>>From the Cube Studios in Palo Alto in Boston, bringing you data-driven insights from the cube and E T R. This is breaking analysis with Dave Valante. >>Making technology predictions in 2022 was tricky business, especially if you were projecting the performance of markets or identifying I P O prospects and making binary forecast on data AI and the macro spending climate and other related topics in enterprise tech 2022, of course was characterized by a seesaw economy where central banks were restructuring their balance sheets. The war on Ukraine fueled inflation supply chains were a mess. And the unintended consequences of of forced march to digital and the acceleration still being sorted out. Hello and welcome to this week's weekly on Cube Insights powered by E T R. In this breaking analysis, we continue our annual tradition of transparently grading last year's enterprise tech predictions. And you may or may not agree with our self grading system, but look, we're gonna give you the data and you can draw your own conclusions and tell you what, tell us what you think. >>All right, let's get right to it. So our first prediction was tech spending increases by 8% in 2022. And as we exited 2021 CIOs, they were optimistic about their digital transformation plans. You know, they rushed to make changes to their business and were eager to sharpen their focus and continue to iterate on their digital business models and plug the holes that they, the, in the learnings that they had. And so we predicted that 8% rise in enterprise tech spending, which looked pretty good until Ukraine and the Fed decided that, you know, had to rush and make up for lost time. We kind of nailed the momentum in the energy sector, but we can't give ourselves too much credit for that layup. And as of October, Gartner had it spending growing at just over 5%. I think it was 5.1%. So we're gonna take a C plus on this one and, and move on. >>Our next prediction was basically kind of a slow ground ball. The second base, if I have to be honest, but we felt it was important to highlight that security would remain front and center as the number one priority for organizations in 2022. As is our tradition, you know, we try to up the degree of difficulty by specifically identifying companies that are gonna benefit from these trends. So we highlighted some possible I P O candidates, which of course didn't pan out. S NQ was on our radar. The company had just had to do another raise and they recently took a valuation hit and it was a down round. They raised 196 million. So good chunk of cash, but, but not the i p O that we had predicted Aqua Securities focus on containers and cloud native. That was a trendy call and we thought maybe an M SS P or multiple managed security service providers like Arctic Wolf would I p o, but no way that was happening in the crummy market. >>Nonetheless, we think these types of companies, they're still faring well as the talent shortage in security remains really acute, particularly in the sort of mid-size and small businesses that often don't have a sock Lacework laid off 20% of its workforce in 2022. And CO C e o Dave Hatfield left the company. So that I p o didn't, didn't happen. It was probably too early for Lacework. Anyway, meanwhile you got Netscope, which we've cited as strong in the E T R data as particularly in the emerging technology survey. And then, you know, I lumia holding its own, you know, we never liked that 7 billion price tag that Okta paid for auth zero, but we loved the TAM expansion strategy to target developers beyond sort of Okta's enterprise strength. But we gotta take some points off of the failure thus far of, of Okta to really nail the integration and the go to market model with azero and build, you know, bring that into the, the, the core Okta. >>So the focus on endpoint security that was a winner in 2022 is CrowdStrike led that charge with others holding their own, not the least of which was Palo Alto Networks as it continued to expand beyond its core network security and firewall business, you know, through acquisition. So overall we're gonna give ourselves an A minus for this relatively easy call, but again, we had some specifics associated with it to make it a little tougher. And of course we're watching ve very closely this this coming year in 2023. The vendor consolidation trend. You know, according to a recent Palo Alto network survey with 1300 SecOps pros on average organizations have more than 30 tools to manage security tools. So this is a logical way to optimize cost consolidating vendors and consolidating redundant vendors. The E T R data shows that's clearly a trend that's on the upswing. >>Now moving on, a big theme of 2020 and 2021 of course was remote work and hybrid work and new ways to work and return to work. So we predicted in 2022 that hybrid work models would become the dominant protocol, which clearly is the case. We predicted that about 33% of the workforce would come back to the office in 2022 in September. The E T R data showed that figure was at 29%, but organizations expected that 32% would be in the office, you know, pretty much full-time by year end. That hasn't quite happened, but we were pretty close with the projection, so we're gonna take an A minus on this one. Now, supply chain disruption was another big theme that we felt would carry through 2022. And sure that sounds like another easy one, but as is our tradition, again we try to put some binary metrics around our predictions to put some meat in the bone, so to speak, and and allow us than you to say, okay, did it come true or not? >>So we had some data that we presented last year and supply chain issues impacting hardware spend. We said at the time, you can see this on the left hand side of this chart, the PC laptop demand would remain above pre covid levels, which would reverse a decade of year on year declines, which I think started in around 2011, 2012. Now, while demand is down this year pretty substantially relative to 2021, I D C has worldwide unit shipments for PCs at just over 300 million for 22. If you go back to 2019 and you're looking at around let's say 260 million units shipped globally, you know, roughly, so, you know, pretty good call there. Definitely much higher than pre covid levels. But so what you might be asking why the B, well, we projected that 30% of customers would replace security appliances with cloud-based services and that more than a third would replace their internal data center server and storage hardware with cloud services like 30 and 40% respectively. >>And we don't have explicit survey data on exactly these metrics, but anecdotally we see this happening in earnest. And we do have some data that we're showing here on cloud adoption from ET R'S October survey where the midpoint of workloads running in the cloud is around 34% and forecast, as you can see, to grow steadily over the next three years. So this, well look, this is not, we understand it's not a one-to-one correlation with our prediction, but it's a pretty good bet that we were right, but we gotta take some points off, we think for the lack of unequivocal proof. Cause again, we always strive to make our predictions in ways that can be measured as accurate or not. Is it binary? Did it happen, did it not? Kind of like an O K R and you know, we strive to provide data as proof and in this case it's a bit fuzzy. >>We have to admit that although we're pretty comfortable that the prediction was accurate. And look, when you make an hard forecast, sometimes you gotta pay the price. All right, next, we said in 2022 that the big four cloud players would generate 167 billion in IS and PaaS revenue combining for 38% market growth. And our current forecasts are shown here with a comparison to our January, 2022 figures. So coming into this year now where we are today, so currently we expect 162 billion in total revenue and a 33% growth rate. Still very healthy, but not on our mark. So we think a w s is gonna miss our predictions by about a billion dollars, not, you know, not bad for an 80 billion company. So they're not gonna hit that expectation though of getting really close to a hundred billion run rate. We thought they'd exit the year, you know, closer to, you know, 25 billion a quarter and we don't think they're gonna get there. >>Look, we pretty much nailed Azure even though our prediction W was was correct about g Google Cloud platform surpassing Alibaba, Alibaba, we way overestimated the performance of both of those companies. So we're gonna give ourselves a C plus here and we think, yeah, you might think it's a little bit harsh, we could argue for a B minus to the professor, but the misses on GCP and Alibaba we think warrant a a self penalty on this one. All right, let's move on to our prediction about Supercloud. We said it becomes a thing in 2022 and we think by many accounts it has, despite the naysayers, we're seeing clear evidence that the concept of a layer of value add that sits above and across clouds is taking shape. And on this slide we showed just some of the pickup in the industry. I mean one of the most interesting is CloudFlare, the biggest supercloud antagonist. >>Charles Fitzgerald even predicted that no vendor would ever use the term in their marketing. And that would be proof if that happened that Supercloud was a thing and he said it would never happen. Well CloudFlare has, and they launched their version of Supercloud at their developer week. Chris Miller of the register put out a Supercloud block diagram, something else that Charles Fitzgerald was, it was was pushing us for, which is rightly so, it was a good call on his part. And Chris Miller actually came up with one that's pretty good at David Linthicum also has produced a a a A block diagram, kind of similar, David uses the term metacloud and he uses the term supercloud kind of interchangeably to describe that trend. And so we we're aligned on that front. Brian Gracely has covered the concept on the popular cloud podcast. Berkeley launched the Sky computing initiative. >>You read through that white paper and many of the concepts highlighted in the Supercloud 3.0 community developed definition align with that. Walmart launched a platform with many of the supercloud salient attributes. So did Goldman Sachs, so did Capital One, so did nasdaq. So you know, sorry you can hate the term, but very clearly the evidence is gathering for the super cloud storm. We're gonna take an a plus on this one. Sorry, haters. Alright, let's talk about data mesh in our 21 predictions posts. We said that in the 2020s, 75% of large organizations are gonna re-architect their big data platforms. So kind of a decade long prediction. We don't like to do that always, but sometimes it's warranted. And because it was a longer term prediction, we, at the time in, in coming into 22 when we were evaluating our 21 predictions, we took a grade of incomplete because the sort of decade long or majority of the decade better part of the decade prediction. >>So last year, earlier this year, we said our number seven prediction was data mesh gains momentum in 22. But it's largely confined and narrow data problems with limited scope as you can see here with some of the key bullets. So there's a lot of discussion in the data community about data mesh and while there are an increasing number of examples, JP Morgan Chase, Intuit, H S P C, HelloFresh, and others that are completely rearchitecting parts of their data platform completely rearchitecting entire data platforms is non-trivial. There are organizational challenges, there're data, data ownership, debates, technical considerations, and in particular two of the four fundamental data mesh principles that the, the need for a self-service infrastructure and federated computational governance are challenging. Look, democratizing data and facilitating data sharing creates conflicts with regulatory requirements around data privacy. As such many organizations are being really selective with their data mesh implementations and hence our prediction of narrowing the scope of data mesh initiatives. >>I think that was right on J P M C is a good example of this, where you got a single group within a, within a division narrowly implementing the data mesh architecture. They're using a w s, they're using data lakes, they're using Amazon Glue, creating a catalog and a variety of other techniques to meet their objectives. They kind of automating data quality and it was pretty well thought out and interesting approach and I think it's gonna be made easier by some of the announcements that Amazon made at the recent, you know, reinvent, particularly trying to eliminate ET t l, better connections between Aurora and Redshift and, and, and better data sharing the data clean room. So a lot of that is gonna help. Of course, snowflake has been on this for a while now. Many other companies are facing, you know, limitations as we said here and this slide with their Hadoop data platforms. They need to do new, some new thinking around that to scale. HelloFresh is a really good example of this. Look, the bottom line is that organizations want to get more value from data and having a centralized, highly specialized teams that own the data problem, it's been a barrier and a blocker to success. The data mesh starts with organizational considerations as described in great detail by Ash Nair of Warner Brothers. So take a listen to this clip. >>Yeah, so when people think of Warner Brothers, you always think of like the movie studio, but we're more than that, right? I mean, you think of H B O, you think of t n t, you think of C N N. We have 30 plus brands in our portfolio and each have their own needs. So the, the idea of a data mesh really helps us because what we can do is we can federate access across the company so that, you know, CNN can work at their own pace. You know, when there's election season, they can ingest their own data and they don't have to, you know, bump up against, as an example, HBO if Game of Thrones is going on. >>So it's often the case that data mesh is in the eyes of the implementer. And while a company's implementation may not strictly adhere to Jamma Dani's vision of data mesh, and that's okay, the goal is to use data more effectively. And despite Gartner's attempts to deposition data mesh in favor of the somewhat confusing or frankly far more confusing data fabric concept that they stole from NetApp data mesh is taking hold in organizations globally today. So we're gonna take a B on this one. The prediction is shaping up the way we envision, but as we previously reported, it's gonna take some time. The better part of a decade in our view, new standards have to emerge to make this vision become reality and they'll come in the form of both open and de facto approaches. Okay, our eighth prediction last year focused on the face off between Snowflake and Databricks. >>And we realized this popular topic, and maybe one that's getting a little overplayed, but these are two companies that initially, you know, looked like they were shaping up as partners and they, by the way, they are still partnering in the field. But you go back a couple years ago, the idea of using an AW w s infrastructure, Databricks machine intelligence and applying that on top of Snowflake as a facile data warehouse, still very viable. But both of these companies, they have much larger ambitions. They got big total available markets to chase and large valuations that they have to justify. So what's happening is, as we've previously reported, each of these companies is moving toward the other firm's core domain and they're building out an ecosystem that'll be critical for their future. So as part of that effort, we said each is gonna become aggressive investors and maybe start doing some m and a and they have in various companies. >>And on this chart that we produced last year, we studied some of the companies that were targets and we've added some recent investments of both Snowflake and Databricks. As you can see, they've both, for example, invested in elation snowflake's, put money into Lacework, the Secur security firm, ThoughtSpot, which is trying to democratize data with ai. Collibra is a governance platform and you can see Databricks investments in data transformation with D B T labs, Matillion doing simplified business intelligence hunters. So that's, you know, they're security investment and so forth. So other than our thought that we'd see Databricks I p o last year, this prediction been pretty spot on. So we'll give ourselves an A on that one. Now observability has been a hot topic and we've been covering it for a while with our friends at E T R, particularly Eric Bradley. Our number nine prediction last year was basically that if you're not cloud native and observability, you are gonna be in big trouble. >>So everything guys gotta go cloud native. And that's clearly been the case. Splunk, the big player in the space has been transitioning to the cloud, hasn't always been pretty, as we reported, Datadog real momentum, the elk stack, that's open source model. You got new entrants that we've cited before, like observe, honeycomb, chaos search and others that we've, we've reported on, they're all born in the cloud. So we're gonna take another a on this one, admittedly, yeah, it's a re reasonably easy call, but you gotta have a few of those in the mix. Okay, our last prediction, our number 10 was around events. Something the cube knows a little bit about. We said that a new category of events would emerge as hybrid and that for the most part is happened. So that's gonna be the mainstay is what we said. That pure play virtual events are gonna give way to hi hybrid. >>And the narrative is that virtual only events are, you know, they're good for quick hits, but lousy replacements for in-person events. And you know that said, organizations of all shapes and sizes, they learn how to create better virtual content and support remote audiences during the pandemic. So when we set at pure play is gonna give way to hybrid, we said we, we i we implied or specific or specified that the physical event that v i p experience is going defined. That overall experience and those v i p events would create a little fomo, fear of, of missing out in a virtual component would overlay that serves an audience 10 x the size of the physical. We saw that really two really good examples. Red Hat Summit in Boston, small event, couple thousand people served tens of thousands, you know, online. Second was Google Cloud next v i p event in, in New York City. >>Everything else was, was, was, was virtual. You know, even examples of our prediction of metaverse like immersion have popped up and, and and, and you know, other companies are doing roadshow as we predicted like a lot of companies are doing it. You're seeing that as a major trend where organizations are going with their sales teams out into the regions and doing a little belly to belly action as opposed to the big giant event. That's a definitely a, a trend that we're seeing. So in reviewing this prediction, the grade we gave ourselves is, you know, maybe a bit unfair, it should be, you could argue for a higher grade, but the, but the organization still haven't figured it out. They have hybrid experiences but they generally do a really poor job of leveraging the afterglow and of event of an event. It still tends to be one and done, let's move on to the next event or the next city. >>Let the sales team pick up the pieces if they were paying attention. So because of that, we're only taking a B plus on this one. Okay, so that's the review of last year's predictions. You know, overall if you average out our grade on the 10 predictions that come out to a b plus, I dunno why we can't seem to get that elusive a, but we're gonna keep trying our friends at E T R and we are starting to look at the data for 2023 from the surveys and all the work that we've done on the cube and our, our analysis and we're gonna put together our predictions. We've had literally hundreds of inbounds from PR pros pitching us. We've got this huge thick folder that we've started to review with our yellow highlighter. And our plan is to review it this month, take a look at all the data, get some ideas from the inbounds and then the e t R of January surveys in the field. >>It's probably got a little over a thousand responses right now. You know, they'll get up to, you know, 1400 or so. And once we've digested all that, we're gonna go back and publish our predictions for 2023 sometime in January. So stay tuned for that. All right, we're gonna leave it there for today. You wanna thank Alex Myerson who's on production and he manages the podcast, Ken Schiffman as well out of our, our Boston studio. I gotta really heartfelt thank you to Kristen Martin and Cheryl Knight and their team. They helped get the word out on social and in our newsletters. Rob Ho is our editor in chief over at Silicon Angle who does some great editing for us. Thank you all. Remember all these podcasts are available or all these episodes are available is podcasts. Wherever you listen, just all you do Search Breaking analysis podcast, really getting some great traction there. Appreciate you guys subscribing. I published each week on wikibon.com, silicon angle.com or you can email me directly at david dot valante silicon angle.com or dm me Dante, or you can comment on my LinkedIn post. And please check out ETR AI for the very best survey data in the enterprise tech business. Some awesome stuff in there. This is Dante for the Cube Insights powered by etr. Thanks for watching and we'll see you next time on breaking analysis.

>> From theCUBE Studios in Palo Alto and Boston, bringing you data driven insights from theCUBE in ETR, this is Breaking Analysis with Dave Vellante. >> The introduction in socialization of data mesh has caused practitioners, business technology executives, and technologists to pause, and ask some probing questions about the organization of their data teams, their data strategies, future investments, and their current architectural approaches. Some in the technology community have embraced the concept, others have twisted the definition, while still others remain oblivious to the momentum building around data mesh. Here we are in the early days of data mesh adoption. Organizations that have taken the plunge will tell you that aligning stakeholders is a non-trivial effort, but necessary to break through the limitations that monolithic data architectures and highly specialized teams have imposed over frustrated business and domain leaders. However, practical data mesh examples often lie in the eyes of the implementer, and may not strictly adhere to the principles of data mesh. Now, part of the problem is lack of open technologies and standards that can accelerate adoption and reduce friction, and that's what we're going to talk about today. Some of the key technology and architecture questions around data mesh. Hello, and welcome to this week's Wikibon CUBE Insights powered by ETR, and in this Breaking Analysis, we welcome back the founder of data mesh and director of Emerging Technologies at Thoughtworks, Zhamak Dehghani. Hello, Zhamak. Thanks for being here today. >> Hi Dave, thank you for having me back. It's always a delight to connect and have a conversation. Thank you. >> Great, looking forward to it. Okay, so before we get into it in the technology details, I just want to quickly share some data from our friends at ETR. You know, despite the importance of data initiative since the pandemic, CIOs and IT organizations have had to juggle of course, a few other priorities, this is why in the survey data, cyber and cloud computing are rated as two most important priorities. Analytics and machine learning, and AI, which are kind of data topics, still make the top of the list, well ahead of many other categories. And look, a sound data architecture and strategy is fundamental to digital transformations, and much of the past two years, as we've often said, has been like a forced march into digital. So while organizations are moving forward, they really have to think hard about the data architecture decisions that they make, because it's going to impact them, Zhamak, for years to come, isn't it? >> Yes, absolutely. I mean, we are moving really from, slowly moving from reason based logical algorithmic to model based computation and decision making, where we exploit the patterns and signals within the data. So data becomes a very important ingredient, of not only decision making, and analytics and discovering trends, but also the features and applications that we build for the future. So we can't really ignore it, and as we see, some of the existing challenges around getting value from data is not necessarily that no longer is access to computation, is actually access to trustworthy, reliable data at scale. >> Yeah, and you see these domains coming together with the cloud and obviously it has to be secure and trusted, and that's why we're here today talking about data mesh. So let's get into it. Zhamak, first, your new book is out, 'Data Mesh: Delivering Data-Driven Value at Scale' just recently published, so congratulations on getting that done, awesome. Now in a recent presentation, you pulled excerpts from the book and we're going to talk through some of the technology and architectural considerations. Just quickly for the audience, four principles of data mesh. Domain driven ownership, data as product, self-served data platform and federated computational governance. So I want to start with self-serve platform and some of the data that you shared recently. You say that, "Data mesh serves autonomous domain oriented teams versus existing platforms, which serve a centralized team." Can you elaborate? >> Sure. I mean the role of the platform is to lower the cognitive load for domain teams, for people who are focusing on the business outcomes, the technologies that are building the applications, to really lower the cognitive load for them, to be able to work with data. Whether they are building analytics, automated decision making, intelligent modeling. They need to be able to get access to data and use it. So the role of the platform, I guess, just stepping back for a moment is to empower and enable these teams. Data mesh by definition is a scale out model. It's a decentralized model that wants to give autonomy to cross-functional teams. So it is core requires a set of tools that work really well in that decentralized model. When we look at the existing platforms, they try to achieve this similar outcome, right? Lower the cognitive load, give the tools to data practitioners, to manage data at scale because today centralized teams, really their job, the centralized data teams, their job isn't really directly aligned with a one or two or different, you know, business units and business outcomes in terms of getting value from data. Their job is manage the data and make the data available for then those cross-functional teams or business units to use the data. So the platforms they've been given are really centralized around or tuned to work with this structure as a team, structure of centralized team. Although on the surface, it seems that why not? Why can't I use my, you know, cloud storage or computation or data warehouse in a decentralized way? You should be able to, but some changes need to happen to those online platforms. As an example, some cloud providers simply have hard limits on the number of like account storage, storage accounts that you can have. Because they never envisaged you have hundreds of lakes. They envisage one or two, maybe 10 lakes, right. They envisage really centralizing data, not decentralizing data. So I think we see a shift in thinking about enabling autonomous independent teams versus a centralized team. >> So just a follow up if I may, we could be here for a while. But so this assumes that you've sorted out the organizational considerations? That you've defined all the, what a data product is and a sub product. And people will say, of course we use the term monolithic as a pejorative, let's face it. But the data warehouse crowd will say, "Well, that's what data march did. So we got that covered." But Europe... The primest of data mesh, if I understand it is whether it's a data march or a data mart or a data warehouse, or a data lake or whatever, a snowflake warehouse, it's a node on the mesh. Okay. So don't build your organization around the technology, let the technology serve the organization is that-- >> That's a perfect way of putting it, exactly. I mean, for a very long time, when we look at decomposition of complexity, we've looked at decomposition of complexity around technology, right? So we have technology and that's maybe a good segue to actually the next item on that list that we looked at. Oh, I need to decompose based on whether I want to have access to raw data and put it on the lake. Whether I want to have access to model data and put it on the warehouse. You know I need to have a team in the middle to move the data around. And then try to figure organization into that model. So data mesh really inverses that, and as you said, is look at the organizational structure first. Then scale boundaries around which your organization and operation can scale. And then the second layer look at the technology and how you decompose it. >> Okay. So let's go to that next point and talk about how you serve and manage autonomous interoperable data products. Where code, data policy you say is treated as one unit. Whereas your contention is existing platforms of course have independent management and dashboards for catalogs or storage, et cetera. Maybe we double click on that a bit. >> Yeah. So if you think about that functional, or technical decomposition, right? Of concerns, that's one way, that's a very valid way of decomposing, complexity and concerns. And then build solutions, independent solutions to address them. That's what we see in the technology landscape today. We will see technologies that are taking care of your management of data, bring your data under some sort of a control and modeling. You'll see technology that moves that data around, will perform various transformations and computations on it. And then you see technology that tries to overlay some level of meaning. Metadata, understandability, discovery was the end policy, right? So that's where your data processing kind of pipeline technologies versus data warehouse, storage, lake technologies, and then the governance come to play. And over time, we decomposed and we compose, right? Deconstruct and reconstruct back this together. But, right now that's where we stand. I think for data mesh really to become a reality, as in independent sources of data and teams can responsibly share data in a way that can be understood right then and there can impose policies, right then when the data gets accessed in that source and in a resilient manner, like in a way that data changes structure of the data or changes to the scheme of the data, doesn't have those downstream down times. We've got to think about this new nucleus or new units of data sharing. And we need to really bring back transformation and governing data and the data itself together around these decentralized nodes on the mesh. So that's another, I guess, deconstruction and reconstruction that needs to happen around the technology to formulate ourselves around the domains. And again the data and the logic of the data itself, the meaning of the data itself. >> Great. Got it. And we're going to talk more about the importance of data sharing and the implications. But the third point deals with how operational, analytical technologies are constructed. You've got an app DevStack, you've got a data stack. You've made the point many times actually that we've contextualized our operational systems, but not our data systems, they remain separate. Maybe you could elaborate on this point. >> Yes. I think this is, again, has a historical background and beginning. For a really long time, applications have dealt with features and the logic of running the business and encapsulating the data and the state that they need to run that feature or run that business function. And then we had for anything analytical driven, which required access data across these applications and across the longer dimension of time around different subjects within the organization. This analytical data, we had made a decision that, "Okay, let's leave those applications aside. Let's leave those databases aside. We'll extract the data out and we'll load it, or we'll transform it and put it under the analytical kind of a data stack and then downstream from it, we will have analytical data users, the data analysts, the data sciences and the, you know, the portfolio of users that are growing use that data stack. And that led to this really separation of dual stack with point to point integration. So applications went down the path of transactional databases or urban document store, but using APIs for communicating and then we've gone to, you know, lake storage or data warehouse on the other side. If we are moving and that again, enforces the silo of data versus app, right? So if we are moving to the world that our missions that are ambitions around making applications, more intelligent. Making them data driven. These two worlds need to come closer. As in ML Analytics gets embedded into those app applications themselves. And the data sharing, as a very essential ingredient of that, gets embedded and gets closer, becomes closer to those applications. So, if you are looking at this now cross-functional, app data, based team, right? Business team, then the technology stacks can't be so segregated, right? There has to be a continuum of experience from app delivery, to sharing of the data, to using that data, to embed models back into those applications. And that continuum of experience requires well integrated technologies. I'll give you an example, which actually in some sense, we are somewhat moving to that direction. But if we are talking about data sharing or data modeling and applications use one set of APIs, you know, HTTP compliant, GraQL or RAC APIs. And on the other hand, you have proprietary SQL, like connect to my database and run SQL. Like those are very two different models of representing and accessing data. So we kind of have to harmonize or integrate those two worlds a bit more closely to achieve that domain oriented cross-functional teams. >> Yeah. We are going to talk about some of the gaps later and actually you look at them as opportunities, more than barriers. But they are barriers, but they're opportunities for more innovation. Let's go on to the fourth one. The next point, it deals with the roles that the platform serves. Data mesh proposes that domain experts own the data and take responsibility for it end to end and are served by the technology. Kind of, we referenced that before. Whereas your contention is that today, data systems are really designed for specialists. I think you use the term hyper specialists a lot. I love that term. And the generalist are kind of passive bystanders waiting in line for the technical teams to serve them. >> Yes. I mean, if you think about the, again, the intention behind data mesh was creating a responsible data sharing model that scales out. And I challenge any organization that has a scaled ambitions around data or usage of data that relies on small pockets of very expensive specialists resources, right? So we have no choice, but upscaling cross-scaling. The majority population of our technologists, we often call them generalists, right? That's a short hand for people that can really move from one technology to another technology. Sometimes we call them pandric people sometimes we call them T-shaped people. But regardless, like we need to have ability to really mobilize our generalists. And we had to do that at Thoughtworks. We serve a lot of our clients and like many other organizations, we are also challenged with hiring specialists. So we have tested the model of having a few specialists, really conveying and translating the knowledge to generalists and bring them forward. And of course, platform is a big enabler of that. Like what is the language of using the technology? What are the APIs that delight that generalist experience? This doesn't mean no code, low code. We have to throw away in to good engineering practices. And I think good software engineering practices remain to exist. Of course, they get adopted to the world of data to build resilient you know, sustainable solutions, but specialty, especially around kind of proprietary technology is going to be a hard one to scale. >> Okay. I'm definitely going to come back and pick your brain on that one. And, you know, your point about scale out in the examples, the practical examples of companies that have implemented data mesh that