision version. This is useful when you are comparing different approaches or working on different kinds of problems. When not all the clauses can be satisfied, you're looking at the optimization version of SAT, called Max-SAT and the goal here is to find the assignment that satisfies the maximum number of clauses, and this is from the NP-hard class. In terms of applications, if we had an efficient SAT solver, or NP-complete problem solver, it would literally, positively influence thousands of problems in applications in industry and science. I'm not going to read this. But this of course gives us some motivation, to work on these kind of problems. Now, our approach to SAT solving, involves embedding the problem in a continuous space, and you use all these to do that. So instead of working zeros and ones, we work with minus one and plus ones, and if we allow the corresponding variables, to change continuously between the two bounds, we formulate the problem with the help of a Clause Matrix. If, if a clause does not contain a variable or its negation, the corresponding matrix element is zero. If it contains the variable in positive form it's one. If it contains the variable in negated form, it's negative one. And now we use this to formulate these products, called clause violation functions, one for every clause, which rarely continues between zero and one and beyond zero if and only if the clause itself is true. Then we form... We define, also define the dynamics, search dynamics in this and the M-dimensional hypercube, where the search happens and if there exists solutions they're sitting in some of the corners of this hypercube. So we define this energy, potential or landscape function as shown here in a way that it, this is zero if and only if all the clauses, all the Kms are zero. All the clauses are satisfied, keeping these auxiliary variables, Ams always positive. And therefore what we do here is a dynamics that is essentially a gradient descent on this potential energy landscape. If you are to keep all the Ams constant then it would get stuck in some local minimum. However what do you do here is, we couple it with the dynamics. We couple it with the clause violation functions as shown here. And if you didn't have these Am here, just had just the Kms, for example, you have essentially, both case you have a positive feedback. You have a decreasing variable, but in that case you'll still get stuck, would still behave... We'll still find solutions better than the constant version or still would get stuck. Only when we put here this Am, which makes them dynamics in this variable exponential like, only then it keeps searching until it finds a solution. And there's a reason for that, that I'm not going to talk about here, but essentially boils down to performing a gradient descent on a globally time-varying landscape. And, and, and this is what works. Now, I'm going to talk about the good or bad, and maybe the ugly. This is, this is... What's good is that it's a hyperbolic dynamical system, which means that if you take any domain in the search space that doesn't have a solution in it or any solution in it, then the number of trajectories in it, the case exponentially quickly and the decay rate is a characteristic, invariant characteristic of the dynamics itself with the dynamical systems called the escape rate. The inverse of that is the timescale in which you find solutions by this dynamical system. And you can see here some trajectories, they are curved because it's, it's not linear but it's transiently curved to give, if there are solutions of course, we could see eventually, it does lead to the solutions. Now, in terms of performance, here what you show, for a bunch of, constraint densities, defined by, M over N, the ratio between clauses to variables, for random SAT problems, is random 3-SAT problems. And they, they, as, as function of N, and we look at, monitor the wall time, the wall clock time, and it, it behaves quite well, it behaves as a, as a polynomialy, until you actually hit, or reach the set on set transition, where the hardest problems are found. But what's more interesting is if you monitor the continuous-time t, the performance in terms of the analog continuous-time t, because that seems to be a polynomial. And the way we show that, is we can see the random K-SAT or random 3-SAT for a fixed constraint density. And we here, what you show here is at the, right at the threshold where it's really hard. And, (clears throat) we monitor the fraction of problems that we have not been able to solve it. We select thousands of problems at that cost rate ratio and we solve them with our algorithm, and we monitor the fraction of problems that have not yet been solved by continuous-time t. And these, as you see these decays exponentially in different decay rates for different system sizes and in this spot shows that this decay rate behaves polynomialy. or actually as a power law. So if you combine these two, you find that the time needed to solve all problems, except maybe appeared fraction of them, scales polynomialy with problem size. So you have polynomial continuous-time complexity. And this is also true, for other types of very hard constraints of the SAT problem such as exact color, because you can always transform them into 3-SAT as we discussed before, Ramsay coloring and, and on these problems, even algorithms like a survey propagation wheel will fail. But this doesn't mean that P equals NP because what you have, first of all, if you were to implement these equations in a device, whose behavior is described by these ODEs, then of course, t the continuous-time variable, becomes a physical wall clock time. And that would be polynomialy scaling but you have other variables, auxiliary variables, which fluctuate in an exponential manner. So if they represent currents or voltages in your realization and it would be an exponential cost algorithm. But this is some kind of trade between time and energy while I know how to generate energy or I don't know how to generate time but I know how to generate energy so it could be useful. But there's other issues as well, especially if you're trying to do this on a digital machine, but also happens, problems happen, appear, other problems appear on in physical devices as well as we discuss later. So if you implement these in GPU, you can, then you can get an order of two magnitude speedup, and you can also modify this, to solve Max-SAT problems quite efficiently, we are competitive with the best, heuristics solvers, this is all the problems in 2016, Max-SAT competition. So, so this, this, this is definitely, this is like a good approach, but there's of course, interesting limitations, I would say interesting, because it kind of makes you think about what it needs and how you can explore this, these observations in understanding better analog continuous-time complexity. If you monitor the discrete number, the number of discrete steps, done by the Runge Kutta integrator, and you solve this on a digital machine. You're using some kind of integrator, and, you know, using the same approach, but now you measure the number of problems you haven't solved, by a given number of discrete steps taken by the integrator. You find out, you have exponential discrete-time complexity. And of course, this is a problem. And if you look closely, what happens, even though the analog mathematical trajectory, that's the red curve here, if you monitor what happens in discrete time, the integrator fluctuates very little. So this is like you know, third or four digits precision, but fluctuates like crazy. So it really is like the integration freezes out, and this is because of the phenomenon of stiffness that I'll talk a little bit, more about a little bit later. So you know, it may look like an integration issue on your digital machines that you could improve and you could definitely improve, but actually the issue is bigger than that. It's, it's deeper than that because on a digital machine there is no time energy conversion. So the auxiliary variables are efficiently represented in a digital machine, so there's no exponential fluctuating current or voltage in your computer when you do this. So if e is not equal NP, then the exponential time complexity or exponential cost complexity has to hit you somewhere. And this is how. But you know one would be tempted to think maybe, this wouldn't be an issue in a analog device, and to some extent is true. Analog devices can be orders of magnitude faster, but they also suffer from their own problems because P not equal NP affects that clause of followers as well. So, indeed if you look at other systems, like Coherent Ising Machine with Measurement-Feedback, or Polariton Condensate Graphs or Oscillator Networks, they all hinge on some kind of, our ability to control real variables with arbitrarily high precision, and Oscillator Networks, you want to read out arbitrarily close frequencies. In case of CIMs, we require identical analog amplitudes which is hard to keep and they kind of fluctuate away from one another, shift away from one another, And, and if you control that, of course, then you can control the performance. So, actually one can ask if whether or not this is a universal bottleneck, and it seems so, as I will argue next. We can recall a fundamental result by A. Schönhage, Graham Schönhage from 1978 who says that, it's a purely computer science proof, that, "If you are able to compute, "the addition, multiplication, division "of real variables with infinite precision then, "you could solve NP-complete problems in polynomial time." He doesn't actually propose a solid work, he just shows mathematically that this will be the case. Now, of course, in real world, you have loss of precision. So the next question is, "How does that affect the computation of our problems?" This is what we are after. Loss of precision means information loss or entropy production. So what we are really looking at, the relationship between hardness and cost of computing of a problem. (clears throat) And according to Sean Harget, there is this left branch, which in principle could be polynomial time, but the question, whether or not this is achievable, that is not achievable, but something more achievable that's on the right-hand side. You know, there's always going to be some information loss, some entropy generation that could keep you away from, possibly from polynomial time. So this is what we'd like to understand. And this information loss, the source of this is not just noise, as, as I will argue in any physical system, but it's also of algorithmic nature. So that is a questionable area or, or approach, but Schönhage's result is purely theoretical, no actual solver is proposed. So we can ask, you know, just theoretically, out of curiosity, "Would in principle be such solvers?" Because he's not proposing a solver. In such properties in principle, if you were to look mathematically, precisely what that solver does, would have the right properties. And I argue, yes, I don't have a mathematical proof but I have some arguments that this would be the case. And this is the case for actually our sitdia solver, that if you could calculate, it's subjectivity in a loss this way, then it would be... Would solve NP-complete problems in polynomial continuous-time. Now, as a matter of fact, this is a bit more difficult question because time in all these can be re-scaled however you want. So what Bournez says, that you actually have to measure the length of the trajectory which is an invariant of the dynamical system or the property of the dynamical system, not of it's parametrization. And we did that. So Shubha Kharel my student did that, by first improving on the stiffness of the problem of the integrations using the implicit solvers and some smart tricks, such that you actually are closer to the actual trajectory and using the same approach to know, what fraction of problems you can solve. We did not give a length of the trajectory, you find that it is polynomialy scaling with the problem size. So we have polynomial scale complexity. That means that our solver is both poly-length, and as it is defined, it's also poly-time analog solver. But if you look at as a discrete algorithm, which will measure the discrete steps on a digital machine, it is an exponential solver, and the reason is because of all this stiffness. So every integrator has to truncate, digitize and truncate the equations. And what it has to do is to keep the integration within this so-called Stimpy TD gen for, for that scheme. And you have to keep this product within Eigenvalues of the Jacobian and the step size within this region, if you use explicit methods, you want to stay within this region. But what happens, that some of the eigenvalues grow fast for stiff problems, and then you're, you're forced to reduce that t, so the product stays in this bounded domain, which means that now you have to, we are forced to take smaller and smaller time steps, so you're, you're freezing out the integration and what I will show you, that's the case. Now you can move to implicit solvers, which is a new trick, in this case, your stability domain is actually on the outside, but what happens in this case, is some of the eigenvalues of the Jacobian, also for this instant start to move to zero, as they are moving to zero, they are going to enter this instability region. So your solver is going to try to keep it out, so it's going to increase the delta t, but if you increase that t, you increase the truncation errors, so you get randomized in the large search space. So it's, it's really not, not willing to work out. Now, one can sort of, introduce a theory or a language to discuss computational, analog computational complexity, using the language from dynamical systems theory. But basically I don't have time to go into this but you have for hard problems, the chaotic object the chaotic saddle in the middle of the search space somewhere, and that dictates how the dynamics happens and invariant properties of the dynamics, of course, of that saddle is what determines performance and many things. So an important measure that we find that, is also helpful in describing, this analog complexity is the so-called Kolmogorov or metric entropy. And basically what this does in an intuitive way, is to describe the rate at which the uncertainty, containing the insignificant digits of a trajectory in the back, they flow towards the significant ones, as you lose information because of errors being, grown or, or or, or developed into larger errors in an exponential, at an exponential rate because you have positive Lyapunov exponents. But this is an invariant property. It's the property of the set of all these, not how you compute them. And it's really the intrinsic rate of accuracy loss of a dynamical system. As I said that you have in such a high dimensional dynamical system, you have positive and negative Lyapunov exponents, as many as the total is the dimension of the space and user dimension, the number of unstable manufactured dimensions and assets now more stable many forms dimensions. And there's an interesting and I think important Pesin equality, equality called the Pesin equality, that connects the information theoretic, as per the rate of information loss with the geometric data each trajectory separate minus cut part which is the escape rate that I already talked about. Now, one can actually prove a simple theorem strike back of the calculation. The idea here is that, you know the rate at which the largest rate at which the closely started trajectory, separate from one another. So now you can say that, that is fine, as long as my trajectory finds the solution, before the trajectory separate too quickly. In that case, I can have the hope, that if I start from some region of the face space, several closely started trajectories, they kind of go into the same solution over time and that's, that's, that's this upper bound of this limit. And it is really showing that it has to be... It's an exponentially smaller number, but it depends on the N, dependence of the exponent right here, which combines information loss rate and the solution time performance. So these, if these exponent here or there, has a large independence, so even a linear independence, then you really have to start trajectories, exponentially closer to one another, in order to end up in the same order. So this is sort of like the, the direction that you are going into, and this formulation is applicable to, to all dynamical systems, deterministic dynamical systems. (clears throat) And I think we can expand this further because the, there is a way of getting the expression for the escape rates in terms of N the number of variables from cycle expansions, that I don't have time to talk about, but it's kind of like a program that you can try to pursue. And this is it. So uh, uh... The conclusions, I think are self-explanatory. I think there is a lot of future in, in analog continuous-time computing. They can be efficient by orders of magnitude than digital ones in solving NP-hard problems, because first of all, many of the systems lack of von Neumann bottleneck, there's parallelism involved and you can also have a larger spectrum of continuous-time dynamical algorithms than discrete ones. And, and, you know, but we also have to be mindful of what are the possibilities, what are the limits? And one, one open question, if any important open question is you know, "What are these limits? "Is there some kind of no-go theorem that tells you that, "you can never perform better than this limit "or, or that limit?" And I think that's, that's the exciting part to, to derive these, these limits and to get to an understanding about what's possible in this, in this area. Thank you.

>> from Austin, Texas. It's Theo Cube, covering pure storage. Accelerate 2019. Brought to you by pure storage. >> Welcome back to the Cube. Lisa Martin Day Volante is my co host were a pure accelerate 2019 in Austin, Texas. A couple of guests joining us. Next. Please welcome Barack elected director product management for slunk. Welcome back to the Cube. Thank you. And guess who's back. Von Stewart. V. P. A. Technology from pure Avon. Welcome back. >> Hey, thanks for having us guys really excited about this topic. >> We are too. All right, so But we'll start with you. Since you're so excited in your nice orange pocket square is peeking out of your jacket there. Talk about the Splunk, your relationship. Long relationship, new offerings, joint value. What's going on? >> Great set up. So Splunk impure have had a long relationship around accelerating customers analytics The speed at which they can get their questions answered the rate at which they could ingest data right to build just more sources. Look at more data, get faster time to take action. However, I shouldn't be leading this conversation because Split Split has released a new architecture, a significant evolution if you will from the traditional Splunk architectural was built off of Daz and a shared nothing architecture. Leveraging replicas, right? Very similar what you'd have with, like, say, in H D. F s Work it load or H c. I. For those who aren't in the analytic space, they've released the new architecture that's disaggregated based off of cashing and an object store construct called Smart Store, which Broth is the product manager for? >> All right, tell us about that. >> So we release a smart for the future as part of spunk Enterprise. $7 to about a near back back in September Timeframe. Really Genesis or Strong Smart Strong goes back to the key customer problem that we were looking to solve. So one of our customers, they're already ingesting a large volume of data, but the need to retain the data for twice, then one of Peter and in today's architecture, what it required was them to kind of lean nearly scale on the amount of hardware. What we realized it. Sooner or later, all customers are going to run into this issue. But if they want in just more data or reading the data for longer periods, of time, they're going to run into this cost ceiling sooner or later on. The challenge is that into this architecture, today's distributes killer dark picture that we have today, which of all, about 10 years back, with the evolution of the Duke in this particular architecture, the computer and story Jacqui located. And because computer storage acqua located, it allows us to process large volumes of data. But if you look at the demand today, we can see that the demand for storage or placing the demand for computer So these are, too to directly opposite trans that we're seeing in the market space. If you need to basically provide performance at scale, there needs to be a better model. They need a better solution than what we had right now. So that's the reason we basically brought Smart store on denounced availability last September. What's Marceau brings to the table is that a D couples computer and storage, So now you can scale storage independent of computers, so if you need more storage or if you need to read in for longer periods of time, you can just kill independent on the storage and with level age, remote object stores like Bill Flash bid to provide that data depository. But most of your active data said still decides locally on the indexers. So what we did was basically broke the paradigm off computer storage location, and we had a small twist. He said that now the computer stories can be the couple, but you bring comfort and stories closer together only on demand. So that means that when you were running a radio, you know, we're running a search, and whenever the data is being looked for that only when we bring the data together. The other key thing that we do is we have an active data set way ensure that the smart store has ah, very powerful cash manager that allows that ensures that the active data set is always very similar to the time when your laptop, the night when your laptop has active data sets always in the cash always on memory. So very similar to that smarts for cash allows you to have active data set always locally on the index. Start your search performance is not impact. >> Yes, this problem of scaling compute and storage independently. You mentioned H. D. F s you saw it early on there. The hyper converged guys have been trying to solve this problem. Um, some of the database guys like snowflakes have solved it in the cloud. But if I understand correctly, you're doing this on Prem. >> So we're doing this board an on Prem as well as in Cloud. So this smart so feature is already available on tramp were also already using a host all off our spun cloud deployments as well. It's available for customers who want obviously deploy spunk on AWS as well. >> Okay, where do you guys fit in? So we >> fit in with customers anywhere from on the hate say this way. But on the small side, at the hundreds of terabytes up into the tens and hundreds of petabytes side. And that's really just kind of shows the pervasiveness of Splunk both through mid market, all the way up through the through the enterprise, every industry and every vertical. So where we come in relative to smart store is we were a coat co developer, a launch partner. And because our object offering Flash Blade is a high performance object store, we are a little bit different than the rest of the Splunk s story partner ecosystem who have invested in slow more of an archive mode of s tree right, we have always been designed and kind of betting on the future would be based on high performance, large scale object. And so we believe smart store is is a ah, perfect example, if you will, of a modern analytics platform. When you look at the architecture with smart store as brush here with you, you want to suffice a majority of your queries out of cash because the performance difference between reading out a cash that let's say, that's NAND based or envy. Emmy based or obtain, if you will. When you fall, you have to go read a data data out of the Objects store, right. You could have a significant performance. Trade off wean mix significantly minimized that performance drop because you're going to a very high bandwith flash blade. We've done comparison test with other other smart store search results have been published in other vendors, white papers and we show Flash blade. When we run the same benchmark is 80 times faster and so what you can now have without architecture is confidence that should you find yourself in a compliance or regulatory issue, something like Maybe GDP are where you've got 72 hours to notify everyone who's been impacted by a breach. Maybe you've got a cybersecurity case where the average time to find that you've been penetrated occurs 206 days after the event. And now you gotta go dig through your old data illegal discovery, you know, questions around, you know, customer purchases, purchases or credit card payments. Any time where you've got to go back in the history, we're gonna deliver those results and order of magnitude faster than any other object store in the market today. That translates from ours. Today's days, two weeks, and we think that falls into our advantage. Almost two >> orders of magnitude. >> Can this be Flash Player >> at 80%? Sorry, Katie. Time 80 x. Yes, that's what I heard. >> Do you display? Consider what flashlight is doing here. An accelerant of spunk, workloads and customer environment. >> Definitely, because the forward with the smart, strong cash way allow high performance at scale for data that's recites locally in the cash. But now, by using a high performance object store like your flash played. Customers can expect the same high performing board when data is in the cash as well as invented sin. Remorseful >> sparks it. Interesting animal. Um, yeah, you have a point before we >> subjects. Well, I don't want to cut you off. It's OK. So I would say commenting on the performance is just part of the equation when you look at that, UM, common operational activities that a splitting, not a storage team. But a Splunk team has to incur right patch management, whether it's at the Splunk software, maybe the operating system, like linen store windows, that spunk is running on, or any of the other components on side on that platform. Patch Management data Re balancing cause it's unequal. Equally distributed, um, hardware refreshes expansion of the cluster. Maybe you need more computer storage. Those operations in terms of time, whether on smart store versus the classic model, are anywhere from 100 to 1000 times faster with smart store so you could have a deployment that, for example, it takes you two weeks to upgrade all the notes, and it gets done in four hours when it's on Smart store. That is material in terms of your operational costs. >> So I was gonna say, Splunk, we've been watching Splunk for a long time. There's our 10th year of doing the Cube, not our 10th anniversary of our 10th year. I think it will be our ninth year of doing dot com. And so we've seen Splunk emerged very cool company like like pure hip hip vibe to it. And back in the day, we talked about big data. Splunk never used that term, really not widely in its marketing. But then when we started to talk about who's gonna own the big data, that space was a cloud era was gonna be mad. We came back. We said, It's gonna be spunk and that's what's happened. Spunk has become a workload, a variety of workloads that has now permeated the organization, started with log files and security kind of kind of cumbersome. But now it's like everywhere. So I wonder if you could talk to the sort of explosion of Splunk in the workloads and what kind of opportunity this provides for you guys. >> So a very good question here, Right? So what we have seen is that spunk has become the de facto platform for all of one structure data as customers start to realize the value of putting their trying to Splunk on the watch. Your spunk is that this is like a huge differentiate of us. Monk is the read only skim on reed which allows you to basically put all of the data without any structure and ask questions on the flight that allows you to kind of do investigations in real time, be more reactive. What's being proactive? We be more proactive. Was being reactive scaleable platform the skills of large data volumes, highly available platform. All of that are the reason why you're seeing an increase that option. We see the same thing with all other customers as well. They start off with one data source with one use case and then very soon they realize the power of Splunk and they start to add additional use cases in just more and more data sources. >> But this no >> scheme on writer you call scheme on Reed has been so problematic for so many big data practitioners because it just became the state of swamp. >> That didn't >> happen with Splunk. Was that because you had very defined use cases obviously security being one or was it with their architectural considerations as well? >> They just architecture, consideration for security and 90 with the initial use cases, with the fact that the scheme on Reid basically gives open subject possibilities for you. Because there's no structure to the data, you can ask questions on the fly on. You can use that to investigate, to troubleshoot and allies and take remedial actions on what's happening. And now, with our new acquisitions, we have added additional capabilities where we can talk, orchestrate the whole Anto and flow with Phantom, right? So a lot of these acquisitions also helping unable the market. >> So we've been talking about TAM expansion all week. We definitely hit it with Charlie pretty hard. I have. You know, I think it's a really important topic. One of things we haven't hit on is tam expansion through partnerships and that flywheel effect. So how do you see the partners ship with Splunk Just in terms of supporting that tam expansion the next 10 years? >> So, uh, analytics, particularly log and Alex have really taken off for us in the last year. As we put more focus on it, we want to double down on our investments as we go through the end of this year and in the next year with with a focus on Splunk um, a zealous other alliances. We think we are in a unique position because the rollout of smart store right customers are always on a different scale in terms of when they want to adopt a new architecture right. It is a significant decision that they have to make. And so we believe between the combination of flash array for the hot tear and flash played for the cold is a nice way for customers with classic Splunk architecture to modernize their platform. Leverage the benefits of data reduction to drive down some of the cost leverage. The benefits of Flash to increase the rate at which they can ask questions and get answers is a nice stepping stone. And when customers are ready because Flash Blade is one of the few storage platforms in the market at this scale out band with optimized for both NFS and object, they can go through a rolling nondestructive upgrade to smart store, have you no investment protection, and if they can't repurpose that flash rate, they can use peers of service to have the flesh raise the hot today and drop it back off just when they're done within tomorrow. >> And what about C for, you know, big workloads, like like big data workloads. I mean, is that a good fit here? You really need to be more performance oriented. >> So flash Blade is is high bandwith optimization, which really is designed for workload. Like Splunk. Where when you have to do a sparse search, right, we'll find that needle in the haystack question, right? Were you breached? Where were you? Briefed. How were you breached? Go read as much data as possible. You've gotta in just all that data, back to the service as fast as you can. And with beast Cloud blocked, Teresi is really optimized it a tear to form of NAND for that secondary. Maybe transactional data base or virtual machines. >> All right, I want more, and then I'm gonna shut up sick. The signal FX acquisition was very interesting to me for a lot of reasons. One was the cloud. The SAS portion of Splunk was late to that game, but now you're sort of making that transition. You saw Tableau you saw Adobe like rip the band Aid Off and it was somewhat painful. But spunk is it. So I wonder. Any advice that you spend Splunk would have toe von as pure as they make that transition to that sass model. >> So I think definitely, I think it's going to be a challenging one, but I think it's a much needed one in there in the environment that we are in. The key thing is to always because two more focus and I'm sure that you're already our customer focus. But the key is key thing is to make sure that any service is up all the time on make sure that you can provide that up time, which is going to be crucial for beating your customers. Elise. >> That's good. That's good guidance. >> You >> just wanted to cover that for you favor of keeping you date. >> So you gave us some of those really impressive stats In terms of performance. >> They're almost too good to be true. >> Well, what's customer feedback? Let's talk about the real world when you're talking to customers about those numbers. What's the reaction? >> So I don't wanna speak for Broth, so I will say in our engagements within their customer base, while we here, particularly from customers of scale. So the larger the environment, the more aggressive they are to say they will adopt smart store right and on a more aggressive scale than the smaller environments. And it's because the benefits of operating and maintaining the indexer cluster are are so great that they'll actually turn to the stores team and say, This is the new architecture I want. This is a new storage platform and again. So when we're talking about patch management, cluster expansion Harbor Refresh. I mean, you're talking for a large sum. Large installs weeks, not two or 3 10 weeks, 12 weeks on end so it can be. You can reduce that down to a couple of days. It changes your your operational paradigm, your staffing. And so it has got high impact. >> So one of the message that we're hearing from customers is that it's far so they get a significant reduction in the infrastructure spent it almost dropped by 2/3. That's really significant file off our large customers for spending a ton of money on infrastructure, so just dropping that by 2/3 is a significant driver to kind of move too smart. Store this in addition to all the other benefits that get smart store with operational simplicity and the ability that it provides. You >> also have customers because of smart store. They can now actually bursts on demand. And so >> you can think of this and kind of two paradigms, right. Instead of >> having to try to avoid some of the operational pain, right, pre purchase and pre provisional large infrastructure and hope you fill it up. They could do it more of a right sides and kind of grow in increments on demand, whether it's storage or compute. That's something that's net new with smart store um, they can also, if they have ah, significant event occur. They can fire up additional indexer notes and search clusters that can either be bare metal v ems or containers. Right Try to, you know, push the flash, too. It's Max. Once they found the answers that they need gotten through. Whatever the urgent issues, they just deep provisionals assets on demand and return back down to a steady state. So it's very flexible, you know, kind of cloud native, agile platform >> on several guys. I wish we had more time. But thank you so much fun. And Deron, for joining David me on the Cube today and sharing all of the innovation that continues to come from this partnership. >> Great to see you appreciate it >> for Dave Volante. I'm Lisa Martin, and you're watching the Cube?

>> live from San Francisco, celebrating 10 years of high tech coverage. It's the Cube covering Veum World 2019. Brought to you by VM Wear and its ecosystem partners. >> Welcome back, everyone. Live cube coverage here in Mosconi, north of the Emerald 2019. I'm Javert David launch their 10th year covering the emerald. We here with this team Cube alumni Von Stuart, vice president technology at pier Storage. Great to see you guys another year, another privilege to sit >> down and have a little chat. >> Another. Another year that Vienna where doesn't die of something storage doesn't go away every year. Containers is going to kill the end where this is revealing. The EM wears resiliency as virtualization platform is just second to none has been, well, document. We've been talking about it because the operational efficiencies of what they've done has been great. You guys air kicking butt in storage on again, a sector that doesn't go away. You gotta put the data somewhere. Eso stores continues toe do Well, Congratulations. What's the big What's the big secret? Thanks. >> Well, we just shared our cue to >> financial results last week. 28% year on your growth. We are the by far the fastest growing storage company, and I think there's a lot of disruption for the legacy vendors. Right now. They're getting hit on all angles. Next. Gen. If vendors like us followed by the cloud as well this platforms like H. C, I think it's been it's been a tough sledding for similar legacy vendors. >> Talk about your relationship with the end, where and why that's been so important for pure because again, again, resiliency operations. At the end of the day, that's what the rubber hits the road, making developers happy, but operating it's a key. Yeah, if you look at >> so that's a really good question. If you look at our business, Veum, where is the number one platform deployed on top of pure storage platforms? And that's probably the case for most of the storage vendors because of their dominant position in the infrastructure. That means, as VM were evolves their product platforms right. Well, that's the pivotal acquisition Veum or Claude Foundation via McLaren AWS. And as that'll expand, you have to as a partner continued to jointly innovate, sometimes hand in hand. Sometimes, you know, on parallel paths to drive value into that that market for those customers or you're not gonna make it. And our investments of engineering wise are significant. We've had a large number of new capability that we've ruled out through the years that are specific to VM, where that are either integrations or enhancements to our platform. You know, we believe through external data points, we are the number one V balls vendor, which is, you know, which was something that being were launched about 78 years back. That kind of dip, but has risen back up. Um, and >> we were key, >> I think, um, design partner right now with the cloud platforms, the Via MacLeod Foundation as well as, ah, humor coordinative us. >> So, as you know, this is our 10th year VM world. You go back to 2010. There was what I used to call the storage cartel. And you weren't part of it, right? Had early access to the AP eyes you had. So obviously e m c was in there. Um, you were really the on lee sort of newbie to reach escape velocity. Your storage. Now there's basically two independent storage companies over a billion dollars. You guys a net up. Um, so >> when I was at both, >> you saw you saw >> the opportunity and okay, leaned in hard. Yeah, there >> was a time when he's >> paid off. But so why do you think, um, you were able to be one of the rare ones to achieve escape velocity when many people said that will never happen. You'll never see another $1,000,000,000 storage company. And then I'm interested in how you're achieving number one in Viv balls. In a world where it seems like, you know, the ecosystem is getting a little tighter between Dow Wand VM where? But how do you guys thrive in that dynamic? >> I think there's a challenge for all vendors in terms of market and try to get your message through right. If you if you one better does something well, the rest of the market tries too obvious. Get that. We've been fortunate enough that through our channel ecosystem, our system's integrator partners right to actually be able to demonstrate the technology that gain there enthusiasm to drive it into the market and then actually demonstrated to the customers. And so how does that show up? Uh, I think it's fair to say our platforms are more intelligent, they're more automated and they they operated a greater scale. Then then the competitors and you can look at this through one lens and say, Well, it's Veum or a P I says in that Make all the storage the same And it's like it does from a via more operational standpoint, but it doesn't mean how you deliver on that value Prop or what us. A platform deliver above and beyond is at parody, and that's really where we demonstrate a significant difference. Let me give you one example. We have a lot of customers. Ah, a lot customer growth in the last 12 months around Custer's who are deploying eight c i, along with all flash raise. Right? And David Floyd had reached out recently and said, Well, wouldn't one, you know, compete with the other? It's like, Yes, there's overlap. But what we're finding from customers is they're looking to say if my applications need to be more cost effective, easy to manage its scale, we actually want to put it on all flash rain, You say, How could that be? I'll give you one simply example. Do you know what it takes anywhere from 10 x 200 x, less time to upgrade your V and where infrastructure on a shared array. Then if it's on on hyper converged because you don't have to go through the evacuation and rehydration of all your data twice right? And so things like that, they're just really simple that you wouldn't pick up in like a marketing scheme. If you are a customer at scale, you go well. I can't afford 100 man hours. I can afford woman. And so it's It's simple things like that. It's rapid provisioning. It's not having Silas that are optimized for performance or availability or cost. It's about saying, you know your time to implement is one time life cycle on hardware. But it's probably something happens every quarter for the next three years, right? >> So this is your point about >> innovation in the innovative vendors. Your the modernization of storage is planning for these use cases where the old way didn't work. >> Yeah, yeah, you mentioned that you were 10 years now, and one of things that I've said over the last six or seven years being up yours, one of things I think is really interesting about pure is that our founder, John Call Grove, came out of the volume manager and file system space at Veritas, right? He was the founder for those products. He understood the intersection between managing a storage array and your application, and that goes through our ethos of our products, where I think a lot of storage platforms, a start up platforms come from George guys who worked on the Harbour side. And so they take a faster, you know, Piper faster from the media, and they make another box that behaves like the other box from an operational perspective. >> So he said, a C I a compliment or competitors. I'm still not sure which. Maybe it's both and then say, Same question for V. San. Yeah, how do you So, >> um, on air that we've put a lot of investment in and started one with via more around the middle of last year was putting V sand with pure storage flash race together, and what you see that materialized now is when you look at via MacLeod Foundation or via MacLeod in eight of us. The management domains must be visa, and that's so that you can have an instant out of the box controlled, um, management plane that Veum where you know, executes on and then you have workload domains and those could be on ah, hyper converge platform. Or they could be on third party storage. And when you put those on pure, then you again, all the advantages that we bring to bear as an infrastructure with all the same simplicity scale in lifecycle management that you get from from just, you know, the VM where std see manager. And so it works very well together. Now, look, I'm sure what I share with you here. They'll be some folks who are on the V sand team that they themselves are to be like, you know, B s. But that's the nature of our business. One >> of these I want to get your thoughts on this side. Vons. You've always >> been kind of on the cutting edge on all the conversations we've had. I gotta ask you about the container revolution, which not new doctor came out many many years ago. Jerry Chen when he funded those guys and we covered that extensively upset there was a small changed kubernetes is all the rage orchestrating the containers is a pivotal role in all the action happening here. It's big part of how things were with the app side. So the question is, how does continues impact the storage world? How do you see that being integrated in? There's talk of putting Cooper names on bare metal, so you start to see HC. I come back. Devices are important, she started. See hardware become important again with that? >> Well, I love you. Drop of pivotal there, right? First off, kudos to Vienna, where for the acquisition pill, little guys are exceptional. What they don't have is a lot of customers, but the customers they do have our large customers, right? So we've got a fair amount of pivotal on pure customers, and they are all at scale. So I think it's a great acquisition for VM, where by by far the most enterprise class form of containers today, >> and they've always kind of been the fold. Now they're officially in the fold. Yes, formalize it. >> And so now that the road map that was shared in terms of what via Moore looks to do to integrate containers into the Essex I platform itself right, it's managing V, EMS and containers next year. That's perfect in terms of not having customers have to pick or choose between which platform and where you're going to play something, allow them to say you can deploy on whichever format you want. It runs in the same ecosystem and management, and then that trickles down to the gun in your storage layer. So we do a lot of object storage within the container ecosystems. Today, a lot of high performance objects because you know the file sizes of instances or applications is much larger than you know, a document filed that you or I might create online. So there's a big need around performance in that space, along with again management at scale. It's >> interesting we sent about about Pivotal and I, By the way, I like the acquisition, too, because I think it was cheap. Any time you can pick up $4 billion asset for 800 million in cash, you know gets my attention. But Pivotal was struggling in the marketplace. The stock price never even came close to its I po. You know, it's spending patterns were down. Do you feel as though the integration will VM Where will supercharge Pivotal? >> I absolutely agree that I've had this view that the container ecosystem was really, um uh, segmented you had comes that built their products off a container. So save your twitter or your Facebook, right? The platform that your customers and interact interact with is all ran by containers. Then you have an enterprise. You have containers, which was more kind of classic applications. Right? And that would take time for the applications to be deployed. And so what did you see now for Mike stuff, right? See if you can run as a container. Right? Run is a container. As the enterprise app start to roll over, the enterprise will start to evolve from virtual machines, two containers. And so I think it's the timing's right. That's not to dismiss any of where people I think is built the brand right now, which is helping companies build next gen platforms. You know, after big sure that I don't name drop customers references to pull back there. Yeah, I think the time is right. >> I'm interested in how you guys can further capitalized on containers. And we've been playing around with this notion of of data assurance containers, Fring complexity. And so, you know, complexities oftentimes your friend, because you're all about simplifying complexity. But so how do you capitalize on this container trend in the next 3 to 5 years? So you've got storage >> needs for containers that either tend to be ephemeral or persistent. And I think when containers were virtually created, it was always this notion that would be ephemeral. And it's like, Yeah, but where's the data reside? Ultimately, there's been significant growth around data persistence, and we've driven that in terms of leveraging the flecks of all drivers that have been put into the community, driving that into our pure service orchestrator RPS O'Toole, which supports pivotal in kubernetes derivatives. Today again, we've got proven large scale installs on this. So it's it's, um, it's providing the same class of storage. Service is simplicity and elegance in your integrations that we have for Vienna, where we've been doing that across pivotal already. Pivotals. Interesting, right? They don't validate hardware, the only validate software. So they validate our P S O and having that same value prop for that that infrastructure, because they are scale, you never find a small scale containers ecosystem, and I keep referencing that point when you get to scale considerations around. What does it take to allow that environment to to remain online and holly performance are significant considerations and weak cell >> There. We'll talk about your event coming up. You guys have pierced accelerate September 17th and 18th Coming up Osti the VM where ecosystem that you're part of here. Big part of that. You guys have a lot of customers. I know you can reveal any news, but what's expected at this show? What can people who are interested in either attending or my peach in some of the notable things that might be happening >> lot orange? We know that >> one. Number two I know the cubes gonna be there >> for two days will be there for two days. >> So hopefully you guys will get a load of conversations with both our our team, product management, engineering, maybe some of leadership, but also customers. I think customers are always the best statement you can make about how your how you're doing and market. I think you will see from us a number of announcements that I am prohibited to share today, but some really big things that we're gonna introduce the market. So it should be excited for that. And some just a great showing of our partner. Our alliance ecosystem will be there. Obviously, VM will be there in force as well as red hat with the open >> again, there's gonna be a cloudy >> future for you. It's girls would be very analytical. It's going to be there elastics going to be there. So, you know, >> you guys like to do first of these shows. I mean, kind of I don't view it first with an all flesh array, but probably one of the first if not first the evergreen thing ticked off a lot of people like, Why didn't we think of that? You were first with sort of bundling envy. Any in the whole thing. The announcement you guys made with video. That was before anybody else. You know, your whole cloud play you like, you like to be first, So we expect another first next month. Hopefully we >> will deliver, and, uh, you're not gonna get me to leak anything. >> Thanks for the insight, Vice President. Reality Lions, that pier storage. David, let me stay with us for more coverage. Robin Madlock. CMO is coming on and, of course, tomorrow. Michael Dell, Pat Girl singer and more and more great guest senior vice presidents from VM wear from all different groups. We'll be asking the tough questions here in the Cube. Thanks for watching.

Section 1 of 13 [00:00:00 - 00:10:04] (NOTE: speaker names may be different in each section) Speaker 1: Ladies and gentlemen our program will begin momentarily. Thank you. (singing) This presentation and the accompanying oral commentary may include forward looking statements that are subject to risks uncertainties and other factors beyond our control. Our actual results, performance or achievements may differ materially and adversely from those anticipated or implied by such statements because of various risk factors. Including those detailed in our annual report on form 10-K for the fiscal year ended July 31, 2017 filed with the SEC. Any future product or roadmap information presented is intended to outline general product direction and is not a commitment to deliver any functionality and should not be used when making any purchasing decision. (singing) Ladies and gentlemen please welcome Vice President Corporate Marketing Nutanix, Julie O'Brien. Julie O'Brien: All right. How about those Nutanix .NEXT dancers, were they amazing or what? Did you see how I blended right in, you didn't even notice I was there. [French 00:07:23] to .NEXT 2017 Europe. We're so glad that you could make it today. We have such a great agenda for you. First off do not miss tomorrow morning. We're going to share the outtakes video of the handclap video you just saw. Where are the customers, the partners, the Nutanix employee who starred in our handclap video? Please stand up take a bow. You are not going to want to miss tomorrow morning, let me tell you. That is going to be truly entertaining just like the next two days we have in store for you. A content rich highly interactive, number of sessions throughout our agenda. Wow! Look around, it is amazing to see how many cloud builders we have with us today. Side by side you're either more than 2,200 people who have traveled from all corners of the globe to be here. That's double the attendance from last year at our first .NEXT Conference in Europe. Now perhaps some of you are here to learn the basics of hyperconverged infrastructure. Others of you might be here to build your enterprise cloud strategy. And maybe some of you are here to just network with the best and brightest in the industry, in this beautiful French Riviera setting. Well wherever you are in your journey, you'll find customers just like you throughout all our sessions here with the next two days. From Sligro to Schroders to Societe Generale. You'll hear from cloud builders sharing their best practices and their lessons learned and how they're going all in with Nutanix, for all of their workloads and applications. Whether it's SAP or Splunk, Microsoft Exchange, unified communications, Cloud Foundry or Oracle. You'll also hear how customers just like you are saving millions of Euros by moving from legacy hypervisors to Nutanix AHV. And you'll have a chance to post some of your most challenging technical questions to the Nutanix experts that we have on hand. Our Nutanix technology champions, our MPXs, our MPSs. Where are all the people out there with an N in front of their certification and an X an R an S an E or a C at the end. Can you wave hello? You might be surprised to know that in Europe and the Middle East alone, we have more than 2,600 >> Julie: In Europe and the Middle East alone, we have more than 2,600 certified Nutanix experts. Those are customers, partners, and also employees. I'd also like to say thank you to our growing ecosystem of partners and sponsors who are here with us over the next two days. The companies that you meet here are the ones who are committed to driving innovation in the enterprise cloud. Over the next few days you can look forward to hearing from them and seeing some fantastic technology integration that you can take home to your data center come Monday morning. Together, with our partners, and you our customers, Nutanix has had such an exciting year since we were gathered this time last year. We were named a leader in the Gartner Magic Quadrant for integrated systems two years in a row. Just recently Gartner named us the revenue market share leader in their recent market analysis report on hyper-converged systems. We know enjoy more than 35% revenue share. Thanks to you, our customers, we received a net promoter score of more than 90 points. Not one, not two, not three, but four years in a row. A feat, I'm sure you'll agree, is not so easy to accomplish, so thank you for your trust and your partnership in us. We went public on NASDAQ last September. We've grown to more than 2,800 employees, more than 7,000 customers and 125 countries and in Europe and the Middle East alone, in our Q4 results, we added more than 250 customers just in [Amea 00:11:38] alone. That's about a third of all of our new customer additions. Today, we're at a pivotal point in our journey. We're just barely scratching the surface of something big and Goldman Sachs thinks so too. What you'll hear from us over the next two days is this: Nutanix is on it's way to building and becoming an iconic enterprise software company. By helping you transform your data center and your business with Enterprise Cloud Software that gives you the power of freedom of choice and flexibility in the hardware, the hypervisor and the cloud. The power of one click, one OS, any cloud. And now, to tell you more about the digital transformation that's possible in your business and your industry and share a little bit around the disruption that Nutanix has undergone and how we've continued to reinvent ourselves and maybe, if we're lucky, share a few hand clap dance moves, please welcome to stage Nutanix Founder, CEO and Chairman, Dheeraj Pandey. Ready? Alright, take it away [inaudible 00:13:06]. >> Dheeraj P: Thank you. Thank you, Julie and thank you every one. It looks like people are still trickling. Welcome to Acropolis. I just hope that we can move your applications to Acropolis faster than we've been able to move people into this room, actually. (laughs) But thank you, ladies and gentlemen. Thank you to our customers, to our partners, to our employees, to our sponsors, to our board members, to our performers, to everybody for their precious time. 'Cause that's the most precious thing you actually have, is time. I want to spend a little bit of time today, not a whole lot of time, but a little bit of time talking about the why of Nutanix. Like why do we exist? Why have we survived? Why will we continue to survive and thrive? And it's simpler than an NQ or category name, the word hyper-convergence, I think we are all complicated. Just thinking about what is it that we need to talk about today that really makes it relevant, that makes you take back something from this conference. That Nutanix is an obvious innovation, it's very obvious what we do is not very complicated. Because the more things change, the more they remain the same, so can we draw some parallels from life, from what's going on around us in our own personal lives that makes this whole thing very natural as opposed to "Oh, it's hyper-converged, it's a category, it's analysts and pundits and media." I actually think it's something new. It's not that different, so I want to start with some of that today. And if you look at our personal lives, everything that we had, has been digitized. If anything, a lot of these gadgets became apps, they got digitized into a phone itself, you know. What's Nutanix? What have we done in the last seven, eight years, is we digitized a lot of hardware. We made everything that used to be single purpose hardware look like pure software. We digitized storage, we digitized the systems manager role, an operations manager role. We are digitizing scriptures, people don't need to write scripts anymore when they automate because we can visually design automation with [com 00:15:36]. And we're also trying to make a case that the cloud itself is not just a physical destination. That it can be digitized and must be digitized as well. So we learn that from our personal lives too, but it goes on. Look at music. Used to be tons of things, if you used to go to [inaudible 00:15:55] Records, I'm sure there were European versions of [inaudible 00:15:57] Records as well, the physical things around us that then got digitized as well. And it goes on and on. We look at entertainment, it's very similar. The idea that if you go to a movie hall, the idea that you buy these tickets, the idea that we'd have these DVD players and DVDs, they all got digitized. Or as [inaudible 00:16:20] want to call it, virtualized, actually. That is basically happening in pretty much new things that we never thought would look this different. One of the most exciting things happening around us is the car industry. It's getting digitized faster than we know. And in many ways that we'd not even imagined 10 years ago. The driver will get digitized. Autonomous cars. The engine is definitely gone, it's a different kind of an engine. In fact, we'll re-skill a lot of automotive engineers who actually used to work in mechanical things to look at real chemical things like battery technologies and so on. A lot of those things that used to be physical are now in software in the car itself. Media itself got digitized. Think about a physical newspaper, or physical ads in newspapers. Now we talk about virtual ads, the digital ads, they're all over on websites and so on is our digital experience now. Education is no different, you know, we look back at the kind of things we used to do physically with physical things. Their now all digital. The experience has become that digital. And I can go on and on. You look at retail, you look at healthcare, look at a lot of these industries, they all are at the cusp of a digital disruption. And in fact, if you look at the data, everybody wants it. We all want a digital transformation for industries, for companies around us. In fact, the whole idea of a cloud is a highly digitized data center, basically. It's not just about digitizing servers and storage and networks and security, it's about virtualizing, digitizing the entire data center itself. That's what cloud is all about. So we all know that it's a very natural phenomenon, because it's happening around us and that's the obviousness of Nutanix, actually. Why is it actually a good thing? Because obviously it makes anything that we digitize and we work in the digital world, bring 10X more productivity and decision making efficiencies as well. And there are challenges, obviously there are challenges, but before I talk about the challenges of digitization, think about why are things moving this fast? Why are things becoming digitally disrupted quicker than we ever imagined? There are some reasons for it. One of the big reasons is obviously we all know about Moore's Law. The fact that a lot of hardware's been commoditized, and we have really miniaturized hardware. Nutanix today runs on a palm-sized server. Obviously it runs on the other end of the spectrum with high-end IBM power systems, but it also runs on palm-sized servers. Moore's Law has made a tremendous difference in the way we actually think about consuming software itself. Of course, the internet is also a big part of this. The fact that there's a bandwidth glut, there's Trans-Pacific cables and Trans-Atlantic cables and so on, has really connected us a lot faster than we ever imagined, actually, and a lot of this was also the telecom revolution of the '90s where we really produced a ton of glut for the internet itself. There's obviously a more subtle reason as well, because software development is democratizing. There's consumer-grade programming languages that we never imagined 10, 15, 20 years ago, that's making it so much faster to write- >> Speaker 1: 15-20 years ago that's making it so much faster to write code, with this crowdsourcing that never existed before with Githubs and things like that, open source. There's a lot more stuff that's happening that's outside the boundary of a corporation itself, which is making things so much faster in terms of going getting disrupted and writing things at 10x the speed it used to be 20 years ago. There is obviously this technology at the tip of our fingers, and we all want it in our mobile experience while we're driving, while we're in a coffee shop, and so on; and there's a tremendous focus on design on consumer-grade simplicity, that's making digital disruption that much more compressed in some of sense of this whole cycle of creative disruption that we talk about, is compressed because of mobility, because of design, because of API, the fact that machines are talking to machines, developers are talking to developers. We are going and miniaturizing the experience of organizations because we talk about micro-services and small two-pizza teams, and they all want to talk about each other using APIs and so on. Massive influence on this digital disruption itself. Of course, one of the reasons why this is also happening is because we want it faster, we want to consume it faster than ever before. And our attention spans are reducing. I like the fact that not many people are watching their cell phones right now, but you can imagine the multi-tasking mode that we are all in today in our lives, makes us want to consume things at a faster pace, which is one of the big drivers of digital disruption. But most importantly, and this is a very dear slide to me, a lot of this is happening because of infrastructure. And I can't overemphasize the importance of infrastructure. If you look at why did Google succeed, it was the ninth search engine, after eight of them before, and if you take a step back at why Facebook succeeded over MySpace and so on, a big reason was infrastructure. They believed in scale, they believed in low latency, they believed in being able to crunch information, at 10x, 100x, bigger scale than anyone else before. Even in our geopolitical lives, look at why is China succeeding? Because they've made infrastructure seamless. They've basically said look, governance is about making infrastructure seamless and invisible, and then let the businesses flourish. So for all you CIOs out there who actually believe in governance, you have to think about what's my first role? What's my primary responsibility? It's to provide such a seamless