I've talked to. I think in all cases, you know, there's only a handful that I've really gone deep with, but it was their hadoop instances, their clusters wouldn't scale, they couldn't scale the business and around it. So that's really a key point of a common pattern that we've seen now. I think in all cases, they went to like the data lake model and AWS. And so that maybe has some violation of the principles, but we'll come back to that. But so let me go on to the next one. Of course, data mesh leans heavily, toward this concept of decentralization, to support domain ownership over the centralized approaches. And we certainly see this, the public cloud players, database companies as key actors here with very large install bases, pushing a centralized approach. So I guess my question is, how realistic is this next point where you have decentralized technologies ruling the roost? >> I think if you look at the history of places, in our industry where decentralization has succeeded, they heavily relied on standardization of connectivity with, you know, across different components of technology. And I think right now you are right. The way we get value from data relies on collection. At the end of the day, collection of data. Whether you have a deep learning machinery model that you're training, or you have, you know, reports to generate. Regardless, the model is bring your data to a place that you can collect it, so that we can use it. And that leads to a naturally set of technologies that try to operate as a full stack integrated proprietary with no intention of, you know, opening, data for sharing. Now, conversely, if you think about internet itself, web itself, microservices, even at the enterprise level, not at the planetary level, they succeeded as decentralized technologies to a large degree because of their emphasis on open net and openness and sharing, right. API sharing. We don't talk about, in the API worlds, like we don't say, you know, "I will build a platform to manage your logical applications." Maybe to a degree but we actually moved away from that. We say, "I'll build a platform that opens around applications to manage your APIs, manage your interfaces." Right? Give you access to API. So I think the shift needs to... That definition of decentralized there means really composable, open pieces of the technology that can play nicely with each other, rather than a full stack, all have control of your data yet being somewhat decentralized within the boundary of my platform. That's just simply not going to scale if data needs to come from different platforms, different locations, different geographical locations, it needs to rethink. >> Okay, thank you. And then the final point is, is data mesh favors technologies that are domain agnostic versus those that are domain aware. And I wonder if you could help me square the circle cause it's nuanced and I'm kind of a 100 level student of your work. But you have said for example, that the data teams lack context of the domain and so help us understand what you mean here in this case. >> Sure. Absolutely. So as you said, we want to take... Data mesh tries to give autonomy and decision making power and responsibility to people that have the context of those domains, right? The people that are really familiar with different business domains and naturally the data that that domain needs, or that naturally the data that domains shares. So if the intention of the platform is really to give the power to people with most relevant and timely context, the platform itself naturally becomes as a shared component, becomes domain agnostic to a large degree. Of course those domains can still... The platform is a (chuckles) fairly overloaded world. As in, if you think about it as a set of technology that abstracts complexity and allows building the next level solutions on top, those domains may have their own set of platforms that are very much doing agnostic. But as a generalized shareable set of technologies or tools that allows us share data. So that piece of technology needs to relinquish the knowledge of the context to the domain teams and actually becomes domain agnostic. >> Got it. Okay. Makes sense. All right. Let's shift gears here. Talk about some of the gaps and some of the standards that are needed. You and I have talked about this a little bit before, but this digs deeper. What types of standards are needed? Maybe you could walk us through this graphic, please. >> Sure. So what I'm trying to depict here is that if we imagine a world that data can be shared from many different locations, for a variety of analytical use cases, naturally the boundary of what we call a node on the mesh will encapsulates internally a fair few pieces. It's not just the boundary of that, not on the mesh, is the data itself that it's controlling and updating and maintaining. It's of course a computation and the code that's responsible for that data. And then the policies that continue to govern that data as long as that data exists. So if that's the boundary, then if we shift that focus from implementation details, that we can leave that for later, what becomes really important is the scene or the APIs and interfaces that this node exposes. And I think that's where the work that needs to be done and the standards that are missing. And we want the scene and those interfaces be open because that allows, you know, different organizations with different boundaries of trust to share data. Not only to share data to kind of move that data to yes, another location, to share the data in a way that distributed workloads, distributed analytics, distributed machine learning model can happen on the data where it is. So if you follow that line of thinking around the centralization and connection of data versus collection of data, I think the very, very important piece of it that needs really deep thinking, and I don't claim that I have done that, is how do we share data responsibly and sustainably, right? That is not brittle. If you think about it today, the ways we share data, one of the very common ways is around, I'll give you a JDC endpoint, or I give you an endpoint to your, you know, database of choice. And now as technology, whereas a user actually, you can now have access to the schema of the underlying data and then run various queries or SQL queries on it. That's very simple and easy to get started with. That's why SQL is an evergreen, you know, standard or semi standard, pseudo standard that we all use. But it's also very brittle, because we are dependent on a underlying schema and formatting of the data that's been designed to tell the computer how to store and manage the data. So I think that the data sharing APIs of the future really need to think about removing this brittle dependencies, think about sharing, not only the data, but what we call metadata, I suppose. Additional set of characteristics that is always shared along with data to make the data usage, I suppose ethical and also friendly for the users and also, I think we have to... That data sharing API, the other element of it, is to allow kind of computation to run where the data exists. So if you think about SQL again, as a simple primitive example of computation, when we select and when we filter and when we join, the computation is happening on that data. So maybe there is a next level of articulating, distributed computational data that simply trains models, right? Your language primitives change in a way to allow sophisticated analytical workloads run on the data more responsibly with policies and access control and force. So I think that output port that I mentioned simply is about next generation data sharing, responsible data sharing APIs. Suitable for decentralized analytical workloads. >> So I'm not trying to bait you here, but I have a follow up as well. So you schema, for all its good creates constraints. No schema on right, that didn't work, cause it was just a free for all and it created the data swamps. But now you have technology companies trying to solve that problem. Take Snowflake for example, you know, enabling, data sharing. But it is within its proprietary environment. Certainly Databricks doing something, you know, trying to come at it from its angle, bringing some of the best to data warehouse, with the data science. Is your contention that those remain sort of proprietary and defacto standards? And then what we need is more open standards? Maybe you could comment. >> Sure. I think the two points one is, as you mentioned. Open standards that allow... Actually make the underlying platform invisible. I mean my litmus test for a technology provider to say, "I'm a data mesh," (laughs) kind of compliant is, "Is your platform invisible?" As in, can I replace it with another and yet get the similar data sharing experience that I need? So part of it is that. Part of it is open standards, they're not really proprietary. The other angle for kind of sharing data across different platforms so that you know, we don't get stuck with one technology or another is around APIs. It is around code that is protecting that internal schema. So where we are on the curve of evolution of technology, right now we are exposing the internal structure of the data. That is designed to optimize certain modes of access. We're exposing that to the end client and application APIs, right? So the APIs that use the data today are very much aware that this database was optimized for machine learning workloads. Hence you will deal with a columnar storage of the file versus this other API is optimized for a very different, report type access, relational access and is optimized around roles. I think that should become irrelevant in the API sharing of the future. Because as a user, I shouldn't care how this data is internally optimized, right? The language primitive that I'm using should be really agnostic to the machine optimization underneath that. And if we did that, perhaps this war between warehouse or lake or the other will become actually irrelevant. So we're optimizing for that human best human experience, as opposed to the best machine experience. We still have to do that but we have to make that invisible. Make that an implementation concern. So that's another angle of what should... If we daydream together, the best experience and resilient experience in terms of data usage than these APIs with diagnostics to the internal storage structure. >> Great, thank you for that. We've wrapped our ankles now on the controversy, so we might as well wade all the way in, I can't let you go without addressing some of this. Which you've catalyzed, which I, by the way, I see as a sign of progress. So this gentleman, Paul Andrew is an architect and he gave a presentation I think last night. And he teased it as quote, "The theory from Zhamak Dehghani versus the practical experience of a technical architect, AKA me," meaning him. And Zhamak, you were quick to shoot back that data mesh is not theory, it's based on practice. And some practices are experimental. Some are more baked and data mesh really avoids by design, the specificity of vendor or technology. Perhaps you intend to frame your post as a technology or vendor specific, specific implementation. So touche, that was excellent. (Zhamak laughs) Now you don't need me to defend you, but I will anyway. You spent 14 plus years as a software engineer and the better part of a decade consulting with some of the most technically advanced companies in the world. But I'm going to push you a little bit here and say, some of this tension is of your own making because you purposefully don't talk about technologies and vendors. Sometimes doing so it's instructive for us neophytes. So, why don't you ever like use specific examples of technology for frames of reference? >> Yes. My role is pushes to the next level. So, you know everybody picks their fights, pick their battles. My role in this battle is to push us to think beyond what's available today. Of course, that's my public persona. On a day to day basis, actually I work with clients and existing technology and I think at Thoughtworks we have given the talk we gave a case study talk with a colleague of mine and I intentionally got him to talk about (indistinct) I want to talk about the technology that we use to implement data mesh. And the reason I haven't really embraced, in my conversations, the specific technology. One is, I feel the technology solutions we're using today are still not ready for the vision. I mean, we have to be in this transitional step, no matter what we have to be pragmatic, of course, and practical, I suppose. And use the existing vendors that exist and I wholeheartedly embrace that, but that's just not my role, to show that. I've gone through this transformation once before in my life. When microservices happened, we were building microservices like architectures with technology that wasn't ready for it. Big application, web application servers that were designed to run these giant monolithic applications. And now we're trying to run little microservices onto them. And the tail was riding the dock, the environmental complexity of running these services was consuming so much of our effort that we couldn't really pay attention to that business logic, the business value. And that's where we are today. The complexity of integrating existing technologies is really overwhelmingly, capturing a lot of our attention and cost and effort, money and effort as opposed to really focusing on the data product themselves. So it's just that's the role I have, but it doesn't mean that, you know, we have to rebuild the world. We've got to do with what we have in this transitional phase until the new generation, I guess, technologies come around and reshape our landscape of tools. >> Well, impressive public discipline. Your point about microservice is interesting because a lot of those early microservices, weren't so micro and for the naysayers look past this, not prologue, but Thoughtworks was really early on in the whole concept of microservices. So be very excited to see how this plays out. But now there was some other good comments. There was one from a gentleman who said the most interesting aspects of data mesh are organizational. And that's how my colleague Sanji Mohan frames data mesh versus data fabric. You know, I'm not sure, I think we've sort of scratched the surface today that data today, data mesh is more. And I still think data fabric is what NetApp defined as software defined storage infrastructure that can serve on-prem and public cloud workloads back whatever, 2016. But the point you make in the thread that we're showing you here is that you're warning, and you referenced this earlier, that the segregating different modes of access will lead to fragmentation. And we don't want to repeat the mistakes of the past. >> Yes, there are comments around. Again going back to that original conversation that we have got this at a macro level. We've got this tendency to decompose complexity based on technical solutions. And, you know, the conversation could be, "Oh, I do batch or you do a stream and we are different."' They create these bifurcations in our decisions based on the technology where I do events and you do tables, right? So that sort of segregation of modes of access causes accidental complexity that we keep dealing with. Because every time in this tree, you create a new branch, you create new kind of new set of tools and then somehow need to be point to point integrated. You create new specialization around that. So the least number of branches that we have, and think about really about the continuum of experiences that we need to create and technologies that simplify, that continuum experience. So one of the things, for example, give you a past experience. I was really excited around the papers and the work that came around on Apache Beam, and generally flow based programming and stream processing. Because basically they were saying whether you are doing batch or whether you're doing streaming, it's all one stream. And sometimes the window of time, narrows and sometimes the window of time over which you're computing, widens and at the end of today, is you are just getting... Doing the stream processing. So it is those sort of notions that simplify and create continuum of experience. I think resonate with me personally, more than creating these tribal fights of this type versus that mode of access. So that's why data mesh naturally selects kind of this multimodal access to support end users, right? The persona of end users. >> Okay. So the last topic I want to hit, this whole discussion, the topic of data mesh it's highly nuanced, it's new, and people are going to shoehorn data mesh into their respective views of the world. And we talked about lake houses and there's three buckets. And of course, the gentleman from LinkedIn with Azure, Microsoft has a data mesh community. See you're going to have to enlist some serious army of enforcers to adjudicate. And I wrote some of the stuff down. I mean, it's interesting. Monte Carlo has a data mesh calculator. Starburst is leaning in, chaos. Search sees themselves as an enabler. Oracle and Snowflake both use the term data mesh. And then of course you've got big practitioners J-P-M-C, we've talked to Intuit, Orlando, HelloFresh has been on, Netflix has this event based sort of streaming implementation. So my question is, how realistic is it that the clarity of your vision can be implemented and not polluted by really rich technology companies and others? (Zhamak laughs) >> Is it even possible, right? Is it even possible? That's a yes. That's why I practice then. This is why I should practice things. Cause I think, it's going to be hard. What I'm hopeful, is that the socio-technical, Leveling Data mentioned that this is a socio-technical concern or solution, not just a technology solution. Hopefully always brings us back to, you know, the reality that vendors try to sell you safe oil that solves all of your problems. (chuckles) All of your data mesh problems. It's just going to cause more problem down the track. So we'll see, time will tell Dave and I count on you as one of those members of, (laughs) you know, folks that will continue to share their platform. To go back to the roots, as why in the first place? I mean, I dedicated a whole part of the book to 'Why?' Because we get, as you said, we get carried away with vendors and technology solution try to ride a wave. And in that story, we forget the reason for which we even making this change and we are going to spend all of this resources. So hopefully we can always come back to that. >> Yeah. And I think we can. I think you have really given this some deep thought and as we pointed out, this was based on practical knowledge and experience. And look, we've been trying to solve this data problem for a long, long time. You've not only articulated it well, but you've come up with solutions. So Zhamak, thank you so much. We're going to leave it there and I'd love to have you back. >> Thank you for the conversation. I really enjoyed it. And thank you for sharing your platform to talk about data mesh. >> Yeah, you bet. All right. And I want to thank my colleague, Stephanie Chan, who helps research topics for us. Alex Myerson is on production and Kristen Martin, Cheryl Knight and Rob Hoff on editorial. Remember all these episodes are available as podcasts, wherever you listen. And all you got to do is search Breaking Analysis Podcast. Check out ETR's website at etr.ai for all the data. And we publish a full report every week on wikibon.com, siliconangle.com. You can reach me by email david.vellante@siliconangle.com or DM me @dvellante. Hit us up on our LinkedIn post. This is Dave Vellante for theCUBE Insights powered by ETR. Have a great week, stay safe, be well. And we'll see you next time. (bright music)

>>welcome back. And thanks for joining us for our second session. External data, your new leading indicators. We'll be hearing from industry leaders as they share best practices and challenges in leveraging external data. This panel will be a true conversation on the part of the possible. All right, let's get to >>it >>today. We're excited to be joined by thought spots. Chief Data Strategy Officer Cindy Housing Deloitte's chief data officer Manteo, the founder and CEO of Eagle Alfa. And it Kilduff and Snowflakes, VP of data marketplace and customer product strategy. Matt Glickman. Cindy. Without further ado, the floor is yours. >>Thank you, Mallory. And I am thrilled to have this brilliant team joining us from around the world. And they really bring each a very unique perspective. So I'm going to start from further away. Emmett, Welcome. Where you joining us from? >>Thanks for having us, Cindy. I'm joining from Dublin, Ireland, >>great. And and tell us a little bit about Eagle Alfa. What do you dio >>from a company's perspective? Think of Eagle Alfa as an aggregator off all the external data sets on a word I'll use a few times. Today is a big advantage we could bring companies is we have a data concierge service. There's so much data we can help identify the right data sets depending on the specific needs of the company. >>Yeah. And so, Emma, you know, people think I was a little I kind of shocked the industry. Going from gardener to a tech startup. Um, you have had a brave journey as well, Going from financial services to starting this company, really pioneering it with I think the most data sets of any of thes is that right? >>Yes, it was. It was a big jump to go from Morgan Stanley. Uh, leave the comforts of that environment Thio, PowerPoint deck and myself raising funding eight years ago s So it was a big jump on. We were very early in our market. It's in the last few years where there's been real momentum and adoption by various types of verticals. The hedge funds were first, maybe then private equity, but corporate sar are following quite quickly from behind. That will be the biggest users, in our view, by by a significant distance. >>Yeah, great. Thank um, it So we're going to go a little farther a field now, but back to the U. S. So, Juan, where you joining us from? >>Hey, Cindy. Thanks for having me. I'm joining you from Houston, Texas. >>Great. Used to be my home. Yeah, probably see Rice University back there. And you have a distinct perspective serving both Deloitte customers externally, but also internally. Can you tell us about that? >>Yeah, absolutely. So I serve as the Lord consultants, chief data officer, and as a professional service firm, I have the responsibility for overseeing our overall data agenda, which includes both the way we use data and insights to run and operate our own business, but also in how we develop data and insights services that we then take to market and how we serve our dealers and clients. >>Great. Thank you, Juan. And last but not least, Matt Glickman. Kind of in my own backyard in New York. Right, Matt? >>Correct. Joining I haven't been into the city and many months, but yes, um, based in New York. >>Okay. Great. And so, Matt, you and Emmett also, you know, brave pioneers in this space, and I'm remembering a conversation you and I shared when you were still a J. P. Morgan, I believe. And you're Goldman Sachs. Sorry. Sorry. Goldman. Can you Can you share that with us? >>Sure. I made the move back in 2015. Um, when everyone thought, you know, my wife, my wife included that I was crazy. I don't know if I would call it Comfortable was emitted, but particularly had been there for a long time on git suffered in some ways. A lot of the pains we're talking about today, given the number of data, says that the amount of of new data sets that are always demand for having run analytics teams at Goldman, seeing the pain and realizing that this pain was not unique to Goldman Sachs, it was being replicated everywhere across the industry, um, in a mind boggling way and and the fortuitous, um, luck to have one of snowflakes. Founders come to pitch snowflake to Goldman a little bit early. Um, they became a customer later, but a little bit early in 2014. And, you know, I realized that this was clearly, you know, the answer from first principles on bond. If I ever was going to leave, this was a problem. I was acutely aware of. And I also was aware of how much the man that was in financial services for a better solution and how the cloud could really solve this problem in particular the ability to not have to move data in and out of these organizations. And this was something that I saw the future of. Thank you, Andi, that this was, you know, sort of the pain that people just expected to pay. Um, this price if you need a data, there was method you had thio. You had to use you either ftp data in and out. You had data that was being, you know, dropped off and, you know, maybe in in in a new ways and cloud buckets or a P i s You have to suck all this data down and reconstruct it. And God forbid the formats change. It was, you know, a nightmare. And then having issues with data, you had a what you were seeing internally. You look nothing like what the data vendors were seeing because they want a completely different system, maybe model completely differently. Um, but this was just the way things were. Everyone had firewalls. Everyone had their own data centers. There was no other way on git was super costly. And you know this. I won't even share the the details of you know, the errors that would occur in the pain that would come from that, Um what I realized it was confirmed. What I saw it snowflake at the time was once everyone moves to run their actual workloads in this in the cloud right where you're now beyond your firewall, you'll have all this scale. But on top of that, you'll be able to point at data from these vendors were not there the traditional data vendors. Or, you know, this new wave of alternative data vendors, for example, like the ones that eagle out for brings together And bring these all these data sets together with your own internal data without moving it. Yeah, this was a fundamental shift of what you know, it's in some ways, it was a side effect of everyone moving to the cloud for costs and scale and elasticity. But as a side effect of that is what we talked about, You know it snowflake summit, you know, yesterday was this notion of a data cloud that would connect data between regions between cloud vendors between customers in a way where you could now reference data. Just like your reference websites today, I don't download CNN dot com. I point at it, and it points me to something else. I'm always seeing the latest version, obviously, and we can, you know, all collaborate on what I'm seeing on that website. That's the same thing that now can happen with data. So And I saw this as what was possible, and I distinctly asked the question, you know, the CEO of the time Is this possible? And not only was it possible it was a fundamental construct that was built into the way that snowflake was delivered. And then, lastly, this is what we learned. And I think this is what you know. M It also has been touting is that it's all great if data is out there and even if you lower that bar of access where data doesn't have to move, how do I know? Right? If I'm back to sitting at Goldman Sachs, how do I know what data is available to me now in this this you know, connected data network eso we released our data marketplace, which was a very different kind of marketplace than these of the past. Where for us, it was really like a global catalog that would elect a consumer data consumer. Noah data was available, but also level the playing field. Now we're now, you know, Eagle, Alfa, or even, you know, a new alternative data vendor build something in their in their basement can now publish that data set so that the world could see and consume and be aligned to, you know, snowflakes, core business, and not where we wouldn't have to be competing or having to take, um, any kind of custody of that data. So adding that catalog to this now ubiquitous access, um really changed the game and, you know, and then now I seem like a genius for making this move. But back then, like I said, we've seen I seem like instant. I was insane. >>Well, given, given that snowflake was the hottest aipo like ever, you were a genius. Uh, doing this, you know, six years in advance. E think we all agree on that, But, you know, a lot of this is still visionary. Um, you know, some of the most leading companies are already doing this. But one What? What is your take our Are you best in class customers still moving the data? Or is this like they're at least thinking about data monetization? What are you seeing from your perspective? >>Yeah, I mean, I did you know, the overall appreciation and understanding of you know, one. I got to get my house in order around my data, um, has something that has been, you know, understood and acted upon. Andi, I do agree that there is a shift now that says, you know, data silos alone aren't necessarily gonna bring me, you know, new and unique insights on dso enriching that with external third party data is absolutely, you know, sort of the the ship that we're seeing our customers undergo. Um, what I find extremely interesting in this space and what some of the most mature clients are doing is, you know, really taking advantage of these data marketplaces. But building data partnerships right there from what mutually exclusive, where there is a win win scenario for for you know, that organization and that could be, you know, retail customers or life science customers like with pandemic, right the way we saw companies that weren't naturally sharing information are now building these data partnership right that are going are going into mutually benefit, you know, all organizations that are sort of part of that value to Andi. I think that's the sort of really important criteria. And how we're seeing our clients that are extremely successful at this is that partnership has benefits on both sides of that equation, right? Both the data provider and then the consumer of that. And there has to be, you know, some way to ensure that both parties are are are learning right, gaining you insights to support, you know, whatever their business organization going on. >>Yeah, great one. So those data partnerships getting across the full value chain of sharing data and analytics Emmett, you work on both sides of the equation here, helping companies. Let's say let's say data providers maybe, like, you know, cast with human mobility monetize that. But then also people that are new to it. Where you seeing the top use cases? Well, >>interestingly, I agree with one of the supply side. One of the interesting trends is we're seeing a lot more data coming from large Corporates. Whether they're listed are private equity backed, as opposed to maybe data startups that are earning money just through data monetization. I think that's a great trend. I think that means a lot of the best. Data said it data is yet to come, um, in terms off the tough economy and how that's changed. I think the category that's had the most momentum and your references is Geo location data. It's that was the category at our conference in December 2000 and 12 that was pipped as the category to watch in 2019. On it didn't become that at all. Um, there were some regulatory concerns for certain types of geo data, but with with covert 19, it's Bean absolutely critical for governments, ministries of finance, central banks, municipalities, Thio crunch that data to understand what's happening in a real time basis. But from a company perspective, it's obviously critical as well. In terms of planning when customers might be back in the High Street on DSO, fourth traditionally consumer transaction data of all the 26 categories in our taxonomy has been the most popular. But Geo is definitely catching up your slide. Talked about being a tough economy. Just one point to contradict that for certain pockets of our clients, e commerce companies are having a field day, obviously, on they are very data driven and tech literate on day are they are really good client base for us because they're incredibly hungry, firm or data to help drive various, uh, decision making. >>Yeah, So fair enough. Some sectors of the economy e commerce, electron, ICS, healthcare are doing great. Others travel, hospitality, Um, super challenging. So I like your quote. The best is yet to come, >>but >>that's data sets is yet to come. And I do think the cloud is enabling that because we could get rid of some of the messy manual data flows that Matt you talked about, but nonetheless, Still, one of the hardest things is the data map. Things combining internal and external >>when >>you might not even have good master data. Common keys on your internal data. So any advice for this? Anyone who wants to take that? >>Sure I can. I can I can start. That's okay. I do think you know, one of the first problems is just a cataloging of the information that's out there. Um, you know, at least within our organization. When I took on this role, we were, you know, a large buyer of third party data. But our organization as a whole didn't necessarily have full visibility into what was being bought and for what purpose. And so having a catalog that helps us internally navigate what data we have and how we're gonna use it was sort of step number one. Um, so I think that's absolutely important. Um, I would say if we could go from having that catalog, you know, created manually to more automated to me, that's sort of the next step in our evolution, because everyone is saying right, the ongoing, uh, you know, creation of new external data sets. It's only going to get richer on DSO. We wanna be able to take advantage of that, you know, at the at the pacing speed, that data is being created. So going from Emanuel catalog to anonymous >>data >>catalog, I think, is a key capability for us. But then you know, to your second point, Cindy is how doe I then connect that to our own internal data to drive greater greater insights and how we run our business or how we serve our customers. Andi, that one you know really is a It's a tricky is a tricky, uh, question because I think it just depends on what data we're looking toe leverage. You know, we have this concept just around. Not not all data is created equal. And when you think about governance and you think about the management of your master data, your internal nomenclature on how you define and run your business, you know that that entire ecosystem begins to get extremely massive and it gets very broad and very deep on DSO for us. You know, government and master data management is absolutely important. But we took a very sort of prioritized approach on which domains do we really need to get right that drive the greatest results for our organization on dso mapping those domains like client data or employee data to these external third party data sources across this catalog was really the the unlocked for us versus trying to create this, you know, massive connection between all the external data that we're, uh, leveraging as well as all of our own internal data eso for us. I think it was very. It was a very tailored, prioritized approach to connecting internal data to external data based on the domains that matter most to our business. >>So if the domains so customer important domain and maybe that's looking at things, um, you know, whether it's social media data or customer transactions, you prioritized first by that, Is that right? >>That's correct. That's correct. >>And so, then, Matt, I'm going to throw it back to you because snowflake is in a unique position. You actually get to see what are the most popular data sets is is that playing out what one described are you seeing that play out? >>I I'd say Watch this space. Like like you said. I mean this. We've you know, I think we start with the data club. We solve that that movement problem, which I think was really the barrier that you tended to not even have a chance to focus on this mapping problem. Um, this notion of concordance, I think this is where I see the big next momentum in this space is going to be a flurry of traditional and new startups who deliver this concordance or knowledge graph as a service where this is no longer a problem that I have to solve internal to my organization. The notion of mastering which is again when everyone has to do in every organization like they used to have to do with moving data into the organization goes away. And this becomes like, I find the best of breed for the different scopes of data that I have. And it's delivered to me as a, you know, as a cloud service that just takes my data. My internal data maps it to these 2nd and 3rd party data sets. Um, all delivered to me, you know, a service. >>Yeah, well, that would be brilliant concordance as a service or or clean clean master data as a service. Um, using augmented data prep would be brilliant. So let's hope we get there. Um, you know, so 2020 has been a wild ride for everyone. If I could ask each of you imagine what is the art of the possible or looking ahead to the next to your and that you are you already mentioned the best is yet to come. Can you want to drill down on that. What what part of the best is yet to come or what is your already two possible? >>Just just a brief comment on mapping. Just this week we published a white paper on mapping, which is available for for anyone on eagle alfa dot com. It's It's a massive challenge. It's very difficult to solve. Just with technology Onda people have tried to solve it and get a certain level of accuracy, but can't get to 100% which which, which, which makes it difficult to solve it. If if if there is a new service coming out against 100% I'm all ears and that there will be a massive step forward for the entire data industry, even if it comes in a few years time, let alone next year, I think going back to the comment on data Cindy. Yes, I think boards of companies are Mawr and Mawr. Viewing data as an asset as opposed to an expense are a cost center on bond. They are looking therefore to get their internal house in order, as one was saying, but also monetize the data they are sitting on lots of companies. They're sitting on potentially valuable data. It's not all valuable on a lot of cases. They think it's worth a lot more than it is being frank. But in some cases there is valuable data on bond. If monetized, it can drop to the bottom line on. So I think that bodes well right across the world. A lot of the best date is yet to come on. I think a lot of firms like Deloitte are very well positioned to help drive that adoption because they are the trusted advisor to a lot of these Corporates. Um, so that's one thing. I think, from a company perspective. It's still we're still at the first base. It's quite frustrating how slow a lot of companies are to move and adopt, and some of them are haven't hired CDO. Some of them don't have their internal house in order. I think that has to change next year. I think if we have this conference at this time next year, I would expect that would hopefully be close to the tipping point for Corporates to use external data. And the Malcolm Gladwell tipping point on the final point I make is I think, that will hopefully start to see multi department use as opposed to silos again. Parliaments and silos, hopefully will be more coordinated on the company's side. Data could be used by marketing by sales by r and D by strategy by finance holds external data. So it really, hopefully will be coordinated by this time next year. >>Yeah, Thank you. So, to your point, there recently was an article to about one of the airlines that their data actually has more value than the company itself now. So I know, I know. We're counting on, you know, integrators trusted advisers like Deloitte to help us get there. Uh, one what? What do you think? And if I can also drill down, you know, financial services was early toe all of this because they needed the early signals. And and we talk about, you know, is is external data now more valuable than internal? Because we need those early signals in just such a different economy. >>Yeah, I think you know, for me, it's it's the seamless integration of all these external data sources and and the signals that organizations need and how to bring those into, you know, the day to day operations of your organization, right? So how do you bring those into, You know, you're planning process. How do you bring that into your sales process on DSO? I think for me success or or where I see the that the use and adoption of this is it's got to get down to that level off of operations for organizations. For this to continue to move at the pace and deliver the value that you know, we're all describing. I think we're going to get there. But I think until organizations truly get down to that level of operations and how they're using this data, it'll sort of seem like a Bolton, right? So for me, I think it's all about Mawr, the seamless integration. And I think to what Matt mentioned just around services that could help connect external data with internal data. I'll take that one step beyond and say, How can we have the data connect itself? Eso I had references Thio, you know, automation and machine learning. Um, there's significant advances in terms of how we're seeing, you know, mapping to occur in a auto generated fashion. I think this specific space and again the connection between external and internal data is a prime example of where we need to disrupt that, you know, sort of traditional data pipeline on. Try to automate that as much as possible. And let's have the data, you know, connect itself because it then sort of supports. You know, the first concept which waas How do we make it more seamless and integrated into, you know, the business processes of the organization's >>Yeah, great ones. So you two are thinking those automated, more intelligent data pipelines will get us there faster. Matt, you already gave us one. Great, Uh, look ahead, Any more to add to >>it, I'll give you I'll give you two more. One is a bit controversial, but I'll throw that you anyway, um, going back to the point that one made about data partnerships What you were saying Cindy about, you know, the value. These companies, you know, tends to be somehow sometimes more about the data they have than the actual service they provide. I predict you're going to see a wave of mergers and acquisitions. Um, that it's solely about locking down access to data as opposed to having data open up. Um to the broader, you know, economy, if I can, whether that be a retailer or, you know, insurance company was thes prime data assets. Um, you know, they could try to monetize that themselves, But if someone could acquire them and get exclusive access that data, I think that's going to be a wave of, um, in a that is gonna be like, Well, we bought this for this amount of money because of their data assets s. So I think that's gonna be a big wave. And it'll be maybe under the guise of data partnerships. But it really be about, you know, get locking down exclusive access to valuable data as opposed to trying toe monetize it itself number one. And then lastly, you know. Now, did you have this kind of ubiquity of data in this interconnected data network? Well, we're starting to see, and I think going to see a big wave of is hyper personalization of applications where instead of having the application have the data itself Have me Matt at Snowflake. Bring my data graph to applications. Right? This decoupling of we always talk about how you get data out of these applications. It's sort of the reverse was saying Now I want to bring all of my data access that I have 1st, 2nd and 3rd party into my application. Instead of having to think about getting all the data out of these applications, I think about it how when you you know, using a workout app in the consumer space, right? I can connect my Spotify or connect my apple music into that app to personalize the experience and bring my music list to that. Imagine if I could do that, you know, in a in a CRM. Imagine I could do that in a risk management. Imagine I could do that in a marketing app where I can bring my entire data graph with me and personalize that experience for, you know, for given what I have. And I think again, you know, partners like thoughts. But I think in a unique position to help enable that capability, you know, for this next wave of of applications that really take advantage of this decoupling of data. But having data flow into the app tied to me as opposed to having the APP have to know about my data ahead of time, >>Yeah, yeah, So that is very forward thinking. So I'll end with a prediction and a best practice. I am predicting that the organizations that really leverage external data, new data sources, not just whether or what have you and modernize those data flows will outperform the organizations that don't. And as a best practice to getting there, I the CDOs that own this have at least visibility into everything they're purchasing can save millions of dollars in duplicate spend. So, Thio, get their three key takeaways. Identify the leading indicators and market signals The data you need Thio. Better identify that. Consolidate those purchases and please explore the data sets the range of data sets data providers that we have on the thought spot. Atlas Marketplace Mallory over to you. >>Wow. Thank you. That was incredible. Thank you. To all of our Panelists for being here and sharing that wisdom. We really appreciate it. For those of you at home, stay close by. Our third session is coming right up and we'll be joined by our partner AWS and get to see how you can leverage the full power of your data cloud complete with the demo. Make sure to tune in to see you >>then

>>from around the >>globe. It's the Cube with digital coverage of AWS reinvent 2020 sponsored by Intel and AWS. Yeah, >>Hi. We are the Cube live covering AWS reinvent 2020. I'm Lisa Martin, and I've got one of our cube alumni back with me. Mike Miller is here. General manager of A W s AI Devices at AWS. Mike, welcome back to the Cube. >>Hi, Lisa. Thank you so much for having me. It's really great to join you all again at this virtual reinvent. >>Yes, I think last year you were on set. We have always had to. That's at reinvent. And you you had the deep race, your car, and so we're obviously socially distance here. But talk to me about deepracer. What's going on? Some of the things that have gone on the last year that you're excited >>about. Yeah, I'd love to tell. Tell you a little bit about what's been happening. We've had a tremendous year. Obviously, Cove. It has restricted our ability to have our in person races. Eso we've really gone gone gangbusters with our virtual league. So we have monthly races for competitors that culminate in the championship. Um, at reinvent. So this year we've got over 100 competitors who have qualified and who are racing virtually with us this year at reinvent. They're participating in a series of knockout rounds that are being broadcast live on twitch over the next week. That will whittle the group down to AH Group of 32 which will have a Siris of single elimination brackets leading to eight finalists who will race Grand Prix style five laps, eight cars on the track at the same time and will crown the champion at the closing keynote on December 15th this year. >>Exciting? So you're bringing a reinforcement, learning together with with sports that so many of us have been missing during the pandemic. We talked to me a little bit about some of the things that air that you've improved with Deep Racer and some of the things that are coming next year. Yeah, >>absolutely so, First of all, Deep Racer not only has been interesting for individuals to participate in the league, but we continue to see great traction and adoption amongst big customers on dare, using Deep Racer for hands on learning for machine learning, and many of them are turning to Deep Racer to train their workforce in machine learning. So over 150 customers from the likes of Capital One Moody's, Accenture, DBS Bank, JPMorgan Chase, BMW and Toyota have held Deep Racer events for their workforces. And in fact, three of those customers Accenture, DBS Bank and J. P. Morgan Chase have each trained over 1000 employees in their organization because they're just super excited. And they find that deep racers away to drive that excitement and engagement across their customers. We even have Capital one expanded this to their families, so Capital One ran a deep raise. Their Kids Cup, a family friendly virtual competition this past year were over. 250 Children and 200 families got to get hands on with machine learning. >>So I envisioned some. You know, this being a big facilitator during the pandemic when there's been this massive shift to remote work has have you seen an uptick in it for companies that talking about training need to be ableto higher? Many, many more people remotely but also train them? Is deep Racer facilitator of that? Yeah, >>absolutely. Deep Racer has ah core component of the experience, which is all virtualized. So we have, ah, console and integration with other AWS services so that racers can participate using a three d racing simulator. They can actually see their car driving around a track in a three D world simulation. Um, we're also selling the physical devices. So you know, if participants want to get the one of those devices and translate what they've done in the virtual world to the real world, they can start doing that. And in fact, just this past year, we made our deep race or car available for purchase internationally through the Amazon Com website to help facilitate that. >>So how maney deep racers air out there? I'm just curious. >>Oh, thousands. Um, you know, And there what? What we've seen is some companies will purchase you, know them in bulk and use them for their internal leagues. Just like you know, JP Morgan Chase on DBS Bank. These folks have their own kind of tracks and racers that they'll use to facilitate both in person as well as the virtual racing. >>I'm curious with this shift to remote that we mentioned a minute ago. How are you seeing deepracer as a facilitator of engagement. You mentioned engagement. And that's one of the biggest challenges that so Maney teams develops. Processes have without being co located with each other deep Brister help with that. I mean, from an engagement perspective, I think >>so. What we've seen is that Deep Racer is just fun to get your hands on. And we really lower the learning curve for machine learning. And in particular, this branch called reinforcement Learning, which is where you train this agent through trial and error toe, learn how to do a new, complex task. Um, and what we've seen is that customers who have introduced Deep Racer, um, as an event for their employees have seen ah, very wide variety of employees. Skill sets, um, kind of get engaged. So you've got not just the hardcore deep data scientists or the M L engineers. You've got Web front end programmers. You even have some non technical folks who want to get their hands dirty. Onda learn about machine learning and Deep Racer really is a nice, gradual introduction to doing that. You can get engaged with it with very little kind of coding knowledge at all. >>So talk to me about some of the new services. And let's look at some specific use case customer use cases with each service. Yeah, >>absolutely. So just to set the context. You know, Amazon's got hundreds. A ws has hundreds of thousands of customers doing machine learning on AWS. No customers of all sizes are embedding machine learning into their no core business processes. And one of the things that we always do it Amazon is We're listening to customers. You know, 90 to 95% of our road maps are driven by customer feedback. And so, as we've been talking to these industrial manufacturing customers, they've been telling us, Hey, we've got data. We've got these processes that are happening in our industrial sites. Um, and we just need some help connecting the dots like, how do we really most effectively use machine learning to improve our processes in these industrial and manufacturing sites? And so we've come up with these five services. They're focused on industrial manufacturing customers, uh, two of the services air focused around, um, predictive maintenance and, uh, the other three services air focused on computer vision. Um, and so let's start with the predictive maintenance side. So we announced Amazon Monitor On and Amazon look out for equipment. So these services both enable predictive maintenance powered by machine learning in a way that doesn't require the customer to have any machine learning expertise. So Mono Tron is an end to end machine learning system with sensors, gateway and an ML service that can detect anomalies and predict when industrial equipment will require maintenance. I've actually got a couple examples here of the sensors in the gateway, so this is Amazon monitor on these little sensors. This little guy is a vibration and temperature sensor that's battery operated, and wireless connects to the gateway, which then transfers the data up to the M L Service in the cloud. And what happens is, um, the sensors can be connected to any rotating machinery like pump. Pour a fan or a compressor, and they will send data up to the machine learning cloud service, which will detect anomalies or sort of irregular kind of sensor readings and then alert via a mobile app. Just a tech or a maintenance technician at an industrial site to go have a look at their equipment and do some preventative maintenance. So um, it's super extreme line to end to end and easy for, you know, a company that has no machine learning expertise to take advantage of >>really helping them get on board quite quickly. Yeah, >>absolutely. It's simple tea set up. There's really very little configuration. It's just a matter of placing the sensors, pairing them up with the mobile app and you're off and running. >>Excellent. I like easy. So some of the other use cases? Yeah, absolutely. >>So So we've seen. So Amazon fulfillment centers actually have, um, enormous amounts of equipment you can imagine, you know, the size of an Amazon fulfillment center. 28 football fields, long miles of conveyor belts and Amazon fulfillment centers have started to use Amazon monitor on, uh, to monitor some of their conveyor belts. And we've got a filament center in Germany that has started using these 1000 sensors, and they've already been able to, you know, do predictive maintenance and prevent downtime, which is super costly, you know, for businesses, we've also got customers like Fender, you know, who makes guitars and amplifiers and musical equipment. Here in the US, they're adopting Amazon monitor on for their industrial machinery, um, to help prevent downtime, which again can cost them a great deal as they kind of hand manufacture these high end guitars. Then there's Amazon. Look out for equipment, which is one step further from Amazon monitor on Amazon. Look out for equipment. Um provides a way for customers to send their own sensor data to AWS in order to build and train a model that returns predictions for detecting abnormal equipment behavior. So here we have a customer, for example, like GP uh, E P s in South Korea, or I'm sorry, g S E P s in South Korea there in industrial conglomerate, and they've been collecting their own data. So they have their own sensors from industrial equipment for a decade. And they've been using just kind of rule basic rules based systems to try to gain insight into that data. Well, now they're using Amazon, look out for equipment to take all of their existing sensor data, have Amazon for equipment, automatically generate machine learning models on, then process the sensor data to know when they're abnormalities or when some predictive maintenance needs to occur. >>So you've got the capabilities of working with with customers and industry that that don't have any ML training to those that do have been using sensors. So really, everybody has an opportunity here to leverage this new Amazon technology, not only for predicted, but one of the things I'm hearing is contact list, being able to understand what's going on without having to have someone physically there unless there is an issue in contact. This is not one of the words of 2020 but I think it probably should be. >>Yeah, absolutely. And in fact, that that was some of the genesis of some of the next industrial services that we announced that are based on computer vision. What we saw on what we heard when talking to these customers is they have what we call human inspection processes or manual inspection processes that are required today for everything from, you know, monitoring you like workplace safety, too, you know, quality of goods coming off of a machinery line or monitoring their yard and sort of their, you know, truck entry and exit on their looking for computer vision toe automate a lot of these tasks. And so we just announced a couple new services that use computer vision to do that to automate these once previously manual inspection tasks. So let's start with a W A. W s Panorama uses computer vision toe improve those operations and workplace safety. AWS Panorama is, uh, comes in two flavors. There's an appliance, which is, ah, box like this. Um, it basically can go get installed on your network, and it will automatically discover and start processing the video feeds from existing cameras. So there's no additional capital expense to take a W s panorama and have it apply computer vision to the cameras that you've already got deployed, you know, So customers are are seeing that, um, you know, computer vision is valuable, but the reason they want to do this at the edge and put this computer vision on site is because sometimes they need to make very low Leighton see decisions where if you have, like a fast moving industrial process, you can use computer vision. But I don't really want to incur the cost of sending data to the cloud and back. I need to make a split second decision, so we need machine learning that happens on premise. Sometimes they don't want to stream high bandwidth video. Or they just don't have the bandwidth to get this video back to the cloud and sometimes their data governance or privacy restrictions that restrict the company's ability to send images or video from their site, um, off site to the cloud. And so this is why Panorama takes this machine learning and makes it happen right here on the edge for customers. So we've got customers like Cargill who uses or who is going to use Panorama to improve their yard management. They wanna use computer vision to detect the size of trucks that drive into their granaries and then automatically assign them to an appropriately sized loading dock. You've got a customer like Siemens Mobility who you know, works with municipalities on, you know, traffic on by other transport solutions. They're going to use AWS Panorama to take advantage of those existing kind of traffic cameras and build machine learning models that can, you know, improve congestion, allocate curbside space, optimize parking. We've also got retail customers. For instance, Parkland is a Canadian fuel station, um, and retailer, you know, like a little quick stop, and they want to use Panorama to do things like count the people coming in and out of their stores and do heat maps like, Where are people visiting my store so I can optimize retail promotions and product placement? >>That's fantastic. The number of use cases is just, I imagine if we had more time like you could keep going and going. But thank you so much for not only sharing what's going on with Deep Racer and the innovations, but also for show until even though we weren't in person at reinvent this year, Great to have you back on the Cube. Mike. We appreciate your time. Yeah, thanks, Lisa, for having me. I appreciate it for Mike Miller. I'm Lisa Martin. You're watching the cubes Live coverage of aws reinvent 2020.

>>from around the globe. It's the Cube covering space and cybersecurity. Symposium 2020 hosted by Cal Poly >>Oven. Welcome back to the Space and Cyber Security Symposium. 2020 I'm John for your host with the Cuban silicon angle, along with Cal Poly, representing a great session here on industry success in developing space and cybersecurity. Resource is Got a great lineup. Brigadier General Steve Hotel, whose are also known as Bucky, is Call Sign director of Space Portfolio Defense Innovation Unit. Preston Miller, chief information security officer at JPL, NASA and Major General retired Clint Crozier, director of aerospace and satellite solutions at Amazon Web services, also known as a W s. Gentlemen, thank you for for joining me today. So the purpose of this session is to spend the next hour talking about the future of workforce talent. Um, skills needed and we're gonna dig into it. And Spaces is an exciting intersection of so many awesome disciplines. It's not just get a degree, go into a track ladder up and get promoted. Do those things. It's much different now. Love to get your perspectives, each of you will have an opening statement and we will start with the Brigadier General Steve Hotel. Right? >>Thank you very much. The Defense Innovation Unit was created in 2015 by then Secretary of Defense Ash Carter. To accomplish three things. One is to accelerate the adoption of commercial technology into the Department of Defense so that we can transform and keep our most relevant capabilities relevant. And also to build what we call now called the national Security Innovation Base, which is inclusive all the traditional defense companies, plus the commercial companies that may not necessarily work with focus exclusively on defense but could contribute to our national security and interesting ways. Um, this is such an exciting time Azul here from our other speakers about space on and I can't, uh I'm really excited to be here today to be able to share a little bit of our insight on the subject. >>Thank you very much. Precedent. Miller, Chief information security officer, Jet Propulsion Lab, NASA, Your opening statement. >>Hey, thank you for having me. I would like to start off by providing just a little bit of context of what brings us. Brings us together to talk about this exciting topic for space workforce. Had we've seen In recent years there's been there's been a trend towards expanding our space exploration and the space systems that offer the great things that we see in today's world like GPS. Um, but a lot of that has come with some Asian infrastructure and technology, and what we're seeing as we go towards our next generation expects of inspiration is that we now want to ensure that were secured on all levels. And there's an acknowledgement that our space systems are just a susceptible to cyber attacks as our terrestrial assistance. We've seen a recent space, uh, policy Directive five come out from our administration, that that details exactly how we should be looking at the cyber principle for our space systems, and we want to prevent. We want to prevent a few things as a result of that of these principles. Spoofing and jamming of our space systems are not authorized commands being sent to those space systems, lots of positive control of our space vehicles on lots of mission data. We also acknowledge that there's a couple of frameworks we wanna adopt across the board of our space systems levers and things like our nice miss cybersecurity frameworks. eso what has been a challenge in the past adopted somebody Cyber principles in space systems, where there simply has been a skill gap in a knowledge gap. We hire our space engineers to do a few things. Very well designed space systems, the ploy space systems and engineer space systems, often cybersecurity is seen as a after thought and certainly hasn't been a line item and in any budget for our spaces in racing. Uh, in the past in recent years, the dynamic started to change. We're now now integrating cyber principles at the onset of development of these life cycle of space. Systems were also taking a hard look of how we train the next generation of engineers to be both adequate. Space engineers, space system engineers and a cyber engineers, as a result to Mrs success on DWI, also are taking a hard look at What do we mean when we talk about holistic risk management for our space assistance, Traditionally risk management and missing insurance for space systems? I've really revolved around quality control, but now, in recent years we've started to adopt principles that takes cyber risk into account, So this is a really exciting topic for me. It's something that I'm fortunate to work with and live with every day. I'm really excited to get into this discussion with my other panel members. Thank you. >>You Preston. Great insight there. Looking forward. Thio chatting further. Um, Clint Closure with a W. S now heading up. A director of aerospace and satellite Solutions, formerly Major General, Your opening statement. >>Thanks, John. I really appreciate that introduction and really appreciate the opportunity to be here in the Space and Cybersecurity Symposium. And thanks to Cal Poly for putting it together, you know, I can't help, but as I think to Cal Poly there on the central California coast, San Luis Obispo, California I can't help but to think back in this park quickly. I spent two years of my life as a launch squadron commander at Vandenberg Air Force Base, about an hour south of Cal Poly launching rockets, putting satellites in orbit for the national intelligence community and so some really fond memories of the Central California coast. I couldn't agree more with the theme of our symposium this week. The space and cyber security we've all come to know over the last decade. How critical spaces to the world, whether it's for national security intelligence, whether it's whether communications, maritime, agriculture, development or a whole host of other things, economic and financial transactions. But I would make the case that I think most of your listeners would agree we won't have space without cybersecurity. In other words, if we can't guaranteed cybersecurity, all those benefits that we get from space may not be there. Preston in a moment ago that all the threats that have come across in the terrestrial world, whether it be hacking or malware or ransomware or are simple network attacks, we're seeing all those migrate to space to. And so it's a really important issue that we have to pay attention to. I also want to applaud Cow Pauling. They've got some really important initiatives. The conference here, in our particular panel, is about developing the next generation of space and cyber workers, and and Cal Poly has two important programs. One is the digital transformation hub, and the other is space data solutions, both of which, I'm happy to say, are in partnership with a W. S. But these were important programs where Cal Poly looks to try to develop the next generation of space and cyber leaders. And I would encourage you if you're interested in that toe. Look up the program because that could be very valuable is well, I'm relatively new to the AWS team and I'm really happy Thio team, as John you said recently retired from the U. S. Air Force and standing up the U. S. Space force. But the reason that I mentioned that as the director of the aerospace and satellite team is again it's in perfect harmony with the theme today. You know, we've recognized that space is critically important and that cyber security is critically important and that's been a W s vision as well. In fact, a W s understands how important the space domain is and coupled with the fact that AWS is well known that at a W s security is job zero and stolen a couple of those to fax A. W. S was looking to put together a team the aerospace and satellite team that focus solely and exclusively every single day on technical innovation in space and more security for the space domain through the cloud and our offerings there. So we're really excited to reimagine agree, envision what space networks and architectures could look like when they're born on the cloud. So that's important. You know, talk about workforce here in just a moment, but but I'll give you just a quick sneak. We at AWS have also recognized the gap in the projected workforce, as Preston mentioned, Um, depending on the projection that you look at, you know, most projections tell us that the demand for highly trained cyber cyber security cloud practitioners in the future outweighs what we think is going to be the supply. And so a ws has leaned into that in a number of ways that we're gonna talk about the next segment. I know. But with our workforce transformation, where we've tried to train free of charge not just a W s workers but more importantly, our customers workers. It s a W s we obsessed over the customer. And so we've provided free training toe over 7000 people this year alone toe bring their cloud security and cyber security skills up to where they will be able to fully leverage into the new workforce. So we're really happy about that too? I'm glad Preston raised SPD five space policy Directive five. I think it's gonna have a fundamental impact on the space and cyber industry. Uh, now full disclosure with that said, You know, I'm kind of a big fan of space policy directives, ESPN, Or was the space policy directive that directed to stand up of the U. S. Space Force and I spent the last 18 months of my life as the lead planner and architect for standing up the U. S. Space force. But with that said, I think when we look back a decade from now, we're going to see that s p d five will have as much of an impact in a positive way as I think SPD for on the stand up of the space Force have already done so. So I'll leave it there, but really look forward to the dialogue and discussion. >>Thank you, gentlemen. Clint, I just wanna say thank you for all your hard work and the team and the people who were involved in standing up Space force. Um, it is totally new. It's a game changer. It's modern, is needed. And there's benefits on potential challenges and opportunities that are gonna be there, so thank you very much for doing that. I personally am excited. I know a lot of people are excited for what the space force is today and what it could become. Thank you very much. >>Yeah, Thanks. >>Okay, So >>with >>that, let me give just jump in because, you know, as you're talking about space force and cybersecurity and you spend your time at Vanderburgh launching stuff into space, that's very technical. Is operation okay? I mean, it's complex in and of itself, but if you think about like, what's going on beyond in space is a lot of commercial aspect. So I'm thinking, you know, launching stuff into space on one side of my brain and the other side of brain, I'm thinking like air travel. You know, all the logistics and the rules of the road and air traffic control and all the communications and all the technology and policy and, you >>know, landing. >>So, Major General Clint, what's your take on this? Because this is not easy. It's not just one thing that speaks to the diversity of workforce needs. What's your reaction to that? >>Yeah. I mean, your observation is right on. We're seeing a real boom in the space and aerospace industry. For all the good reasons we talked about, we're recognizing all the value space from again economic prosperity to exploration to being ableto, you know, improve agriculture and in weather and all those sorts of things that we understand from space. So what I'm really excited about is we're seeing this this blossom of space companies that we sort of referred to his new space. You know, it used to be that really only large governments like the United States and a handful of others could operate in the space domain today and largely infused because of the technological innovation that have come with Cyber and Cyrus Space and even the cloud we're seeing more and more companies, capabilities, countries, all that have the ability, you know. Even a well funded university today can put a cube sat in orbit, and Cal Poly is working on some of those too, by the way, and so it's really expanded the number of people that benefits the activity in space and again, that's why it's so critically important because we become more and more reliant and we will become more and more reliant on those capabilities that we have to protect him. It's fundamental that we do. So, >>Bucky, I want you to weigh in on this because actually, you you've flown. Uh, I got a call sign which I love interviewing people. Anyone who's a call sign is cool in my book. So, Bucky, I want you to react to that because that's outside of the technology, you know, flying in space. There's >>no >>rule. I mean, is there like a rules? I mean, what's the rules of the road? I mean, state of the right. I mean, what I mean, what what's going? What's gonna have toe happen? Okay, just logistically. >>Well, this is very important because, uh and I've I've had access thio information space derived information for most of my flying career. But the amount of information that we need operate effectively in the 21st century is much greater than Thanet has been in the past. Let me describe the environment s so you can appreciate a little bit more what our challenges are. Where, from a space perspective, we're going to see a new exponential increase in the number of systems that could be satellites. Uh, users and applications, right? And so eso we're going we're growing rapidly into an environment where it's no longer practical to just simply evolved or operate on a perimeter security model. We and with this and as I was brought up previously, we're gonna try to bring in MAWR commercial capabilities. There is a tremendous