infrastructure, that lines of business can flourish with their applications, with their developers that can write code 10x faster than ever before. And a lot of these tenets of infrastructure, the fact of the matter is you need to have this always-on philosophy. The fact that it's breach-safe culture. Or the fact that operating systems are hardware agnostic. A lot of these tenets basically embody what Nutanix really stands for. And that's the core of what we really have achieved in the last eight years and want to achieve in the coming five to ten years as well. There's a nuance, and obviously we talk about digital, we talk about cloud, we talk about everything actually going to the cloud and so on. What are the things that could slow us down? What are the things that challenge us today? Which is the reason for Nutanix? Again, I go back to this very important point that the reason why we think enterprise cloud is a nuanced term, because the word "cloud" itself doesn't solve for a lot of the problems. The public cloud itself doesn't solve for a lot of the problems. One of the big ones, and obviously we face it here in Europe as well, is laws of the land. We have bureaucracy, which we need to deal with and respect; we have data sovereignty and computing sovereignty needs that we need to actually fulfill as well, while we think about going at breakneck speed in terms of disrupting our competitors and so on. So there's laws of the land, there's laws of physics. This is probably one of the big ones for what the architecture of cloud will look like itself, over the coming five to ten years. Our take is that cloud will need to be more dispersed than they have ever imagined, because computing has to be local to business operations. Computing has to be in hospitals and factories and shop floors and power plants and on and on and on... That's where you really can have operations and computing really co-exist together, cause speed is important there as well. Data locality is one of our favorite things; the fact that computing and data have to be local, at least the most relevant data has to be local as well. And the fact that electrons travel way faster when it's actually local, versus when you have to have them go over a Wide Area Network itself; it's one of the big reasons why we think that the cloud will actually be more nuanced than just some large data centers. You need to disperse them, you need to actually think about software (cloud is about software). Whether data plane itself could be dispersed and even miniaturized in small factories and shop floors and hospitals. But the control plane of the cloud is centralized. And that's the way you can have the best of both worlds; the control plane is centralized. You think as if you're managing one massive data center, but it's not because you're really managing hundreds or thousands of these sites. Especially if you think about edge-based computing and IoT where you really have your tentacles in tens of thousands of smaller devices and so on. We've talked about laws of the land, which is going to really make this digital transformation nuanced; laws of physics; and the third one, which is really laws of entropy. These are hackers that do this for adrenaline. These are parochial rogue states. These are parochial geo-politicians, you know, good thing I actually left the torture sign there, because apparently for our creative designer, geo-politics is equal to torture as well. So imagine one bad tweet can actually result in big changes to the way we actually live in this world today. And it's important. Geo-politics itself is digitized to a point where you don't need a ton of media people to go and talk about your principles and what you stand for and what you strategy for, for running a country itself is, and so on. And these are all human reasons, political reasons, bureaucratic reasons, compliance and regulations reasons, that, and of course, laws of physics is yet another one. So laws of physics, laws of the land, and laws of entropy really make us take a step back and say, "What does cloud really mean, then?" Cause obviously we want to digitize everything, and it all should appear like it's invisible, but then you have to nuance it for the Global 5000, the Global 10000. There's lots of companies out there that need to really think about GDPR and Brexit and a lot of the things that you all deal with on an everyday basis, actually. And that's what Nutanix is all about. Balancing what we think is all about technology and balancing that with things that are more real and practical. To deal with, grapple with these laws of the land and laws of physics and laws of entropy. And that's where we believe we need to go and balance the private and the public. That's the architecture, that's the why of Nutanix. To be able to really think about frictionless control. You want things to be frictionless, but you also realize that you are a responsible citizen of this continent, of your countries, and you need to actually do governance of things around you, which is computing governance, and data governance, and so on. So this idea of melding the public and the private is really about melding control and frictionless together. I know these are paradoxical things to talk about like how do you really have frictionless control, but that's the life you all lead, and as leaders we have to think about this series of paradoxes itself. And that's what Nutanix strategy, the roadmap, the definition of enterprise cloud is really thinking about frictionless control. And in fact, if anything, it's one of the things is also very interesting; think about what's disrupting Nutanix as a company? We will be getting disrupted along the way as well. It's this idea of true invisibility, the public cloud itself. I'd like to actually bring on board somebody who I have a ton of respect for, this leader of a massive company; which itself is undergoing disruption. Which is helping a lot of its customers undergo disruption as well, and which is thinking about how the life of a business analyst is getting digitized. And what about the laws of the land, the laws of physics, and laws of entropy, and so on. And we're learning a lot from this partner, massively giant company, called IBM. So without further ado, Bob Picciano. >> Bob Picciano: Thanks, >> Speaker 1: Thank you so much, Bob, for being here. I really appreciate your presence here- >> Bob Picciano: My pleasure! >> Speaker 1: And for those of you who actually don't know Bob, Bob is a Senior VP and General Manager at IBM, and is all things cognitive and obviously- >> Speaker 1: IBM is all things cognitive. Obviously, I learn a lot from a lot of leaders that have spent decades really looking at digital disruption. >> Bob: Did you just call me old? >> Speaker 1: No. (laughing) I want to talk about experience and talking about the meaning of history, because I love history, actually, you know, and I don't want to make you look old actually, you're too young right now. When you talk about digital disruption, we look at ourselves and say, "Look we are not extremely invisible, we are invisible, but we have not made something as invisible as the public clouds itself." And hence as I. But what's digital disruption mean for IBM itself? Now, obviously a lot of hardware is being digitized into software and cloud services. >> Bob: Yep. >> Speaker 1: What does it mean for IBM itself? >> Bob: Yeah, if you allow me to take a step back for a moment, I think there is some good foundational understanding that'll come from a particular point of view. And, you talked about it with the number of these dimensions that are affecting the way businesses need to consider their competitiveness. How they offer their capabilities into the market place. And as you reflected upon IBM, you know, we've had decades of involvement in information technology. And there's a big disruption going on in the information technology space. But it's what I call an accretive disruption. It's a disruption that can add value. If you were to take a step back and look at that digital trajectory at IBM you'd see our involvement with information technology in a space where it was all oriented around adding value and capability to how organizations managed inscale processes. Thinking about the way they were going to represent their businesses in a digital form. We came to call them applications. But it was how do you open an account, how do you process a claim, how do you transfer money, how do you hire an employee? All the policies of a company, the way the people used to do it mechanically, became digital representations. And that foundation of the digital business process is something that IBM helped define. We invented the role of the CIO to help really sponsor and enter in this notion that businesses could re represent themselves in a digital way and that allowed them to scale predictably with the qualities of their brand, from local operations, to regional operations, to international operations, and show up the same way. And, that added a lot of value to business for many decades. And we thrived. Many companies, SAP all thrived during that span. But now we're in a new space where the value of information technology is hitting a new inflection point. Which is not about how you scale process, but how you scale insight, and how you scale wisdom, and how you scale knowledge and learning from those operational systems and the data that's in those operational systems. >> Speaker 1: How's it different from 1993? We're talking about disruption. There was a time when IBM reinvented itself, 20-25 years ago. >> Bob: Right. >> Speaker 1: And you said it's bigger than 25 years ago. Tell us more. >> Bob: You know, it gets down. Everything we know about that process space right down to the very foundation, the very architecture of the CPU itself and the computer architecture, the von Neumann architecture, was all optimized on those relatively static scaled business processes. When you move into the notion where you're going to scale insight, scale knowledge, you enter the era that we call the cognitive era, or the era of intelligence. The algorithms are very different. You know the data semantically doesn't integrate well across those traditional process based pools and reformation. So, new capabilities like deep learning, machine learning, the whole field of artificial intelligence, allows us to reach into that data. Much of it unstructured, much of it dark, because it hasn't been indexed and brought into the space where it is directly affecting decision making processes in a business. And you have to be able to apply that capability to those business processes. You have to rethink the computer, the circuitry itself. You have to think about how the infrastructure is designed and organized, the network that is required to do that, the experience of the applications as you talked about have to be very natural, very engaging. So IBM does all of those things. So as a function of our transformation that we're on now, is that we've had to reach back, all the way back from rethinking the CPU, and what we dedicate our time and attention to. To our services organization, which is over 130,000 people on the consulting side helping organizations add digital intelligence to this notion of a digital business. Because, the two things are really a confluence of what will make this vision successful. >> Speaker 1: It looks like massive amounts of change for half a million people who work with the company. >> Bob: That's right. >> Speaker 1: I'm sure there are a lot of large customers out here, who will also read into this and say, "If IBM feels disrupted ... >> Bob: Uh hm >> Speaker 1: How can we actually stay not vulnerable? Actually there is massive amounts of change around their own competitive landscape as well. >> Bob: Look, I think every company should feel vulnerable right. If you're at this age, this cognitive era, the age of digital intelligence, and you're not making a move into being able to exploit the capabilities of cognition into the business process. You are vulnerable. If you're at that intersection, and your competitor is passing through it, and you're not taking action to be able to deploy cognitive infrastructure in conjunction with the business processes. You're going to have a hard time keeping up, because it's about using the machines to do the training to augment the intelligence of our employees of our professionals. Whether that's a lawyer, or a doctor, an educator or whether that's somebody in a business function, who's trying to make a critical business decision about risk or about opportunity. >> Speaker 1: Interesting, very interesting. You used the word cognitive infrastructure. >> Bob: Uh hm >> Speaker 1: There's obviously computer infrastructure, data infrastructure, storage infrastructure, network infrastructure, security infrastructure, and the core of cognition has to be infrastructure as well. >> Bob: Right >> Speaker 1: Which is one of the two things that the two companies are working together on. Tell us more about the collaboration that we are actually doing. >> Bob: We are so excited about our opportunity to add value in this space, so we do think very differently about the cognitive infrastructure that's required for this next generation of computing. You know I mentioned the original CPU was built for very deterministic, very finite operations; large precision floating point capabilities to be able to accurately calculate the exact balance, the exact amount of transfer. When you're working in the field of AI in cognition. You actually want variable precision. Right. The data is very sparse, as opposed to the way that deterministic or scorecastic operations work, which is very dense or very structured. So the algorithms are redefining the processes that the circuitry actually has to run. About five years ago, we dedicated a huge effort to rethink everything about the chip and what we made to facilitate an orchestra of participation to solve that problem. We all know the GPU has a great benefit for deep learning. But the GPU in many cases, in many architectures, specifically intel architectures, it's dramatically confined by a very small amount of IO bandwidth that intel allows to go on and off the chip. At IBM, we looked at all 686 roughly square millimeters of our chip and said how do we reuse that square area to open up that IO bandwidth? So the innovation of a GPU or a FPGA could really be utilized to it's maximum extent. And we could be an orchestrator of all of the diverse compute that's going to be necessary for AI to really compel these new capabilities. >> Speaker 1: It's interesting that you mentioned the fact that you know power chips have been redefined for the cognitive era. >> Bob: Right, for Lennox for the cognitive era. >> Speaker 1: Exactly, and now the question is how do you make it simple to use as well? How do you bring simplicity which is where ... >> Bob: That's why we're so thrilled with our partnership. Because you talked about the why of Nutanix. And it really is about that empowerment. Doing what's natural. You talked about the benefits of calm and being able to really create that liberation of an information technology professional, whether it's in operations or in development. Having the freedom of action to make good decisions about defining the infrastructure and deploying that infrastructure and not having to second guess the physical limitations of what they're going to have to be dealing with. >> Speaker 1: That's why I feel really excited about the fact that you have the power of software, to really meld the two forms together. The intel form and the power form comes together. And we have some interesting use cases that our CIO Randy Phiffer is also really exploring, is how can a power form serve as a storage form for our intel form. >> Bob: Sure. >> Speaker 1: It can serve files and mocks and things like that. >> Bob: Any data intensive application where we have seen massive growth in our Lennox business, now for our business, Lennox is 20% of the revenue of our power systems. You know, we started enabling native Lennox distributions on top of little Indian ones, on top of the power capabilities just a few years ago, and it's rocketed. And the reason for that if for any data intensive application like a data base, a no sequel database or a structured data base, a dupe in the unstructured space, they typically run about three to four times better price performance on top of Lennox on power, than they will on top of an intel alternative. >> Speaker 1: Fascinating. >> Bob: So all of these applications that we're talking about either create or consume a lot of data, have to manage a lot of flexibility in that space, and power is a tremendous architecture for that. And you mentioned also the cohabitation, if you will, between intel and power. What we want is that optionality, for you to utilize those benefits of the 3X better price performance where they apply and utilize the commodity base where it applies. So you get the cost benefits in that space and the depth and capability in the space for power. >> Speaker 1: Your tongue in cheek remark about commodity intel is not lost on people actually. But tell us about... >> Speaker 1: Intel is not lost on people actually. Tell us about ... Obviously we digitized Linux 10, 15 years ago with [inaudible 00:40:07]. Have you tried to talk about digitizing AIX? That is the core of IBM's business for the last 20, 25, 30 years. >> Bob: Again, it's about this ability to compliment and extend the investments that businesses have made during their previous generations of decision making. This industry loves to talk about shifts. We talked about this earlier. That was old, this is new. That was hard, this is easy. It's not about shift, it's about using the inflection point, the new capability to extend what you already have to make it better. And that's one thing that I must compliment you, and the entire Nutanix organization. It's really empowering those applications as a catalog to be deployed, managed, and integrated in a new way, and to have seamless interoperability into the cloud. We see the AIX workload just having that same benefit for those businesses. And there are many, many 10's of thousands around the world that are critically dependent on every element of their daily operations and productivity of that operating platform. But to introduce that into that network effect as well. >> Speaker 1: Yeah. I think we're looking forward to how we bring the same cloud experience on AIX as well because as a company it keeps us honest when we don't scoff at legacy. We look at these applications the last 10, 15, 20 years and say, "Can we bring them into the new world as well?" >> Bob: Right. >> Speaker 1: That's what design is all about. >> Bob: Right. >> Speaker 1: That's what Apple did with musics. We'll take an old world thing and make it really new world. >> Bob: Right. >> Speaker 1: The way we consume things. >> Bob: That governance. The capability to help protect against the bad actors, the nefarious entropy players, as you will. That's what it's all about. That's really what it takes to do this for the enterprise. It's okay, and possibly easier to do it in smaller islands of containment, but when you think about bringing these class of capabilities into an enterprise, and really helping an organization drive both the flexibility and empowerment benefits of that, but really be able to depend upon it for international operations. You need that level of support. You need that level of capability. >> Speaker 1: Awesome. Thank you so much Bob. Really appreciate you coming. [crosstalk 00:42:14] Look forward to your [crosstalk 00:42:14]. >> Bob: Cheers. Thank you. >> Speaker 1: Thanks again for all of you. I know that people are sitting all the way up there as well, which is remarkable. I hope you can actually see some of the things that Sunil and the team will actually bring about, talk about live demos. We do real stuff here, which is truly live. I think one of the requests that I have is help us help you navigate the digital disruption that's upon you and your competitive landscape that's around you that's really creating that disruption. Thank you again for being here, and welcome again to Acropolis. >> Speaker 3: Ladies and gentlemen, please welcome Chief Product and Development Officer, Nutanix Sunil Potti. >> Sunil Potti: Okay, so I'm going to just jump right in because I know a bunch of you guys are here to see the product as well. We are a lot of demos lined up for you guys, and we'll try to mix in the slides, and the demos as well. Here's just an example of the things I always bring up in these conferences to look around, and say in the last few months, are we making progress in simplifying infrastructure? You guys have heard this again and again, this has been our mantra from the beginning, that the hotter things get, the more differentiated a company like Nutanix can be if we can make things simple, or keep things simple. Even though I like this a lot, we found something a little bit more interesting, I thought, by our European marketing team. If you guys need these tea bags, which you will need pretty soon. It's a new tagline for the company, not really. I thought it was apropos. But before I get into the product and the demos, to give you an idea. Every time I go to an event you find ways to memorialize the event. You meet people, you build relationships, you see something new. Last night, nothing to do with the product, I sat beside someone. It was a customer event. I had no idea who I was sitting beside. He was a speaker. How many of you guys know him, by the way? Sir Ranulph Fiennes. Few hands. Good for you. I had no idea who I was sitting beside. I said, "Oh, somebody called Sir. I should be respectful." It's kind of hard for me to be respectful, but I tried. He says, "No, I didn't do anything in the sense. My grandfather was knighted about 100 years ago because he was the governor of Antigua. And when he dies, his son becomes." And apparently Sir Ranulph's dad also died in the war, and so that's how he is a sir. But then I started looking it up because he's obviously getting ready to present. And the background for him is, in my opinion, even though the term goes he's the World's Greatest Living Explorer. I would have actually called it the World's Number One Stag, and I'll tell you why. Really, you should go look it up. So this guy, at the age of 21, gets admitted to Special Forces. If you're from the UK, this is as good as it gets, SAS. Six, seven years into it, he rebels, helps out his local partner because he doesn't like a movie who's building a dam inside this pretty village. And he goes and blows up a dam, and he's thrown out of that Special Forces. Obviously he's in demolitions. Goes all the way. This is the '60's, by the way. Remember he's 74 right now. The '60's he goes to Oman, all by himself, as the only guy, only white guy there. And then around the '70's, he starts truly exploring, truly exploring. And this is where he becomes really, really famous. You have to go see this in real life, when he sees these videos to really appreciate the impact of this guy. All by himself, he's gone across the world. He's actually gone across Antarctica. Now he tells me that Antarctica is the size of China and India put together, and he was prepared for -50 to 60 degrees, and obviously he got -130 degrees. Again, you have to see the videos, see his frostbite. Two of his fingers are cut off, by the way. He hacksawed them himself. True story. And then as he, obviously, aged, his body couldn't keep up with him, but his will kept up with him. So after a recent heart attack, he actually ran seven marathons. But most importantly, he was telling me this story, at 65 he wanted to do something different because his body was letting him down. He said, "Let me do something easy." So he climbed Mount Everest. My point being, what is this related to Nutanix? Is that if Nutanix is a company, without technology, allows to spend more time on life, then we've accomplished a piece of our vision. So keep that in mind. Keep that in mind. Now comes the boring part, which is the product. The why, what, how of Nutanix. Neeris talked about this. We have two acts in this company. Invisible Infrastructure was what we started off. You heard us talk about it. How did we do it? Using one-click technologies by converging infrastructure, computer storage, virtualization, et cetera, et cetera. What we are now about is about changing the game. Saying that just like we'd applicated what powers Google and Amazon inside the data center, could we now make them all invisible? Whether it be inside or outside, could we now make clouds invisible? Clouds could be made invisible by a new level of convergence, not about computer storage, but converging public and private, converging CAPEX and OPEX, converging consumption models. And there, beyond our core products, Acropolis and Prism, are these new products. As you know, we have this core thesis, right? The core thesis says what? Predictable workloads will stay inside the data center, elastic workloads will go outside, as long as the experience on both sides is the same. So if you can genuinely have a cloud-like experience delivered inside a data center, then that's the right a- >> Speaker 1: Genuinely have a cloud like experience developed inside the data center. And that's the right answer of predictable workloads. Absolutely the answer of elastic workloads, doesn't matter whether security or compliance. Eventually a public cloud will have a data center right beside your region, whether through local partner or a top three cloud partner. And you should use it as your public cloud of choice. And so, our goal is to ensure that those two worlds are converged. And that's what Calm does, and we'll talk about that. But at the same time, what we found in late 2015, we had a bunch of customers come to us and said "Look, I love this, I love the fact that you're going to converge public and private and all that good stuff. But I have these environments and these apps that I want to be delivered as a service but I want the same operational tooling. I don't want to have two different environments but I don't want to manage my data centers. Especially my secondary data centers, DR data centers." And that's why we created Xi, right? And you'll hear a lot more about this, obviously it's going to start off in the U.S but very rapidly launch in Europe, APJ globally in the next 9-12 months. And so we'll spend some quality time on those products as well today. So, from the journey that we're at, we're starting with the score cloud that essentially says "Look, your public and private needs to be the same" We call that the first instantiation of your cloud architectures and we're essentially as a company, want to build this enterprise cloud operating system as a fabric across public and private. But that's just the starting point. The starting point evolves to the score architecture that we believe that the cloud is being dispersed. Just like you have a public and a private cloud in the core data centers and so forth, you'll need a similar experience inside your remote office branch office, inside your DR data centers, inside your branches, and it won't stop there. It'll go all the way to the edge. All we're already seeing this right? Not just in the army where your forward operating bases in Afghanistan having a three note cluster sitting inside a tent. But we're seeing this in a variety of enterprise scenarios. And here's an example. So, here's a customer, global oil and gas company, has couple of primary data centers running Nutanix, uses GCP as a core public cloud platform, has a whole bunch of remote offices, but it also has this interesting new edge locations in the form of these small, medium, large size rigs. And today, they're in the process of building a next generation cloud architecture that's completely dispersed. They're using one node, coming out on version 5.5 with Nutanix. They're going to use two nodes, they're going to throw us three nods, multicultural architectures. Day one, they're going to centrally manage it using Prism, with one click upgrades, right? And then on top of that, they're also now provisioning using Calm, purpose built apps for the various locations. So, for example, there will be a re control app at the edge, there's an exploration data lag in Google and so forth. My point being that increasingly this architecture that we're talking about is happening in real time. It's no longer just an existing cellular civilization data center that's being replatformed to look like a private cloud and so forth, or a hybrid cloud. But the fact that you're going into this multi cloud era is getting excel bated, the more someone consumes AWL's GCP or any public cloud, the more they're excel bating their internal transformation to this multi cloud architecture. And so that's what we're going to talk about today, is this construct of ONE OS and ONE Click, and when you think about it, every company has a standard stack. So, this is the only slide you're going to see from me today that's a stack, okay? And if you look at the new release coming out, version 5.5, it's coming out imminently, easiest way to say it is that it's got a ton of functionality. We've jammed as much as we can onto one slide and then build a product basically, okay? But I would encourage you guys to check out the release, it's coming out shortly. And we can go into each and every feature here, we'd be spending a lot of time but the way that we look at building Nutanix products as many of you know, it is not feature at a time. It's experience at a time. And so, when you really look at Nutanix using a lateral view, and that's how we approach problems with our customers and partners. We think about it as a life cycle, all the way from learning to using, operating, and then getting support and experiences. And today, we're going to go through each of these stages with