benefit with increasing the diversity of sources of information. We use it right now. The military relies very heavily on commercial SAT com. We have our military capabilities, but the commercial capabilities give us capacity that we need and we can. We can vary that over time. The same will be true for remote sensing for other broadband communications capabilities on doing other interesting effects. Also, in the modern era, we doom or operations with our friends and allies, our regional partners all around the world, in order to really improve our interoperability and have rapid exchange of information, commercial information, sources and capabilities provides the best means of doing that. So that so that the imperative is very important and what all this describes if you want to put one word on it. ISS, we're involving into ah hybrid space architectures where it's gonna be imperative that we protect the integrity of information and the cyber security of the network for the things most important to us from a national security standpoint. But we have to have the rules that that allows us to freely exchange information rapidly and in a way that that we can guarantee that the right users are getting the right information at the right. >>We're gonna come back to that on the skill set and opportunities for people driving. That's just looking. There's so much opportunity. Preston, I want you to react to this. I interviewed General Keith Alexander last year. He formerly ran Cyber Command. Um, now he's building Cyber Security Technologies, and his whole thesis is you have to share. So the question is, how do you share and lock stuff down at the same time when you have ah, multi sided marketplace in space? You know, suppliers, users, systems. This is a huge security challenge. What's your reaction to this? Because we're intersecting all these things space and cybersecurity. It's just not easy. What's your reaction? >>Absolutely, Absolutely. And what I would say in response to that first would be that security really needs to be baked into the onset of how we develop and implement and deploy our space systems. Um, there's there's always going to be the need to collect and share data across multiple entities, particularly when we're changing scientific data with our mission partners. Eso with that necessitates that we have a security view from the onset, right? We have a system spaces, and they're designed to share information across the world. How do we make sure that those, uh, those other those communication channels so secure, free from interception free from disruption? So they're really done? That necessitates of our space leaders in our cyber leaders to be joining the hip about how to secure our space systems, and the communications there in Clinton brought up a really good point of. And then I'm gonna elaborate on a little bit, just toe invite a little bit more context and talk about some the complexities and challenges we face with this advent of new space and and all of our great commercial partners coming into therefore way, that's going to present a very significant supply chain risk management problems that we have to get our hands around as well. But we have these manufacturers developing these highly specialized components for the space instruments, Um, that as it stands right now, it's very little oversight And how those things air produced, manufactured, put into the space systems communication channels that they use ports protocols that they use to communicate. And that's gonna be a significant challenge for us to get get our hands around. So again, cybersecurity being brought in. And the very onset of these development thes thes decisions in these life cycles was certainly put us in a best better position to secure that data in our in our space missions. >>Yeah, E just pick up on that. You don't mind? Preston made such a really good point there. But you have to bake security in up front, and you know there's a challenge and there's an opportunity, you know, with a lot of our systems today. It was built in a pre cyber security environment, especially our government systems that were built, you know, in many cases 10 years ago, 15 years ago are still on orbit today, and we're thankful that they are. But as we look at this new environment and we understand the threats, if we bake cybersecurity in upfront weaken balance that open application versus the risk a long as we do it up front. And you know, that's one of the reasons that our company developed what we call govcloud, which is a secure cloud, that we use thio to manage data that our customers who want to do work with the federal government or other governments or the national security apparatus. They can operate in that space with the built in and baked in cybersecurity protocols. We have a secret region that both can handle secret and top secret information for the same reasons. But when you bake security into the upfront applications, that really allows you to balance that risk between making it available and accessible in sort of an open architecture way. But being sure that it's protected through things like ITAR certifications and fed ramp, uh, another ice T certifications that we have in place. So that's just a really important point. >>Let's stay high level for a man. You mentioned a little bit of those those govcloud, which made me think about you know, the tactical edge in the military analogy, but also with space similar theater. It's just another theater and you want to stand stuff up. Whether it's communications and have facilities, you gotta do it rapidly, and you gotta do it in a very agile, secure, I high availability secure way. So it's not the old waterfall planning. You gotta be fast is different. Cloud does things different? How do you talk to the young people out there, whether it's apparent with with kids in elementary and middle school to high school, college grad level or someone in the workforce? Because there are no previous jobs, that kind of map to the needs out there because you're talking about new skills, you could be an archaeologist and be the best cyber security guru on the planet. You don't have to have that. There's no degree for what, what we're talking about here. This >>is >>the big confusion around education. I mean, you gotta you like math and you could code you can Anything who wants to comment on that? Because I think this >>is the core issue. I'll say there are more and more programs growing around that educational need, and I could talk about a few things we're doing to, but I just wanna make an observation about what you just said about the need. And how do you get kids involved and interested? Interestingly, I think it's already happening, right. The good news. We're already developing that affinity. My four year old granddaughter can walk over, pick up my iPad, turn it on. Somehow she knows my account information, gets into my account, pulls up in application, starts playing a game. All before I really even realized she had my iPad. I mean, when when kids grow up on the cloud and in technology, it creates that natural proficiency. I think what we have to do is take that natural interest and give them the skill set the tools and capabilities that go with it so that we're managing, you know, the the interest with the technical skills. >>And also, like a fast I mean, just the the hackers are getting educated. Justus fast. Steve. I mean e mean Bucky. What do you do here? You CIt's the classic. Just keep chasing skills. I mean, there are new skills. What are some of those skills? >>Why would I amplify eloquent? Just said, First of all, the, uh, you know, cyber is one of those technology areas where commercial side not not the government is really kind of leading away and does a significant amount of research and development. Ah, billions of dollars are spent every year Thio to evolve new capabilities. And a lot of those companies are, you know, operated and and in some cases, led by folks in their early twenties. So the S O. This is definitely an era and a generation that is really poised in position. Well, uh, Thio take on this challenge. There's some unique aspects to space. Once we deploy a system, uh, it will be able to give me hard to service it, and we're developing capabilities now so that we could go up and and do system upgrades. But that's not a normal thing in space that just because the the technical means isn't there yet. So having software to find capabilities, I's gonna be really paramount being able to dio unique things. The cloud is huge. The cloud is centric to this or architectural, and it's kind of funny because d o d we joke because we just discovered the cloud, you know, a couple years ago. But the club has been around for a while and, uh, and it's going to give us scalability on and the growth potential for doing amazing things with a big Data Analytics. But as Preston said, it's all for not if if we can't trust the data that we receive. And so one of the concepts for future architectures is to evolve into a zero trust model where we trust nothing. We verify and authenticate everyone. And, uh, and that's that's probably a good, uh, point of departure as we look forward into our cybersecurity for space systems into the future. >>Block everyone. Preston. Your reaction to all this gaps, skills, What's needed. I mean it Z everyone's trying to squint through this >>absolutely. And I wanna want to shift gears a little bit and talk about the space agencies and organizations that are responsible for deploying these spaces into submission. So what is gonna take in this new era on, and what do we need from the workforce to be responsive to the challenges that we're seeing? First thing that comes to mind is creating a culture of security throughout aerospace right and ensuring that Azzawi mentioned before security isn't an afterthought. It's sort of baked into our models that we deploy and our rhetoric as well, right? And because again we hire our spaces in years to do it very highly. Specialized thing for a highly specialized, uh, it's topic. Our effort, if we start to incorporate rhetorically the importance of cybersecurity two missing success and missing assurance that's going to lend itself toe having more, more prepared on more capable system engineers that will be able to respond to the threats accordingly. Traditionally, what we see in organizational models it's that there's a cyber security team that's responsible for the for the whole kit kaboodle across the entire infrastructure, from enterprise systems to specialize, specialize, space systems and then a small pocket of spaces, years that that that are really there to perform their tasks on space systems. We really need to bridge that gap. We need to think about cybersecurity holistically, the skills that are necessary for your enterprise. I t security teams need to be the same skills that we need to look for for our system engineers on the flight side. So organizationally we need we need to address that issue and approach it, um todo responsive to the challenges we see our our space systems, >>new space, new culture, new skills. One of the things I want to bring up is looking for success formulas. You know, one of the things we've been seeing in the past 10 years of doing the Cube, which is, you know, we've been called the ESPN of Tech is that there's been kind of like a game ification. I want to. I don't wanna say sports because sports is different, but you're seeing robotics clubs pop up in some schools. It's like a varsity sport you're seeing, you know, twitch and you've got gamers out there, so you're seeing fun built into it. I think Cal Poly's got some challenges going on there, and then scholarships air behind it. So it's almost as if, you know, rather than going to a private sports training to get that scholarship, that never happens. There's so many more scholarship opportunities for are not scholarship, but just job opportunities and even scholarships we've covered as part of this conference. Uh, it's a whole new world of culture. It's much different than when I grew up, which was you know, you got math, science and English. You did >>it >>and you went into your track. Anyone want to comment on this new culture? Because I do believe that there is some new patterns emerging and some best practices anyone share any? >>Yeah, I do, because as you talked about robotics clubs and that sort of things, but those were great and I'm glad those air happening. And that's generating the interest, right? The whole gaming culture generating interest Robotic generates a lot of interest. Space right has captured the American in the world attention as well, with some recent NASA activities and all for the right reasons. But it's again, it's about taking that interested in providing the right skills along the way. So I'll tell you a couple of things. We're doing it a w s that we found success with. The first one is a program called A W s Academy. And this is where we have developed a cloud, uh, program a cloud certification. This is ah, cloud curriculum, if you will, and it's free and it's ready to teach. Our experts have developed this and we're ready to report it to a two year and four year colleges that they can use is part of the curriculum free of charge. And so we're seeing some real value there. And in fact, the governor's in Utah and Arizona recently adopted this program for their two year schools statewide again, where it's already to teach curriculum built by some of the best experts in the industry s so that we can try to get that skills to the people that are interested. We have another program called A W s educate, and this is for students to. But the idea behind this is we have 12 cracks and you can get up to 50 hours of free training that lead to A W s certification, that sort of thing. And then what's really interesting about that is all of our partners around the world that have tied into this program we manage what we call it ws educate Job board. And so if you have completed this educate program now, you can go to that job board and be linked directly with companies that want people with those skills we just helped you get. And it's a perfect match in a perfect marriage there. That one other piece real quickly that we're proud of is the aws Uh restart program. And that's where people who are unemployed, underemployed or transitioning can can go online. Self paced. We have over 500 courses they can take to try to develop those initial skills and get into the industry. And that's been very popular, too, So that those air a couple of things we're really trying to lean into >>anyone else want to react. Thio that question patterns success, best practices, new culture. >>I'd like Thio. The the wonderful thing about what you just touched on is problem solving, right, And there's some very, very good methodologies that are being taught in the universities and through programs like Hacking for Defense, which is sponsored by the National Security Innovation Network, a component of the I you where I work but the But whether you're using a lien methodologies or design school principals or any other method, the thing that's wonderful right now and not just, uh, where I work at the U. The Space force is doing this is well, but we're putting the problem out there for innovators to tackle, And so, rather than be prescriptive of the solutions that we want to procure, we want we want the best minds at all levels to be able to work on the problem. Uh, look at how they can leverage other commercial solutions infrastructure partnerships, uh, Thio to come up with a solution that we can that we can rapidly employ and scale. And if it's a dual use solution or whether it's, uh, civil military or or commercial, uh, in any of the other government solutions. Uh, that's really the best win for for the nation, because that commercial capability again allows us to scale globally and share those best practices with all of our friends and allies. People who share our values >>win win to this commercial. There's a business model potential financial benefits as well. Societal impact Preston. I want to come to you, JPL, NASA. I mean, you work in one of the most awesome places and you know, to me, you know, if you said to me, Hey, John, come working JP like I'm not smart enough to go there like I mean, like, it's a pretty It's intimidating, it might seem >>share folks out there, >>they can get there. I mean, it's you can get there if you have the right skills. I mean I'm just making that up. But, I mean, it is known to be super smart And is it attainable? So share your thoughts on this new culture because you could get the skills to get there. What's your take on all this >>s a bucket. Just missing something that really resonated with me, right? It's do it your love office. So if you put on the front engineer, the first thing you're gonna try to do is pick it apart. Be innovative, be creative and ways to solve that issue. And it has been really encouraging to me to see the ground welcome support an engagement that we've seen across our system. Engineers in space. I love space partners. A tackling the problem of cyber. Now that they know the West at risk on some of these cyber security threats that that they're facing with our space systems, they definitely want to be involved. They want to take the lead. They want to figure things out. They wanna be innovative and creative in that problem solving eso jpl We're doing a few things. Thio Raise the awareness Onda create a culture of security. Andi also create cyber advocates, cybersecurity advocates across our space engineers. We host events like hacked the lad, for example, and forgive me. Take a pause to think about the worst case scenarios that could that could result from that. But it certainly invites a culture of creative problem solving. Um, this is something that that kids really enjoy that are system engineers really enjoyed being a part off. Um, it's something that's new refreshing to them. Eso we were doing things like hosting a monthly cybersecurity advocacy group. When we talk about some of the cyber landscape of our space systems and invite our engineers into the conversation, we do outweighs programs specifically designed to to capture, um, our young folks, uh, young engineers to deceive. They would be interested and show them what this type of security has to offer by ways of data Analytic, since the engineering and those have been really, really successful identifying and bringing in new talent to address the skill gaps. >>Steve, I want to ask you about the d. O. D. You mentioned some of the commercial things. How are you guys engaging the commercial to solve the space issue? Because, um, the normalization in the economy with GPS just seeing spaces impacts everybody's lives. We we know that, um, it's been talked about. And and there's many, many examples. How are you guys the D o. D. From a security standpoint and or just from an advancement innovation standpoint, engaging with commercials, commercial entities and commercial folks? >>Well, I'll throw. I'll throw a, uh, I'll throw ah, compliment to Clint because he did such an outstanding job. The space forces already oriented, uh, towards ah, commercial where it's appropriate and extending the arms. Leveraging the half works on the Space Enterprise Consortium and other tools that allow for the entrepreneurs in the space force Thio work with their counterparts in a commercial community. And you see this with the, uh, you know, leveraging space X away to, uh, small companies who are doing extraordinary things to help build space situational awareness and, uh, s So it's it's the people who make this all happen. And what we do at at the D. O. D level, uh, work at the Office of Secretary defense level is we wanna make sure that they have the right tools to be able to do that in a way that allows these commercial companies to work with in this case of a space force or with cyber command and ways that doesn't redefine that. The nature of the company we want we want We want commercial companies to have, ah, great experience working with d o d. And we want d o d toe have the similar experience working, working with a commercial community, and and we actually work interagency projects to So you're going to see, uh, General Raymond, uh, hey, just recently signed an agreement with the NASA Esa, you're gonna see interagency collaborations on space that will include commercial capabilities as well. So when we speak as one government were not. You know, we're one voice, and that's gonna be tremendous, because if you're a commercial company on you can you can develop a capability that solves problems across the entire space enterprise on the government side. How great is that, Right. That's a scaling. Your solution, gentlemen. Let >>me pick you back on that, if you don't mind. I'm really excited about that. I mentioned new space, and Bucky talked about that too. You know, I've been flying satellites for 30 years, and there was a time where you know the U. S. Government national security. We wouldn't let anybody else look at him. Touch him. Plug into, um, anything else, right. And that probably worked at the time. >>But >>the world has changed. And more >>importantly, >>um, there is commercial technology and capability available today, and there's no way the U. S government or national security that national Intel community can afford economically >>to >>fund all that investment solely anymore. We don't have the manpower to do it anymore. So we have this perfect marriage of a burgeoning industry that has capabilities and it has re sources. And it has trained manpower. And we are seeing whether it's US Space Force, whether it's the intelligence community, whether it's NASA, we're seeing that opened up to commercial providers more than I've ever seen in my career. And I can tell you the customers I work with every day in a W s. We're building an entire ecosystem now that they understand how they can plug in and participate in that, and we're just seeing growth. But more importantly, we're seeing advanced capability at cheaper cost because of that hybrid model. So that really is exciting. >>Preston. You know you mentioned earlier supply chain. I don't think I think you didn't use the word supply chain. Maybe you did. But you know about the components. Um, you start opening things up and and your what you said baking it in to the beginning, which is well known. Uh, premise. It's complicated. So take me through again, Like how this all gonna work securely because And what's needed for skill sets because, you know, you're gonna open. You got open source software, which again, that's open. We live in a free society in the United States of America, so we can't lock everything down. You got components that are gonna be built anywhere all around the world from vendors that aren't just a certified >>or maybe >>certified. Um, it's pretty crazy. So just weigh in on this key point because I think Clint has it right. And but that's gonna be solved. What's your view on this? >>Absolutely. And I think it really, really start a top, right? And if you look back, you know, across, um in this country, particularly, you take the financial industry, for example, when when that was a burgeoning industry, what had to happen to ensure that across the board. Um, you know, your your finances were protected these way. Implemented regulations from the top, right? Yeah. And same thing with our health care industry. We implemented regulations, and I believe that's the same approach we're gonna need to take with our space systems in our space >>industry >>without being too directive or prescriptive. Instance she ating a core set of principles across the board for our manufacturers of space instruments for deployment and development of space systems on for how space data and scientific data is passed back and forth. Eso really? We're gonna need to take this. Ah, holistic approach. Thio, how we address this issue with cyber security is not gonna be easy. It's gonna be very challenging, but we need to set the guard rails for exactly what goes into our space systems, how they operate and how they communicate. >>Alright, so let's tie this back to the theme, um, Steve and Clint, because this is all about workforce gaps, opportunities. Um, Steve, you mentioned software defined. You can't do break fix in space. You can't just send a technician up in the space to fix a component. You gotta be software defined. We're talking about holistic approach, about commercial talk about business model technology with software and policy. We need people to think through, like you know. What the hell are you gonna do here, right? Do you just noticed road at the side of the road to drive on? There's no rules of engagement. So what I'm seeing is certainly software Check. If you wanna have a job for the next millennial software policy who solves two problems, what does freedom looked like in space Congestion Contention and then, obviously, business model. Can you guys comment on these three areas? Do you agree? And what specific person might be studying in grad school or undergraduate or in high school saying, Hey, I'm not a techie, but they can contribute your thoughts. I'll >>start off with, uh, speak on on behalf of the government today. I would just say that as policy goes, we need to definitely make sure that we're looking towards the future. Ah, lot of our policy was established in the past under different conditions, and, uh, and if there's anything that you cannot say today is that space is the same as it was even 10 years ago. So the so It's really important that our policy evolves and recognizes that that technology is going to enable not just a new ways of doing things, but also force us to maybe change or or get rid of obsolete policies that will inhibit our ability to innovate and grow and maintain peace with with a rapid, evolving threat. The for the for the audience today, Uh, you know, you want some job assurance, cybersecurity and space it's gonna be It's gonna be an unbelievable, uh, next, uh, few decades and I couldn't think of a more exciting for people to get into because, you know, spaces Ah, harsh environment. We're gonna have a hard time just dud being able differentiate, you know, anomalies that occur just because of the environment versus something that's being hacked. And so JPL has been doing this for years on they have Cem Cem great approaches, but but this is this is gonna be important if you put humans on the moon and you're going to sustain them there. Those life support systems are gonna be using, you know, state of the art computer technology, and which means, is also vulnerable. And so eso the consequences of us not being prepared? Uh, not just from our national security standpoint, but from our space exploration and our commercial, uh, economic growth in space over the long term all gonna be hinged on this cyber security environment. >>Clint, your thoughts on this too ill to get. >>Yeah. So I certainly agree with Bucky. But you said something a moment ago that Bucky was talking about as well. But that's the idea that you know in space, you can't just reach out and touch the satellite and do maintenance on the satellite the way you can't a car or a tank or a plane or a ship or something like that. And that is true. However, right, comma, I want to point out. You know, the satellite servicing industry is starting to develop where they're looking at robotic techniques in Cape abilities to go up in services satellite on orbit. And that's very promising off course. You got to think through the security policy that goes with that, of course. But the other thing that's really exciting is with artificial intelligence and machine learning and edge computing and database analytics and all those things that right on the cloud. You may not even need to send a robotic vehicle to a satellite, right? If you can upload and download software defined, fill in the blank right, maybe even fundamentally changing the mission package or the persona, if you will, of the satellite or the spacecraft. And that's really exciting to, ah, lot >>of >>security policy that you've gotta work through. But again, the cloud just opens up so many opportunities to continue to push the boundaries. You know, on the AWS team, the aerospace and satellite team, which is, you know, the new team that I'm leading. Now our motto is to the stars through the cloud. And there are just so many exciting opportunities right for for all those capabilities that I just mentioned to the stars through the cloud >>President, your thoughts on this? >>Yes, eso won >>a >>little bit of time talking about some of the business model implications and some of the challenges that exists there. Um, in my experience, we're still working through a bit of a language barrier of how we define risk management for our space systems. Traditionally traditionally risk management models is it is very clear what poses a risk to a flight mission. Our space mission, our space system. Um, and we're still finding ways to communicate cyber risk in the same terms that are system engineers are space engineers have traditionally understood. Um, this is a bit of a qualitative versus quantitative, a language barrier. But however adopting a risk management model that includes cybersecurity, a za way to express wish risk to miss the success, I think I think it would be a very good thing is something that that we have been focused on the J. P o as we Aziz, we look at the 34 years beyond. How do >>we >>risk that gap and not only skills but communication of cyber risk and the way that our space engineers and our project engineers and a space system managers understand >>Clinton, like Thio talk about space Force because this is the most popular new thing. It's only a couple of nine months in roughly not even a year, uh, already changing involving based on some of the reporting we've done even here at this symposium and on the Internet. Um, you know, when I was growing up, you know, I wasn't there when JFK said, you know, we're gonna get to the moon. I was born in the sixties, so, you know, when I was graduating my degree, you know, Draper Labs, Lincoln Lab, JPL, their pipeline and people wasn't like a surge of job openings. Um, so this kind of this new space new space race, you know, Kennedy also said that Torch has been passed to a new generation of Americans. So in a way that's happening right now with space force. A new generation is here is a digital generation. It's multi disciplinary generation. Could you take a minute and share, uh, for for our audience? And here at this symposium, um, the mission of Space Force and where you see it going because this truly is different. And I think anyone who's young e I mean, you know, if this was happening when I was in college would be like dropping everything. I'm in there, I think, cause there's so many areas thio jump into, um, it's >>intellectually challenging. >>It's intoxicating in some level. So can you share your thoughts? >>Yeah. Happy to do that. Of course. I I need to remind everybody that as a week ago I'm formally retired. So I'm not an official spokesman for US forces. But with that, you know, it said I did spend the last 18 months planning for it, designing and standing it up. And I'll tell you what's really exciting is you know, the commander of, uh, US Base Force General J. Raymond, who's the right leader at the right time. No question in my >>mind. But >>he said, I want to stand up the Space Force as the first fully digital service in the United States. Right? So he is trying >>to bake >>cloud baked cybersecurity, baked digital transformational processes and everything we did. And that was a guidance he gave us every day, every day. When we rolled in. He said, Remember, guys, I don't wanna be the same. I don't wanna be stale. I want new thinking, new capabilities and I want it all to be digital on. That's one of the reasons When we brought the first wave of people into the space force, we brought in space operations, right. People like me that flew satellites and launch rockets, we brought in cyber space experts, and we brought in intelligence experts. Those were the first three waves of people because of that, you know, perfect synergy between space and cyber and intel all wrapped in >>it. >>And so that was really, really smart. The other thing I'll say just about, you know, Kennedy's work. We're going to get to the moon. So here we are. Now we're going back to the Moon Project Artemus that NASA is working next man first woman on the moon by 2024 is the plan and >>then >>with designs to put a permanent presence on the moon and then lean off to march. So there was a lot to get excited about. I will tell you, as we were taking applications and looking at rounding out filling out the village in the U. S. Space Force, we were overwhelmed with the number of people that wanted, and that was a really, really good things. So they're off to a good start, and they're just gonna accomplishment major things. I know for sure. >>Preston, your thoughts on this new generation people out there were like I could get into this. This is a path. What's your what's your opinion on this? And what's your >>E could, uh, you so bold as to say >>that >>I feel like I'm a part of that new generation eso I grew up very much into space. Uh, looking at, um, listen to my, uh, folks I looked up to like Carl Sagan. Like like Neil Tyson. DeGrasse on did really feeling affinity for what What this country has done is for is a space program are focused on space exploration on bond. Through that, I got into our security, as it means from the military. And I just because I feel so fortunate that I could merge both of those worlds because of because of the generational, um, tailoring that we do thio promote space exploration and also the advent of cybersecurity expertise that is needed in this country. I feel like that. We are We are seeing a conversions of this too. I see a lot of young people really getting into space exploration. I see a lot of young people as well. Um uh, gravitating toward cybersecurity as a as a course of study. And to see those two worlds colliding and converse is something that's very near and dear to me. And again, I I feel like I'm a byproduct of that conversion, which is which, Really, Bothwell for space security in the future, >>we'll your great leader and inspiration. Certainly. Senior person as well. Congratulations, Steve. You know, young people motivational. I mean, get going. Get off the sidelines. Jump in Water is fine, Right? Come on in. What's your view on motivating the young workforce out there and anyone thinking about applying their skills on bringing something to the table? >>Well, look at the options today. You have civil space President represents you have military space. Uh, you have commercial space on and even, you know, in academia, the research, the potential as a as an aspiring cyber professional. All of you should be thinking about when we when we When? When we first invented the orbit, which eventually became the Internet, Uh, on Lee, we were, uh if all we had the insight to think Well, geez, you know whether the security implications 2030 years from now of this thing scaling on growing and I think was really good about today's era. Especially as Clint said, because we were building this space infrastructure with a cyber professionals at ground zero on dso the So the opportunity there is to look out into the future and say we're not just trying to secure independent her systems today and assure the free for all of of information for commerce. You know, the GPS signal, Uh, is Justus much in need of protection as anything else tied to our economy, But the would have fantastic mission. And you could do that. Uh, here on the ground. You could do it, uh, at a great companies like Amazon Web services. But you can also one of these states. Perhaps we go and be part of that contingency that goes and does the, uh, the se's oh job that that president has on the moon or on Mars and, uh, space will space will get boring within a generation or two because they'll just be seen as one continuum of everything we have here on Earth. And, uh, and that would be after our time. But in the meantime, is a very exciting place to be. And I know if I was in in my twenties, I wanna be, uh, jumping in with both feet into it. >>Yeah, great stuff. I mean, I think space is gonna be around for a long long time. It's super exciting and cybersecurity making it secure. And there's so many areas defeating on. Gentlemen, thank you very much for your awesome insight. Great panel. Um, great inspiration. Every one of you guys. Thank you very much for for sharing for the space and cybersecurity symposium. Appreciate it. Thank you very much. >>Thanks, John. Thank you. Thank you. Okay, >>I'm >>John for your host for the Space and Cybersecurity Symposium. Thanks for watching.

>>live from Atlanta, Georgia. It's the Q covering Answerable Fest 2019. Brought to you by >>Red Hat. >>Okay, welcome back. It runs two cubes. Live coverage of Ansel Fest here in Atlanta, Georgia. I'm John for a host of the Cube with stewed Minutemen. Analysts were looking angle. The Cube are next to guest Tom Anderson and most product owner. Red Hat is part of the sensible platform automation properly announced. And Richard Henshaw, product manager. Guys, welcome to the Cube Way had all the execs on yesterday and some customers all pretty jazzed up about this year, mainly around just the timing of how automation is really hitting the scene and some of the scale that's going on. You guys had big news with the answerable automation platform. New addition to the portfolio. What's the feedback? >>So far, I think the feedback has been super positive. We have customers have come to us. A lot of the last little one said, Hey, we're maturing. We're moving along the automation maturity curve, right, and we have multiple teams coming to us and saying, Hey, can you help us connect this other team? We've had a lot of success doing cloud provisioning or doing network automation were doing security automation. What have you and they're coming to us and saying, Help us give us kind of the story if you will, to be able to connect these other teams in our organization. And so that way I kind of feel the pole for this thing to move from a tool that automates this or that. This task for that task. Too much more of a platform center. >>It seems to be scaling out in terms of what automation is touching these days. And look at the numbers six million plus activations on get Hub versus other projects. So activities high in the community. But this seems to be much more broader. Scope now. Bring more things together. What's the rationale behind? What's the reasoning? What's the strategy? But the main thing is, >>automation is got to that point where it's becoming the skill set that we do. So it was always the focus. You know, I'm a database administrator. I'm assists out, man. I'm a middle where I'm a nap deaf on those people, then would do task inside their job. But now we're going to the point off, actually, anybody that can see apiece. Technology can automate piece technology in the clouds have shown This is the way to go forward with the things what we had. We bring that not just in places where it's being created from scratch, a new How do you bring that into what's existing? Because a lot of our customers have 20 or 30 years like a heritage in the I T estate. How do you do with all of that? You can't just rebuild everything into new as well. So you gotta be ableto automate across both of those areas and try and keep. You know, we say it's administrative efficiency versus organization effectiveness. Now how do I get to the point of the organization? Could be effective, supposed just doing things that make my job easier. And that's what we're gonna bring with applying automation capability that anybody can take advantage of. >>Richard. I actually felt the keynote demo this morning did a nice job of that line that they set it up with is this is this is tools that that all the various roles and teams just get it, and it's not the old traditional okay, I do my piece and set it up and then throw it over the wall. There was that, you know? Oh, I've got the notification and then some feedback loops and, you know, we huddled for something and it gets done rather fast, not magic. It's still when I get a certain piece done. Okay, I need to wait for it's actually be up and running, but you know, you're getting everybody into really a enterprise collaboration, almost with the tool driving those activities together >>on that. And that's why yesterday said that focus on collaboration is the great thing. All teams need to do that to be more successful because you get Maur inclusivity, Maurin puts. But organizations also need to coordinate what activities they're doing because they have rules, regulations, structures and standards they have to apply. Make sure that those people can do things in a way that's guided for them so that they're they're effective at what they're trying to do. >>Okay, I think I'm going to explain what's in the platform first because an engine and tower and there, what else is in there, what's new? What's what our customers is going to see. That's new. That's different >>it's the new components are automation Hope Collections, which is a technology inside answer ball itself. On also Automation Analytics and the casing is that engine and terrorist of the beating heart of the platform. But it's about building the body around the outside. So automation is about discover abilities like, What can we find out? What automation can I do that I'm allowed to do? Um, and let six is about the post activity. So I've automated all these things. I've done all this work well, How did it go? Who did what, who did? How much of what? How well did it work? How much did it failed? Succeeds and then, once you build on that, you don't start to expand out into other areas. So what? KP eyes, How much of what I do is automated versus no automated? You can start to instigate other aspects of business change, then Gamification amongst teams. Who's the Who's the boat? The closest motive here into the strategy input source toe How? >>Find out what's working right, essentially and sharing mechanism to for other groups in terms of knowing what's happening >>and how is my platform performing which areas are performing well, which airs might not be performing well. And then, as we move down the road, kind of how my performing against my peers are other organizations that are automating using the ants will automation platform doing? And am I keeping up on my doing better? That kind of stuff. >>So, Tom, there's a robust community as we was talking about. Their platform feels like it builds on yet to change the dynamic a little bit. When you talk about the automation hub and collections, you've already got a long list of the ecosystem vendors that are participating here. Bring us two through a little bit. What led Thio. You know all these announcements and where you expect, you know, how would this change the dynamics of >>the body? And maybe we'll split up that question. I'll talk a little bit about partners because it's both partners and customers in community here that's been driving us this way. I'll talk a little bit about partners and Rich talk about the customer piece here, which is partners have been traditionally distributing their content there. Ansel automation content through our engine capability. So our engine release cycle, or cadence, has been sort of the limiting factor to how fast they can get content out to their users and what what the collections does is part of the platforms allows us to separate those things. Rich talked about it yesterday in his keynote, having that stable platform. But you having yet having content be able to read fast. And our partners love that idea because they can content. They can develop content, create content, get into their users hands faster. So partners like at five and Microsoft you've seen on stage here are both huge contributors. And they've been part of the pole for us to get to the platform >>from a customer perspective. And the thing I love most about doing this job with the gas of customers is because I was a customer on Guy was danceable customer, and then I came over to this side on Dhe. I now go and see customers. I see what they've done, and I know what that's what I want to do. Or that's what I was trying to do. And she started to see those what people wanted to achieve, and I was said yesterday it is moving away from should I automate. How would we automate Maura? What should I automate? And so we'll start to see how customers are building their capabilities. And there's no there's many different ways people do. This is about different customers, >>you know. What's interesting is you guys have such a great success formula first. Well, congratulations. It's great to see how this is turning into such a wider market, because is not just the niche configuration management. More automation become with cloud to point a whole new wider category. So congratulations. The formula we see with success is good product, community customers adopting and then ecosystem that seems to be the successful former in these kinds of growth growth waves you guys experiencing? What is the partnering with you mentioned? S five Microsoft? Because that, to me, is gonna be a tipping point in a tel sign for you guys because you got the community. You got the customers that check check ecosystem. What's the partner angle? How do they involve? Take us through that. What's going on? They're >>so you're absolutely so you know, kind of platform velocity will be driven by partner adoption and how many things customers can automate on that platform or through that platform and for us I mean, the example was in the demo this morning where they went to the automation hub and they pulled down the F five collection, plugged it into a workflow, and they were automating. What are partners? Experience through their customers is Look, if I'm a customer, I have a multi cloud environment or hybrid cloud environment. I've got automation from AWS. I've got azure automation via more automation. Five. Got Sisko. I've got Palo Alto. I've got all these different automation tools to try and string them together, and the customers are coming and telling those vendors Look, we don't want to use your automation to end this automation tooling that one we want to use Ansel is the common substrate if you will automation substrate across this platform. So that's motivating the partners to come to us and say, Hey, I had I was out five Aspire last week, and they're all in a natural. I mean, it's really impressive to see just how much there in unanswerable and how much they're being driven by their customers when they do Ansell workshops without five, they say the attendance is amazing so they're being pulled by their customers and therefore the partners are coming to us. And that's driving our platform kind of usability across the across the scale. >>Another angle we'll see when we talk to the engineers of the partners that are actually doing the work to work with danceable is that they're seeing is ah, change also in how they it's no longer like an individual customer side individual day center because everything is so much more open and so much more visible. You know there's value in there, making it appealing and easy for their customers to gain advantage of what they're doing. And also the fact that the scales across those customers as well because they have their internal team's doing it, saying the same things and so bringing them to an automation capable, like Ansel have to push. That means that they also gained some of the customers appreciation for them, making it easier to do their tasking collaboration with us and you know, the best collaborations. We've got some more partners, all initiated by customers, saying Hey, I want you to go and get danceable content, >>the customer driving a lot of behavior, the guest system. Correct. On the just another point, we've been hearing a lot of security side separate sector, but cyber security. A lot of customers are building teams internally, Dev teams building their own stacks and then telling the suppliers a support my AP eyes. So now you start to see more of a P I integration point. Is that something that is gonna be something that you guys gonna be doubling down on? What's that? What's the approach there? How does that partner connected scale with the customers? So we've >>been eso Ansel security automation, which is the automation connecting I. P. S. C. P. S that kind of stuff. It is almost a replay of what we did the network automation space. So we saw a need in the network automation space. We feel that we became a catalyst in the community with our partners and our customers and our and our contributors. And after about three years now, Ansel Network automation is a huge piece of our business and adoption curve. We're doing the exactly see the exact same thing in the security automation space compliance. The side over here, we're talking about kind of automating the connections between your firewalls, your threat detection systems and all that kind of stuff. So we're working with a set of partners, whether it's Cisco, whether it's Palo Alto, whether it's whether it's resilient by the EMS, resilient and being able to connect and automate the connections between the threat and the response and and all of that kind of >>the same trajectory as the network automation >>Zach. Same trajectory, just runnin the same play and it's working out right now. We're on that kind of early part of that curve, that adoption curve, and we have partners jumping in with us. >>You're talking to customers. We've heard certain stories. You know how I got, you know, 1000 hours of work down to a dozen hours of work there. Is there anything built into the tool today that allows them to kind of generate those those hero stats O. R. Any anything along those lines? >>Talk about analytic committee from yes, >>well, again without any analytic side. I mean, those things starts become possible that one of the things we've been doing is turning on Maur more metrics. And it's actually about mining the data for the customer because Tower gives this great focal point for all the automation that's going on. It's somewhere that everything comes through. So when we export that and then we can we can do that work for all the customers rather than have to duel themselves. Then you start to build those pictures and we start with a few different areas. But as we advance with those and start, see how people use them and start having that conversation customers about what data they want to use and how they want to use it, I think that's gonna be very possible. You know, it's so >>important. E think was laid out here nicely. That automation goes from a tactical solution to more strategic, but more and more how customers can leverage that data and be data driven. That's that's gonna drive them for it. And any good customer examples you have of the outcomes. No, you're talking to a lot of >>PS one from this morning. Yeah, >>so I mean, I'll be Esther up this morning, and I think that the numbers they used in the demo that she's like, you know, last year they did 100,000 from launch to the end of the year. 100,000 changes through their platform on this year so far that in a 1,000,000. So now you know, from my recollection, that's about the same time frame on either side of the year. So that's a pretty impressive acceleration. Side of things. We've had other ones where people have said, You know how many times you were telling some customers yesterday? What used to take eight hours to a D R test with 20 or 30 people in for the weekend now takes 12 minutes for two People on the base is just pushing a few buttons just as they go through and confirm everything worked that that type of you can't get away from that type of change. >>J. P. Morgan example yesterday was pretty compelling. I mean, time savings and people are, I mean, this legit times. I mean, we're talking serious order of magnitude, time savings. So that's awesome. Then I want to ask you guys, Next is we're seeing another pattern in the market where amongst your customer base, where it's the same problem being automated, allover the place so playbooks become kind of key as that starts to happen is that where the insights kind of comes in? Can you help us kind of tie that together? Because if I'm a large enterprise with its I'm decentralized or centralized, are organized problem getting more gear? I'm getting more clouds, game or operations. There's more surface area of stuff and certainly five g I ot is coming around the corner. Mention security. All this is expanding to be much more touchpoints. Automation seems to be the killer app for this automation, those mundane task, but also identifying new things, right? Can you guys comment on that? >>Yeah, so maybe I'll start rich. You could jump in, which is a little bit around, uh, particularly those large accounts where you have these different disparate teams taking a approach to automate something, using Ansel and then be able to repeat or reuse that somewhere else. The organization. So that idea of being for them to be able to curate they're automation content that they've created. Maybe they pulled something down from galaxy. Maybe they've got something from our automation husband. They've made it their own, and now they want to curate that and spread it across the organization to either obviously become more efficient, but also in four standards. That's where automation hub is going to come into play here. Not only will it be a repo for certify content from us and our partners, but it will also be an opportunity for them to curate their own content and share it across the organization. >>Yeah, I think when you tie those two things together and you've got that call discover abilities, I had away go and find what I want. And then the next day, the next day, after you've run the automation, you then got the nerve to say, Well, who's who's using the right corporate approved rolls? Who's using the same set of rolls from the team that builds the standards to make sure you're gonna compliant build again, showing the demo That's just admin has his way of doing it, puts the security baseline application on top and you go, Oh, okay, who's running that security baseline continuously every time. So you can both imposed the the security standards in the way the build works. But you can also validate that everybody is actually doing the security standards. >>You what I find fascinating about what you guys are doing, and I think this is came out clearly yesterday and you guys are talking about it. And some of the community conversations is a social construct here. Going on is that there's a cultural shift where the benefits that you guys are throwing off with the automation is creating a network effect within the companies. So it's not just having a slack channel on texting. The servers are up or down. It's much more of a tighter bond between the stakeholders inside the company's. Because you have people from different geography is you have champions driving change. And there's some solidarity happening between the groups of people, whether they're silo door decentralized. So there's a whole new social network, almost a cultural shift that's happening with the standardization of the substrate. Can you guys comment on this dynamic? Did you see this coming? You planning forward? Are you doubling down on it? >>I think so. And we talk about community right on how important that is. But how did you create that community internally and so ask balls like the catalyst so most teams don't actually need to understand in their current day jobs. Get on all the Dev ops, focus tools or the next generation. Then you bring answer because they want to automate, and suddenly they go. Okay, Now I need to understand source control, and it's honest and version. I need to understand how to get pulls a full request on this and so on and so forth on it changes that provides this off. The catalyst for them to focus on what changed they have to make about how they work, because what they wanted to do was something that requires them to do you no good disciplines and good behaviors that previously there was no motivation or need to do. I think >>Bart for Microsoft hit on that yesterday. You know, if you saw Bart Session but their network engineers having to get familiar with concepts of using automation almost like software development, life cycles right and starting to manage those things in repose. And think of it that way, which is intimidating at first for people who are not used to. But once they're over that kind of humping understand that the answer language itself is simple, and our operations person admin can use it. No problem, >>he said himself. Didn't my network engineers have become network developers. >>It's funny watching and talking to a bunch of customers. They all have their automation journey that they're going through. And I hear the Gamification I'm like, Okay, what if I have certain levels I have to reach in it unlocked capabilities, you know, in the community along the way. Maybe that could build a built in the future. >>Maybe it's swag based, you know, you >>get level C shows that nice work environment when you're not talking about the server's down on some slack channel when you're actually focusing on work. Yeah, so that mean that's the shift. That's what I'm saying, going >>firefighting to being able to >>do for throwing bombs. Yeah, wars. And the guy was going through this >>myself. Now you start a lot of the different team to the deaf teams and the ops teams. And I say it would be nice if these teams don't have to talk to complain about something that hadn't worked. It was Mexican figured it was just like I just like to talk to you because you're my friend. My colleague and I'd like to have a chat because everything's working because it's all automated, so it's consistent. It's repeatable. That's a nice, nice way. It can change the way that people get to interact because it's no longer only phoned me up when something's wrong. I think that absent an interesting dynamic >>on our survey, our customer base in our community before things one of the four things that came up was happier employees. Because if they're getting stuff done and more efficient, they have more time to actually self actualizing their job. That becomes an interesting It's not just a checkbox in some HR manual actually really impact. >>And I kind of think the customers we've heard talk rvs, gentlemen, this morning gave me a lot of the fear initially is, well, I automate myself out of a job, and what we've heard from everybody is that's not absolutely That's not actually true at all. It just allows them to do higher value things that, um or pro >>after that big data, that automation thing. That's ridiculous. >>I didn't use it yesterday. My little Joe Comet with that is when I tried to explain to my father what I do. Andi just said Well, in the 19 seventies, they said that computers you mean we'll do a two day week on? That hasn't come >>true. Trade your beeper and for a phone full of pots. But Richard, Thanks for coming on. Thanks for unpacking the ants. Full automation platforms with features. Congratulations. Great to see the progress. Thank you, Jonah. Everybody will be following you guys to Cuba. Coverage here in Atlanta, First Amendment Stevens for day two of cube coverage after this short break.

>>live from Atlanta, Georgia. It's the Q covering Answerable Fest 2019. Brought to you by Red Hat. >>Hey, welcome back, everyone. It's the cubes. Live coverage here in Atlanta, Georgia, for answerable fast. Part of redheads. Big news. Ansel Automation Platform was announced. Among other things, they're great products. I'm John for ear, with my coast to minimum, but two great guests. You unpack all the automation platform features and benefits. Walter Bentley, senior manager. Automation Practicing red hat and vj Job Olu, director of Red Hat Consulting Guys Thanks for coming on. Thanks. So the activity is high. The buzz this year seems to be at an inflection point as this category really aperture grows big time seeing automation, touching a lot of things. Standardization. We heard glue layer standard substrate. This is what answer is becoming so lots of service opportunity, lot of happy customers, a lot of customers taking it to the next level. And a lot of customers trying to consolidate figure out hadn't make answerable kind of a standard of other couples coming in. You guys on the front lines doing this. What's the buzz? What's the main store? What's the top story going on around the service is how to deploy this. What are you guys seeing? >>So I think what we're seeing now is customers. Reactor building automation. For a long time, I have been looking at it at a very tactical level, which is very department very focused on silo. Whether country realizes with this modern develops and the change in how they actually go to the market, they need to bring the different teams together. So they're actually looking at watching my enterprise automation strategy be how to actually take what I've learned in one organization. And I still roll it across the enterprise so that now struggling and figuring out how to be scared, what we have, how do we change the culture of the organization to collaborate a lot more and actually drive automation across enterprise? >>Walter One of the things we've been we've talked about all the time in the Cube, and it's become kind of cliche. Digital transformation. Okay, I heard that before, and three things people process, technology, process and capability you guys have done You mentioned the siloed having capabilities that's been there. Check was done very, very well as a product technology Red hat in the portfolio. Great synergies. We talked about rail integration, all the benefits there. But the interesting thing this year that I've noticed is the people side of the equation is interesting. The people are engaged, is changing their role because automation inherently changes there, function in the organization because it takes away probably the mundane tasks. This is a big part of the equation. You guys air hitting that mark. How do you How are you guys seeing that? How you accelerating that has that changing your job, >>right? So customers are now economy realizing that going after automation in a very tactical manner is not exactly getting them what they want as a far as a return on investment in the automation. And what they're realizing is that they need to do more. And they're coming to us and more of an enterprise architectural level and say we want to talk mortgage grander strategy. And what they're coming to realize is that having just one small team of people that were calling the Dev Ops team is not gonna be ableto drive that adoption across the organization. So what we're trying to do is work with customers to show them how they collaboration in the culture of peace is huge. It's a huge part of adopting automation. Answerable is no longer considered a emerging tech anymore. And and I when I say that, I mean a lot of organizations are using answerable in many different ways. They're past that point, and now they're moving on to the next part, which is what is our holistic strategy and how we're gonna approach automation. And And we wanted leverage danceable, unanswerable tower to do that. >>Does that change how you guys do your roll out your practices in some of your programs? >>Well, we did have to make some adjustments in the sense of recognizing that the cultural piece is a pivotal part of it, and we can go in and we can write playbooks and rolls, and we can do all those things really great. But now we need to go in and help them structure themselves in a way where they can foster that collaboration and keep a moment. >>And I'll actually add on to that so reactive, large, open innovation labs three years ago, and what we have to learn doing that is using labs and allows practices to actually help customers embrace new culture and change. How they actually operate has actually helped us take those practices and bring it into our programs and kind of drive that to our customers. So we actually run our automation adoption program and the journey for customers through those practices that we actually learned in open innovation loves like open practice, library, even storming priority sliders and all of those modern techniques. So the goal is to help our customers understand those practices and actually embrace them and bring them into the organization to drive the change that that's looking for within the organization. >>A. J. Is there anything particular for those adoption practices when you're talking about Cloud? Because the communication amongst teams silos, you know, making things simpler is something that we absolutely do need for cloud. So I'm just curious how you connect kind of the cloud journey with the automation journey. >>So all of the journey program that actually created, whether it's a contender adoption program or the automation adoption program, we actually followed the same practices. So whether you're actually focused on a specific automation to, like, answerable or actually embarking on hybrid multicolored journey. We actually use the same practices so the customers don't have toe learn new things every time you have to go from one product, one of the so that actually brings a consistent experience to customers in driving change within the organization. So let's picture whether it is focusing automation focused on cloud migrating to the cloud. The practices remained the same, and the focus is about not trying to boil the ocean on day one. Try to break it into manageable chunks that give it a gun back to the business quickly learned from the mistakes that you make in each of the way and actually build upon it and actually be successful. >>So, Walter, I always love when we get to talk to the people that are working straight with customers because you come here to the conference, it's like, Oh, it's really easy Get started. It doesn't matter what role or what team you're in. Everybody could be part of it. But when you get to the actual customers, they're stumbling blocks. You know what are some of those things? What are some of the key things that stop people from taking advantage of all the wonderful things that all the users here are doing >>well. One of the things that I've identified and we've identified as a team is a lot of organizations always want to blow the ocean. And when and when it comes down to automation, they feel that if they are not doing this grand transformation and doing this this huge project, then they're not doing automation. And the reality is is that we're Trent with showing them that you can break things up into smaller chunks, as Visi alluded to. And even if you fail, you fail fast and you can start over again because you're dealing with things in a smaller chunk. And we've also noticed that by doing that, we're able to show them to return on investment faster so they can show their leadership, and their leadership can stand behind that and want to doom. Or so that's one of the areas. And then I kind of alluded to the other area, which is you have to have everybody involved. You want just subject matter experts riding content to do the automation. You don't want that just being one silo team. You want to have everybody involved and collaborate as much as possible. >>Maybe can you give us an example? Is about the r A y How fast to people get the results and, you know, prove toe scale this out. >>So with the automation adoption journey, what we're able to do is is that we come in and sit down with our customers and walk them through how to properly document their use cases. What the dependencies, What integration points, possibly even determining what is that? All right, ranking for that use case. And then we move them very quickly in the next increment. And in the next increment, we actually step them through, taking those use cases, breaking them down into minimum viable products and then actually putting those in place. So within a 90 day or maybe a little bit more than a little bit more than the 90 day window, were able to show the customer in many different parts of the organization how they're able to take advantage of automation and how the return on investment with hopes of obviously reducing either man hours or being able to handle something that is no a mundane task that you had to do manually over and over again. >>What are some of the things that people get confused about when they look at the breath of what's going on with the automation platform? When I see tool to platform, transitions are natural. We've seen that many times in the industry that you guys have had product success, got great community, that customers, they're active. And now you've got an ecosystem developing so kind of things air popping on all cylinders here. >>So the biggest challenge that we're actually being seeing customers is they actually now come to realize that it's very difficult to change the culture of the organization right there, actually embarking on this journey and the biggest confusion that is, how do we actually go make those changes? How do we bring some of the open practice some of the open source collaboration that Riddle had into the organization so they actually can operate in a more open source, collaborative way, and what we have actually learned is we actually have what we call its communities of practice within Red Hack. It is actually community off consultants, engineers and business owners. The actual collaborate and work together on offering the solutions to the market. So we're taking those experiences back to our customers and enabling them to create those communities of practice and automation community that everybody can be a part off. They can share experiences and actually learn from each other much easier than kind of being a fly on the wall or kind of throwing something or defense to see what sticks and what does not. >>What's interesting about the boiling the ocean comment you mentioned Walter and B J is your point. There is, is that the boil? The ocean is very aspirational. We need change rights. That's more of the thing outcome that they're looking for. But to get there is really about taking those first steps, and the folks on the front lines have you their applications. They're trying to solve or manage. Getting those winds is key. So one of things that I'm interested in is the analytics piece showing the victory so in the winds early is super important because that kind of shows the road map of what the outcome may look like versus the throw the kitchen, sink at it and, you know, boil the ocean of which we know to the failed strategy. Take us through those analytics. What are some of the things that people tend to knock down first? What are some of the analytical points that people look at for KP eyes? Can you share some insight into that? >>Sure, sure. So we always encourage our customers to go after the platform first. And I know that may sound the obvious, but the platform is something that is pretty straightforward. Every organization has it. Every organization struggles with provisioning, whether of a private cloud, public cloud, virtualization, you name it. So we have the customer kind of go after the platform first and look at some of their day to operations. And we're finding that that's where the heaviest return on investment really sits. And then once you get past that, we can start looking like in the end, work flows. You know, can they tie service now to tower, to be able to make a complete work flow of someone that's maybe requesting a BM, and they can actually go through that whole workflow by by leveraging tower and integration point like service. Now those air where we're finding that the operators of these systems going getting the fastest benefit. And it also, of course, benefits the business at the end of the day because they get what they need a lot fast. >>It's like a best practice and for you guys, you've seen that? Yes, sir. Docked with that out of E. J. What's your comment on all this? >>So going back to the question on metrics Automation is great, but it does not provide anybody to the business under the actually show. What was the impact, whether it's from a people standpoint, cost standpoint or anything else. So what we try to drive is enable customers. You can't build the baseline off where they are today, and as they're going through the incremental journey towards automation, measure the success of that automation against the baseline. And that actually adds the other way back to the customer. As a business you didn't get to see. I was creating a storage land. I was doing it probably 15 times a month. Take it or really even automated. It spend like a day created a playbook. I'll save myself probably half, of course, and that could be doing something that's better. So building those metrics and with the automation analytics that actually came in the platform trying those bass lines. So the number of executions, actually the huge value they'll actually be ableto realize the benefits of automation and measure the success off within enterprise. >>So I'm a customer prospect, like I want to get a win. I don't want to get fired. I won't get promoted. Right, I say, Okay, I gotta get a baseline and knock down some playbooks. Knock that down first. That what you're gonna getting it. That's a good starting. >>Starting. Understand your baseline today. Plan your backlog as to what you want to knock down. And once you know them down, build a dashboard as to what the benefits were, what the impact was actually built upon it. You actually will see an incremental growth in your success with automation. >>And then you go to the workflow and too, and that's your selling point for the next level. Absolutely good playbook. Is that the automation programs that in a nutshell or is that more of a best practice >>those components of the ah, the automation adoption journey that we allow the customer to kind of decide how they want their journey to be crafted. Of course, we have a very specific way of going about and walking them through it. But we allowed in the kind of crap that journey and that is those the two components that make up the automation. >>We're gonna put you guys on the spot with the tough question We heard from G. P. Morgan yesterday on the Kino, which I thought was very compelling. You know, days, hours, two minutes. All this is great stuff. It's real impact. Other customers validate that. So, congratulations. Can you guys share any anecdotal stories? You know, the name customers? Just about situations Where customs gone from this to this old way, new way and throw some numbers around Shearson Samantha >>is not a public reference, but I like to give you a customer. Exactly. Retail company. When we first actually went and ran a discovery session, it took them 72 days to approach in an instance. And the whole point was not because it took that long. It because every task haven't s l. A We're actually wait for the Acela manually. Go do that. We actually went in >>with our 72 hours, two days, two days, >>actually, going with the automation? We Actually, it was everybody was working on the S L. A. We actually brought it down to less than a day. So you just gave the developers looking to code 71 days back for him to start writing code. So that's the impact that we see automation bringing back to the customers, right? And you'll probably find the use causes across everywhere. Whether J. P. Morgan Chase you actually had the British Army and everyone here on states talking about it. It is powerful, but it is powerful relief you can measure and learn from it >>as the baseline point. Get some other examples because that's that's, uh, that's 70 days is that mostly delay its bureaucracy. It's It's so much time. >>It's manual past and many of the manual tasks that actually waiting for a person to do the task >>waterfall past things sound, although any examples you can >>yes, so the one example that always stands out to me and again, it's a pretty interviewing straight forward. Is Citrix patching? So we work with the organization. They were energy company, and they wanted to automate patching their searches environment, patching this citrus environment took six weekends and it took at least five or six engineers. And we're talking about in bringing an application owners, the folks who are handling the bare metal, all all that whole window. And by automating most of the patching process, we were able to bring it down to one weekend in one engineer who could do it from home and basically monitor the process instead of having to be interactive and active with it. And to me, that that was a huge win. Even though it's, you know, it's such dispatching. >>That's the marketing plan. Get your weekends back. Absolutely awesome. Shrimp on the barbecue, You know, Absolutely great job, guys. Thanks for the insight. Thanks. Come on. The key. Really appreciate it. Congratulations. Thank you. Thanks for sharing this queue here. Live coverage. Danceable fest. Where the big news is the ass. Full automation platform. Breaking it down here on the Q. I'm John. First to Minutemen. We're back with more coverage after this short break