you. And who better to talk about it than our local version of an architect, Steven Poitras please come up on stage. I don't know where you are, Steven come on up. You tucked your shirt in? >> Speaker 2: Just for you guys today. >> Speaker 1: Okay. Alright. He's sort of putting on his weight. I know you used a couple of tight buckles there. But, okay so Steven so I know we're looking for the demo here. So, what we're going to do is, the first step most of you guys know this, is we've been quite successful with CE, it's been a great product. How many of you guys like CE? Come on. Alright. I know you had a hard time downloading it yesterday apparently, there's a bunch of guys had a hard time downloading it. But it's been a great way for us not just to get you guys to experience it, there's more than 25,000 downloads and so forth. But it's also a great way for us to see new features like IEME and so forth. So, keep an eye on CE because we're going to if anything, explode the way that we actually use as a way to get new features out in the next 12 months. Now, one thing beyond CE that we did, and this was something that we did about ... It took us about 12 months to get it out. While people were using CE to learn a lot, a lot of customers were actually getting into full blown competitive evals, right? Especially with hit CI being so popular and so forth. So, we came up with our own version called X-Ray. >> Speaker 2: Yup. >> Speaker 1: What does X-Ray do before we show it? >> Speaker 2: Yeah. Absolutely. So, if we think about back in the day we were really the only ACI platform out there on the market. Now there are a few others. So, to basically enable the customer to objectively test these, we came out with X-Ray. And rather than talking about the slide let's go ahead and take a look. Okay, I think it's ready. Perfect. So, here's our X-Ray user interface. And essentially what you do is you specify your targets. So, in this case we have a Nutanix 80150 as well as some of our competitors products which we've actually tested. Now we can see on the left hand side here we see a series of tests. So, what we do is we go through and specify certain workloads like OLTP workloads, database colocation, and while we do that we actually inject certain test cases or scenarios. So, this can be snapshot or component failures. Now one of the key things is having the ability to test these against each other. So, what we see here is we're actually taking a OLTP workload where we're running two virtual machines, and then we can see the IOPS OLTP VM's are actually performing here on the left hand side. Now as we're actually go through this test we perform a series of snapshots, which are identified by these red lines here. Now as you can see, the Nutanix platform, which is shown by this blue line, is purely consistent as we go through this test. However, our competitor's product actually degrades performance overtime as these snapshots are taken. >> Speaker 1: Gotcha. And some of these tests by the way are just not about failure or benchmarking, right? It's a variety of tests that we have that makes real life production workloads. So, every couple of months we actually look at our production workloads out there, subset those two cases and put it into X-Ray. So, X-Ray's one of those that has been more recently announced into the public. But it's already gotten a lot of update. I would strongly encourage you, even if you an existing Nutanix customer. It's a great way to keep us honest, it's a great way for you to actually expand your usage of Nutanix by putting a lot of these real life tests into production, and as and when you look at new alternatives as well, there'll be certain situations that we don't do as well and that's a great way to give us feedback on it. And so, X-Ray is there, the other one, which is more recent by the way is a fact that most of you has spent many days if not weeks, after you've chosen Nutanix, moving non-Nutanix workloads. I.e. VMware, on three tier architectures to Atrio Nutanix. And to do that, we took a hard look and came out with a new product called Xtract. >> Speaker 2: Yeah. So essentially if we think about what Nutanix has done for the data center really enables that iPhone like experience, really bringing it simplicity and intuitiveness to the data center. Now what we wanted to do is to provide that same experience for migrating existing workloads to us. So, with Xtract essentially what we've done is we've scanned your existing environment, we've created design spec, we handled the migration process ... >> Steven: ... environment, we create a design spec. We handle for the migration process as well as the cut over. Now, let's go ahead and take a look in our extract user interface here. What we can see is we have a source environment. In this case, this is a VC environment. This can be any VC, whether it's traditional three tier or hypherconverged. We also see our Nutanix target environments. Essentially, these are our AHV target clusters where we're going to be migrating the data and performing the cut over to you. >> Speaker 2: Gotcha. Steven: The first thing that we do here is we go ahead and create a new migration plan. Here, I'm just going to specify this as DB Wave 2. I'll click okay. What I'm doing here is I'm selecting my target Nutanix cluster, as well as my target Nutanix container. Once I'll do that, I'll click next. Now in this case, we actually like to do it big. We're actually going to migrate some production virtual machines over to this target environment. Here, I'm going to select a few windows instances, which are in our database cluster. I'll click next. At this point, essentially what's occurring is it's going through taking a look at these virtual machines as well as taking a look at the target environment. It takes a look at the resources to ensure that we actually have enough, an ample capacity to facilitate the workload. The next thing we'll do is we'll go ahead and type in our credentials here. This is actually going to be used for logging into the virtual machine. We can do a new device driver installation, as well as get any static IP configuration. Well specify our network mapping. Then from there, we'll click next. What we'll do is we'll actually save and start. This will go through create the migration plan. It'll do some analysis on these virtual machines to ensure that we can actually log in before we actually start migrating data. Here we have a migration, which has been in progress. We can see we have a few virtual machines, obviously some Linux, some Windows here. We've cut over a few. What we do to actually cut over these VMS, is go ahead select the VMS- Speaker 2: This is the actual task of actually doing the final stage of cut over. Steven: Yeah, exactly. That's one of the nice things. Essentially, we can migrate the data whenever we want. We actually hook into the VADP API's to do this. Then every 10 minutes, we send over a delta to sync the data. Speaker 2: Gotcha, gotcha. That's how one click migration can now be possible. This is something that if you guys haven't used this, this has been out in the wild, just for a month or so. Its been probably one of our bestselling, because it's free, bestselling features of the recent product release. I've had customers come to me and say, "Look, there are situations where its taken us weeks to move data." That is now minutes from the operator perspective. Forget where the director, or the VP, it's the line architecture and operator that really loves these tools, which is essentially the core of Nutanix. That's one of our core things, is to make sure that if we can keep the engineer and the architect truly happy, then everything else will be fine for us, right? That's extract. Then we have a lot of things, right? We've done the usual things, there's a tunnel functionality on day zero, day one, day two, kind of capabilities. Why don't we start with something around Prism Central, now that we can do one click PC installs? We can do PC scale outs, we can go from managing thousands of VMS, tens of thousands of VMS, while doing all the one click operations, right? Steven: Yep. Speaker 2: Why don't we take a quick look at what's new in Prism Central? Steven: Yep. Absolutely. Here, we can see our Prism element interface. As you mentioned, one of the key things we added here was the ability to deploy Prism Central very simply just with a few clicks. We'll actually go through a distributed PC scale of deployment here. Here, we're actually going to deploy, as this is a new instance. We're going to select our 5.5 version. In this case, we're going to deploy a scale out Prism Central cluster. Obviously, availability and up-time's very critical for us, as we're mainly distributed systems. In this case we're going to deploy a scale-out PC cluster. Here we'll select our number of PC virtual machines. Based upon the number of VMS, we can actually select our size of VM that we'd deploy. If we want to deploy 25K's report, we can do that as well. Speaker 2: Basically a thousand to tens of thousands of VM's are possible now. Steven: Yep. That's a nice thing is you can start small, and then scale out as necessary. We'll select our PC network. Go ahead and input our IP address. Now, we'll go to deploy. Now, here we can see it's actually kicked off the deployment, so it'll go provision these virtual machines to apply the configuration. In a few minutes, we'll be up and running. Speaker 2: Right. While Steven's doing that, one of the things that we've obviously invested in is a ton of making VM operations invisible. Now with Calm's, what we've done is to up level that abstraction. Two applications. At the end of the day, more and more ... when you go to AWS, when you go to GCP, you go to [inaudible 01:04:56], right? The level of abstractions now at an app level, it's cloud formations, and so forth. Essentially, what Calm's able to do is to give you this marketplace that you can go in and self-service [inaudible 01:05:05], create this internal cloud like environment for your end users, whether it be business owners, technology users to self-serve themselves. The process is pretty straightforward. You, as an operator, or an architect, or [inaudible 01:05:16] create these blueprints. Consumers within the enterprise, whether they be self-service users, whether they'll be end business users, are able to consume them for a simple marketplace, and deploy them on whether it be a private cloud using Nutanix, or public clouds using anything with public choices. Then, as a single frame of glass, as operators you're doing conversed operations, at an application centric level between [inaudible 01:05:41] across any of these clouds. It's this combination of producer, consumer, operator in a curated sense. Much like an iPhone with an app store. It's the core construct that we're trying to get with Calm to up level the abstraction interface across multiple clouds. Maybe we'll do a quick demo of this, and then get into the rest of the stuff, right? Steven: Sure. Let's check it out. Here we have our Prism Central user interface. We can see we have two Nutanix clusters, our cloudy04 as well as our Power8 cluster. One of the key things here that we've added is this apps tab. I'm clicking on this apps tab, we can see that we have a few [inaudible 01:06:19] solutions, we have a TensorFlow solution, a [inaudible 01:06:22] et cetera. The nice thing about this is, this is essentially a marketplace where vendors as well as developers could produce these blueprints for consumption by the public. Now, let's actually go ahead and deploy one of these blueprints. Here we have a HR employment engagement app. We can see we have three different tiers of services part of this. Speaker 2: You need a lot of engagement at HR, you know that. Okay, keep going. Steven: Then the next thing we'll do here is we'll go and click on. Based upon this, we'll specify our blueprint name, HR app. The nice thing when I'm deploying is I can actually put in back doors. We'll click clone. Now what we can see here is our blueprint editor. As a developer, I could actually go make modifications, or even as an in-user given the simple intuitive user interface. Speaker 2: This is the consumers side right here, but it's also the [inaudible 01:07:11]. Steven: Yep, absolutely. Yeah, if I wanted to make any modifications, I could select the tier, I could scale out the number of instances, I could modify the packages. Then to actually deploy, all I do is click launch, specify HR app, and click create. Speaker 2: Awesome. Again, this is coming in 5.5. There's one other feature, by the way, that is coming in 5.5 that's surrounding Calm, and Prism Pro, and everything else. That seems to be a much awaited feature for us. What was that? Steven: Yeah. Obviously when we think about multi-tenant, multi-cloud role based access control is a very critical piece of that. Obviously within the organization, we're going to have multiple business groups, multiple units. Our back's a very critical piece. Now, if we go over here to our projects, we can see in this scenario we just have a single project. What we've added is if you want to specify certain roles, in this case we're going to add our good friend John Doe. We can add them, it could be a user or group, but then we specify their role. We can give a developer the ability to edit and create these blueprints, or consumer the ability to actually provision based upon. Speaker 2: Gotcha. Basically in 5.5, you'll have role based access control now in Prism and Calm burned into that, that I believe it'll support custom role shortly after. Steven: Yep, okay. Speaker 2: Good stuff, good stuff. I think this is where the Nutanix guys are supposed to clap, by the way, so that the rest of the guys can clap. Steven: Thank you, thank you. Okay. What do we have? Speaker 2: We have day one stuff, obviously there's a ton of stuff that's coming in core data path capabilities that most of you guys use. One of the most popular things is synchronous replication, especially in Europe. Everybody wants to do [Metro 01:08:49] for whatever reason. But we've got something new, something even more enhanced than Metro, right? Steven: Yep. Speaker 2: Do you want to talk a little bit about it? Steven: Yeah, let's talk about it. If we think about what we had previously, we started out with a synchronous replication. This is essentially going to be your higher RPO. Then we moved into Metro cluster, which was RPO zero. Those are two ins of the gamete. What we did is we introduced new synchronous replication, which really gives you the best of both worlds where you have very, very decreased RPO's, but zero impact in line mainstream performance. Speaker 2: That's it. Let's show something. Steven: Yeah, yeah. Let's do it. Here, we're back at our Prism Element interface. We'll go over here. At this point, we provisioned our HR app, the next thing we need to do is to protect that data. Let's go here to protection domain. We'll create a new PD for our HR app. Speaker 2: You clearly love HR. Steven: Spent a lot of time there. Speaker 2: Yeah, yeah, yeah. Steven: Here, you can see we have our production lamp DBVM. We'll go ahead and protect that entity. We can see that's protected. The next thing we'll do is create a schedule. Now, what would you say would be a good schedule we should actually shoot for? Speaker 2: I don't know, 15 minutes? Steven: 15 minutes is not bad. But I ... Section 7 of 13 [01:00:00 - 01:10:04] Section 8 of 13 [01:10:00 - 01:20:04] (NOTE: speaker names may be different in each section) Speaker 1: ... 15 minutes. Speaker 2: 15 minutes is not bad, but I think the people here deserve much better than that, so I say let's shoot for ... what about 15 seconds? Speaker 1: Yeah. They definitely need a bathroom break, so let's do 15 seconds. Speaker 2: Alright, let's do 15 seconds. Speaker 1: Okay, sounds good. Speaker 2: K. Then we'll select our retention policy and remote cluster replicate to you, which in this case is wedge. And we'll go ahead and create the schedule here. Now at this point we can see our protection domain. Let's go ahead and look at our entities. We can see our database virtual machine. We can see our 15 second schedule, our local snapshots, as well as we'll start seeing our remote snapshots. Now essentially what occurs is we take two very quick snapshots to essentially see the initial data, and then based upon that then we'll start taking our continuous 15 second snaps. Speaker 1: 15 seconds snaps, and obviously near sync has less of impact than synchronous, right? From an architectural perspective. Speaker 2: Yeah, and that's a nice thing is essentially within the cluster it's truly pure synchronous, but externally it's just a lagged a-sync. Speaker 1: Gotcha. So there you see some 15 second snapshots. So near sync is also built into five-five, it's a long-awaited feature. So then, when we expand in the rest of capabilities, I would say, operations. There's a lot of you guys obviously, have started using Prism Pro. Okay, okay, you can clap. You can clap. It's okay. It was a lot of work, by the way, by the core data pad team, it was a lot of time. So Prism Pro ... I don't know if you guys know this, Prism Central now run from zero percent to more than 50 percent attach on install base, within 18 months. And normally that's a sign of true usage, and true value being supported. And so, many things are new in five-five out on Prism Pro starting with the fact that you can do data[inaudible 01:11:49] base lining, alerting, so that you're not capturing a ton of false positives and tons of alerts. We go beyond that, because we have this core machine-learning technology power, we call it cross fit. And, what we've done is we've used that as a foundation now for pretty much all kinds of operations benefits such as auto RCA, where you're able to actually map to particular [inaudible 01:12:12] crosses back to who's actually causing it whether it's the network, a computer, and so forth. But then the last thing that we've also done in five-five now that's quite different shading, is the fact that you can now have a lot of these one-click recommendations and remediations, such as right-sizing, the fact that you can actually move around [inaudible 01:12:28] VMs, constrained VMs, and so forth. So, I now we've packed a lot of functionality in Prism Pro, so why don't we spend a couple of minutes quickly giving a sneak peak into a few of those things. Speaker 2: Yep, definitely. So here we're back at our Prism Central interface and one of the things we've added here, if we take a look at one of our clusters, we can see we have this new anomalies portion here. So, let's go ahead and select that and hop into this. Now let's click on one of these anomaly events. Now, essentially what the system does is we monitor all the entities and everything running within the system, and then based upon that, we can actually determine what we expect the band of values for these metrics to be. So in this scenario, we can see we have a CPU usage anomaly event. So, normal time, we expect this to be right around 86 to 100 percent utilization, but at this point we can see this is drastically dropped from 99 percent to near zero. So, this might be a point as an administrator that I want to go check out this virtual machine, ensure that certain services and applications are still up and running. Speaker 1: Gotcha, and then also it changes the baseline based on- Speaker 2: Yep. Yeah, so essentially we apply machine-learning techniques to this, so the system will dynamically adjust based upon the value adjustment. Speaker 1: Gotcha. What else? Speaker 2: Yep. So the other thing here that we mentioned was capacity planning. So if we go over here, we can take a look at our runway. So in this scenario we have about 30 days worth of runway, which is most constrained by memory. Now, obviously, more nodes is all good for everyone, but we also want to ensure that you get the maximum value on your investment. So here we can actually see a few recommendations. We have 11 overprovision virtual machines. These are essentially VMs which have more resources than are necessary. As well as 19 inactives, so these are dead VMs essentially that haven't been powered on and not utilized. We can also see we have six constrained, as well as one bully. So, constrained VMs are essentially VMs which are requesting more resources than they actually have access to. This could be running at 100 percent CPU utilization, or 100 percent memory, or storage utilization. So we could actually go in and modify these. Speaker 1: Gotcha. So these are all part of the auto remediation capabilities that are now possible? Speaker 2: Yeah. Speaker 1: What else, do you want to take reporting? Speaker 2: Yeah. Yeah, so I know reporting is a very big thing, so if we think about it, we can't rely on an administrator to constantly go into Prism. We need to provide some mechanism to allow them to get emailed reports. So what we've done is we actually autogenerate reports which can be sent via email. So we'll go ahead and add one of these sample reports which was created today. And here we can actually get specific detailed information about our cluster without actually having to go into Prism to get this. Speaker 1: And you can customize these reports and all? Speaker 2: Yep. Yeah, if we hop over here and click on our new report, we can actually see a list of views we could add to these reports, and we can mix and match and customize as needed. Speaker 1: Yeah, so that's the operational side. Now we also have new services like AFS which has been quite popular with many of you folks. We've had hundreds of customers already on it live with SMB functionality. You want to show a couple of things that is new in five-five? Speaker 2: Yeah. Yep, definitely. So ... let's wait for my screen here. So one of the key things is if we looked at that runway tab, what we saw is we had over a year's worth of storage capacity. So, what we saw is customers had the requirement for filers, they had some excess storage, so why not actually build a software featured natively into the cluster. And that's essentially what we've done with AFS. So here we can see we have our AFS cluster, and one of the key things is the ability to scale. So, this particular cluster has around 3.1 or 3.16 billion files, which are running on this AFS cluster, as well as around 3,000 active concurrent sessions. Speaker 1: So basically thousands of concurrent sessions with billions of files? Speaker 2: Yeah, and the nice thing with this is this is actually only a four node Nutanix cluster, so as the cluster actually scales, these numbers will actually scale linearly as a function of those nodes. Speaker 1: Gotcha, gotcha. There's got to be one more bullet here on this slide so what's it about? Speaker 2: Yeah so, obviously the initial use case was realistically for home folders as well as user profiles. That was a good start, but it wasn't the only thing. So what we've done is we've actually also introduced important and upcoming release of NFS. So now you can now use NFS to also interface with our [crosstalk 01:16:44]. Speaker 1: NFS coming soon with AFS by the way, it's a big deal. Big deal. So one last thing obviously, as you go operationalize it, we've talked a lot of things on features and functions but one of the cool things that's always been seminal to this company is the fact that we all for really good customer service and support experience. Right now a lot of it is around the product, the people, the support guys, and so forth. So fundamentally to the product we have found ways using Pulse to instrument everything. With Pulse HD that has been allowed for a little bit longer now. We have fine grain [inaudible 01:17:20] around everything that's being done, so if you turn on this functionality you get a lot of information now that we built, we've used when you make a phone call, or an email, and so forth. There's a ton of context now available to support you guys. What we've now done is taken that and are now externalizing it for your own consumption, so that you don't have to necessarily call support. You can log in, look at your entire profile across your own alerts, your own advisories, your own recommendations. You can look at collective intelligence now that's coming soon which is the fact that look, here are 50 other customers just like you. These are the kinds of customers that are using workloads like you, what are their configuration profiles? Through this centralized customer insights portal you going to get a lot more insight, not just about your own operations, but also how everybody else is also using it. So let's take a quick look at that upcoming functionality. Speaker 2: Yep. Absolutely. So this is our customer 360 portal, so as [inaudible 01:18:18] mentioned, as a customer I can actually log in here, I can get a high-level overview of my existing environment, my cases, the status of those cases, as well as any relevant announcements. So, here based upon my cluster version, if there's any updates which are available, I can then see that here immediately. And then one of the other things that we've added here is this insights page. So essentially this is information that previously support would leverage to essentially proactively look out to the cluster, but now we've exposed this to you as the customer. So, clicking on this insights tab we can see an overview of our environment, in this case we have three Nutanix clusters, right around 550 virtual machines, and over here what's critical is we can actually see our cases. And one of the nice things about this is these area all autogenerated by the cluster itself, so no human interaction, no manual intervention was required to actually create these alerts. The cluster itself will actually facilitate that, send it over to support, and then support can get back out to you automatically. Speaker 1: K, so look for customer insights coming soon. And obviously that's the full life cycle. One cool thing though that's always been unique to Nutanix was the fact that we had [inaudible 01:19:28] security from day one built-in. And [inaudible 01:19:31] chunk of functionality coming in five-five just around this, because every release we try to insert more and more security capabilities, and the first one is around data. What are we doing? Speaker 2: Yeah, absolutely. So previously we had support for data at rest encryption, but this did have the requirement to leverage self-encrypting drives. These can be very expensive, so what we've done, typical to our fashion is we've actually built this in natively via software. So, here within Prism Element, I can go to data at rest encryption, and then I can go and edit this configuration here. Section 8 of 13 [01:10:00 - 01:20:04] Section 9 of 13 [01:20:00 - 01:30:04] (NOTE: speaker names may be different in each section) Steve: Encryption and then I can go and edit this configuration here. From here I could add my CSR's. I can specify KMS server and leverage native software base encryption without the requirement of SED's. Sunil: Awesome. So data address encryption [inaudible 01:20:15] coming soon, five five. Now data security is only one element, the other element was around network security obviously. We've always had this request about what are we doing about networking, what are we doing about network, and our philosophy has always been simple and clear, right. It is that the problem in networking is not the data plan. Problem in networking is the control plan. As in, if a packing loss happens to the top of an ax switch, what do we do? If there's a misconfigured board, what do we do? So we've invested a lot in full blown new network visualization that we'll show you a preview of that's all new in five five, but then once you can visualize you can take action, so you can actually using our netscape API's now in five five. You can optovision re lands on the switch, you can update reps on your load balancing pools. You can update obviously rules on your firewall. And then we've taken that to the next level, which is beyond all that, just let you go to AWS right now, what do you do? You take 100 VM's, you put it in an AWS security group, boom. That's how you get micro segmentation. You don't need to buy expensive products, you don't need to virtualize your network to get micro segmentation. That's what we're doing with five five, is built in one click micro segmentation. That's part of the core product, so why don't we just quickly show that. Okay? Steve: Yeah, let's take a look. So if we think about where we've been so far, we've done the comparison test, we've done a migration over to a Nutanix. We've deployed our new HR app. We've protected it's data, now we need to protect the network's. So one of the things you'll see that's new here is this security policies. What we'll do is we'll actually go ahead and create a new security policy and we'll just say this is HR security policy. We'll specify the application type, which in this case is HR. Sunil: HR of course. Steve: Yep and we can see our app instance is automatically populated, so based upon the number of running instances of that blueprint, that would populate that drop-down. Now we'll go ahead and click next here and what we can see in the middle is essentially those three tiers that composed that app blueprint. Now one of the important things is actually figuring out what's trying to communicate with this within my existing environment. So if I take a look over here on my left hand side, I can essentially see a few things. I can see a Ha Proxy load balancer is trying to communicate with my app here, that's all good. I want to allow that. I can see some sort of monitoring service is trying to communicate with all three of the tiers. That's good as well. Now the last thing I can see here is this IP address which is trying to access my database. Now, that's not designed and that's not supposed to happen, so what we'll do is we'll actually take a look and see what it's