>>live from Atlanta, Georgia. It's the Q covering Answerable Fest 2019. Brought to you by Red Hat. >>Okay, welcome back. Everyone is the live Cube coverage for two days here in Atlanta, Georgia for instable fest. I'm John Furrier, My Coast stupid in with the Cube. Ted Julian, vice president, product management, formerly CEO. Resilient now part of an IBM company. Back to doing V P of product management. Again, you don't really ask. Welcome to welcome back to the Cube. Good to see you. It's a >>pleasure to be here. Thanks. >>So I see product management. Holistic thinking is the big discussion here. The thing that's coming out of this event is configuration management, a siloed point activity now, more of a platform. You're seeing more of a systems architecture thinking going into some of these platform discussion. Security certainly has been there. They're here now. A lot of pressure, the out of things built in with security but maintaining the onslaught of threats and landscape changes going on. That's what you do. >>It's rough out there. >>What what's going on? What are the key trends that customers should be aware of when thinking about configurations? Because automation can help. Yeah, maybe all use cases, but >>way need to do something and because customers definitely need help. The alerts that they're dealing with them both in the volume and the severity is like nothing we've ever seen before. At the same time we're talking about earlier, right, the regulatory impact also really big difference just in the last two or three years. Huge skills, gap shortage also a critical problem. People can't find enough people to do this work. That's very difficult to keep so clearly we need to do something different. And there's no doubt that orchestration and automation and configuration management, as a component of that is we've barely scratched the surface of the potential there. To help solve some of >>the open source is, is helping a lot of people now. Seeing the light first was cloud, the skeptics said. There's no security and cloud now. There is open source securities there, but still, proprietary systems have security. But the mayor may not be talented. Your point, so automation is an opportunity. How are companies dealing with the mishmash or the multi platform solutions that are out there >>at your right to ask the question it is driving, um, the problem in a big way. Years ago we tried this security automation within security, like in the early days of firewalls and the Web and stuff like that, and it didn't go well. Unintended consequences. But think two things have changed. The environments changed, which has raised the stakes for the need to be able to do this stuff to a whole different level. But at the same time, the technology matured enormously. There's been multiple platforms shifts since then, and so security teams. They're both kind of desperate for a better solution, but also better options now than they had before. And so it's for this reason that we're starting to see people adopt orchestration and automation now in a way that we didn't see in the last time around. >>But the thing is that we were hearing here is that people are trying to automate the same things and some of these holes in the infrastructure, whether it's an S three bucket, this is basic stuff. This is not rocket science. Yeah, so on these known use cases, this makes total sense that a playbook or automation could help kind of feel those holes. >>We talk about it as a journey, you know? And I don't think any two organizations journey is the same, nor does it really even need to be the same. So we've seen some customers, for example, take the approach of what's a high volume type of incident that we deal with. And if we could apply orchestration and automation, they were gonna get great our eye right? We see 4000 phishing attacks every month or what have you. And that's certainly one way to do it. Yeah, but those other times with one, >>though, I have to go >>into that point. There's other people that are like, you know, gathering forensics on an end point right now. Incredibly manual process. We need to be able to do that globally. Do we do it every day? No, we don't. But if we could automate that and get those results back in more like a couple hours, as opposed to two days, because the guy we need in Sweden is out of the office or whatever, that could mean the difference between ah, low level incident were able to contain and something that goes global. And so that's the use case we wanna chase, so I don't think there's a right or wrong answer. >>Depends on the environment. Ah, whole host of the whole thing about security is no general purpose software anymore. You have to really make it custom because every environments different. >>I mean, gosh, you guys Aaron Arcee, right? It's nuts. There's thousands of vendors. I mean, there's hundreds of vendors that are really products. They're not the features masquerading as products that are masquerading as companies. But there's a reason why that's been the case, and it's because the risk is so high. >>The desperation to >>yes, exactly good word choice. Yeah. >>So what? One of the things that reminded me of security is this morning hearing about, you know, J P. Morgan going through the transformation from the ticketing system. Tau wait to make a great case study two. I need to be able to automate things. So, you know, we know that response time is so critically important in the security area. So tell us how that meshes together from security and automation toe be able to response, and you know, whether it be patching or, you know, responding to an attack, >>there's huge opportunity gains there on. We've seen customers do some really remarkable things that start with what you're discussing, which is if we could automate that fishing process to a degree and we have 4000 of those a month and we're able to maybe shrink a response time by 80 some or more percent, which is what we've seen. That's a lot of savings right there. And you know, the meat and potatoes there is. You already have a fishing Neil Alias. Probably that that employees report those phishing attacks, too. But what if we just monitored that? We stripped those emails, stripped out the attachments, and we could automate all the manual grunt work that an analyst would otherwise do right? Is that and is there in execute a ble? Is that execute herbal? Unknown bad? What command and control servers is it talk to? Are those known bads those air 10 tabs That analyst could have opening their browser if we could automate all of that. So when they go into the case, it's all just sitting there for them. Huge time saver. >>It's the great proof point of the people plus machines. How do you make make sure that the people that when they get the information, they're not having to do too much grunt work. They get really focused on the things where their expertise in skill sets are needed, as opposed to just buried. You >>nailed it. I mean, automation is a great role to play, but it really is a subset of orchestration. It's when you can bring those two things together and really fuse the people process and technology via orchestration. That's when you get really game changing improvements. >>Talk about the relationship between you guys or silly, unanswerable. Where's the fit? What you guys doing together? Why year give a quick plug for what you working on? >>Yeah, absolutely. So just by working with customers, we kind of discovered that there was this growing groundswell of answerable use within our customer base. It was largely an I T, whereas that IBM resilient. We're selling mainly in a security. Um, and once we uncovered that were like, Oh my gosh, there's all these integrations that already exists. They're already using them for I t use cases on that side of the house, but a lot of the same work needs to be done as part of a security workflow. And so we built our integration where, literally you install that integration into resilient. And we have a visual workflow editor where you can define a sophisticated workflow. And what's that? Integration is in place. All of your instable integrations air there for you. You drag and drop them on near workflow. You can string them all together. I mean, it's really, really powerful. >>It's interesting. Stew and I and David Lattin Ovary Brother Q. Post. We got hundreds of events we see every conference. Everyone's going for the control plane layer. Don't control the data. I mean, it's aspiration, but it's You can't just say it. You gotta earn it. What's happening here is interesting in this country. Configuration management. Little sector is growing up because they control the plumbing, the control of the hardware, the piece parts right to the operating system. So the abstraction lee. It provides great value as it moves up the stack, no doubt, and this is where the impact is, and you guys are seeing it. So this dependency between or the interdependence between software glue that ties the core underpinnings together, whether it's observe ability data. It's not a silo, just context, which they're integrating together. This the collision course? Yeah. What's the impact gonna be here? What's your thesis on this? >>That's why there is such great synergy is because they are really were sort of the domain expertise Doreen experts on the security point of view and our ability to leverage that automation set of functions that answerable provides into this framework where you can define that workflow and all the rest that specific to some security use cases eyes just very, very complimentary to one another. >>This is a new kind of a 2.0 Kana infrastructure dynamic, where this enables program ability. Because if these are the control switch is on the gear and the equipment and the network routes, >>yeah, and where things get really interesting is when you do that in the context of ah, workflow and a case management system, which is part of what we provide, then you get a lot of really valuable metrics that are otherwise lost. If you're purely just at a point to point tool to to automation realm, and that allows you to look at organizational improvements because you're able to marry. Well, first of all, you can do things like better understand what kind of value those I t controls. Air providing you and the automation that you're able to deliver. But you can relate that to your people in your process as well. And so you can see, for example, that while we have two teams, they're doing that the ones in the day shift ones in the night shift. They have access to the same tool sets, but ones more effective than the other. First of all, you know that. But then, having known that you can now drill into that and figure out OK, why is the day shift better than the night shift? And you can say, Oh, well, they're doing things a little bit differently, maybe with how they're orchestrating this other team is, Or maybe they're not orchestrating it. All right? And you're having that. And then now you are able to knowledge share and, um improve that process to drive that continuous improvement. >>So this operational efficiency comes from breaking down these siloed exactly mentality data sets or staff? >>Yeah, and pairing. That was not just as I said, the IittIe automation aspect of weaken now do that 80% faster. But what about the people in the process aspect? We even bring that into the mix as well. You get that next limit layer of insight which kind of allows you to tap into another layer of productivity. >>So this is an alignment issue. This brings that back. The core cultural shift of Dev ups. This is the beginning of what operationalize ng Dev ops looks like. >>Yes. Yeah, >>people are working together. >>It's really, really well put. I mean, it gets back to how this question got started, which is what is this energy? And to me, this energy really is that you have these siloed all too often siloed functions of I t operations and security operations. And this integration between resilient and answerable is the glue that starts to pull those two things together to unlock everything we just talked about. >>Awesome. That's great. >>Yeah, well, you know, research has shown that you know, Dev Ops embracing, delivering and shipping code more frequently actually can improve security. Not You know what? We have to go through this separate process and slow everything down. So are you seeing what? What is that kind of end state organization look like? Oh, >>I mean, that's a huge transformation. And it's something that on the security field we've been struggling with for the longest time, because when we were in kind of a waterfall mode of sort of doing things I mean your timeframe of uncovering a security issue, addressing it in code code, getting deployed to a meaningful enough fashion and over a long enough time to get a benefit that could be years, right? But now that we're in this model, I mean, that could be so much, much more quickly obtained and obviously not only other great just General Roo I improvements that come from that, but your ability to shrink the threat window as a result of this as well as huge and that is crucial because all the same things that us, the good guys they're doing to be able to automate our defenses, the bad guys, they're doing the same thing in terms of how they're automating their attacks. And so we really have to. We have no choice. >>So, Ted, you were acquired by IBM. IBM made quite sizeable acquisition with Red Hat. Tell us what your IBM with danceable. How that should play out >>there is just enormous potential. And answerable is a big, big piece of it, without a doubt. And I think we're just scratching the tip of the iceberg for the benefits. They're just in the from resilience point of view. And, you know, we're not to stay in touch because we have some really interesting things coming down the pike in terms of next gen platforms and the role that that answer will complain those two and how those stretch across the security portfolio with an IBM more broadly and then even beyond that. >>Well, we want to keep in touch. We certainly have initiated Cube coverage this year on security. Cyber little bit going for a broader than the enterprise. Looking at the edge edges. You know about the perimeter. Being just disabled by this new service area takes one penetration lightbulb I p address. So again, organizing and configuring these policy based systems sounds like a configuration problem. Yeah, it is. This is where the software's gonna do it. Ted, Thanks for coming on. Sharing the insights. Any other updates on your front. What do you are most interested in what? Give us a quick update on what you're working on. >>Um, well, we're just getting started with the answerable stuff, so that's particularly notable here, but also kind of modern, modernizing our portfolio, and that really gets to the whole open shift side of the equation and the Red Hat acquisition as well, So not ready to announce anything yet. But some interesting things going on there that that kind of pull this all together and that serve as just one part of the foundation for the marriage between red at 9 p.m. and wanna sneak a value can bring the >>customers any sneak peek at all on the new direct. Sorry time. At least lips sink ships Don't do it. Love to no. >>Blame me for asking. >>Hey, I got a feeling hasn't automation. And somewhere in there Ted, thanks for sharing your insights. It was great to see Cuba coverage here. Danceable fest. I'm jumpers to minimum, breaking out all the action as this new automation feeds A I's gonna change the stack game as data is moving up to stack. This isn't Cube. Bring all the data will be back up to the short break. >>Um

>>live from Atlanta, Georgia. It's the Q covering answerable Best 2019. Brought to you by Red Hat. >>Welcome back. Everyone keeps live coverage of answerable fast here in Atlanta. Georgia John for my coach do Minutemen were here. Stephanie chairs to the vice president of general manager of the rail business unit. Red Hat. Great to see you. Nice to see you, too. You have all your three year career. IBM now Invincible. Back, Back in the fold. >>Yeah. >>So last time we chatted at Red Hat Summit Rail. Eight. How's it going? What's the update? >>Yeah, so we launched. Related some. It was a huge opportunity for arrested Sort of Show it off to the world. A couple of key things we really wanted to do There was make sure that we showed up the red hat portfolio. It wasn't just a product launch. It was really a portfolio. Lunch feedback so far on relate has been great. We have a lot of adopters on their early. It's still pretty early days. When you think about it, it's been about a little over 445 months. So, um, still early days the feedback has been good. You know it's actually interesting when you run a subscription based software model, because customers can choose to go to eight when they need those features and when they assess those features and they can pick and choose how they go. But we have a lot of folks who have areas of relate that they're testing the feature function off. >>I saw a tweet you had on your Twitter feed 28 years old, still growing up, still cool. >>Yeah, >>I mean 28 years old, The world's an adult now >>know Lennox is running. The enterprise is now, and now it's about how do you bring new innovation in when we launched Relate. We focused really on two sectors. One was, how do we help you run your business more efficiently? And then how do we help you grow your business with innovation? One of the key things we did, which is probably the one that stuck with me the most, was we actually partnered with the Redhead Management Organization and we pulled in the capability of what's called insights into the product itself. So all carbon subscription 678 all include insights, which is a rules based engine built upon the data that we have from, you know, over 15 years of helping customers run large scale Lennox deployments. And we leverage that data in order to bring that directly to customers. And that's been huge for us. And it's not only it's a first step into getting into answerable. >>I want to get your thoughts on We're here and Ansel Fest ate one of our two day coverage. The Red Hat announced the answer Automation platform. I'll see. That's the news. Why is this show so important in your mind? I mean, you see the internal. You've seen the history of the industry's a lot of technology changes happening in the modern enterprises. Now, as things become modernized both public sector and commercial, what's the most important thing happening? Why is this as well fest so important this year? >>To me, it comes down to, I'd say, kind of two key things. Management and automation are becoming one of the key decision makers that we see in our customers, and that's really driven by. They need to be efficient with what they have running today, and they need to be able to scale and grow into innovation. platform. So management and automation is a core critical decision point. I think the other aspect is, you know, Lennox started out 28 years ago proving to the world how open source development drives innovation. And that's what you see here. A danceable fest. This is the community coming together to drive innovation, super modular, able to provide impact right from everything from how you run your legacy systems to how you bring security to it into how do you bring new applications and deploy them in a safe and consistent way? It spans the whole gambit. >>So, Stephanie, you know, there's so much change going on in the industry you talked about, you know what's happening in Relate. I actually saw a couple of hello world T shirts which were given out at Summit in Boston this year, maybe help tie together how answerable fits into this. How does it help customers, you know, take advantage of the latest technology and and and move their companies along to be able to take advantage of some of the new features? >>Yeah, and so I really believe, of course, that unopened hybrid cloud, which is our vision of where people want to go, You need Lennox. So Lenox sits at the foundation. But to really deploy it in in a reasonable way in a Safeway in an efficient way, you need management on automation. So we've started on this journey. When we launched, we announced its summit that we brought in insights and that was our first step included in we've seen incredible uptick. So, um, when we launch, we've seen 87% increase since May in the number of systems that are linked in, we're seeing 33% more increase in coverage of rules based and 152% increase in customers who are using it. What that does is it creates a community of people using and getting value from it, but also giving value back because the more data we have, the better the rules get. So one interesting thing at the end of May, the engineering team they worked with all the customers that currently have insights. Lincoln and they did a scan for Specter meltdown, which, of course, everyone knows about in the industry with the customers who had systems hooked up, they found 100 and 76,000 customer systems that were vulnerable to Spector meltdown. What we did was we had unanswerable playbook that could re mediate that problem. We proactively alerted those customers. So now you start to see problems get identified with something like insights. Now you bring an answerable and answerable tower. You can effectively decide. So I want to re mediate. I can re mediate automatically. I can schedule that remediation for what's best for my company. So, you know, we've tied these three things together kind of in the stepwise function. In fact, if you have a real subscription, you've hooked up to insights. If insights finds an issue, there's a fix it and with answerable, creates a playbook. Now I can use that playbook and answerable tower so really ties through nicely through the whole portfolio to be able to to do everything in feeling. >>It also creates collaboration to these playbooks can be portable, move across the organization, do it once. That's the automation pieces that >>yeah, absolutely. So now we're seeing automation. How do you look at it across multiple teams within an organization so you could have a tower, a tower admin be able to set rules and boundaries for teams, I can have an array l writes. I t operations person be able to create playbooks for the security protocols. How do I set up a system being able to do things repeatedly and consistently brings a whole lot of value and security and efficiency? >>One of the powers of answerable is that it can live in a header Ji. In this environment, you got your windows environment. You know, I've talked of'em where customers that are using it and, of course, in cloud help help us understand kind of the realm. You know why rail plus answerable is, you know, an optimal solution for customers in those header ingenious environment. And what would love I heard a little bit in the keynote about kind of the road map where it's going. Maybe you can talk to about where those would fit together. >>Yeah, perfect and e think your comment about Header genius World is is Keith. That is the way we live, And folks will have to live in a head or a genius, a cz far as the eye can see. And I think that's part of the value, right to bring choice when you look at what we do with rail because of the close collaboration we have between my team and Theo team. That in the management bu around insights are engineering team is actively building rules so we can bring added value from the sense of we have our red Hat engineers who build rail creating rules to mitigate things, to help things with migration. So us develop well, Aden adoption. We put in in place upgrades, of course, in the product. But also there's a whole set of rules curated, supported by red hat that help you upgrade to relate from a prior version. So it's the tight engineering collaboration that we can bring. But to your point, it's, you know, we want to make sure that answerable and answerable tower and the rules that are set up bring added value to rebel and make that simple. But it does have to be in a head of a genius world. I'm gonna live with neighbors in any data center. Of course, >>what one of the pieces of the announcement talked about collections, eyes there, anything specific from from your team that it should be pointed out about from a collections in the platform announcement. >>So I think I think his collection starts to starts to grow on. Git brings out sort of the the simplicity of being pulled. It pulled playbooks and rolls on and pull that all in tow. One spot. We'll be looking at key scenarios that we pulled together that mean the most Terrell customers. Migration, of course, is one. We have other spaces, of course. Where we work with key ecosystem partners, of course, ASAP, Hana, running on rail has been a big focus for us in partnership with S A P. We have a playbook for installing ASAP Hana on Well, so this collaboration will continue to grow. I think collections offers a huge opportunity for a simpler experience to be able to kind of do a automated solution, if you will kind of on your floor >>automation for all. That's the theme here. >>That's what I >>want to get your thoughts on. The comment you made about analytical analytics keep it goes inside rail. This seems to be a key area for insights. Tying the two things together so kind of cohesive. But decoupled. I see how that works. What kind of analytical cables are you guys serving up today and what's coming around the corner because environments are changing. Hybrid and multi cloud are part of what everyone's talking about. Take care of the on premises. First, take care of the public cloud. Now, hybrids now on operating model has to look the same. This is a key thing. What kind of new capabilities of analytics do you see? >>Yes, that's it. So let me step you through that a little bit because because your point is exactly right. Our goal is to provide a single experience that can be on Prem or off Prem and provides value across both, as as you choose to deploy. So insights, which is the analytics engine that we use built upon our data. You can have that on Prem with. Well, you can have it off from with well, in the public cloud. So where we have data coming in from customers who are running well on the public cloud, so that provides a single view. So if you if you see a security vulnerability, you can skin your entire environment, Which is great. Um, I mentioned earlier. The more people we have participating, the more value comes so new rules are being created. So as a subscription model, you get more value as you go. And you can see the automation analytics that was announced today as part of the platform. So that brings analytics capabilities to, you know, first to be able to see what who's running what, how much value they're getting out of analytics, that the presentation by J. P. Morgan Chase was really compelling to see the value that automation is delivering to them. For a company to be ableto look at that in a dashboard with analytics automation, that's huge value, they can decide. Do we need to leverage it here more? Do we need to bring it value value here? Now you combine those two together, right? It's it, And being informed is the best. >>I want to get your reaction way Make common. Are opening student in our opening segment around the J. P. Morgan comment, you know, hours, two minutes, days, two minutes, depending on what the configurations. Automation is a wonderful thing. Where pro automation, as you know, we think it's gonna be huge category, but we took, um ah survey inside our community. We asked our practitioners in our community members about automation, and then they came back with the following. I want to get your reaction. Four. Major benefits. Automation focused efforts allows for better results. Efficiency. Security is a key driver in all this. You mentioned that automation drives job satisfaction, and then finally, the infrastructure Dev ops folks are getting re skilled up the stack as the software distraction. Those are the four main points of why automation is impacting enterprise. Do you agree with that? You make comments on some of those points? >>No, I do. I agree. I think skills is one thing that we've seen over and over again. Skills is skills. His key. We see it in Lennox. We have to help, right? Bridge window skills in tow. Lennox skills. I think automation that helps with skills development helps not only individuals but helps the company. I think the 2nd 2nd piece that you mentioned about job satisfaction at the end of the day, all of us want to have impact. And when you can leverage automation for one individual toe, have impact that that is much broader than they could do before with manual tasks. That's just that's just >>you know, Stew and I were talking also about the one of the key note keywords that kept on coming out and the keynote was scales scales, driving a lot of change in the industry at many levels. Certainly, software automation drives more value. When you have scale because you scaling more stuff, you can manually configure his stuff. A scale software certainly is gonna be a big part of that. But the role of cloud providers, the big cloud providers see IBM, Amazon, all the big enterprises like Microsoft. They're traveling massive scale. So there's a huge change in the open source community around how to deal with scale. This is a big topic of conversation. What's your thoughts on this? Sending general opinions on how the scales change in the open source equation. Is it more towards platforms, less tools, vice versa? Is there any trends? You see? >>I think it's interesting because I think when I think a scale, I think both volume right or quantity as the hyper scale ours do. I think also it's about complexity. I think I think the public clouds have great volume that they have to deal with in numbers of systems, but they have the ability to customize leveraging development teams and leveraging open source software they can customize. They can customize all the way down to the servers and the processor chips. As we know for most folks, right, they scale. But when they scale across on Prem in off from its adding complexity for them. And I think automation has value both in solving volume issues around scale, but also in complexity issues around scale. So even you know mid size businesses if they want a leverage on Prem, an off ramp to them, that's complexity scale. And I think automation has a huge amount of value to >>bring that abstracts away. The complexity automated, absolutely prized job satisfaction but also benefits of efficiency >>absolutely intimately. The greatest value of efficiency is now. There's more time to bring an innovation right. It's a zoo, Stephanie. >>Last thing I wondering, What feedback are you hearing from customers? You know, one of the things that struck me we're talking about the J. P. Morgan is they made great progress. But he said they had about a year of working with security of the cyber, the control groups to help get them through that knothole of allowing them toe really deploy automation. So, you know, usually something like answerable. You think? Oh, I can get a team. Let me get it going. But, oh, wait, no, Hold on. Corporate needs to make its way through. What is that something you hear generally? Is that a large enterprise thing? You know what? What are you hearing from customers that you're >>talking? I think I think we see it more and more, and it came up in the discussions today. The technical aspect is one aspect. The sort of cultural or the ability to pull it in is a whole separate aspect. And you think that technology from all of us who are engineers, we think, Well, that's the tough bit. But actually, the culture bit is just it's hard. One thing that that I see over and over again is the way cos air structured has a big impact. The more silo the teams are, do they have a way to communicate because fixing that so that you, when you bring in automation, it has that ability to sort of drive more ubiquitous value across. But if you're not structured toe leverage that it's really hard if your I T ops guys don't talk to the application folks bringing that value is very hard, so I think it is kind of going along in parallel right. The technical capabilities is one aspect. How you get your organization structure to reap the benefits is another aspect, and it's a journey. That's that's really what I see from folks. It is a journey. And, um, I think it's inspiring to see the stories here when they come back and talk about it. But to me the most, the greatest thing about it's just start right. Just start wherever you are and and our goal is to try and help on ramps for folks wherever their journey is, >>is a graft over people's careers and certainly the modernization of the enterprise and public sector and governments from how they procure technology to how they deploy and consume it is radically changing very quickly. By the way too scale on these things were happening. I've got to get your take on. I want to get your expert opinion on this because you have been in the industry of some of the different experiences. The cloud one Datta was the era of compute storage startups started Airbnb start all these companies examples of cloud scale. But now, as we start to get into the impact to businesses in the enterprise with hybrid multi cloud, there's a cloud. 2.0 equation again mentioned Observe Ability was just network management at White Space. Small category. Which company going public? It's important now kind of subsystem of cloud 2.0, automation seems to feel the same way we believe. What's your definition of cloud to point of cloud? One daughter was simply stand up some storage and compete. Use the public cloud and cloud to point is enterprise. What does that mean to you? What? How would you describe cloud to point? >>So my view is Cloud one Dato was all about capability. Cloud to Dato is all about experience, and that is bringing a whole do way that we look at every product in the stack, right? It has to be a seamless, simple experience, and that's where automation and management comes in in spades. Because all of that stuff you needed incapability having it be secure, having it be reliable, resilient. All of that still has to be there. But now you now you need the experience or to me, it's all about the experience and how you pull that together. And that's why we're hoping. You know, I'm thrilled here to be a danceable fast cause. The more I can work with the teams that are doing answerable and insights and the management aspect in the automation, it'll make the rail experience better >>than people think it's. Software drives it all. Absolutely. Adam, Thanks for sharing your insights on the case. Appreciate you coming back on and great to see you. >>Great to be here. Good to see >>you. Coverage here in Atlanta. I'm John for Stupid Men Cube coverage here and answerable Fest Maur coverage. After the short break, we'll be right back. >>Um