doing. Now hopping over to this database virtual machine or the hack VM, what we can see is it's trying to perform a brute force log in attempt to my MySQL database. This is not good. We can see obviously it can connect on the socket, however, it hasn't guessed the right password. In order to lock that down, we'll go back to our policies here and we're going to click deny. Once we've done that, we'll click next and now we'll go to Apply Now. Now we can see our newly created security policy and if we hop back over to this VM, we can now see it's actually timing out and what this means is that it's not able to communicate with that database virtual machine due to micro segmentation actively blocking that request. Sunil: Gotcha and when you go back to the Prism site, essentially what we're saying now is, it's as simple as that, to set up micro segmentation now inside your existing clusters. So that's one click micro segmentation, right. Good stuff. One other thing before we let Steve walk off the stage and then go to the bathroom, but is you guys know Steve, you know he spends a lot time in the gym, you do. Right. He and I share cubes right beside each other by the way just if you ever come to San Jose Nutanix corporate headquarters, you're always welcome. Come to the fourth floor and you'll see Steve and Sunil beside each other, most of the time I'm not in the cube, most of the time he's in the gym. If you go to his cube, you'll see all kinds of stuff. Okay. It's true, it's true, but the reason why I brought this up, was Steve recently became a father, his first kid. Oh by the way this is, clicker, this is how his cube looks like by the way but he left his wife and his new born kid to come over here to show us a demo, so give him a round of applause. Thank you, sir. Steve: Cool, thanks, Sunil. That was fun. Sunil: Thank you. Okay, so lots of good stuff. Please try out five five, give us feedback as you always do. A lot of sessions, a lot of details, have fun hopefully for the rest of the day. To talk about how their using Nutanix, you know here's one of our favorite customers and partners. He normally comes with sunglasses, I've asked him that I have to be the best looking guy on stage in my keynotes, so he's going to try to reduce his charm a little bit. Please come on up, Alessandro. Thank you. Alessandro R.: I'm delighted to be here, thank you so much. Sunil: Maybe we can stand here, tell us a little bit about Leonardo. Alessandro R.: About Leonardo, Leonardo is a key actor of the aerospace defense and security systems. Helicopters, aircraft, the fancy systems, the fancy electronics, weapons unfortunately, but it's also a global actor in high technology field. The security information systems division that is the division I belong to, 3,000 people located in Italy and in UK and there's several other countries in Europe and the U.S. $1 billion dollar of revenue. It has a long a deep experience in information technology, communications, automation, logical and physical security, so we have quite a long experience to expand. I'm in charge of the security infrastructure business side. That is devoted to designing, delivering, managing, secure infrastructures services and secure by design solutions and platforms. Sunil: Gotcha. Alessandro R.: That is. Sunil: Gotcha. Some of your focus obviously in recent times has been delivering secure cloud services obviously. Alessandro R.: Yeah, obviously. Sunil: Versus traditional infrastructure, right. How did Nutanix help you in some of that? Alessandro R.: I can tell something about our recent experience about that. At the end of two thousand ... well, not so recent. Sunil: Yeah, yeah. Alessandro R.: At the end of 2014, we realized and understood that we had to move a step forward, a big step and a fast step, otherwise we would drown. At that time, our newly appointed CEO confirmed that the IT would be a core business to Leonardo and had to be developed and grow. So we decided to start our digital transformation journey and decided to do it in a structured and organized way. Having clear in mind our targets. We launched two programs. One analysis program and one deployments programs that were essentially transformation programs. We had to renew ourselves in terms of service models, in terms of organization, in terms of skills to invest upon and in terms of technologies to adopt. We were stacking a certification of technologies that adopted, companies merged in the years before and we have to move forward and to rationalize all these things. So we spent a lot of time analyzing, comparing technologies, and evaluating what would fit to us. We had two main targets. The first one to consolidate and centralize the huge amount of services and infrastructure that were spread over 52 data centers in Italy, for Leonardo itself. The second one, to update our service catalog with a bunch of cloud services, so we decided to update our data centers. One of our building block of our new data center architecture was Nutanix. We evaluated a lot, we had spent a lot of time in analysis, so that wasn't a bet, but you are quite pioneers at those times. Sunil: Yeah, you took a lot of risk right as an Italian company- Alessandro R.: At this time, my colleague used to say, "Hey, Alessandro, think it over, remember that not a CEO has ever been fired for having chose IBM." I apologize, Bob, but at that time, when Nutanix didn't run on [inaudible 01:29:27]. We have still a good bunch of [inaudible 01:29:31] in our data center, so that will be the chance to ... Audience Member: [inaudible 01:29:37] Alessandro R.: So much you must [inaudible 01:29:37] what you announced it. Sunil: So you took a risk and you got into it. Alessandro R.: Yes, we got into, we are very satisfied with the results we have reached. Sunil: Gotcha. Alessandro R.: Most of the targets we expected to fulfill have come and so we are satisfied, but that doesn't mean that we won't go on asking you a big discount ... Sunil: Sure, sure, sure, sure. Alessandro R.: On price list. Sunil: Sure, sure, so what's next in terms of I know there are some interesting stuff that you're thinking. Alessandro R.: The next- Section 9 of 13 [01:20:00 - 01:30:04] Section 10 of 13 [01:30:00 - 01:40:04] (NOTE: speaker names may be different in each section) Speaker 1: So what's next, in terms of I know you have some interesting stuff that you're thinking of. Speaker 2: The next, we have to move forward obviously. The name Leonardo is inspired to Leonardo da Vinci, it was a guy that in terms of innovation and technology innovation had some good ideas. And so, I think, that Leonardo with Nutanix could go on in following an innovation target and following really mutual ... Speaker 1: Partnership. Speaker 2: Useful partnership, yes. We surely want to investigate the micro segmentation technologies you showed a minute ago because we have some looking, particularly by the economical point of view ... Speaker 1: Yeah, the costs and expenses. Speaker 2: And we have to give an alternative to the technology we are using. We want to use more intensively AHV, again as an alternative solution we are using. We are selecting a couple of services, a couple of quite big projects to build using AHV talking of Calm we are very eager to understand the announcement that they are going to show to all of us because the solution we are currently using is quite[crosstalk 01:31:30] Speaker 1: Complicated. Speaker 2: Complicated, yeah. To move a step of automation to elaborate and implement[inaudible 01:31:36] you spend 500 hours of manual activities that's nonsense so ... Speaker 1: Manual automation. Speaker 2: (laughs) Yes, and in the end we are very interested also in the prism features, mostly the new features that you ... Speaker 1: Talked about. Speaker 2: You showed yesterday in the preview because one bit of benefit that we received from the solution in the operations field means a bit plus, plus to our customer and a distinctive plus to our customs so we are very interested in that ... Speaker 1: Gotcha, gotcha. Thanks for taking the risk, thanks for being a customer and partner. Speaker 2: It has been a pleasure. Speaker 1: Appreciate it. Speaker 2: Bless you, bless you. Speaker 1: Thank you. So, you know obviously one OS, one click was one of our core things, as you can see the tagline doesn't stop there, it also says "any cloud". So, that's the rest of the presentation right now it's about; what are we doing, to now fulfill on that mission of one OS, one cloud, one click with one support experience across any cloud right? And there you know, we talked about Calm. Calm is not only just an operational experience for your private cloud but as you can see it's a one-click experience where you can actually up level your apps, set up blueprints, put SLA's and policies, push them down to either your AWS, GCP all your [inaudible 01:33:00] environments and then on day one while you can do one click provisioning, day two and so forth you will see new and new capabilities such as, one-click migration and mobility seeping into the product. Because, that's the end game for Calm, is to actually be your cloud autonomy platform right? So, you can choose the right cloud for the right workload. And talk about how they're building a multi cloud architecture using Nutanix and partnership a great pleasure to introduce my other good Italian friend Daniele, come up on stage please. From Telecom Italia Sparkle. How are you sir? Daniele: Not too bad thank you. Speaker 1: You want an espresso, cappuccino? Daniele: No, no later. Speaker 1: You all good? Okay, tell us a little about Sparkle. Daniele: Yeah, Sparkle is a fully owned subsidy of Telecom Italia group. Speaker 1: Mm-hmm (affirmative) Daniele: Spinned off in 2003 with the mission to develop the wholesale and multinational corporate and enterprise business abroad. Huge network, as you can see, hundreds of thousands of kilometers of fiber optics spread between; south east Asia to Europe to the U.S. Most of it proprietary part of it realized on some running cables. Part of them proprietary part of them bilateral part of them[inaudible 01:34:21] with other operators. 37 countries in which we have offices in the world, 700 employees, lean and clean company ... Speaker 1: Wow, just 700 employees for all of this. Daniele: Yep, 1.4 billion revenues per year more or less. Speaker 1: Wow, are you a public company? Daniele: No, fully owned by TIM so far. Speaker 1: So, what is your experience with Nutanix so far? Daniele: Well, in a way similar to what Alessandro was describing. To operate such a huge network as you can see before, and to keep on bringing revenues for the wholesale market, while trying to turn the bar toward the enterprise in a serious way. Couple of years ago the management team realized that we had to go through a serious transformation, not just technological but in terms of the way we build the services to our customers. In terms of how we let our customer feel the Sparkle experience. So, we are moving towards cloud but we are moving towards cloud with connectivity attached to it because it's in our cord as a provider of Telecom services. The paradigm that is driving today is the on-demand, is the dynamic and in order to get these things we need to move to software. Most of the network must become invisible as the Nutanix way. So, we decided instead of creating patchworks onto our existing systems, infrastructure, OSS, BSS and network systems, to build a new data center from scratch. And the paradigm being this new data center, the mantra was; everything is software designed, everything must be easy to manage, performance capacity planning, everything must be predictable and everything to be managed by few people. Nutanix is at the moment the baseline of this data center for what concern, let's say all the new networking tools, meaning as the end controllers that are taking care of automation and programmability of the network. Lifecycle service orchestrator, network orchestrator, cloud automation and brokerage platform and everything at the moment runs on AHV because we are forcing our vendors to certify their application on AHV. The only stack that is not at the moment AHV based is on a specific cloud platform because there we were really looking for the multi[inaudible 01:37:05]things that you are announcing today. So, we hope to do the migration as soon as possible. Speaker 1: Gotcha, gotcha. And then looking forward you're going to build out some more data center space, expose these services Daniele: Yeah. Speaker 1: For the customers as well as your internal[crosstalk 01:37:21] Daniele: Yeah, basically yes for sure we are going to consolidate, to invest more in the data centers in the markets on where we are leader. Italy, Turkey and Greece we are big data centers for [inaudible 01:37:33] and cloud, but we believe that the cloud with all the issues discussed this morning by Diraj, that our locality, customer proximity ... we think as a global player having more than 120 pops all over the world, which becomes more than 1000 in partnerships, that the pop can easily be transformed in a data center, so that we want to push the customer experience of what we develop in our main data centers closer to them. So, that we can combine traditional infrastructure as a service with the new connectivity services every single[inaudible 01:38:18] possibly everything running. Speaker 1: I mean, it makes sense, I mean I think essentially in some ways to summarize it's the example of an edge cloud where you're pushing a micro-cloud closer to the customers edge. Daniele: Absolutely. Speaker 1: Great stuff man, thank you so much, thank you so much. Daniele: Pleasure, pleasure. Thank you. Speaker 1: So, you know a couple of other things before we get in the next demo is the fact that in addition to Calm from multi-cloud management we have Zai, we talked about for extended enterprise capabilities and something for you guys to quickly understand why we have done this. In a very simple way is if you think about your enterprise data center, clearly you have a bunch of apps there, a bunch of public clouds and when you look at the paradigm you currently deploy traditional apps, we call them mode one apps, SAP, Exchange and so forth on your enterprise. Then you have next generation apps whether it be [inaudible 01:39:11] space, whether it be Doob or whatever you want to call it, lets call them mode two apps right? And when you look at these two types of apps, which are the predominant set, most enterprises have a combination of mode one and mode two apps, most public clouds primarily are focused, initially these days on mode two apps right? And when people talk about app mobility, when people talk about cloud migration, they talk about lift and shift, forklift [inaudible 01:39:41]. And that's a hard problem I mean, it's happening but it's a hard problem and ends up that its just not a one time thing. Once you've forklift, once you move you have different tooling, different operation support experience, different stacks. What if for some of your applications that mattered ... Section 10 of 13 [01:30:00 - 01:40:04] Section 11 of 13 [01:40:00 - 01:50:04] (NOTE: speaker names may be different in each section) Speaker 1: What if, for some of your applications that matter to you, that are your core enterprise apps that you can retain the same toolimg, the same operational experience and so forth. And that is what we achieve to do with Xi. It is truly making hybrid invisible, which is a next act for this company. It'll take us a few years to really fulfill the vision here, but the idea here is that you shouldn't think about public cloud as a different silo. You should think of it as an extension of your enterprise data centers. And for any services such as DR, whether it would be dev test, whether it be back-up, and so-forth. You can use the same tooling, same experience, get a public cloud-like capability without lift and shift, right? So it's making this lift and shift invisible by, soft of, homogenizing the data plan, the network plan, the control plan is what we really want to do with Xi. Okay? And we'll show you some more details here. But the simplest way to understand this is, think of it as the iPhone, right? D has mentioned this a little bit. This is how we built this experience. Views IOS as the core, IP, we wrap it up with a great package called the iPhone. But then, a few years into the iPhone era, came iTunes and iCloud. There's no apps, per se. That's fused into IOS. And similarly, think about Xi that way. The more you move VMs, into an internet-x environment, stuff like DR comes burnt into the fabric. And to give us a sneak peek into a bunch of the com and Xi cable days, let me bring back Binny who's always a popular guys on stage. Come on up, Binny. I'd be surprised in Binny untucked his shirt. He's always tucking in his shirt. Binny Gill: Okay, yeah. Let's go. Speaker 1: So first thing is com. And to show how we can actually deploy apps, not just across private and public clouds, but across multiple public clouds as well. Right? Binny Gill: Yeah, basically, you know com is about simplifying the disparity between various public clouds out there. So it's very important for us to be able to take one application blueprint and then quickly deploy in whatever cloud of your choice. Without understanding how one cloud is different. Speaker 1: Yeah, that's the goal. Binny Gill: So here, if you can see, I have market list. And by the way, this market list is a great partner community interest. And every single sort of apps come up here. Let me take a sample app here, Hadoop. And click launch. And now where do you want me to deploy? Speaker 1: Let's start at GCP. Binny Gill: GCP, okay. So I click on GCP, and let me give it a name. Hadoop. GCP. Say 30, right. Clear. So this is one click deployment of anything from our marketplace on to a cloud of your choice. Right now, what the system is doing, is taking the intent-filled description of what the application should look like. Not just the infrastructure level but also within the merchant machines. And it's creating a set of work flows that it needs to go deploy. So as you can see, while we were talking, it's loading the application. Making sure that the provisioning workflows are all set up. Speaker 1: And so this is actually, in real time it's actually extracting out some of the GCP requirements. It's actually talking to GCP. Setting up the constructs so that we can actually push it up on the GCP personally. Binny Gill: Right. So it takes a couple of minutes. It'll provision. Let me go back and show you. Say you worked with deploying AWS. So you Hadoop. Hit address. And that's it. So again, the same work flow. Speaker 1: Same process, I see. Binny Gill: It's going to now deploy in AWS. Speaker 1: See one of the keys things is that we actually extracted out all the isms of each of these clouds into this logical substrate. Binny Gill: Yep. Speaker 1: That you can now piggy-back off of. Binny Gill: Absolutely. And it makes it extremely simple for the average consumer. And you know we like more cloud support here over time. Speaker 1: Sounds good. Binny Gill: Now let me go back and show you an app that I had already deployed. Now 13 days ago. It's on GCP. And essentially what I want to show you is what is the view of the application. Firstly, it shows you the cost summary. Hourly, daily, and how the cost is going to look like. The other is how you manage it. So you know one click ways of upgrading, scaling out, starting, deleting, and so on. Speaker 1: So common actions, but independent of the type of clouds. Binny Gill: Independent. And also you can act with these actions over time. Right? Then services. It's learning two services, Hadoop slave and Hadoop master. Hadoop slave runs fast right now. And auditing. It shows you what are the important actions you've taken on this app. Not just, for example, on the IS front. This is, you know how the VMs were created. But also if you scroll down, you know how the application was deployed and brought up. You know the slaves have to discover each other, and so on. Speaker 1: Yeah got you. So find game invisibility into whatever you were doing with clouds because that's been one of the complaints in general. Is that the cloud abstractions have been pretty high level. Binny Gill: Yeah. Speaker 1: Yeah. Binny Gill: Yeah. So that's how we make the differences between the public clouds. All go away for the Indias of ... Speaker 1: Got you. So why don't we now give folks ... Now a lot of this stuff is coming in five, five so you'll see that pretty soon. You'll get your hands around it with AWS and tree support and so forth. What we wanted to show you was emerging alpha version that is being baked. So is a real production code for Xi. And why don't we just jump right in to it. Because we're running short of time. Binny Gill: Yep. Speaker 1: Give folks a flavor for what the production level code is already being baked around. Binny Gill: Right. So the idea of the design is make sure it's not ... the public cloud is no longer any different from your private cloud. It's a true seamless extension of your private cloud. Here I have my test environment. As you can see I'm running the HR app. It has the DB tier and the Web tier. Yeah. Alright? And the DB tier is running Oracle DB. Employee payroll is the Web tier. And if you look at the availability zones that I have, this is my data center. Now I want to protect this application, right? From disaster. What do I do? I need another data center. Speaker 1: Sure. Binny Gill: Right? With Xi, what we are doing is ... You go here and click on Xi Cloud Services. Speaker 1: And essentially as the slide says, you are adding AZs with one click. Binny Gill: Yeps so this is what I'm going to do. Essentially, you log in using your existing my.nutanix.com credentials. So here I'm going to use my guest credentials and log in. Now while I'm logging in what's happening is we are creating a seamless network between the two sides. And then making the Xi cloud availability zone appear. As if it was my own. Right? Speaker 1: Gotcha. Binny Gill: So in a couple of seconds what you'll notice this list is here now I don't have just one availability zone, but another one appears. Speaker 1: So you have essentially, real time now, paid a one data center doing an availability zone. Binny Gill: Yep. Speaker 1: Cool. Okay. Let's see what else we can do. Binny Gill: So now you think about VR setup. Now I'm armed with another data center, let's do DR Center. Now DR set-up is going to be extremely simple. Speaker 1: Okay but it's also based because on the fact that it is the same stack on both sides. Right? Binny Gill: It's the same stack on both sides. We have a secure network lane connecting the two sides, on top of the secure network plane. Now data can flow back and forth. So now applications can go back and forth, securely. Speaker 1: Gotcha, okay. Let's look at one-click DR. Binny Gill: So for one-click DR set-up. A couple of things we need to know. One is a protection rule. This is the RPO, where does it apply to? Right? And the connection of the replication. The other one is recovery plans, in case disaster happens. You know, how do I bring up my machines and application work-order and so on. So let me first show you, Protection Rule. Right? So here's the protection rule. I'll create one right now. Let me call it Platinum. Alright, and source is my own data center. Destination, you know Xi appears now. Recovery point objective, so maybe in a one hour these snapshots going to the public cloud. I want to retain three in the public side, three locally. And now I select what are the entities that I want to protect. Now instead of giving VMs my name, what I can do is app type employee payroll, app type article database. It covers both the categories of the application tiers that I have. And save. Speaker 1: So one of the things here, by the way I don't know if you guys have noticed this, more and more of Nutanix's constructs are being eliminated to become app-centric. Of course is VM centric. And essentially what that allows one to do is to create that as the new service-level API/abstraction. So that under the cover over a period of time, you may be VMs today, maybe containers tomorrow. Or functions, the day after. Binny Gill: Yep. What I just did was all that needs to be done to set up replication from your own data center to Xi. So we started off with no data center to actually replication happening. Speaker 1: Gotcha. Binny Gill: Okay? Speaker 1: No, no. You want to set up some recovery plans? Binny Gill: Yeah so now set up recovery plan. Recovery plans are going to be extremely simple. You select a bunch of VMs or apps, and then there you can say what are the scripts you want to run. What order in which you want to boot things. And you know, you can set up access these things with one click monthly or weekly and so on. Speaker 1: Gotcha. And that sets up the IPs as well as subnets and everything. Binny Gill: So you have the option. You can maintain the same IPs on frame as the move to Xi. Or you can make them- Speaker 1: Remember, you can maintain your own IPs when you actually use the Xi service. There was a lot of things getting done to actually accommodate that capability. Binny Gill: Yeah. Speaker 1: So let's take a look at some of- Binny Gill: You know, the same thing as VPC, for example. Speaker 1: Yeah. Binny Gill: You need to possess on Xi. So, let's create a recovery plan. A recovery plan you select the destination. Where does the recovery happen. Now, after that Section 11 of 13 [01:40:00 - 01:50:04] Section 12 of 13 [01:50:00 - 02:00:04] (NOTE: speaker names may be different in each section) Speaker 1: ... does the recovery happen. Now, after that you have to think of what is the runbook that you want to run when disaster happens, right? So you're preparing for that, so let me call "HR App Recovery." The next thing is the first stage. We're doing the first stage, let me add some entities by categories. I want to bring up my database first, right? Let's click on the database and that's it. Speaker 2: So essentially, you're building the script now. Speaker 1: Building the script- Speaker 2: ... on the [inaudible 01:50:30] Speaker 1: ... but in a visual way. It's simple for folks to understand. You can add custom script, add delay and so on. Let me add another stage and this stage is about bringing up the web tier after the database is up. Speaker 2: So basically, bring up the database first, then bring up the web tier, et cetera, et cetera, right? Speaker 1: That's it. I've created a recovery plan. I mean usually it's complicated stuff, but we made it extremely simple. Now if you click on "Recovery Points," these are snapshots. Snapshots of your applications. As you can see, already the system has taken three snapshots in response to the protection rule that we had created just a couple minutes ago. And these are now being seeded to Xi data centers. Of course this takes time for seeding, so what I have is a setup already and that's the production environment. I'll cut over to that. This is my production environment. Click "Explore," now you see the same application running in production and I have a few other VMs that are not protected. Let's go to "Recovery Points." It has been running for sometime, these recover points are there and they have been replicated to Xi. Speaker 2: So let's do the failover then. Speaker 1: Yeah, so to failover, you'll have to go to Xi so let me login to Xi. This time I'll use my production account for logging into Xi. I'm logging in. The first thing that you'll see in Xi is a dashboard that gives you a quick summary of what your DR testing has been so far, if there are any issues with the replication that you have and most importantly the monthly charges. So right now I've spent with my own credit card about close to 1,000 bucks. You'll have to refund it quickly. Speaker 2: It depends. If the- Speaker 1: If this works- Speaker 2: IF the demo works. Speaker 1: Yeah, if it works, okay. As you see, there are no VMs right now here. If I go to the recovery points, they are there. I can click on the recovery plan that I had created and let's see how hard it's going to be. I click "Failover." It says three entities that, based on the snapshots, it knows that it can recovery from source to destination, which is Xi. And one click for the failover. Now we'll see what happens. Speaker 2: So this is essentially failing over my production now. Speaker 1: Failing over your production now. [crosstalk 01:52:53] If you click on the "HR App Recovery," here you see now it started the recovery plan. The simple recovery plan that we had created, it actually gets converted to a series of tasks that the system has to do. Each VM has to be hydrated, powered on in the right order and so on and so forth. You don't have to worry about any of that. You can keep an eye on it. But in the meantime, let's talk about something else. We are doing failover, but after you failover, you run in Xi as if it was your own setup and environment. Maybe I want to create a new VM. I create a VM and I want to maybe extend my HR app's web tier. Let me name it as "HR_Web_3." It's going to boot from that disk. Production network, I want to run it on production network. We have production and test categories. This one, I want to give it employee payroll category. Now it applies the same policies as it's peers will. Here, I'm going to create the VM. As you can see, I can already see some VMs coming up. There you go. So three VMs from on-prem are now being filled over here while the fourth VM that I created is already being powered. Speaker 2: So this is basically realtime, one-click failover, while you're using Xi for your [inaudible 01:54:13] operations as well. Speaker 1: Exactly. Speaker 2: Wow. Okay. Good stuff. What about- Speaker 1: Let me add here. As the other cloud vendors, they'll ask you to make your apps ready for their clouds. Well we tell our engineers is make our cloud ready for your apps. So as you can see, this failover is working. Speaker 2: So what about failback? Speaker 1: All of them are up and you can see the protection rule "platinum" has been applied to all four. Now let's look at this recovery plan points "HR_Web_3" right here, it's already there. Now assume the on-prem was already up. Let's go back to on-prem- Speaker 2: So now the scenario is, while Binny's coming up, is that the on-prem has come back up and we're going to do live migration back as in a failback scenario between the data centers. Speaker 1: And how hard is it going to be. "HR App Recovery" the same "HR App Recovery", I click failover and the system is smart enough to understand the direction is reversed. It's also smart enough to figure out "Hey, there are now the four VMs are there instead of three." Xi to on-prem, one-click failover again. Speaker 2: And it's rerunning obviously the same runbook but in- Speaker 1: Same runbook but the details are different. But it's hidden from the customer. Let me go to the VMs view and do something interesting here. I'll group them by availability zone. Here you go. As you can see, this is a hybrid cloud view. Same management plane for both sides public and private. There are two availability zones, the Xi availability zone is in the cloud- Speaker 2: So essentially you're moving from the top- Speaker 1: Yeah, top- Speaker 2: ... to the bottom. Speaker 1: ... to the bottom. Speaker 2: That's happening in the background. While this is happening, let me take the time to go and look at billing in Xi. Speaker 1: Sure, some of the common operations that you can now see in a hybrid view. Speaker 2: So you go to "Billing" here and first let me look at my account. And account is a simple page, I have set up active directory and you can add your own XML file, upload it. You can also add multi-factor authentication, all those things are simple. On the billing side, you can see more details about how did I rack up $966. Here's my credit card. Detailed description of where the cost is coming from. I can also download previous versions, builds. Speaker 1: It's actually Nutanix as a service essentially, right? Speaker 2: Yep. Speaker 1: As a subscription service. Speaker 2: Not only do we go to on-prem as you can see, while we were talking, two VMs have already come back on-prem. They are powered off right now. The other two are on the wire. Oh, there they are. Speaker 1: Wow. Speaker 2: So now four VMs are there. Speaker 1: Okay. Perfect. Sometimes it works, sometimes it doesn't work, but it's good. Speaker 2: It always works. Speaker 1: Always works. All right. Speaker 2: As you can see the platinum protection rule is now already applied to them and now it has reversed the direction of [inaudible 01:57:12]- Speaker 1: Remember, we showed one-click DR, failover, failback, built into the product when Xi ships to any Nutanix fabric. You can start with DSX on premise, obviously when you failover to Xi. You can start with AHV, things that are going to take the same paradigm of one-click operations into this hybrid view. Speaker 2: Let's stop doing lift and shift. The era has come for click and shift. Speaker 1: Binny's now been promoted to the Chief Marketing Officer, too by the way. Right? So, one more thing. Speaker 2: Okay. Speaker 1: You know we don't stop any conferences without a couple of things that are new. The first one is something that we should have done, I guess, a couple of years ago. Speaker 2: It depends how you look at it. Essentially, if you look at the cloud vendors, one of the key things they have done is they've built services as building blocks for the apps that run on top of them. What we have done at Nutanix, we've built core services like block services, file services, now with Calm, a marketplace. Now if you look at [inaudible 01:58:14] applications, one of the core building pieces is the object store. I'm happy to announce that we have the object store service coming up. Again, in true Nutanix fashion, it's going to be elastic. Speaker 1: Let's- Speaker 2: Let me show you. Speaker 1: Yeah, let's show it. It's something that is an object store service by the way that's not just for your primary, but for your secondary. It's obviously not just for on-prem, it's hybrid. So this is being built as a next gen object service, as an extension of the core fabric, but accommodating a bunch of these new paradigms. Speaker 2: Here is the object browser. I've created a bunch of buckets here. Again, object stores can be used in various ways: as primary object store, or for secondary use cases. I'll show you both. I'll show you a Hadoop use case where Hadoop is using this as a primary store and a backup use case. Let's just jump right in. This is a Hadoop bucket. AS you can see, there's a temp directory, there's nothing interesting there. Let me go to my Hadoop VM. There it is. And let me run a Hadoop job. So this Hadoop job essentially is going to create a bunch of files, write them out and after that do map radius on top. Let's wait for the job to start. It's running now. If we go back to the object store, refresh the page, now you see it's writing from benchmarks. Directory, there's a bunch of files that will write here over time. This is going to take time. Let's not wait for it, but essentially, it is showing Hadoop that uses AWS 3 compatible API, that can run with our object store because our object store exposes AWS 3 compatible APIs. The other use case is the HYCU backup. As you can see, that's a- Section 12 of 13 [01:50:00 - 02:00:04] Section 13 of 13 [02:00:00 - 02:13:42] (NOTE: speaker names may be different in each section) Vineet: This is the hycu back up ... As you can see, that's a back-up software that can back-up WSS3. If you point it to Nutanix objects or it can back-up there as well. There are a bunch of back-up files in there. Now, object stores, it's very important for us to be able to view what's going on there and make sure there's no objects sprawled because once it's easy to write objects, you just accumulate a lot of them. So what we wanted to do, in true Nutanix style, is give you a quick overview of what's happening with your object store. So here, as you can see, you can look at the buckets, where the load is, you can look at the bucket sizes, where the data is, and also what kind of data is there. Now this is a dashboard that you can optimize, and customize, for yourself as well, right? So that's the object store. Then we go back here, and I have one more thing for you as well. Speaker 2: Okay. Sounds good. I already clicked through a slide, by the way, by mistake, but keep going. Vineet: That's okay. That's okay. It is actually a quiz, so it's good for people- Speaker 2: Okay. Sounds good. Vineet: It's good for people to have some clues. So the quiz is, how big is my SAP HANA VM, right? I have to show it to you before you can answer so you don't leak the question. Okay. So here it is. So the SAP HANA VM here vCPU is 96. Pretty beefy. Memory is 1.5 terabytes. The question to all of you is, what's different in this screen? Speaker 2: Who's a real Prism user here, by the way? Come on, it's got to be at least a few. Those guys. Let's see if they'll notice something. Vineet: What's different here? Speaker 3: There's zero CVM. Vineet: Zero CVM. Speaker 2: That's right. Yeah. Yeah, go ahead. Vineet: So, essentially, in the Nutanix fabric, every server has to run a [inaudible 02:01:48] machine, right? That's where the storage comes from. I am happy to announce the Acropolis Compute Cloud, where you will be able to run the HV on servers that are storage-less, and add it to your existing cluster. So it's a compute cloud that now can be managed from Prism Central, and that way you can preserve your investments on your existing server farms, and add them to the Nutanix fabric. Speaker 2: Gotcha. So, essentially ... I mean, essentially, imagine, now that you have the equivalent of S3 and EC2 for the enterprise now on Premisis, like you have the equivalent compute and storage services on JCP and AWS, and so forth, right? So the full flexibility for any kind of workload is now surely being available on the same Nutanix fabric. Thanks a lot, Vineet. Before we wrap up, I'd sort of like to bring this home. We've announced a pretty strategic partnership with someone that has always inspired us for many years. In fact, one would argue that the genesis of Nutanix actually was inspired by Google and to talk more about what we're actually doing here because we've spent a lot of time now in the last few months to really get into the product capabilities. You're going to see some upcoming capabilities and 55X release time frame. To talk more about that stuff as well as some of the long-term synergies, let me invite Bill onstage. C'mon up Bill. Tell us a little bit about Google's view in the cloud. Bill: First of all, I want to compliment the demo people and what you did. Phenomenal work that you're doing to make very complex things look really simple. I actually started several years ago as a product manager in high availability and disaster recovery and I remember, as a product manager, my engineers coming to me and saying "we have a shortage of our engineers and we want you to write the fail-over routines for the SAP instance that we're supporting." And so here's the PERL handbook, you know, I haven't written in PERL yet, go and do all that work to include all the network setup and all that work, that's amazing, what you are doing right there and I think that's the spirit of the partnership that we have. From a Google perspective, obviously what we believe is that it's time now to harness the power of scale security and these innovations that are coming out. At Google we've spent a lot of time in trying to solve these really large problems at scale and a lot of the technology that's been inserted into the industry right now. Things like MapReduce, things like TenserFlow algorithms for AI and things like Kubernetes and Docker were first invented at Google to solve problems because we had to do it to be able to support the business we have. You think about search, alright? When you type in search terms within the search box, you see a white screen, what I see is all the data-center work that's happening behind that and the MapReduction to be able to give you a search result back in seconds. Think about that work, think about that process. Taking and pursing those search terms, dividing that over thousands of [inaudible 02:05:01], being able to then search segments of the index of the internet and to be able to intelligent reduce that to be able to get you an answer within seconds that is prioritized, that is sorted. How many of you, out there, have to go to page two and page three to get the results you want, today? You don't because of the power of that technology. We think it's time to bring that to the consumer of the data center enterprise space and that's what we're doing at Google. Speaker 2: Gotcha, man. So I know we've done a lot of things now over the last year worth of collaboration. Why don't we spend a few minutes talking through a couple things that we're started on, starting with [inaudible 02:05:36] going into com and then we'll talk a little bit about XI. Bill: I think one of the advantages here, as we start to move up the stack and virtualize things to your point, right, is virtual machines and the work required of that still takes a fair amount of effort of which you're doing a lot to reduce, right, you're making that a lot simpler and seamless across both On-Prem and the cloud. The next step in the journey is to really leverage the power of containers. Lightweight objects that allow you to be able to head and surface functionality without being dependent upon the operating system or the VM to be able to do that work. And then having the orchestration layer to be able to run that in the context of cloud and On-Prem We've been very successful in building out the Kubernetes and Docker infrastructure for everyone to use. The challenge that you're solving is how to we actually bridge the gap. How do we actually make that work seamlessly between the On-Premise world and the cloud and that's where our partnership, I think, is so valuable. It's cuz you're bringing the secret sauce to be able to make that happen. Speaker 2: Gotcha, gotcha. One last thing. We talked about Xi and the two companies are working really closely where, essentially the Nutanix fabric can seamlessly seep into every Google platform as infrastructure worldwide. Xi, as a service, could be delivered natively with GCP, leading to some additional benefits, right? Bill: Absolutely. I think, first and foremost, the infrastructure we're building at scale opens up all sorts of possibilities. I'll just use, maybe, two examples. The first one is network. If you think about building out a global network, there's a lot of effort to do that. Google is doing that as a byproduct of serving our consumers. So, if you think about YouTube, if you think about there's approximately a billion hours of YouTube that's watched every single day. If you think about search, we have approximately two trillion searches done in a year and if you think about the number of containers that we run in a given week, we run about two billion containers per week. So the advantage of being able to move these workloads through Xi in a disaster recovery scenario first is that you get to take advantage of the scale. Secondly, it's because of the network that we've built out, we had to push the network out to the edge. So every single one of our consumers are using YouTube and search and Google Play and all those services, by the way we have over eight services today that have more than a billion simultaneous users, you get to take advantage of that network capacity and capability just by moving to the cloud. And then the last piece, which is a real advantage, we believe, is that it's not just about the workloads you're moving but it's about getting access to new services that cloud preventers, like Google, provide. For example, are you taking advantage like the next generation Hadoop, which is our big query capability? Are you taking advantage of the artificial intelligence derivative APIs that we have around, the video API, the image API, the speech-to-text API, mapping technology, all those additional capabilities are now exposed to you in the availability of Google cloud that you can now leverage directly from systems that are failing over and systems that running in our combined environment. Speaker 2: A true converged fabric across public and private. Bill: Absolutely. Speaker 2: Great stuff Bill. Thank you, sir. Bill: Thank you, appreciate it. Speaker 2: Good to have you. So, the last few slides. You know we've talked about, obviously One OS, One Click and eCloud. At the end of the day, it's pretty obvious that we're evaluating the move from a form factor perspective, where it's not just an OS across multiple platforms but it's also being distributed genuinely from consuming itself as an appliance to a software form factor, to subscription form factor. What you saw today, obviously, is the fact that, look you know we're still continuing, the velocity has not slowed down. In fact, in some cases it's accelerated. If you ask my quality guys, if you ask some of our customers, we're coming out fast and furious with a lot of these capabilities. And some of this directly reflects, not just in features, but also in performance, just like a public cloud, where our performance curve is going up while our price-performance curve is being more attractive over a period of time. And this is balancing it with quality, it is what differentiates great companies from good companies, right? So when you look at the number of nodes that have been shipping, it was around ten more nodes than where we were a few years ago. But, if you look at the number of customer-found defects, as a percentage of number of nodes shipped it is not only stabilized, it has actually been coming down. And that's directly reflected in the NPS part. That most of you guys love. How many of you guys love your Customer Support engineers? Give them a round of applause. Great support. So this balance of velocity, plus quality, is what differentiates a company. And, before we call it a wrap, I just want to leave you with one thing. You know, obviously, we've talked a lot about technology, innovation, inspiration, and so forth. But, as I mentioned, from last night's discussion with Sir Ranulph, let's think about a few things tonight. Don't take technology too seriously. I'll give you a simple story that he shared with me, that puts things into perspective. The year was 1971. He had come back from Aman, from his service. He was figuring out what to do. This was before he became a world-class explorer. 1971, he had a job interview, came down from Scotland and applied for a role in a movie. And he failed that job interview. But he was selected from thousands of applicants, came down to a short list, he was a ... that's a hint ... he was a good looking guy and he lost out that role. And the reason why I say this is, if he had gotten that job, first of all I wouldn't have met him, but most importantly the world wouldn't have had an explorer like him. The guy that he lost out to was Roger Moore and the role was for James Bond. And so, when you go out tonight, enjoy with your friends [inaudible 02:12:06] or otherwise, try to take life a little bit once upon a time or more than once upon a time. Have fun guys, thank you. Speaker 5: Ladies and gentlemen please make your way to the coffee break, your breakout sessions will begin shortly. Don't forget about the women's lunch today, everyone is welcome. Please join us. You can find the details in the mobile app. Please share your feedback on all sessions in the mobile app. There will be prizes. We will see you back here and 5:30, doors will open at 5, after your last breakout session. Breakout sessions will start sharply at 11:10. Thank you and have a great day. Section 13 of 13 [02:00:00 - 02:13:42]

>> Announcer: Live from midtown Manhattan, it's the Cube. Covering Big Data New York City 2017. Brought to you by SiliconANGLE Media and its ecosystem sponsors. >> Welcome back everyone, we are here live in New York City, in Manhattan for BigData NYC, our event we've been doing for five years in conjunction with Strata Data which is formerly Strata Hadoop, which was formerly Strata Conference, formerly Hadoop World. We've been covering the big data space going on ten years now. This is the Cube. I'm here with Aaron Kalb, whose Head of Product and co-founder at Alation. Welcome to the cube. >> Aaron Kalb: Thank you so much for having me. >> Great to have you on, so co-founder head of product, love these conversations because you're also co-founder, so it's your company, you got a lot of equity interest in that, but also head of product you get to have the 20 mile stare, on what the future looks, while inventing it today, bringing it to market. So you guys have an interesting take on the collaboration of data. Talk about what the means, what's the motivation behind that positioning, what's the core thesis around Alation? >> Totally so the thing we've observed is a lot of people working in the data space, are concerned about the data itself. How can we make it cheaper to store, faster to process. And we're really concerned with the human side of it. Data's only valuable if it's used by people, how do we help people find the data, understand the data, trust in the data, and that involves a mix of algorithmic approaches and also human collaboration, both human to human and human to computer to get that all organized. >> John Furrier: It's interesting you have a symbolics background from Stanford, worked at Apple, involved in Siri, all this kind of futuristic stuff. You can't go a day without hearing about Alexia is going to have voice-activated, you've got Siri. AI is taking a really big part of this. Obviously all of the hype right now, but what it means is the software is going to play a key role as an interface. And this symbolic systems almost brings on this neural network kind of vibe, where objects, data, plays a critical role. >> Oh, absolutely, yeah, and in the early days when we were co-founding the company, we talked about what is Siri for the enterprise? Right, I was you know very excited to work on Siri, and it's really a kind of fun gimmick, and it's really useful when you're in the car, your hands are covered in cookie dough, but if you could answer questions like what was revenue last quarter in the UK and get the right answer fast, and have that dialogue, oh do you mean fiscal quarter or calendar quarter. Do you mean UK including Ireland, or whatever it is. That would really enable better decisions and a better outcome. >> I was worried that Siri might do something here. Hey Siri, oh there it is, okay be careful, I don't want it to answer and take over my job. >> (laughs) >> Automation will take away the job, maybe Siri will be doing interviews. Okay let's take a step back. You guys are doing well as a start up, you've got some great funding, great investors. How are you guys doing on the product? Give us a quick highlight on where you guys are, obviously this is BigData NYC a lot going on, it's Manhattan, you've got financial services, big industry here. You've got the Strata Data event which is the classic Hadoop industry that's morphed into data. Which really is overlapping with cloud, IoTs application developments all kind of coming together. How do you guys fit into that world? >> Yeah, absolutely, so the idea of the data lake is kind of interesting. Psychologically it's sort of a hoarder mentality, oh everything I've ever had I want to keep in the attic, because I might need it one day. Great opportunity to evolve these new streams of data, with IoT and what not, but just cause you can get to it physically doesn't mean it's easy to find the thing you want, the needle in all that big haystack and to distinguish from among all the different assets that are available, which is the one that is actually trustworthy for your need. So we find that all these trends make the need for a catalog to kind of organize that information and get what you want all the more valuable. >> This has come up a lot, I want to get into the integration piece and how you're dealing with your partnerships, but the data lake integration has been huge, and having the catalog has come up with, has been the buzz. Foundationally if you will saying catalog is important. Why is it important to do the catalog work up front, with a lot of the data strategies? >> It's a great question, so, we see data cataloging as step zero. Before you can prep the data in a tool like Trifacta, PACSAT, or Kylo. Before you can visualize it in a tool like Tableau, or MicroStrategy. Before you can do some sort of cool prediction of what's going to happen in the future, with a data science engine, before any of that. These are all garbage in garbage out processes. The step zero is find the relevant data. Understand it so you can get it in the right format. Trust that it's good and then you can do whatever comes next >> And governance has become a key thing here, we've heard of the regulations, GDPR outside of the United States, but also that's going to have an arms length reach over into the United States impact. So these little decisions, and there's going to be an Equifax someday out there. Another one's probably going to come around the corner. How does the policy injection change the catalog equation? A lot of people are building machine learning algorithms on top of catalogs, and they're worried they might have to rewrite everything. How do you balance the trade off between good catalog design and flexibility on the algorithm side? >> Totally yes it's a complicated thing with governance and consumption right. There's people who are concerned with keeping the data safe, and there are people concerned with turning that data into real value, and these can seem to be at odds. What we find is actually a catalog as a foundation for both, and they are not as opposed as they seem. What Alation fundamentally does is we make a map of where the data is, who's using what data, when, how. And that can actually be helpful if your goal is to say let's follow in the footsteps of the best analyst and make more insights generated or if you want to say, hey this data is being used a lot, let's make sure it's being used correctly. >> And by the right people. >> And by the right people exactly >> Equifax they were fishing that pond dry months, months before it actually happened. With good tools like this they might have seen this right? Am I getting it right? >> That's exactly right, how can you observe what's going on to make sure it's compliant and that the answers are correct and that it's happening quickly and driving results. >> So in a way you're taking the collective intelligence of the user behavior and using that into understanding what to do with the data modeling? >> That's exactly right. We want to make each person in your organization as knowledgeable as all of their peers combined. >> So the benefit then for the customer would be if you see something that's developing you can double down on it. And if the users are using a lot of data, then you can provision more technology, more software. >> Absolutely, absolutely. It's sort of like when I was going to Stanford, there was a place where the grass was all dead, because people were riding their bikes diagonally across it. And then somebody smart was like, we're going to put a real gravel path there. So the infrastructure should follow the usage, instead of being something you try to enforce on people. >> It's a classic design meme that goes around. Good design is here, the more effective design is the path. >> Exactly. >> So let's get into the integration. So one of the hot topics here this year obviously besides cloud and AI, with cloud really being more the driver, the tailwind for the growth, AI being more the futuristic head room, is integration. You guys have some partnerships that you announced with integration, what are some of the key ones, and why are they important? >> Absolutely, so, there have been attempts in the past to centralize all the data in one place have one warehouse or one lake have one BI tool. And those generally fail, for different reasons, different teams pick different stacks that work for them. What we think is important is the single source of reference One hub with spokes out to all those different points. If you think about it it's like Google, it's one index of the whole web even though the web is distributed all over the place. To make that happen it's very important that we have partnerships to get data in from various sources. So we have partnerships with database vendors, with Cloudera and Hortonworks, with different BI tools. What's new are a few things. One is with Cloudera Navigator, they have great technical metadata around security and lineage over HGFS, and that's a way to bolster our catalog to go even deeper into what's happening in the files before things get surfaced and higher for places where we have a deeper offering today. >> So it's almost a connector to them in a way, you kind of share data. >> That's exactly right, we've a lot of different connectors, this is one new one that we have. Another, go ahead. >> I was going to go ahead continue. >> I was just going to say another place that is exciting is data prep tools, so Trifacta and Paxata are both places where you can find and understand an alation and then begin to manipulate in those tools. We announced with Paxata yesterday, the ability to click to profile, so if you want to actually see what's in some raw compressed avro file, you can see that in one click. >> It's interesting, Paxata has really been almost lapping, Trifacta because they were the leader in my mind, but now you've got like a Nascar race going on between the two firms, because data wrangling is a huge issue. Data prep is where everyone is stuck right now, they just want to do the data science, it's interesting. >> They are both amazing companies and I'm happy to partner with both. And actually Trifacta and Alation have a lot of joint customers we're psyched to work with as well. I think what's interesting is that data prep, and this is beginning to happen with analyst definitions of that field. It isn't just preparing the data to be used, getting it cleaned and shaped, it's also preparing the humans to use the data giving them the confidence, the tools, the knowledge to know how to manipulate it. >> And it's great progress. So the question I wanted to ask is now the other big trend here is, I mean it's kind of a subtext in this show, it's not really front and center but we've been seeing it kind of emerge as a concept, we see in the cloud world, on premise vs cloud. On premise a lot of people bring in the dev ops model in, and saying I may move to the cloud for bursting and some native applications, but at the end of the day there is a lot of work going on on premise. A lot of companies are kind of cleaning house, retooling, replatforming, whatever you want to do resetting. They are kind of getting their house in order to do on prem cloud ops, meaning a business model of cloud operations on site. A lot of people doing that, that will impact the story, it's going to impact some of the server modeling, that's a hot trend. How do you guys deal with the on premise cloud dynamic? >> Totally, so we just want to do what's right for the customer, so we deploy both on prem and in the cloud and then from wherever the Alation server is it will point to usually a mix of sources, some that are in the cloud like vetshifter S3 often with Amazon today, and also sources that are on prem. I do think I'm seeing a trend more and more toward the cloud and we have people that are migrating from HGFS to S3 is one thing we hear a lot about it. Strata with sort of dupe interest. But I think what's