>> from our studios in the heart of Silicon Valley, Palo Alto, California It is a cute conversation >> live in. Welcome to a special cube conversation here in Palo Alto. The Cube Studios. Jon, for your host. We're here with a special panel. Talk about the new brand of tech leaders in this era of cloud computing data. Aye, aye. And engineering excellence with us. We have Christine Heckart to CEO of Scaler J. P. Krishna of Marthe Moorthy. These s VP of engineering a Copa software and Patna saying, VP of engineering a glass door. Guys, welcome to come the Cube conversation. Welcome, engineer. And you guys are all running engineering organizations. You've been a former engineer now running a big company CEO, engineering led company. This is a big trend that's clearly defined. No one needs any validation. Cloud computing has certainly changed the game, eh? I certainly the hottest trend with respect, the data machine learning and the benefits. They're changing the cultures of companies changing how things were built, how people are hired. You're starting to see a complete shift towards old way and new ways. I want to get your thoughts about the engineering opportunities. What is engineering excellence today mean in this modern error? >> Well, for us it we talk a lot about mastery and setting up an environment where engineers have a chance to build their own mastery. But they can also have the necessary tools and technologies to be master of their domain. And these domains, especially if it's cloud base. They're very distributed. They're very, very fast moving. There's a lot of continual risk s so you have to set them up in the right way so they could be successful. >> What's your thoughts? I mean, you guys air cutting edge startup? >> Yes. For us, it's very important that the environment, the working moment for engineers, is organically inspiring. And what I mean by that is when every engineer no, why are there what are they doing? Well, how their work is impacting the company in the business initiators. At the same time, we are making sure that their interests are aligned with Albert projects and work in a way that we are also in a healthy, very extending and stretching their skills when their work has a purpose. And that's what our mission is, which is we want to make sure that everybody finds an opportunity where they feel there's a purpose that its purpose driven, that's when we feel like it. That's a great environment where they will be inspired to come every day and deliver their 110% >> J p excellence and engineering. I mean, this is what people strive for. >> So excellent points from both off them and I. I think I have a slightly different take on it as well. Today's business is we are asked to respond really, really fast, maybe hear the tongue a gel everywhere, John, right? So it's about how do we respond to the needs of the business as quickly as you can On dhe, it becomes the mantra for the organization. Having said that, there is another side to it. The dark side is technical debt. That's something we all have toe grapple with because you're moving fast, you're making decisions. You're hoping things all right, You want to prove your thesis out there, but at the same time, you don't wantto put yourself behind so that it might come and bite you later. So it's finding that balance is really, really important, and that becomes the focal point of the organization. How do you move fast, but at the same time Hold it. Oh, do you not slow yourself down in the >> future? That's a great point. I want to get probably your thoughts. That's because open source has been really a different game changer from the old way to the new way. Because you could work with people from different companies. You can work on projects that a better man for other people as well. So it's got a communal aspect to it. But also there is an element of speed the same time agile forces, this kind of concept. So technical debt. You want to move fast, we gotta recover. You kind of know how to get there. How is open source? Change that in Europe in >> well, number one thing that opens and allows all smaller company especially but more companies is that now you you can take on an open source project and start rather starting from ground zero. You can start somewhere where you know it's already helped, and you have a framework ready to start working on. So you're not every two single time we're building our thinking off a new idea you're not starting. Okay, Now let me school start from ground up, right? So you already are at a certain level, the second area where, like you said, you know, we're a Joe. Uh, we have open source, but we also have certain level of customization that the customers needed our application needs. And that's what inspires engineers as well, which is taking the challenger for K. We have a code based. Now let me build something more interesting, more innovative. And then what they also love is giving back to the community. It's we're not. The companies are not just tech community engineering team. We are have a bigger engineering community now, the whole tackle, and that's what makes a big difference for us working in Silicon Valley to even be part of that and contributing factor. >> J P Talk about technical debt when it comes back to the modern era because you can go back to It's been around for a while. Technical dead concerts, not new, but it's always been kind of the water cooler come with core lead engineer and the team. The Aussies have a term called feature creeping. You know, the old days. I don't get it. The feature creep. Actually, it kind of takes it away because of you. If you're applying technical debt properly, you're managing the velocity of the project. So the question is, how is technical debt evolved to the management levels of senior engineering managers? Because that seems to be a key variable in managing the speed and quality of the teams with managing the table. Done. Now, management is what some other conversations. >> So the game depends on the stage of the company Onda stage of the projects you are. If you're in a really mature suffer environment, very you're not making a lot of change. It's OK. It's not the primary conversation off the topic. But if you're trying to you capture a market or promote an idea, it becomes the fundamental thesis, forgetting things out there quickly Now, getting things out there quickly doesn't mean you get to let users suffer. You had to build it in the right way, needs toe work, but at the same time it needs to be just enough so that we can We can get the feedback from from the user's on. At the same time, you probably would have left out potentially features on. Maybe you didn't even make certain decisions on Let's say, hi availability or our scalability. Maybe you wanna prove it out in only one region of the world and so on. So you have to find those balances, and it becomes part of the planning conversations right in the front. And as you go into the further iterations of the product, it becomes part of the prioritization conversation of the product managers because it's not just about getting one part done and getting it out there. But as it reached the full level of maturity that you would want, >> I'm sure there's a lot of debates about an engineer organizations because, you know, engineers a very vocal you. Yeah, so you could fall in love with your product of your time to market, maybe taking some technical debt to get product market fit. And that's my baby, though, when you got a re platform or re scale it to make it scale, bringing with your point you mentioned. How do you guys manage? Because this becomes a talent management. People say, Oh, you gotta manage the ECOWAS. But if some people are managing the project in there. They're going to fire over their skis on technical debt. You gotta kind of rain that in. How do you guys manage the people side of the equation? That because it's an art and a science at the same time? What's your thoughts? >> Well, I'll say this, um, supporting al aspects of change, right? That's also is an injury leader. It's a core responsibility and call it a priority for us, not just the technical debt, but also the market shifts. Technology shifts. We have new tech coming in. We have involving in evolving every technology. So how do via dear to and make sure that it's very important that engineering is supporting and kind of coming up with these technologies a tte the same time? We are not just pulling down to their version of grades and all of them, so in a jest, it's it's a core aspect of leadership to make sure that you, as we are supporting these changes, were also making sure that these changes are not pulling us down. So that should be proper quality checks. There should be a proper conversation and roadmap items which is saying that it's not attack debt. It's more of a tech investment, and we are talking about so that we're in lock steps with our business partner and not behind, so that now we're saying Okay, we need a whole quarter to develop new things. So it's an aspect of filmmaking. Sure, team this motivated >> This comes back to culture. Next question. I want to get you guys thoughts on this building. A positive work culture given engineering led organization. Christine, you're leading that now to start up because your own real fast a lot. A lot of engineers. They're probably a lot of opinions on what that looks like. What is the cultural quick? Because this sets the DNA early on for startup. But as you're maturing organization, you gotta track the best talent. And some say, Well, we work on We saw hard problems. That's kind of cliche, but ultimately you do have to kind of have that problem solving aspect. You gotta have a culture what is a successful work culture for engineering. >> So every everybody talks about engineers wanna solve hard problems. I think that's true. But as Pablo said earlier, if you can help every engineer connect what they're doing, every day to the higher purpose. The organization to the problem that you're solving and how that makes the customers like better in our case, were accompanied by engineers for engineer. So our engineers get really excited about giving other engineers in the world a better day. We have taken it one step further recently by starting a peer network because one of my observations coming into this organization is there are so many peer networks in I t. Because it's been a 30 year industry. There are tons of pure organizations for CEOs. There are tons appear organizations for C. M. O's, but there really aren't for engineers. And if we want to help engineers really develop their career and their full skill set and therefore develop into their full potential, it's about more than just training them. It's about giving them context and full social skills and giving them places where they can learn not just from the other engineers in their company, but from engineers across the organization or across the industry at their same level, and maybe from very different industries and maybe in very different environments. So I think in our case, you know, really trying to bring these peer networks together has been one way that we can not only pay it forward for our own engineers, but also help a lot of other engineers around of the industry >> how you guys handling the engineering talent pertaining, attracting and keeping the best now. >> So I think that's where the whole company comes together, in my view. So as an injuring leader, it's not just that I said the tune of my engineering or as to what? That hiring his top priority. It's where the whole company comes together. You're recruiting team to build the stellar interview process. You are, you know, heads of other orcs to make sure that across the board you're helping define a mission for your company that resonates with your candidates who would want to work with you. So it's a collective effort of building a stellar environment for us glass door when one of the few values is transparency and we live and die by it, which means that when someone is higher, they need to see that be within the company. We are transparent, so we'd share a lot of data. A lot of information, good and bad with every single person in the company. It's never, um, hidden at the same time. We build and set up trust in them to say, Hey, it's confidential. Make sure that it doesn't leave the company and it's been 11 years and it hasn't It has never been the case. >> What class door you don't want have a glass door entry on black. Gotta be transparent. That's the culture. Culture matters minutes. Your culture is all about sharing and being open. >> You will see it. So that's what this is, what God goes down spike for as well, right? Building transparency within the company culture and more and more as we see many stories that we have seen for various companies. And sometimes I get a bad story, too, and I get an invitation. Oh, you're from class door, you know. But that helps overall Rios living and working for user's and professionals. >> Cross is big for you guys, >> absolutely professionals who are in this world looking for a job and life because you're spending a lot of time at work. So we want you to get up every day and be inspired and happy about where you're going to work and for that. That's why we have sharing a lot of the insights about the company's from reviews and ratings and CEO data to make sure that when you make your decision of the next move, you are you can be fully trust. You could be fully confident that the date of your sharing the new with that you're making a good decision. >> J. P. Your thoughts. You guys are on a tear. We've got a great coverage of your the annual conference in Vegas. Recent cube coverage. Your company on paper looks like you're targeting one segment, but you have a lot of range and you're technical platform with data. Um, how you guys articulating to engineering? How do you keep them? What if some of the stories you tell them to attract them to join you guys? >> So number one thing is about the talent that we already have in hopes. So people want to come to work at a place where they can learn, contribute on dhe, also for their Carrie Carrie Respert, both inside Cooper and as the lead on coming into Cooper. They look at it and they say, Oh, you have ah, wide variety of things going on here. You're solving a business problem. But at the same time, the technology stocks are different. You're on all the best clothes are there, so that's an easy attraction for them to come in. But also, it's not just about getting people, and how do you retain them on? We've been lucky. That had very low tuition for many years. Right now in the engineering organization, especially in the value, it is a big deal. Andi. I think part of the things that that is the collaboration and cooperation that they get from everybody on. You know, it's an age old saying diversity and thought, unity in action, right? So I really promote people thinking about radius ideas and alternatives. But there is a time for that debate. And once we agree on a solution, we all pulled in and try to make that successful. And then you repeat that often, and it becomes part of part of the culture and the way the organization operates as >> a follow up to culture. One thing that's become pretty clear is that's global engineering. You mention the valley very competitive, some start ups that they get on that rocket ship can get all the great talent. If you will public everyone. Everyone gets rich of one's happy, a good mission behind it, you know, win win outside. Some stars have to attract talent. You've got to start going on here. You might have a good colonel of great engineers, but you have development environments all over the world, so remote is a big thing. How do you manage the engineer remote? It's a time zone base. Does it put leaders in charge? Is there a philosophy in the Amazon? Has a two pizza team is their big thing. You get small groups. How did you guys view the engineering makeup? Because this becomes a part of the operational tension but operating model of engineering thoughts >> I can go first. I think there is a tension between keeping teams working on one problem on not distributing it across the world for efficiency reasons. But at the same time, how do you all owe for continuity, especially if you have a problem in one area? Can somebody else from another region step in in a different time zone continuing? That's always a problem, and then the other one is in a landscape like ours, in which is not uncommon for many, many companies. It is not that they built a lot of fragmented things. They all need to work together. So having a level of continuity within the radius remote centers is really critical on everybody has their own recipe for this one. But the ones that works for us and I've seen that played out many times, is if you can get a set off teams, toe, focus on certain problem areas and become experts in those >> cohesive within their >> within the physical, and then also have enough critical mass within a center that gives you the good balance between working on. One thing. Worse is knowing everything. So so that works for us, and I I think that's that's the way to get out >> of the operating system. It is a couple highly cohesive, >> and you need to have the right technical leaders on both sides and be willing to collaborate with each other >> partner thoughts >> I want to emphasize on the last statement you really need strong good, really, you know, trusted leaders in the location to Canada, then inculcated more bigger team everything Glassdoor groove from one location to four locations in last three years. And one thing that we learned after our first remote location that we started was that when we seeded our new remote location with few people from the original location that hoped start, you know, the similar aspects of what glassware stands for and over core at those and values. And then, as we added, new people, they just can easily just transfer to them so that hope does in a big way. And then he moved to Chicago with the same idea and, of course, Brazil. Now with the same >> knowledge transfer culture transfer, >> it all makes it easy. Even you have few people seating from the original location that was court for us. >> Pop in actually started their first remote office in San Francisco, which has now become their headquarters. So she has a lot of experience. Everyone of scale er's customers globally. You know, we sell the engineer, so we're dealing with with our customers who are dealing with this problem all the time. And in addition to culture, one thing that seems to bubble up regularly is can do you know when they need a common tool set and where they can do their own thing. How do you, you know, balance that and where do you need a single source of truth that people can agree on? And again, where can people have different points of view? >> You're talking sing associates from code base to what could >> be whatever, Like in our case, it's yeah, if you're going to troubleshoot something, you know, where the logs, the truth in the logs, Are you gonna have a single source for that? But for other people, it could be the data that they're bringing in or how they analyze the business. But if you can be proactive about understanding, when is commonality of tools of approach, of philosophy, of data, whatever, when it's commonality going to be what we drive and when are we going to allow people to do their own thing? And if you can put that framework in place than people know when they have the latitude and when they got a snap to grit and you could move a lot more quickly and there's kind of a technical debt that isn't code based? It's more about this kind of stuff, right? It's tool based its process and culture based. And if you can be more proactive about avoiding that debt, then you're gonna move more quickly. >> Videoconferencing. Very, very important. You should be able to jump on a video Constance very easily to be able to connect with someone driving just a phone calls all of these face time, different areas of face time Technology plays a big role >> technology. This is This is a modern management challenge for the new way to leave because it used to be just outsource. Here's the specs member, the old P. R. D S and M R D's. There's the specs, and you just kind of build it. Now it's much more collaborative to your point. There's really product and engineering going on, and it's gotta be. It's evolving. This is a key new ingredient >> because the expectation on the quality of product is so much more higher than competition is so much more. >> And when you know these engineers build in a lot of cases, they have to operate it now. So, like you say, whether it's a free service to a consumer, Aurens in enterprise, the expectation is perfect. No downtime, no hiccups >> and the reward incentives now become a big part of this now. New way of doing things. So I gotta ask the natural question. What's the reward system? Because Google really kind of pioneered the idea of a host 20% of your time work on your own project. That was about a decade or so ago. Now it's evolved beyond that to free lunches and all these other perks, but this has got to appeal to the human being behind it. What are some of the reward mechanisms? You guys see his management that's that's helpful in growing, nurturing and scaling up engineering organizations. >> Well, engineers are human, and as every human autonomy is critical for any aspects of moderation. And that's what please the core level. Then, of course, lunches, matter and other perks and benefits matter. Snacks of pours. Good coffee machine definitely is the core of it, but autonomy of what you want to do and is that the line. But what we want or what we are trying to deliver, and the aspect and the information of I did and rolled this out, what was the impact of it? That new should go back to that engineer who built that. So threading it through to the end and from the start is its very core for everybody to know because I want to know what I'm as I'm going every day. How is it helping >> and we really try. I personally try Thio. Make sure that each human on the team, regardless of their function, that we understand their potential and their career aspirations because a lot of times the the normal ladder, whatever that lander is, might not be right for every person. And people can pivot and use their skills in very, very different ways, and we need to invest in their ability to try new things. If it doesn't work out, let him come back. So you know, we try to spend time as a company for engineers not just in our company, but beyond. To really help them build out their own career, build out their own brands. Engineers more and more could be, you know, on TV shows and doing blog's and building out their own personal brand in their point of view. And that gives them impact. That goes beyond the one piece of code that they're writing for a company in a given day or a week. >> J. P you guys went public stock options. All these things going on as well. Your thoughts? Yeah, >> I just came back from a trip to my newest Dev center in Hyderabad, India. It's funny. I had sessions with every team over there. The number one topic was full >> s >> so excited about food. So there is something primal about food. Having said that, I think, uh, praise and recognition the age old things. They matter so much. That's what I've seen You acknowledge what somebody has done and kind of feedback to elect partner was saying, The impact that it creates, you know, it's it's a lot more fulfilling than monetary incentives. Not that they're not useful. Occasionally they are. But I think repeating that on doing it more often creates a sense off. Okay, here's what we can accomplish as a team. It is how I can contribute to it, and that creates a normal sense of purpose. >> Austin, you guys talked about tools of commonality is kind of key. It's always gonna be debates about which tools, much codes, languages to use, encoding, etcetera. But this brings up the notion of application development as you get continuous development. This is the operating model for modern engineering. What's the state of the art? What do you guys seeing as a best practice as managers to keep the machinery humming and moving along? And what what's on the horizon? What's next? >> Yeah, in my view, I would just say So what's humming and what state of the art I think I is core thio. Most of the systems and applications, the, uh, the core aspect of pretty much every company as you see, and that's the buzz word, even in Silicon Valley for the right reasons, is how we have built our platforms, insistence and ideas. But now let's make it smarter, and every company now has a lot of data. We are swimming in data, but it's very important that we can pick and pull the the core insides from that data to then power the same product and same system to make it more smarter, right? The whole goal for us ourselves is where they're making our platform or smarter, with the goal of making it more personalized and making sure that as users are navigating a project, pages they are seeing more personalized information so that they're not wasting their time there. We can make faster decisions in more rich data set, which is very catered towards them. So smart, so building that intelligence is core. >> And with continues, integration comes, continues risk. All right, so no risk, no reward. And so we live in an era of freemium. Free service is so you know why not take the risk? You don't have to do an A B test. You got digital. You do a B, C D and use all kinds of analytics. So this is actually a creative opportunity for engineering as they get to the front lines you mentioned earlier getting part of the empowerment. How is the risk taking changing the management? >> You know, I deal with class off users were willing to pay money, so I don't know if I can talk a lot about the freedom aspect of the problem. But now there's always desire for new functionality. If you want it, otherwise you don't want it. There's a lot of risk of worsens that's still floating around, especially in the interprets there today. On it is a big tension that you have to deal with. If you're not careful, then you can introduce problems on believing you're operating on the cloud and you're servicing thousands of customers. A small change can bring down the entire ecosystem, so you'll take it very seriously. You're helping others run their business, and that means you had invest in the right tools and processes. >> So you guys are actually Freemium business model, but still engineers. I got a test that they want to take the rhythms. So is it a cloud sand boxing? How is the risk taking managed? How you guys encouraging risk without having people hurt? You don't >> wantto overburden engineers to the point. They feel stifled and they cannot do anything. So there is a right balance. So you know, there are many techniques we follow the. For example, we roll out the software, tow US staging environment so customers can play around and make sure things are not breaking for their comfort more so than for us. But it is an important part of the equation, and then internally, you have to invest a lot of planning. Appropriately, there are the high risk content on the features, and then there are the low risk ones. You want to think about experimentation frameworks in no way be testing and so on and more importantly, about automation and testing. I don't think if a customer logs a bug and finds the problem, they don't want to see it one more time. Ever really have to make sure that those things don't happen when you're investing robust automation around testing processes because there isn't enough time for the complexity of these applications for destiny thing, man, >> this whale automation with cloud comes in containers kubernetes. All of >> those things, you know you heard will enable engineers with the technology said so that they contested scale. You have to provide access to production like data because you have to worry about no privacy, security and all those aspects. But at the same time, they need to have access to the variety off configurations that are out there so that they contested meaningful so to invest in all of those things. >> But I'll take it back to kind of where we started. This, which is the human factor with continuous delivery, is this continuous risk, and it doesn't matter if this engineer is supporting a free consumer application or the highest end of enterprise. When something goes wrong, this, their stress level goes through the roof and you know, how can we equipped? These people, too, solve problems in real time to have that visibility, to have whatever tool said or date or whatever they need? Because at the end of the day, a bad day for an engineer is a day when something is breaking and they're the ones that have to stay up all night and fix it and a good day for an engineer. A human being is the day they get to go home and have dinner with the family or not be woken up in the night. And there is >> for kite surfing or whatever, you >> know, whatever they dio, there's, you know, there is truly a human way. We think about engineers and engineers get up every day, and they want to change the world and they want to make an impact. And thank God we have, you know, teams of engineers that do that for all of us, and they're human beings, and there's a level of continuous stress that we've injected into their lives every day and to the extent that we, as companies and managers and leaders, can help take some of that burden off of them. The world becomes >> the whole being seeing the results of their work to is rewarding as well. >> Scaler does a lot of stuff there, so I have to call that are at the same time in a lot of very good nuggets, J P. Brother. But one more thing that has shifted in terms of how process of practice works is more of more. Engineers now participate very early on in product development is in the day. They try to understand what is the context and why are we doing. And we do a lot of users research to understand that that process, so that they have full context, that they are building in developing eso they're more of a partner now and not an afterthought. >> Think agile And Dev ops to me has proven that the notion of silos and waterfall practices has democratizing flatten. The organization's out where interdisciplinary crossovers are happening. >> Oh, yes, >> and this has been an interesting art of management is encouraging the right person that crust over the right line was you give people little taste, but sometimes they may not belong there kind of called herding cats in the old days. But now it's more of managing kind of interests and growth there. >> That original Dev ops model, though if you have anybody read the Phoenix project like years ago, but it it was really about bringing different points of view. It's a diversity thing. It's bringing different points of view around the table before the first line. It is written so that you're thinking about every angle on the problem and on the ongoing operation of whatever you're building >> Well, it's all about diversity and inclusion and diversity. I was with states, inclusion and diversity, diversity, inclusion Because male and females are involved. We have two females in tech here. This has been a discussion. We still don't have the numbers up to the senior levels within engineering in general. What has to happen to move the needle for women in tech and or inclusionary people involved in engineering to get the right perspective? What's what's >> not? Start with J P because he's actually a huge champion, and without the men involved, we don't have a solutions, >> inclusion and diversity, J. P your thoughts on this was super important. >> Yeah, Number one is recognition. I was stealing Christine yesterday. I just came back from India. That's like told you I took a picture there of my management team. Came back here, looked at it. There is no female, No right, it's crazy. I mean, it's not that we're not trying on gum it. We had the same problem and we started our center in 2015 right? There was a group picture off the team. There was like they were like two women on the thing. We put a lot of effort into it on. Two years later, a significant chunk of the organization has got women embedded in the team's came because we tried. We went out. Look, for those who are good in this area is not that we compromised on the qualifications. It's really about putting some energy in tow, getting the right resumes and then looking at it. The other thing. We're also doing his cultivation. You have to go to the grassroots because there are just enough women engineers. It's unfortunate, for whatever reasons, they're not taking up that professional military enough studies written on it So last two years we weigh, have conducted something called rails. Girls in India, 150 school age children, Women. I mean, girls come in and then we have supported them, run their classes, hold a class. And that helps, you know, even if 10% off them, you know, choose to take up this profession. It's gonna be a big boost. And we have to do a lot more of those in my opinion. >> Europe T rex President Leading Engineering. What's your view? >> Well, I'll say this, you know, for the people who are participating in helping drive this mission just like J. P. I say thank you, especially for men who are participating in it. We cannot do this without you, but for all the people who, if they're not participate in participating in helping drive this mission, I have all share this one data, uh, one of the initiative that glass or drives this gender pay gap, which is also an outcome off, not having diverse outlook at all levels into in the workplace. And we in our economic research team. They did a study and they shared a projection off when will be closed. The gender pay gap. It's 2017. That's depressing. So for for me, when I hear people who say you know, they, they don't want to participate or they don't think this is the right approach of solving for diversity in workplace, I say Okay, but that's not the reason for you to not participate and stay out. If it join it, join it in your own way. But it's only when l offers. Can I see it as a real problem and participate just like Gibby, as you said grassroot level as well as outside One of the example that I told my team when they say, You know, we don't want to drop the bar, the quality bar, I say Sure, don't drive it, but don't drop it. But if you have two candidates, one with a diverse background, Um, who who might be after cable to the same job in 2 to 3 months over someone who slam dunk today, let's invest in the person who is bringing the diverse background for 2 to 3 months and then make them successful. That's not dropping the bar that's still supporting and investing in helping diversity. >> My good friend and heat you saw at IBM. They put out a survey said Diversity, inclusion, diversity. First companies have a bit of advantage, so the investment is so much lower in the bars, more bringing perspective because if we tell about software here has male and female and that's being 17% female, it's >> not just, you know, I had two things to the comments, all of which I agree with one. It's not just a pipeline problem. It is a a culture problem where people have to feel welcome and it has to be a comfortable environment, and they have to believe that their diverse point of view matters and doesn't matter if they're men or women. But there are lots of times when we all make it hard for somebody with a different point of view to enter the conversation. So we have to do a better job of creating the culture, and secondly, there's a saying you have to see it to be it. We have to see people of diversity, gender and of every other type, cognitive diversity of all types at every level in the company. And, you know, we had the same thing, so I'm lucky enough to send a Fortune 500 public board. And I spend a lot of my time helping women and people of color and diversity get on public boards. But if you go back seven years ago, we were 14% women on public boards and it did not move and it did not move and it did not move and in one year popped over 20%. And that's before the loss. So you know, you make these linear projections we can with effort, yes, actually make >> a >> difference. It just takes a very concerted effort. And in this case, particularly for engineering and for leadership, it is making a concerted effort at every level, from board to CEO to executive team to all levels down. Making sure we have inclusion and diversity in >> this is a modern management challenge in the new way of leading managing >> this process. These things, This >> is the big challenge, folks, thanks so much for coming on. Really appreciate. Final question for you guys is what if you could summarize the new way to lead and his modern error from an engineering standpoint, building out of companies building along durable value creation with its company a product or service. What is the key keys to success >> as a leader >> as a leader has a new brand of leaders. >> I would say, You know, this lot goes into, I'm sure you need to know engineering and all the strategic aspect of your job. But the core aspect I feel, is as a leader, my success depends on the quality of relationships I'm building with my team and members that I work with. So that goes into the people aspect, the people connection that goes into it, >> J p. >> Absolutely People are are a big portion of the story. I also feel understanding the problem and driving for results. You know, it's not just about building something. It's about building for a purpose. What is it that you're you're tryingto accomplish and continuing to find that? And working with the teams is so critical for success, especially in a fast moving in Christine. >> Yeah, I agree. It is all about the people, and I think old and new. This hasn't changed. People need to feel like they belong and they're being appreciated, and they're being heard >> scaler. Glass door Copa software. You guys do a great work. Thanks for sharing the engineering inputs, Thio. Leading successful companies. >> Thank you for >> your leadership. Thank you. >> Thank you so much. >> I'm shot for the Q. Thanks for watching. >> Well.