happening is people are realizing as each Equifax in turn happens, that this old wild west model of oh you surround your bank with people on horseback and it's physically in one place. With data it isn't like that, most people are saying I'd rather have the A+ teams at Salesforce or Amazon or Google be responsible for my security, then the people I can get over in the midwest. >> And the Paxata guys have loved the term Data Democracy, because that is really democratization, making the data free but also having the governance thing. So tell me about the Data Lake governance, because I've never loved the term Data Lake, I think it's more of a data ocean, but now you see data lake, data lake, data lake. Are they just silos of data lakes happening now? Are people trying to connect them? That's key, so that's been a key trend here. How do you handle the governance across multiple data lakes? >> That's right so the key is to have that single source of reference, so that regardless of which lake or warehouse, or little siloed Sequel server somewhere, that you can search in a single portal and find that thing no matter where it is. >> John: Can you guys do that? >> We can do that, yeah, I think the metaphor for people who haven't seen it really is Google, if you think about it, you don't even know what physical server a webpage is hosted from. >> Data lakes should just be invisible >> Exactly. >> So your interfacing with multiple data lakes, that's a value proposition for you. >> That's right so it could be on prem or in the cloud, multi-cloud. >> Can you share an example of a customer that uses that and kind of how it's laid out? >> Absolutely, so one great example of an interesting data environment is eBay. They have the biggest teradata warehouse in the world. They also have I believe two huge data lakes, they have hive on top of that, and Presto is used to sort of virtualize it across a mixture of teradata, and hive and then direct Presto query It gets very complicated, and they have, they are a very data driven organization, so they have people who are product owners who are in jobs where data isn't in their job title and they know how to look at excel and look at numbers and make choices, but they aren't real data people. Alation provides that accessibility so that they can understand it. >> We used to call the Hadoop world the car show for the data world, where for a long time it was about the engine what was doing what, and then it became, what's the car, and now how's it drive. Seeing that same evolution now where all that stuff has to get done under the hood. >> Aaron: Exactly. >> But there are still people who care about that, right. They are the mechanics, they are the plumbers, whatever you want to call them, but then the data science are the guys really driving things and now end users potentially, and even applications bots or what nots. It seems to evolve, that's where we're kind of seeing the show change a little bit, and that's kind of where you see some of the AI things. I want to get your thoughts on how you or your guys are using AI, how you see AI, if it's AI at all if it's just machine learning as a baby step into AI, we all know what AI could be, but it's really just machine learning now. How do you guys use quote AI and how has it evolved? >> It's a really insightful question and a great metaphor that I love. If you think about it, it used to be how do you build the car, and now I can drive the car even though I couldn't build it or even fix it, and soon I don't even have to drive the car, the car will just drive me, all I have to know is where I want to go. That's sortof the progression that we see as well. There's a lot of talk about deep learning, all these different approaches, and it's super interesting and exciting. But I think even more interesting than the algorithms are the applications. And so for us it's like today how do we get that turn by turn directions where we say turn left at the light if you want to get there And eventually you know maybe the computer can do it for you The thing that is also interesting is to make these algorithms work no matter how good your algorithm is it's all based on the quality of your training data. >> John: Which is a historical data. Historical data in essence the more historical data you have you need that to train the data. >> Exactly right, and we call this behavior IO how do we look at all the prior human behavior to drive better behavior in the future. And I think the key for us is we don't want to have a bunch of unpaid >> John: You can actually get that URL behavioral IO. >> We should do it before it's too late (Both laugh) >> We're live right now, go register that Patrick. >> Yeah so the goal is we don't want to have a bunch of unpaid interns trying to manually attack things, that's error prone and that's slow. I look at things like Luis von Ahn over at CMU, he does a thing where as you're writing in a CAPTCHA to get an email account you're also helping Google recognize a hard to read address or a piece of text from books. >> John: If you shoot the arrow forward, you just take this kind of forward, you almost think augmented reality is a pretext to what we might see for what you're talking about and ultimately VR are you seeing some of the use cases for virtual reality be very enterprise oriented or even end consumer. I mean Tom Brady the best quarterback of all time, he uses virtual reality to play the offense virtually before every game, he's a power user, in pharma you see them using virtual reality to do data mining without being in the lab, so lab tests. So you're seeing augmentation coming in to this turn by turn direction analogy. >> It's exactly, I think it's the other half of it. So we use AI, we use techniques to get great data from people and then we do extra work watching their behavior to learn what's right. And to figure out if there are recommendations, but then you serve those recommendations, either it's Google glasses it appears right there in your field of view. We just have to figure out how do we make sure, that in a moment of you're making a dashboard, or you're making a choice that you have that information right on hand. >> So since you're a technical geek, and a lot of folks would love to talk about this, so I'll ask you a tough question cause this is something everyone is trying to chase for the holy grail. How do you get the right piece of data at the right place at the right time, given that you have all these legacy silos, latencies and network issues as well, so you've got a data warehouse, you've got stuff in cold storage, and I've got an app and I'm doing something, there could be any points of data in the world that could be in milliseconds potentially on my phone or in my device my internet of thing wearable. How do you make that happen? Because that's the struggle, at the same time keep all the compliance and all the overhead involved, is it more compute, is it an architectural challenge how do you view that because this is the big challenge of our time. >> Yeah again I actually think it's the human challenge more than the technology challenge. It is true that there is data all over the place kind of gathering dust, but again if you think about Google, billions of web pages, I only care about the one I'm about to use. So for us it's really about being in that moment of writing a query, building a chart, how do we say in that moment, hey you're using an out of date definition of profit. Or hey the database you chose to use, the one thing you chose out of the millions that is actually is broken and stale. And we have interventions to do that with our partners and through our own first party apps that actually change how decisions get made at companies. >> So to make that happen, if I imagine it, you'd have to need access to the data, and then write software that is contextually aware to then run, compute, in context to the user interaction. >> It's exactly right, back to the turn by turn directions concept you have to know both where you're trying to go and where you are. And so for us that can be the from where I'm writing a Sequel statement after join we can suggest the table most commonly joined with that, but also overlay onto that the fact that the most commonly joined table was deprecated by a data steward data curator. So that's the moment that we can change the behavior from bad to good. >> So a chief data officer out there, we've got to wrap up, but I wanted to ask one final question, There's a chief data officer out there they might be empowered or they might be just a CFO assistant that's managing compliance, either way, someone's going to be empowered in an organization to drive data science and data value forward because there is so much proof that data science works. From military to play you're seeing examples where being data driven actually has benefits. So everyone is trying to get there. How do you explain the vision of Alation to that prospect? Because they have so much to select from, there's so much noise, there's like, we call it the tool shed out there, there's like a zillion tools out there there's like a zillion platforms, some tools are trying to turn into something else, a hammer is trying to be a lawnmower. So they've got to be careful on who the select, so what's the vision of Alation to that chief data officer, or that person in charge of analytics to scale operational analytics. >> Absolutely so we say to the CDO we have a shared vision for this place where your company is making decisions based on data, instead of based on gut, or expensive consultants months too late. And the way we get there, the reason Alation adds value is, we're sort of the last tool you have to buy, because with this lake mentality, you've got your tool shed with all the tools, you've got your library with all the books, but they're just in a pile on the floor, if you had a tool that had everything organized, so you just said hey robot, I need an hammer and this size nail and this text book on this set of information and it could just come to you, and it would be correct and it would be quick, then you could actually get value out of all the expense you've already put in this infrastructure, that's especially true on the lake. >> And also tools describe the way the works done so in that model tools can be in the tool shed no one needs to know it's in there. >> Aaron: Exactly. >> You guys can help scale that. Well congratulations and just how far along are you guys in terms of number of employees, how many customers do you have? If you can share that, I don't know if that's confidential or what not >> Absolutely, so we're small but growing very fast planning to double in the next year, and in terms of customers, we've got 85 customers including some really big names. I mentioned eBay, Pfizer, Safeway Albertsons, Tesco, Meijer. >> And what are they saying to you guys, why are they buying, why are they happy? >> They share that same vision of a more data driven enterprise, where humans are empowered to find out, understand, and trust data to make more informed choices for the business, and that's why they come and come back. >> And that's the product roadmap, ethos, for you guys that's the guiding principle? >> Yeah the ultimate goal is to empower humans with information. >> Alright Aaron thanks for coming on the Cube. Aaron Kalb, co-founder head of product for Alation here in New York City for BigData NYC and also Strata Data I'm John Furrier thanks for watching. We'll be right back with more after this short break.

>> Announcer: Live from Los Angeles it's The Cube covering Open Source Summit North America 2017. Brought to you by the Linux Foundation and Red Hat. >> Hey, welcome back everyone. We're here live in L.A. for the Linux Foundation Open Source Summit North America. I'm John Furrier, your host, with Stu Miniman, my co-host. Our next guest Jim Zemlin, Executive Director of the Linux Foundation, runs the whole show. Welcome back to The Cube, great to see you. >> Thank you, thank you. Runs the whole show is a little bit of an overstatement. >> Well, certainly great keynote up there, I mean, a lot of things coming together. Just some structural things. Let's get the update on what's going on structurally with the Linux Foundation, one, and then two, the keynote today, this morning, really kind of laid out the state of the union, if you will, and all cylinders are pumping, no doubt, on open source. So give the quick update on kind of what's going on with the Linux Foundation and then let's get in some of the trends inside the open source movement. >> Yeah, I mean, our organization has grown quite a bit in the last few years as evident by all the people who are here at this event. But our focus is really on the projects that are important to, you know, the stability, security, and growth of the global internet and of large-scale systems. And when you look at Linux or Node.js or things like our networking projects which are powering the production networks for 3 1/2 billion people, what we're really focused on is making sure those projects are healthy, making sure that they have great developers who write incredible code, that it's used to power things like China Mobile's network or AT&T's production network. And then, those firms are employing the developers who then write more code, you get more solutions, products, services based on Linux or whatever. More reinvestment, lather, rinse, repeat. It's that cycle we're trying to promote. >> So before we get into some of the stats, structurally, I know this show, we've Cube comments out there, clarify the structure. How the shows are rolling out, how are you guys putting together the big-tent events, and how developers can get involved in the specific events across, but now there's a ton of projects. But just at a high level, what's the structure? >> Yeah, so, you know, and I'll throw out a few stats. We have about 25,000 developers that attend all of our events which are all over the world. But we have our Open Source Summit which is really sort of a summit to come together and talk about these big-picture issues around sustainability to allow for cross-project collaboration. We have project-specific events so the CloudNativeCon, KubeCon event which is coming up in Austin which is going to be blow-out, you know, I'm expecting thousands of people. I think probably three, 4,000 people. >> And even more platinum sponsors than I've ever seen on any project before so huge demand. >> It's crazy, yeah. Yeah, you know, get it while it's good, right? All these things kind of go up and down but they're on the upswing. So we have project-specific and then in the networking sector, we have have the Open Networking Summit which is sort of similar to the Open Source Summit but much more focused on networking technology, SDN, and NFD, and that is going to be in L.A. next year and we'll have a U.S. event and then a European and an Asian. >> And this show's purpose is what? How would you position the Open Source Summit? >> The Open Source Summit is where all the projects come together and do cross-pollination. I mean, the idea here is that if you're just always in your silo, you can't actually appreciate what someone else is doing that may improve your project. >> And Jim, there's a couple of events that came together to make this 'cause it was LinuxCon, ContainerCon, and MesosCon is also co-resident so. >> Exactly, so we just decided after a while that all these events could come together and again, this cross-pollination of ideas. >> And they kind of did, they're just different hotels in Seattle last time. >> Yeah, exactly. That's enough, it's just going to be Open Source-- >> It's a big-tent event. >> It's a big-tent event and it really reflects how open source has gone mainstream in a way that I don't think any of us would've predicted even maybe five, six years ago. >> It's pretty massive. Just to quote some stats. 23 million plus open source developers, what you shared onstage there, want to get to your keynote. 41 billion lines of code. 1,000 plus new projects a day. 10,000 new versions pushed per day. 64 million repos on GitHub. Just amazing growth so this kind of points to obviously the rising tide is floating all boats. I made a comment, I tweeted, in the spirit of the joke of standing on the shoulders of giants before you, it's like, what shoulders are we standing on now? Because there's so many projects. Is there going to be like a legacy like the dual-star, badge values, been around for a while? You mentioned old news and you bring up Linus onstage. I mean, some projects are older, more mature, Bruce Wayne, Tier One, meat and potatoes, some got a little bit more flair and fashion to it, if you will. So you got new dynamics going on. Share your thoughts on this. >> Yeah, I mean, it's like the shoulders you're standing on are almost like stage-diving, right? Where it's just lots of people's shoulders that you're really bouncing around on. But the idea here, and what we really focus on, is what are the most important projects in the world and how do we make sure we sustain those projects. So those are the ones that you're going to generally see focused on here. Like, you know, if you've got two people contributing to one small repo for a very small project, that's probably not something that's going to be super high-profile here. But what we're trying to do is bring together sort of the big projects and also the key contributors. You know, if you look at the distribution of contribution, and this is the thing, I think, if you're a developer listening to something like this, someone who gives just one commit to a project to solve some kind of problem they might have, that's the vast majority of people. Somebody who does maybe five to 10 commits, you know, a little bit less, quite a bit less. The vast majority of code, people who give 25 or more commits to a project, small group of folks, they're here. >> I know Stu wants to ask a question, one final question on the growth 'cause this kind of reminds me of sports as we're like the ESPN of tech here for the community. If you look at the growth, you put a slide in there by SourceClear that show the projection, by 2026, at 400 million libraries, putting it today around, I think, 64 million. This is going to be like an owners meeting. It's kind of like they get together, this event because you are going to have so many projects 'cause this is kind of the vibe you got going on in here. The scale is massive, this is going to be almost like the owners meeting, the teams. Expansion's going to be coming, you have to deal with that, that's challenging. >> We're ready to grow, I mean, we've been working on systems and staffing and processes to help scale with that. You know, we take seriously that that code runs modern society. It keeps us private or doesn't as we saw with the Equifax hack which was a CVE in an open source project and we want to be ready to up our game. Let's say we could have secure coding class at this very event for the greatest developers who are working on our most important projects in the world. Would that make all of our lives better? Yes, absolutely. >> Yes, absolutely would. Yeah and you want to enable that, that's where you're going. >> That's exactly where we're going. >> Jim, the quote that jumped out at me that you gave in the keynote was, projects with sustainable ecosystems are the ones that matter. How do we balance all this? I heard in, you know, Linus's Q and A it was, look, individual's important but companies are important. You put up a slide and said, there's thousands and thousands of projects, sometimes we're going to get some really awesome stuff from three people contributing code versus the massive ecosystem with all the platinum providers so, it's always in technology, it's an and and it's very nuanced but how do we get our arms around this? How do we know where to focus? >> It's worth going back in time to understand where the future is going and study innovation theory, you know, Eric von Hippel at MIT, or Karim Lakhani at Harvard Business School. And you look at the framework, which is, you have corporations who underwrite a lot of development by hiring developers who have an equal importance in this and then users of that software. So those are your main constituents and sometimes they're the same people, right, or the same things. They're not mutually exclusive, they're actually self-reinforcing if you get the formula right and you make sure that the project is in good shape so that it gives confidence to industry or society that, hey, we can count on that. I think Heartbleed and OpenSSL maybe rattled people's cages like, hey, can we count on, not just this project, but can we count on open source period? So we spent a ton of time working with that project to provide them millions in resources, audited their code, expanded their testing, and we learned a hell of a lot about how to support these communities in the most important developer projects in the world and create that positive feedback loop, that's what we're doing. >> Yeah and Jim, it's, as an analyst, one of the things we're always asked is, right, how do I choose the right technology? Whereas companies now are contributing here so it's not just I'm putting dollars in, I'm putting manpower into this. And the foundations sometimes get a lot of lung from people, saying it's like, oh well, people throw money and what do they get out of it? I liked what I heard today, you talking about this cycle, and maybe talk to our audience a little bit about CHAOSS which I though was a nice, tongue-in-cheek acronym to say how you're actually going to bring order to the chaos that we see in the open source world. >> I'm going to come to this but I want to answer one quick question about the roles of organizations like ours. We are the roadies, the supporting cast, and the plumbers and the janitors of the system that keep things going but the real rock stars are the developers. If you think about it, Linux is worth $10 billion. An average kernel developer makes probably, let's say $150,000 a year, by the way, they make more than your average developer because they're in such high demand. The role of organizations like ours is such a tiny fraction financially of what is really fueling this model but it's an important one. What we ask ourselves all the time is, why do you need us? Who cares, right? Like, throw your code up on GitHub, you don't need the Linux Foundation, right? Why do we even exist? And the answer is to do things like this Community Health Analytics for Open Source Software, to provide the infrastructure for sustainability. Sustainability is something that we need to measure, right? How many developers are contributing to a project? Are they from a diverse community so that if one group goes away, there'll be somebody else there to do that work? How much test coverage do they have? Are there code quality metrics that we could look at? Do they have security practices like a responsible disclosure policy, a security mailing list? Have they recently fuzzed their code? Are they a community that's welcoming for people of different backgrounds? And so on and so forth. If you don't have a healthy project, you kind of don't want to bet your company on this project by using it in a production system, right? But here's the interesting thing, how many people are using that code in production also is a metric for health, right? Because that's where the reinvestment is going to come in the form of developers who are working on it. >> There's a difference between being proactive and jamming something down someone's throat. So you're taking an approach, if I get this right, to be kind of the same open source ethos, use some KPIs, key performance indicators, to give them a sense of success. But it's not an edict saying-- >> No, no, it can't be an edict. What you want to do is preserve the organic innovation that goes on in open source and get projects to go, and you'll notice that curve of sort of value to volume goes up and to the left, we could've written it to the right but, you know, the whole copyleft thing we love. How do you get that organic innovation to kind of go from this small project up and to the left? How do you capture that? Well, give tools to everyone so that they can better self-analyze. >> John: You get exponential growth with that. >> Exactly. >> If you try to control, it's linear but you bring it to the community, you get exponential growth. >> Exactly, so we studied a ton of innovation theory, we looked at how we could build frameworks to facilitate this kind of form of mass innovation and so that's where tools like CHAOSS which is being worked on by Red Hat and a lot of companies who want to figure out which project should I work on? How can I spot that one earlier? And we're excited about it. >> You know, I always joke, being the old guy that I am, in the late '80s, early '90s, '80s particularly when I was coding. We did everything, we wrote all the code. You bring up an interesting stat and you put the finger on, at least for me, and I think this is where a lot of us old timers who had to do all the libraries from scratch. You mentioned the code sandwich, the code club, the club sandwich, how code's being made and the interesting thing, as you point out, 90% of most great software is done with open source where the 10% innovation is done with original code or original content, if you will, and that that is the norm. So open source is now called the code sandwich because you can put your differentiation and that's a good use of time. >> That's the meat, right. >> That's the meat, it's not a wish sandwich to use the old Blues Brothers example but I mean look, the thing is is that that's dynamic is real, the code is leverageable, and that this is the dynamic so where'd the number come from? Because that seems really high to me but I love it. >> So that number came from a combination of Sonatype, SourceClear, and other organizations that monitor commercial reuse of software on a global basis. So these are the folks who are actually working with commercial industry to look at the makeup of their code, basically. You don't have to go far to look at a Node.js developer, they're using Node.js, they're taking packages out of NPM, and they're writing, they're cut and paste masters, but they write this critical component that's the meat of their application, it's what they do. >> But that's the innovation fabric that's happening. >> It also is a requirement because let's look at a modern, luxury vehicle today. It has 100 million lines of code in it. That's more than an F-35, like, fighter jet. That's an unbelievable amount of code. Toyota, who we work with, and you know, our AGL, our Automotive Grade Linux, is in their Camry. They couldn't write that code on their own. It's just too much. And this is how we get to autonomous vehicle control and things like that. >> I know you got a tight schedule, I want to make one more comment, get your reaction to it. I made a tweet and said, it's open bar in open source and with a reference to all the goodness being donated by companies, Google TensorFlow, there's a lot of other things coming in, these libraries. A lot of people are bringing really, really big IP to the table, IoT, and I kind of made an open remark 'cause a lot of the young kids, they think this is normal, like, well it's going to get better. Keep on drinking that open source. Is this normal? Is it going to be more like this in the future? Because you have essentially real intellectual property, like say from Google, being given to the open source communities as a gift for innovation. I mean, that is just unprecedented greatness. >> The reason for that is they're not doing it necessarily altruistically although I think you can take it that way, they're doing it in a way that betters themselves and others at the same time. I mean, it is a form of collective capitalism where they've realized, my value's over here, it is better for me to collaborate on underlying infrastructure software that my customers don't care about that's not critical to my system but I absolutely have to have and I'm going to focus on data or I'm going to focus on much higher-level innovation. And what that's doing is creating this hockey stick of innovation where, as we share more and more and more infrastructure software, and as that keeps moving up and up the stack, we all benefit. >> So in the theory of the management, bring up management theory, their theory, I'd love to get your thoughts on, is that they're betting on scale rather than trying to go for profits in the short-term, they'd much rather share intellectual property on the back-end value of scale and scale's the new competitive advantage. >> Exactly, take Kubernetes as an example. The fact that, today, and just even a couple years ago this wasn't known, we didn't quite know where this was going to be, but today you can take Node.js, build a container, you know, take an application, throw it into a container, and use Kubernetes to run it on Azure, Amazon, Google, or in a private cloud. That definition, the ability to do that, unlocks this massive developer productivity which creates more value which is more business opportunity for all these guys. You know, they're not doing it 'cause they're nice people, they're doing it 'cause they're unlocking market potential. >> And they're the real rock stars. Jim you're doing a great job. Congratulations on your success. You got a lot of growth in front of you, a lot of challenges and opportunities certainly with that and of course, the tech athletes out there doing the coding, they're the real rock stars, they're the real athletes. Of course, we get more on The Cube, thanks for your support with The Cube as well, appreciate that. >> Jim: Thank you, thanks for everything. >> Alright, this is live coverage from Open Source Summit North America in Los Angeles, California. I'm John Furrier, Stu Miniman, we'll be back with more live coverage after this short break.

(energetic techno music) >> Announcer: Live from Washington D.C., it's theCUBE. Covering AWS Public Sector Summit 2017. Brought to you by Amazon Web Services, and its partner, Ecosystem. >> Interviewer: So what can Fugue do for you? Well, I'm going to guess that they can take your agency to the Cloud. >> Josh: You're, you're correct, Jeff. >> John W.: That's exactly what I'm looking at over here, the Fugue booth here, on the show floor at AWS Public Sector Summit 2017. Welcome inside, live on theCUBE channel, John Wells and John Furrier, and Josh Stella, who is the founder, and CEO of Fugue. Did I get it right, by the way? >> You did get it right. >> Jeff: You're taking the agencies to the Cloud, correct. >> Taking agencies to the Cloud, taking companies to the Cloud, too, but of course, this is worldwide public sector, so we're focused on the agencies today. >> Yeah, we were just talking before this even started, just a little historical background here, you were with Amazon back in 2012, when this show started, and you told me that your commission with your colleagues was to get 600 attendees. >> Yeah, we wanted to get 600, I think we got 750, which is classic Amazon style, right. >> John W.: Bonus year. >> We go over. But yeah, over 10,000 registered this year, it's amazing. >> Which shows you that this explosive growth of this area, in terms of the public sector. So let's talk about Fugue a little bit. >> Sure. >> Before we dive a little bit, share with our viewers, core competencies, what your primary mission is. >> So Fugue is an automation system. Fugue is a way to completely automate the Cloud API surface. It's true infrastructure as code, so unlike a deployment tool that just builds something on Cloud, Fugue builds it, monitors it, self-heals it, modifies it every time, alerts if anything drifts, and we've added a layer to that for policy as codes. So you can actually express the rules of your organization, so if you're a government agency, those might be NIST or FISMA rules. If you're a start-up, those might be, we don't open SSH to the world. Those can be just expressed as code. So Fugue fully automates the stack, it doesn't just do deployment, and we just released the team conductor, that will manage dozens of AWS accounts for you, so many of our customers in financial services, and other enterprises have many, many AWS accounts. Fugue allows you to kind of centralize all of that control without slowing down your developers. Without getting in the way of going fast. >> John W.: And what, why is that big news? >> It's big news because in the past, the whole core value prop of Cloud is to go fast, is to innovate, iterate, be disruptive, and move quickly. What happens, though, is as you do that, at the beginning, when you're starting small, it looks pretty easy. You can go fast. But you learn pretty quickly over time that things get very messy and complex. So Fugue accelerates that going-fast part, but keeps everything kind of within the bounds of knowing who's running things, knowing what resources you're actually using. Who built what, who has permissions to do what. So it's really this foundational layer for organizations to build and control Cloud environments. >> Josh, one of the things we talked about in the opening was the government's glacial case of innovation over the years. But the pressure is on the innovate. So the, lot of emphasis on innovation. In an environment that's constrained by regulation, governance, policies. So they have kind of an Achilles heal there, but Cloud gives them an opportunity at a scale point to do something differently, I want to dip into that, but I'll set this question up by quoting a CIO I chatted with who's in the government sector. He's like, "Look, Cloud's like, jumping out of a plane "with a parachute I didn't even know was going to open up." So this is kind of a mindset, he was over generalizing, but again, to the point is, trust, scale, execution, risk. >> Mhm, mhm. >> It's a huge thing. >> Absolutely. >> How do you guys solve that problem for the agencies that want to go to the Cloud, because, certainly they want to go there, I think it's a new normal as Werner said. What do you guys do to make that go away? How do you make it go faster? >> Sure, so Amazon and other Cloud vendors have done a great job of building a very highly trusted, low level infrastructure that you can put together into systems. That's really the core offering. But there's still, in government agencies, as you point out, this need to follow rules and regulations and policies, and check those. So, one of the things Fugue does, is allows you to actually turn those rules into executable compiled code. So, instead of finding out you're breaking a rule a month later, in some meeting somewhere, that's going to loop back, it'll tell you in ten milliseconds. And how to fix it. So we allow you to go just as fast as anyone can on Cloud, but meeting all those extra constraints and so on. >> So you codify policies, and governance type stuff, right? >> That's part of what we do, but we also automate the entire infrastructure and grid. >> So this is the key, this is what I want to kind of jump to that next point. That's cool, but it would make sense that machine learning would probably be like an interesting take away. Cuz' everyone talks about training, data models, and it sounds like what you're doing, if you codify the policies, you probably set up well for growing and scaling in that world. Is that something that's on your radar? >> Sure. >> How do you guys look at that whole, okay I've got machine learning coming down the pike, everyone wants to get their hands on some libraries, and they want to get to unsupervised at some point. >> Yes, yeah it's a great question. So Fugue is really a bridge to that future where the entire infrastructure layer is automated and dynamic. And that's what you're talking about, where you have machine learning that are helping you make decisions about how to do computing. A lot of folks aren't ready for that yet. They're still thinking about the Cloud as kind of a remote data center, in our view, it's actually just a big distributed computer. And so, when you think about things like whether it's machine learning, or just algorithms to run over time that modify these environments to make them more efficient. Fugue is definitely built to get you there, but we start where you're comfortable now, which is just the first thing we have. >> Yeah of course, when you're still early to tells in the water, all kinds of data issues, you see the growth there. So the question is, what is the low hanging fruit for you? What are the use cases? Where are you guys winning, and what's new with your codifying the policies that you're releasing here? What's the use cases, and what're you guys releasing? >> Yeah, so common use case for us is integration with CI, CD, and DevOps for the entire infrastructure chain. So, you'll have organizations that want to go to a fully automated deployment management of infrastructure. And what they've learned in the past is, without Fugue, they might get some of the deployment automated, with a traditional CM tool or something like this, but because they're not doing the self healing, the constant maintenance on the environment, the updating of the environment, the alerting on it, there's a big missing link in terms of that automation. So, we're getting a lot of resonance in the financial services sector, and folks who are sophisticated on Cloud, and are doing large-scale Cloud operations. So, if you think about, uh, Netflix can build full automation for themselves, because they're Netflix. But not everyone fits in that boat. So Fugue is sort of the sorts of capabilities that Netflix built in a very specific way for themselves, we don't use their tools. We're a general purpose solution to that same class of problems. So, really, where we're winning is in automation of, again, deployments and operations of those deployments, but also in things like policy. We're seeing that not just in government but in the private sector as well. >> What are the big bottlenecks, what are the roadblocks for the industry? >> The roadblocks for the industry certainly are bringing, sort of, a legacy patterns to Cloud. Imagining it's a remote data center, thinking of it as virtual machines and storage, instead of just, infinite compute, and infinite resources that you put together. >> John F.: So the mindset's the bottleneck. >> Absolutely, it's cultural, yeah, yeah. And skillset, because in the DevOps Cloud world, everything should be code, and therefore everyone has to be a developer. And so, that's a little new. >> Is scale a big issue for you guys, with your customers? Is that something that they're looking for? And what's the kind of, scope of some of your customers and your use cases in government Clouds. >> Yeah, sure, absolutely. I mean, a lot of us came from AWS, so we know how to build things at scale. But yeah, y'know, a lot of folks start small with Fugue, but they go to very large, very quickly, has been our experience. So, scale across dozens, or hundreds AWS accounts-- >> That's where the automation, if they're not set up properly, bites them in the butt pretty much, right? >> Absolutely, absolutely. So yeah, we get a lot of that too. Going back in and helping people put their system back together the right way for Cloud, because they went there from the-- >> Alright, so what's the magnified learnings from this, from your experience with your company, mobile rounds of finance, you guys are well financed, one of the best venture capitals, the firm's NEA, great backer, you guys are doing well. Over the years, what have you learned, what's the magnification of the learnings, and how do you apply it to today's marketplace? >> Um, we are in a massive transition. We're just beginning to see the effects of this transition. So, from 1947 until the Cloud, you just had faster, smaller, Von Neumann machines in a box. You had any ax that got down to the size of your wristwatch. The Cloud is intrinsically different. And so there is an opportunity now, that's a challenge, but it's a massive opportunity to get this new generation of computing right. So I'd say that the learnings for me, as a technologist coming into a CEO role, are how to relate these deeply technical concepts to the world in ways that are approachable, and that can show people a path that they want to get involved with. But I think the learnings that I've had at AWS and at Fugue are, this is the beginning of this ride. It's not going to end at containers, it's not going to end at Lambda, it's going to continue to evolve. And the Cloud in ten years is going to look massively different than it does now. >> So, when you said, "to get it right," the computer, I mean, such as, or in what way, I mean, we have paths right, routes you could take. So you're saying that there are a lot of options that will be pitfalls, and the others that would be great opportunities. >> Well, that's absolutely right. So, for example, betting on the wrong technologies too soon, in terms of where the Cloud is going to finally land, is a box canyon, right. That's an architectural dead end. If you cannot compose systems across all these disparate Cloud surfaces, the application boundary, the system boundary is now drawn across services. You used to be able to open an IDE, and see your application. Well, now that might be spread across virtual machines, containers, Lambda, virtual discs, block storage, machine learning services, human language recognition services. That's your application boundary. So, if you can't understand all of that in context, you're in real trouble. Because the change is accelerating. If you look at the rate of new services, year over year in the Cloud, it's going up, not down. So the future's tougher. >> So, if I'm a government service, though, and I think John just talked about this, I'm just now getting confidence, right? >> Yes. >> I'm really feeling a little bit better, because I met somebody to hold my hand. And then I hear on the other hand, say, we have to make sure we get this right. So now all of a sudden, I'm backing off the edge again. I'm not so sure. So how do you get your public sector client base to take those risks, or take those daring steps, if you will. You know, we've had a lot of really great conversations and have a lot of great relationships in public sector, what we're seeing there is, like in the commercial world. I mean, public sector wasn't that far behind commercial on Cloud. When I was at Amazon, y'know, five years ago, I worked mostly with public sector costumers, and they were trying hard there, they were champions already, moving there. So, one of the things that Fugue does very effectively is, because we have this ability to deterministically, programmatically follow the rules, it takes it off of the humans, having to go and check. And that's always the slow and expensive part. So we can give a lot of assurance to these government agencies that, for example, if one of their development teams chooses to deploy something to Cloud, in the past, they'd have to go look for that. Well, with Fugue, they literally cannot deploy it, unless it's correct. And that's what I mean by "get it right." Is the developer, who's sitting there, and I've been a developer for decades, they want to do things by the rules. They want to do things correctly. But they don't always want to read the stack of books like this, and follow, y'know, check their boxes. So, with Fugue, you just get a compiler error and you keep going. >> Josh, I wanted to ask you about a new category we see emerging, it's really not kind of mainstream yet, by Wikibon research, and still getting in theCUBE, we get to see things a little bit early. Plus we have a data science team to skim through the predictive analytics. One thing that's clear is SAS businesses are emerging. So, SAS is growing at an astounding rate, platform is a service, and infrastructure's a service, I mean, Javassist doesn't think to see it that way, I don't you do either. It's infrastructure and SAS pretty much. So pretty much, everyone's going to, at some point, be a Cloud service provider. And there'll be a long tail distribution, we believe, on niche, to completely huge, and the big ones are going to be the Amazons, the Facebooks, the Google, but then there's going to be service providers that is going to emerge. They're going to be on Clouds, with governments, so we believe that to be true. If you believe that to be true, then the question is, how do I scale it? So, now I'm a solution architect in an enterprise. And like you said, it's intrinsically different in the Cloud than it was, say on premise, or even the critical traditional enterprise computing. I've got to now completely change my architectural view. >> Yes. >> If you think it's a big computer, then you've got to be an operating systems guy. (laughs) You've got to say, okay, there's a linker, there's a load, there's a compiler, I've got subsystems, I got IO. You got to start thinking that way. How do you talk to your friends, and colleagues, and customers around how to be a new solutions architect. >> Yeah, so I think it's a balancing act. Because we are this transition stage, right. The modern Cloud is still a Prius. (chuckles) And the future Cloud is the Tesla, in terms of how customers use it. We're in this transition phase in technologies, so you have to have one foot in both camps. Immutable infrastructure patterns are incredibly important to any kind of new development, and if you go to the Fugue.cosite or O'Reily, we wrote a little book with them on immutable infrastructure patterns. So, the notion there is, you don't maintain anything, you just replace it. So you stand a compute instance, Verner likes to talk about, these are cattle, not pets, Y'know, or paper cuff computing, that's right. You never touch it, you never do configuration management, you crumple it up, throw it away, and make a new one. That's the right new pattern, but a lot of the older systems that people still rely upon don't work that way. So, you have to have a foot in each camp as a solutions architect in Cloud, or as the CEO of a Cloud company. You have to understand both of those, and understand how to bridge between them. And understand it's an evolution-- >> And the roles within the architecture, as well. >> That's right. >> They coexist, this coexistence. >> Absolutely. You know, it's interesting you said, "everyone's going to become a service provider." I'd put that a little differently, the only surface that matters in the future is APIs. Everything is APIs. And how you express your APIs is a business question. But, fundamentally, that's where we are. So, whether you're a sales force with a SAS, I really don't like the infrastructure and SAS delineation, because I think the line's very blurred. It's just APIs that you compose into applications. >> Well, it's a tough one, this is good debate we could have, certainly, we aren't going to do it live on theCUBE, and arm wrestle ourselves here, and talk about it. But, one of the things about the Cloud that's amazing is the horizontal scalability of it. So, you have great scalability horizontally, but also, you need to have specialty, specialism at the app layers. >> Josh: Yes. >> You can't pick one or the other, they're not mutually exclusive. >> Josh: That's right. >> So, you say, okay, what does a stack look like? (laughs) If everything's in API, where the hell's the stack? >> Yeah, well that's why we write Fugue. Because Fugue does unify all that. Right, you can design one composition in Fugue. One description of that stack. And then run the whole thing as a process, like you would run Apache. >> So you're essentially wrapping a system around, you like almost what Docker Containers is for microservices. You are for computing. >> And including the container's managers. (John F. Laughs) So that's just one more service to us, that's exactly right. And, y'know, you asked me earlier, "how does this affect agencies?" So one thing we're really excited about today is, we just announced today, we're live on GovCloud, so we support GovCloud now, you can run in the commercial regions, you can run in GovCloud, and one of the cool things you can do with Fugue, because of that system wrapping capability, is build systems in public regions, and deploy them on GovCloud and they'll just work, instead of having to figure out the differences. >> Oh that's what what you think about the Cloud, standing up's something that's a verb now. "Hey I'm going to stand this up." That's, what used to be Cloud language, now that's basically app language. >> I think what you're getting at here is something near to my heart, which is all there are anymore are applications. Talking about infrastructure is kind of like calling a chair an assembly of wood. What we're really about are these abstractions, and the application is the first class citizen. >> I want to be comfortable, and sit down, take a load off. >> Josh: That's right, that's right. >> That's what a chair does. And there's different versions. >> John W.: You don't want to stand up, you want to sit down. >> And there's different, there's the Tesla of the chairs, and then there's the wooden hard chair for your lower back, for your back problems. >> Josh: Exactly, exactly. >> The Tesla really is a good use case, because that points to the, what I call, the fine jewelry of a product. Right, they really artistically built amazing product, where the value is not so much the car, yeah there's some innovations with the car, you've got that, with electric. But it's the data. The data powering the car that brings back the question of the apps and the data, again, I want to spend all my time thinking about how to create a sustainable, competitive advantage, and serve my customers, rather than figure out how to architect solutions that require configuration management, and tons of labor. This is here the shift is. This is where the shift is going from non-differentiated operations to high-value added capabilities. So, it's not like jobs are going up. Yeah, some jobs are going away, I believe that. But, it's like saying bank tellers were going to kill the bank industry. Actually, more branches opened up as a result. >> Oh yeah, this is the democratization of computing as a service. And that's only going to grow computing as a whole. Getting back to the, kind of, fine jewelry, you talked about data as part of that, I believe another part of that is the human experience of using something. And I think that is often missing in enterprise software. So, you'll see in the current release of Fugue, we just put into Beta a very, we've spent about two years on it, a graphic user interface that shows you everything about the system in an easily digestible way. And so, I think that the, kind of, the effect of the iPhone on computing in the enterprise is important to understand, too. The person that's sitting there at an enterprise environment during their day job gets in their Tesla, because they also love beautiful things. >> Well, I mean, no other places for you guys to do that democratization, and liberation, if you will. The government Cloud, and public sector, is the public sector. They need, right now they've been on antiquated systems for (chuckles) yeah, not only just antiquated, siloed, y'know, Cobol systems, main framed, and they've got a lot of legacy stuff. >> There is, there's a lot of legacy stuff, and they're a lot of inefficiencies in the process model in how things get done, and so, we love that AWS has come in, and when we were there, we helped do that part. And now with Fugue, we want to take these customers to kind of, the next level of being able to move forward quickly. >> Well, if you want to take your agency to the Cloud, Fugue is your vehicle to do that. Josh Stella, founder, CEO. Thanks for being with us here on theCUBE. >> Thanks so much. >> We appreciate it. We'll continue, live from Washington, D.C. Nation's capital here, AWS Public Sector Summit, 2017 on theCUBE. >> John F.: Alright, great job, well done. (upbeat techno music)