>> live from Boston, Massachusetts. It's the Cube covering A W s reinforce 2019. Brought to you by Amazon Web service is and its ecosystem partners. >> Well, welcome back. Everyone's Cube Live coverage here in Boston, Massachusetts, for AWS. Reinforce Amazon Web sources. First inaugural conference around security. It's not Osama. It's a branded event. Big time ecosystem developing. We have returning here. Cube Alumni Bill Jeff for VP of strategy and the partnerships that Iron Net Cyber Security Company. Welcome back. Thanks. General Keith Alexander, who was on a week and 1/2 ago. And it was public sector summit. Good to see you. Good >> to see you. Thanks for >> having my back, but I want to get into some of the Iran cyber communities. We had General Qi 1000. He was the original commander of the division. So important discussions that have around that. But don't get your take on the event. You guys, you're building a business. The minute cyber involved in public sector. This is commercial private partnership. Public relations coming together. Yeah. Your models are sharing so bringing public and private together important. >> Now that's exactly right. And it's really great to be here with eight of us were really close partner of AWS is we'll work with them our entire back in today. Runs on AWS really need opportunity. Get into the ecosystem, meet some of the folks that are working that we might work with my partner but to deliver a great product, right? And you're seeing a lot of people move to cloud, right? And so you know some of the big announcement that are happening here today. We're willing. We're looking to partner up with eight of us and be a first time provider for some key new Proactiv elves. AWS is launching in their own platform here today. So that's a really neat thing for us to be partnered up with this thing. Awesome organization. I'm doing some of >> the focus areas around reinforcing your party with Amazon shares for specifics. >> Yes. So I don't know whether they announced this capability where they're doing the announcement yesterday or today. So I forget which one so I'll leave that leave that leave that once pursued peace out. But the main thing is, they're announcing couple of new technology plays way our launch party with them on the civility place. So we're gonna be able to do what we were only wanted to do on Prem. We're gonna be able to do in the cloud with AWS in the cloud formation so that we'll deliver the same kind of guy that would deliver on prime customers inside their own cloud environments and their hybrid environment. So it's a it's a it's a sea change for us. The company, a sea change for a is delivering that new capability to their customers and really be able to defend a cloud network the way you would nonpregnant game changer >> described that value, if you would. >> Well, so you know, one of the key things about about a non pregnant where you could do you could look at all the flows coming past you. You look at all the data, look at in real time and develop behavior. Lana looks over. That's what we're doing our own prime customers today in the cloud with his world who looked a lox, right? And now, with the weight of your capability, we're gonna be able to integrate that and do a lot Maur the way we would in a in a in a normal sort of on Prem environment. So you really did love that. Really? Capability of scale >> Wagon is always killed. The predictive analytics, our visibility and what you could do. And too late. Exactly. Right. You guys solve that with this. What are some of the challenges that you see in cloud security that are different than on premise? Because that's the sea, So conversation we've been hearing. Sure, I know on premise. I didn't do it on premises for awhile. What's the difference between the challenge sets, the challenges and the opportunities they provide? >> Well, the opportunities air really neat, right? Because you've got that even they have a shared responsibility model, which is a little different than you officially have it. When it's on Prem, it's all yours essential. You own that responsibility and it is what it is in the cloud. Its share responsible to cloud provider the data holder. Right? But what's really cool about the cloud is you could deliver some really interesting Is that scale you do patch updates simultaneously, all your all your back end all your clients systems, even if depending how your provisioning cloud service is, you could deliver that update in real time. You have to worry about. I got to go to individual systems and update them, and some are updated. Summer passed. Some aren't right. Your servers are packed simultaneously. You take him down, you're bringing back up and they're ready to go, right? That's a really capability that for a sigh. So you're delivering this thing at scale. It's awesome now, So the challenge is right. It's a new environment so that you haven't dealt with before. A lot of times you feel the hybrid environment governed both an on Prem in sanitation and class sensation. Those have to talkto one another, right? And you might think about Well, how do I secure those those connections right now? And I think about spending money over here when I got all seduced to spend up here in the cloud. And that's gonna be a hard thing precisely to figure out, too. And so there are some challenges, but the great thing is, you got a whole ecosystem. Providers were one of them here in the AWS ecosystem. There are a lot here today, and you've got eight of us as a part of self who wants to make sure that they're super secure, but so are yours. Because if you have a problem in their cloud, that's a challenge. Them to market this other people. You talk about >> your story because your way interviews A couple weeks ago, you made a comment. I'm a recovering lawyer, kind of. You know, we all laughed, but you really start out in law, right? >> How did you end up here? Yeah, well, the truth is, I grew up sort of a technology or myself. My first computer is a trash 80 a trs 80 color computer. RadioShack four k of RAM on board, right. We only >> a true TRS 80. Only when I know what you're saying. That >> it was a beautiful system, right? Way stored with sword programs on cassette tapes. Right? And when we operated from four Keita 16 k way were the talk of the Rainbow Computer Club in Santa Monica, California Game changer. It was a game here for 16. Warning in with 60 give onboard. Ram. I mean, this is this is what you gonna do. And so you know, I went from that and I in >> trouble or something, you got to go to law school like you're right >> I mean, you know, look, I mean, you know it. So my dad, that was a chemist, right? So he loved computers, love science. But he also had an unrequited political boners body. He grew up in East Africa, Tanzania. It was always thought that he might be a minister in government. The Socialist came to power. They they had to leave you at the end of the day. And he came to the states and doing chemistry, which is course studies. But he still loved politics. So he raised at NPR. So when I went to college, I studied political science. But I paid my way through college doing computer support, life sciences department at the last moment. And I ran 10 based. He came on climate through ceilings and pulled network cable do punch down blocks, a little bit of fibrous placing. So, you know, I was still a murderer >> writing software in the scythe. >> One major, major air. And that was when when the web first came out and we had links. Don't you remember? That was a text based browser, right? And I remember looking to see him like this is terrible. Who would use http slash I'm going back to go for gophers. Awesome. Well, turns out I was totally wrong about Mosaic and Netscape. After that, it was It was it was all hands on >> deck. You got a great career. Been involved a lot in the confluence of policy politics and tech, which is actually perfect skill set for the challenge we're dealing. So I gotta ask you, what are some of the most important conversations that should be on the table right now? Because there's been a lot of conversations going on around from this technology. I has been around for many decades. This has been a policy problem. It's been a societal problem. But now this really focus on acute focus on a lot of key things. What are some of the most important things that you think should be on the table for techies? For policymakers, for business people, for lawmakers? >> One. I think we've got to figure out how to get really technology knowledge into the hands of policymakers. Right. You see, you watch the Facebook hearings on Capitol Hill. I mean, it was a joke. It was concerning right? I mean, anybody with a technology background to be concerned about what they saw there, and it's not the lawmakers fault. I mean, you know, we've got to empower them with that. And so we got to take technologist, threw it out, how to get them to talk policy and get them up on the hill and in the administration talking to folks, right? And one of the big outcomes, I think, has to come out of that conversation. What do we do about national level cybersecurity, Right, because we assume today that it's the rule. The private sector provides cyber security for their own companies, but in no other circumstance to expect that when it's a nation state attacker, wait. We don't expect Target or Wal Mart or any other company. J. P. Morgan have surface to air missiles on the roofs of their warehouses or their buildings to Vegas Russian bear bombers. Why, that's the job of the government. But when it comes to cyberspace, we expect Private Cummings defending us everything from a script kiddie in his basement to the criminal hacker in Eastern Europe to the nation state, whether Russia, China, Iran or North Korea and these nation states have virtually a limited resource. Your armies did >> sophisticated RND technology, and it's powerful exactly like a nuclear weaponry kind of impact for digital. >> Exactly. And how can we expect prices comes to defend themselves? It's not. It's not a fair fight. And so the government has to have some role. The questions? What role? How did that consist with our values, our principles, right? And how do we ensure that the Internet remains free and open, while still is sure that the president is not is not hampered in doing its job out there. And I love this top way talk about >> a lot, sometimes the future of warfare. Yeah, and that's really what we're talking about. You go back to Stuxnet, which opened Pandora's box 2016 election hack where you had, you know, the Russians trying to control the mean control, the narrative. As you pointed out, that that one video we did control the belief system you control population without firing a shot. 20 twenties gonna be really interesting. And now you see the U. S. Retaliate to Iran in cyberspace, right? Allegedly. And I was saying that we had a conversation with Robert Gates a couple years ago and I asked him. I said, Should we be Maur taking more of an offensive posture? And he said, Well, we have more to lose than the other guys Glasshouse problem? Yeah, What are your thoughts on? >> Look, certainly we rely intimately, inherently on the cyber infrastructure that that sort of is at the core of our economy at the core of the world economy. Increasingly, today, that being said, because it's so important to us all the more reason why we can't let attacks go Unresponded to write. And so if you're being attacked in cyberspace, you have to respond at some level because if you don't, you'll just keep getting punched. It's like the kid on the playground, right? If the bully keeps punching him and nobody does anything, not not the not the school administration, not the kid himself. Well, then the boy's gonna keep doing what he's doing. And so it's not surprising that were being tested by Iran by North Korea, by Russia by China, and they're getting more more aggressive because when we don't punch back, that's gonna happen. Now we don't have to punch back in cyberspace, right? A common sort of fetish about Cyrus is a >> response to the issue is gonna respond to the bully in this case, your eggs. Exactly. Playground Exactly. We'll talk about the Iran. >> So So if I If I if I can't Yeah, the response could be Hey, we could do this. Let them know you could Yes. And it's a your move >> ate well, And this is the key is that it's not just responding, right. So Bob Gates or told you we can't we talk about what we're doing. And even in the latest series of alleged responses to Iran, the reason we keep saying alleged is the U. S has not publicly acknowledged it, but the word has gotten out. Well, of course, it's not a particularly effective deterrence if you do something, but nobody knows you did it right. You gotta let it out that you did it. And frankly, you gotta own it and say, Hey, look, that guy punch me, I punch it back in the teeth. So you better not come after me, right? We don't do that in part because these cables grew up in the intelligence community at N S. A and the like, and we're very sensitive about that But the truth is, you have to know about your highest and capabilities. You could talk about your abilities. You could say, Here are my red lines. If you cross him, I'm gonna punch you back. If you do that, then by the way, you've gotta punch back. They'll let red lines be crossed and then not respond. And then you're gonna talk about some level of capabilities. It can't all be secret. Can't all be classified. Where >> are we in this debate? Me first. Well, you're referring to the Thursday online attack against the intelligence Iranian intelligence community for the tanker and the drone strike that they got together. Drone take down for an arm in our surveillance drones. >> But where are we >> in this debate of having this conversation where the government should protect and serve its people? And that's the role. Because if a army rolled in fiscal army dropped on the shores of Manhattan, I don't think Citibank would be sending their people out the fight. Right? Right. So, like, this is really happening. >> Where are we >> on this? Like, is it just sitting there on the >> table? What's happening? What's amazing about it? Hi. This was getting it going well, that that's a Q. What's been amazing? It's been happening since 2012 2011 right? We know about the Las Vegas Sands attack right by Iran. We know about North Korea's. We know about all these. They're going on here in the United States against private sector companies, not against the government. And there's largely been no response. Now we've seen Congress get more active. Congress just last year passed to pass legislation that gave Cyber command the authority on the president's surgery defenses orders to take action against Russia, Iran, North Korea and China. If certain cyber has happened, that's a good thing, right to give it. I'll be giving the clear authority right, and it appears the president willing to make some steps in that direction, So that's a positive step. Now, on the back end, though, you talk about what we do to harden ourselves, if that's gonna happen, right, and the government isn't ready today to defend the nation, even though the Constitution is about providing for the common defense, and we know that the part of defense for long. For a long time since Secretary Panetta has said that it is our mission to defend the nation, right? But we know they're not fully doing that. How do they empower private sector defense and one of keys That has got to be Look, if you're the intelligence community or the U. S. Government, you're Clinton. Tremendous sense of Dad about what you're seeing in foreign space about what the enemy is doing, what they're preparing for. You have got to share that in real time at machine speed with industry. And if you're not doing that and you're still count on industry to be the first line defense, well, then you're not empowered. That defense. And if you're on a pair of the defense, how do you spend them to defend themselves against the nation? State threats? That's a real cry. So >> much tighter public private relationship. >> Absolutely, absolutely. And it doesn't have to be the government stand in the front lines of the U. S. Internet is, though, is that you could even determine the boundaries of the U. S. Internet. Right? Nobody wants an essay or something out there doing that, but you do want is if you're gonna put the private sector in the in the line of first defense. We gotta empower that defense if you're not doing that than the government isn't doing its job. And so we gonna talk about this for a long time. I worked on that first piece of information sharing legislation with the House chairman, intelligence Chairman Mike Rogers and Dutch Ruppersberger from Maryland, right congressman from both sides of the aisle, working together to get a fresh your decision done that got done in 2015. But that's just a first step. The government's got to be willing to share classified information, scaled speed. We're still not seeing that. Yeah, How >> do people get involved? I mean, like, I'm not a political person. I'm a moderate in the middle. But >> how do I How do people get involved? How does the technology industry not not the >> policy budgets and the top that goes on the top tech companies, how to tech workers or people who love Tad and our patriots and or want freedom get involved? What's the best approach? >> Well, that's a great question. I think part of is learning how to talk policy. How do we get in front policymakers? Right. And we're I run. I run a think tank on the side at the National Institute at George Mason University's Anton Scalia Law School Way have a program funded by the Hewlett Foundation who were bringing in technologists about 25 of them. Actually. Our next our second event. This Siri's is gonna be in Chicago this weekend. We're trained these technologies, these air data scientists, engineers and, like talk Paul's right. These are people who said We want to be involved. We just don't know how to get involved And so we're training him up. That's a small program. There's a great program called Tech Congress, also funded by the U. A. Foundation that places technologists in policy positions in Congress. That's really cool. There's a lot of work going on, but those are small things, right. We need to do this, its scale. And so you know, what I would say is that their technology out there want to get involved, reach out to us, let us know well with our partners to help you get your information and dad about what's going on. Get your voice heard there. A lot of organizations to that wanna get technologies involved. That's another opportunity to get in. Get in the building is a >> story that we want to help tell on be involved in David. I feel passion about this. Is a date a problem? So there's some real tech goodness in there. Absolutely. People like to solve hard problems, right? I mean, we got a couple days of them. You've got a big heart problems. It's also for all the people out there who are Dev Ops Cloud people who like to work on solving heart problems. >> We got a lot >> of them. Let's do it. So what's going on? Iron? Give us the update Could plug for the company. Keith Alexander found a great guy great guests having on the Cube. That would give the quick thanks >> so much. So, you know, way have done two rounds of funding about 110,000,000. All in so excited. We have partners like Kleiner Perkins Forge point C five all supporting us. And now it's all about We just got a new co CEO in Bill Welshman. See Scaler and duo. So he grew Z scaler. $1,000,000,000 valuation he came in to do Oh, you know, they always had a great great exit. Also, we got him. We got Sean Foster in from from From Industry also. So Bill and Sean came together. We're now making this business move more rapidly. We're moving to the mid market. We're moving to a cloud platform or aggressively and so exciting times and iron it. We're coming toe big and small companies near you. We've got the capability. We're bringing advanced, persistent defense to bear on his heart problems that were threat analytics. I collected defence. That's the key to our operation. We're excited >> to doing it. I call N S A is a service, but that's not politically correct. But this is the Cube, so >> Well, look, if you're not, if you want to defensive scale, right, you want to do that. You know, ECE knows how to do that key down here at the forefront of that when he was in >> the government. Well, you guys are certainly on the cutting edge, riding that wave of common societal change technology impact for good, for defence, for just betterment, not make making a quick buck. Well, you know, look, it's a good business model by the way to be in that business. >> I mean, It's on our business cards. And John Xander means it. Our business. I'd say the Michigan T knows that he really means that, right? Rather private sector. We're looking to help companies to do the right thing and protect the nation, right? You know, I protect themselves >> better. Well, our missions to turn the lights on. Get those voices out there. Thanks for coming on. Sharing the lights. Keep covers here. Day one of two days of coverage. Eight of us reinforce here in Boston. Stay with us for more Day one after this short break.

(upbeat music) >> Live from Las Vegas, it's theCUBE! Covering Informatica World 2019. Brought to you by Informatica. >> Welcome back everyone to theCUBE's live coverage of Informatica World here in Las Vegas. I am your host, Rebecca Knight. We are joined by John Lieto. He is the Director, Data Management at Wolters Kluwer. Thank you so much for coming on the show. >> Very welcome. >> So, Wolters Kluwer is a global provider of professional information, software solutions, tax information. Tell our viewers a little bit more about the company and about your role at the company. >> Yeah, so Wolters Kluwer, I would say probably 20 years ago, was a typical holding company. Has a very long history of publishing in Europe. It's over 185 years old in Europe. But, went on a journey to acquire businesses that were in the services business with a focus on legal, but there are also big concentrations in health divisions, tax and accounting, really a professional company. Very, very, very big in print. What happened over the last 10, 15 years though, it's completely flipped over to digital. In fact, it's been one of the more successful transformations. So now we're mostly in the digital space and electronic space. So where I come in, and my business unit comes in, CT Corporation is a 126-year-old company. Number one player in registered agent services. Legal information, helping companies like Informatica stay in compliance. United States is 50 states with 50 sets of rules, plus international. So typically, companies of any size get a provider. Sometimes their law firms will do it, but a lot of times, it's going to be CT Corporations, things like that. My role in the company, I've been there 19 years, I've had a mix of roles, mostly in the business but a little technical. I'm the Director of Data Management, I am basically in charge of managing governance and data quality for the business. It is focused on the customer right now and all things related to customer, but we're expanding into other domains like vendors, products, suppliers and supporting of pretty large digital transformation. >> So I'm sure in your role you have a lot of practical insights for MDM practitioners but before we go there, I want to hear from you about the customer mindset, I mean, this is a moment for data governance and security... >> Sure >> and privacy, a real inflection point, and like Wolters Kluwer, so many companies undergoing their own digital transformations. How would you describe the customer mindset about all of this? How are customers wrapping their brains around it? >> So for us, we're not in a very regulated business. We touch customers that are heavily regulated, but we're not, we're a service company, right? Most of the stuff, the data we deal with is public knowledge, right? A company's data is public knowledge, you can go in any state website and find out when Informatica was formed, who the board of directors are, so it's all public. But customers are extremely sensitive about where their data is, and what we're doing with it, so we were on top of that, especially for our foreign customers. Internally the CT and Wolters Kluwer we have to be very, very, very customer-focused 'cause it's a very direct service, right? So it's all about the customer. How we got to this point of using Informatica MDM, Massive Data Management, is trying to get close to the customer, trying to understand the customer. Our customers go from J P Morgan to these big, big, big companies that have investments in companies that you wouldn't even know they're related to that customer. So they rely on us to help them stay compliant. How do I deal with these diverse businesses that are under my portfolio, and how do I keep them compliant in the States? So we have all this data and we help our customers understand it, and know what to do next, almost anticipate where they're going to fall out of compliance in the State. >> So what is your advice for the people who are really starting, for the executives starting at square one, trying to think about a master data management solution? >> Yeah, great question. And it's really where the heart of my devotion has been the last year. I would say the most important thing is start with a business case. Understand where your business is going. Make it about what outcomes are you looking for. Really thoroughly understand that. Also take the systems or the subjects that are important to you, your company, and profile it. Understand that data. You can come to an MDM project, a master data management project, with so much knowledge first, don't just say, well everybody is doing master data management, we should do it too. I mean, it might be true, but you're really not going to get the outcomes. And then focus your project to hit those business goals, 'cause MDM is a process and a tool, it's not an answer. You need to use that tool to get to where you are, so for us the number one thing was reduce duplication, okay, MDM tools do that, so we're trying to get to the golden record, okay. Data quality, I don't have the good phone numbers I have bad email addresses, oh, mass data management does that too. So, again, it's going for the outcomes you're driving for, and MDM happens to be a good tool for that. >> So it's really about defining the objectives before you even jump in. >> Absolutely. >> Do you recommend experiments? What's the approach you... >> Wonderful question. In data we call it profiling, right? And you want to go in small wins, because one of the things that will happen to anyone in this space is the business is really not sure about this investment. These days, data is becoming so huge that's becoming a lot easier for guys like me to win a business case, but two years ago it was pretty hard. I'm sorry I just lost my train of thought. >> But that's an interesting point, just talking about the overcoming the skepticism within these companies to latch on to this idea, and as you were saying, the announcing the small wins, really getting everyone on board. >> Thank you. What we did is, we had profiled, found a problem, oh, we have definitive cost duplication, we've got email addresses that are completely bogus. Let's just to take those two. And we did small little pilots. We'd use tools we had, completely manual ad-hoc, let's fix 200 records, let's take a really important customer that we're trying to onboard, or expand, and let's fix that data, and then show the outcomes. Go for the quick wins. Communicate, communicate, communicate. Once we did that, and we did a series of, I want to say, 30 or 40 of these. That built our requirement set. We built the requirement set by doing. It was so easy that way to show victories, but too, to really get the requirements to a point where we could build the system. We happened to fall on that method, from prior learnings of not doing well on projects that had nothing to do with MDM. So for this one, I think the other piece of advice that I would give folks, is we built a data management team of business analysts that know our business and data. It is really critical that you keep this function out of IT. IT is your supporter and your partner. This does not go to IT. So we know our data. I have a guy on my team that's 45 years in the company, a woman who's 28 years in the company, just for example. So we can do a lot without a tool, and what's happening is now we are live for going on eight months now, and we're staying on top, making sure the tool's delivering what it's supposed to deliver, based on our deep knowledge. >> And I think that what you're talking about really, is introducing this technology and this new way of thinking, and it's really all about change management. >> It truly is. >> One of the things that we're talking a lot here in theCUBE about is the skills gap, and this is a problem throughout the technology industry. How big a problem is it for you at Wolters Kluwer? And what are you doing to make sure that you have the right technical talent on your team, and as we're saying, not just the technical talent but also the understanding of the business? >> One thing to understand is Wolters Kluwer is a fairly big company, and we as a company are just starting this journey. I have a small data management team in one business unit at Wolters Kluwer. There's another business unit within our health division that has data management, and that's all that I know of that is a formal data management. That's pretty small, so it's just beginning. What we're doing, we're trying to communicate, communicate, communicate. I am having some success because in our next huge journey, which is a digital transformation, a six-year project, data now is center. I've been asked to actually be the business sponsor for the data track, which, two years ago, that would not have happened. So I take that as a win, but you make a fair point, skills and understanding, both at the business and technical level is always a challenge, and it's justifying bringing in that skill set. No we can just outsource that, or we'll just use a consultant. I'm right now fighting a battle to bring in a data architect, full-time, they don't understand that... >> Just that role. >> You have to architect things. We've now done that, so what you have, because I' doing the data governance piece right now, and what I'm finding is, it's not the Wild West, but you can't always know what the parts of the organization is doing, and a lack of an architect is not keeping all the plumbing all centralized. So, a I build this data governance, I'm going to centralize data definitions and data glossary, data catalog, but I'm going to be looking around and going, okay, how do I actually have the technology piece architected correctly and that's the piece I'm really trying to pump, so hopefully when we build this data layer we're building my goal is to prove to the business that you need to fill this role. It's not me, it's going to be someone who really is deep, deep, deep in architecture. >> Hire a contractor, get that small win. >> That's what we're doing. (laughing) >> And then, the proof. I learned that from you, John. >> I'm actually in the process of just doing that. >> Excellent! >> One of those vendors is here. >> Well, we'll look forward to talking to you next year and hearing an update. >> Yeah, there you go. >> John Lieto, thank you so much for coming on theCUBE. >> You're very welcome, thank you. >> I'm Rebecca Knight, we will have more of theCUBE's live coverage of Informatica World. Stay tuned! (upbeat musing)

>> from our studios in the heart of Silicon Valley, Palo Alto, California It is a cute conversation. >> Hi, I'm Peter. Boris, And welcome to another cube conversation from our wonderful studios and beautiful Paolo Alto, California. One of the biggest challenge that every enterprises faces how to attend to the volumes of data that are being generated by applications. But more importantly, that the business is now requiring because they want to find new derivative sources of value in their digital business. Transformations is gonna require a significant retooling and rethinking of how we used eight is an asset. And the directions that infrastructure, data management and business are gonna move together over the course of next few years. Now, have that conversation. Got a couple of great guests here. Josie Swoop is a VP of marketing veritas. Welcome to Cuba or back to the Cube. Yeah, thanks. Peter and Rick Clark is a CEO of opt are welcome. Thank you for the first time. >> Great to be here, >> So let me start here. Joey, why don't we start with you? Give us a quick update on Veritas and where your customers are indicating the direction needs to go. >> We've just had, ah, record breaking financial year for us, which ended in end of March. So since divestiture from semantic, as you know better, Toss has been through a transformation and then on a path to growth. So our core businesses are humming with just like I said, the second half of the year specifically was great for us. What we're hearing from customers, Peter, is that they want to elevate their their business problems away from infrastructure to business outcomes. That what they ask veritas to do is, can you abstract away some of those infrastructure plumbing problems, storage, security, data protection and focus on what the applications can give us. That's number one. Number two is Can we standardize? I mean, the example of Southwest comes to mind, right? They have the same plane so they can reroute those planes anytime they have the same pilots flying those planes so they can to standardize. So they collapsed better. And then, lastly, to your point value of data over volume. Everybody talks about the volume. What about the value of data? What is veritas do for for me? Mr. You know God's a customer in our tax extract value of that data, which is growing day by day. >> Well, one of the most interesting things about this challenge of businesses faces they try to attend to these things is that data is often characterizes the new oil. And we we push back against that Because >> data is a new kind of asset, it's an asset that's easily copied. It's an asset that's easily shared. You can easily integrate it. You can apply it to multiple uses with zero loss of fidelity and what it does currently. And so the whole notion of creating new options in the value of data's intrinsic to the questions of digital business. So that suggests that we need to start thinking Maur about data protection, not just from the standpoint of protecting data once it's been created and is sitting there so we can recover it. But new types of utilization, new ways of thinking about data data as it's going to be used, understanding more about dating, protecting that Rick, would you kind of Does that resonate? >> Yeah, absolutely. You know, one of the things that we've sort of seed in the marketplace is certainly over the last 10 years, the Data Sena has become so complex. This is massive fragmentation of data across highly virtualized infrastructures. And then, when public clouds came along, customers didn't really know what workloads they should move up into those clouds. And so what we saw is a huge problem. Is areas of cost and efficiencies, massive problems of risk and then obviously the amount of money that cos of spending on compliance. And so what we were really focusing on is the gaps. What do you not know about? And so we would really >> about your data >> about your data. Exactly. So we really measure the hot beat off the data protection environment, and from that we could actually see where are you? Risk where your exposure, where you're spending too much money, >> Where's your opportunities? Seize your opportunities. So we've got a notion of the the solution that folks are looking for, something that provides greater visibility into their end and data from a risk exposure opportunity. New sources of utilization standpoint talk a bit about how >> at four >> rounds out the veritas portfolio as it pertains of these things that you're seeing customers asked for taking data closer to outcomes and away from the device orientation? >> Absolutely. So Vatos has always been known to be a leader and data protection. We've done that for over 20 years. We also were the first pioneers in software defined storage. And we're number one in market share, according to I. D. C and Gardner as well. Ah, but again to my earlier point, customers have been asking. So what? We've done the plumbing really well and you've scaled. How do you take this to the next level? Extract value from all that data you're sitting on top of that you're protecting. And that's where apt are comes into the picture. We've built some tools natively within veritas of the last three or four years where we try to go and classify the data on in jest, identify things like P I information sensitive data, rock data, redundant, obsolete, trivial data that we can delete. There was a customer who recently deleted 30,000,000 files, just press the delete button and this isn't a highly regulated environment, >> but they were still pretty darn eggs. >> They definitely where but we were able to give them that visualization and information that they required. Now the question those customers are asking us or we're asking us. Before avatar came into the picture was at the infrastructure level. How do I know how much I'm spending on my data protection environments? Do I know where the growth ISS is it all in the traditional workloads of oracle ASAP, Or is it in virtual or is it in the cloud? Right. Am I putting too much data on tape? Is it costing me enough? Can extract the value from that data. So they were asking us infrastructure visualization and i D analytics. Questions which only apt are could answer. And we have some joint customers they were actually using. Apt are already not just with to monitor the vatos ecosystem, but even some of our competitors and the broader i t ecosystem on a single planet class. And that's where I think after really shines is is the agnostic approach they take beyond just veritas are beyond just another storage vendor. >> Well, so way certainly subscribed to this notion that data protection is going to It's gonna be extended, but it's gonna become a strategic digital business capability that does have to be re funk around the concept of data value and sounds like that's the direction you're taking, and you guys have clearly seen that as well. But obviously some of your customers have seen it. So talk to us a little bit about how customers helped you two guys together. >> Yeah, that's a great question. Was interesting. Actually. We had some of the largest companies in the globe actually using ourself with many of the fortune Tien using up self with J. P. Morgan Chase quote calm Western digital. And they came to us with these very precise problems around, you know, howto optimize my risk within the environment, had a streamline, obviously the costs and compliance. And we found that they were very common questions. And so we actually created this agnostic intelligence built into the software a rules engine that would have to correlate data from all of these disparate data sources. Whether Tom primer on the cloud tying that together would provide impactful insights to our customers that could sold real world problems. And we'll do it with kind of what we call the easy button. One of the big problems with a lot of software products out there today. Is there a point solutions to manage pots of the infrastructure companies wanted a single pane of glass where I could see everything across all of my storage. All of my data protection on prim and cloud. And that's really what we bring to the table, that single paying the class. And we do it very simply at scale for the largest customers. And that's in many ways was the synergy, obviously, with a partnership with Veritas. >> So give us some sense of how how customers will see the benefits of this from a rollout standpoint over the next 6 to 18. >> Right? So Step One in this journey for us is to ensure there are customers. Understand that we're going to continue to have that open an agnostic approach Apt are suddenly is not gonna become proprietary batter toss product. It's going to continue on its on its mission to be agnostic across various storage data protection and cloud environments. That's number one. Number two is we're gonna bring the the artificial intelligence and machine learning capabilities that we have in house with Veritas combined that with some of the things that Rick just docked, abide with the capabilities adapt our has combine, it's our customers can gain. I know add value. The one plus one equals three approach there as well. So those air, like the two key pillars for us going forward and eventually will extend apt are to an end to in Data Analytics platform not just I d analytics, where we're looking at infrastructure, but an end to end data. Plus I t analytics platform that spans Veritas is will Is the broader a IittIe ecosystem? >> Well, so it's good to hear that you're gonna let apt are continue to focus on data value as opposed to veritas value. Right talk. Talk to me a little bit. About what Does that analytics piece really mean? Howard Customers going to use it? How are they using it today? How are they gonna >> let me carry that? Said is roughly 30,000 unique metrics that we actually gather across the whole I t infrastructure and we'll look at a classic use cases. One of exposure. What? A lot of companies been enormous amount of money on the data protection infrastructure. The using disparity, tools and technologies they don't always go with. One platform like net backup is an example, right? And so with that, come challenges because there's gonna be gaps they might be backing up a Windows server where they're the backup policy says they're just backing up. The C drive will interrogate VM, where all the hyper visor will look at the network and see that there's a D Dr attached to that volume as well. And there's no backup data protection policy. So enormous amount of exposure if they tried to do a restore, obviously, from the d Dr where there's no protection, right from a cost perspective, there's an enormous amount of white space problem in the storage industry. More and more companies are moving from spinning distal flash arrays. A lot of companies is struggling with How do I protect those old flash A raise the using snapshots that using cloud they're tearing to the cloud the using different backup products. Obviously, we'd prefer that they used their backup, but with our software, we can provide that that inside across the entire data protection framework and storage and show you where is your risk? Where is your inefficiency, where you double protecting things into spending too much, much money? This whole notion of data protection is transaction. A lot of people do what's called distant, distant eight still being voted off site. How do you know that all those transactions are successful? How do you know you can restore based on those s L A's and tying that into you? See, M d B. That's what appetite does. >> So I'ma throw a little bit of a curveball here. So having worked within 90 worked with N i t organizations, it can be I ke historically can has been rolled to the compartmentalizing segment you administrated for servers in Australia for storage of people who are administrating applications and and subsystems. And the cloud is munge ing a fair amount of that together. But one of the places that has always required coordination, collaboration and even more important practice has been in the area of restore firms were shops that did not practice how they would restore, you know, hopefully they never had a problem. But if they did have a problem, if they hadn't practiced that process, they would likely we're not gonna be successful in bringing the business up. Gets even more important digital business. Can you give us a little bit of visibility into how this combination taking the metadata, the metrics of visibility. Taking the high quality service is bringing them together is going to streamline, restore within their prices. >> So first, let me address the first point you made, which is what I call the rise of the versatile is too right. So there are no more specialists in certain jobs. The versatile listen, the cloud or in virtual tend to do three or four jobs when there's back up our story virtualization itself on DDE. What the's Verceles want is to explain an easy barton to restore their VM environment or their big data. And my mother there Hadoop environment. They're not really worried. As a central I t. Team that Hey, what am I going to do with the entire data estate? How did I restore that? So that's the first step. Second step, as the world of I t gets more more complicated on the rise of the worst list continues to happen. Thes folks want to be able to have a resiliency plan. They want to be able to rehearse these restores right, and if they don't have a resiliency plan built in if the data protection is so siloed and does not help them build a resiliency plan. And to end that restore is not gonna be successful. Likely? Right. And that's where Veritas and companies like Veritas come in to help them build those resiliency plans and to end. >> But let me take you back to so the financial industry, for example, there are rules about how fast you you have to be able to restore. I gotta believe that visibility into data that is a value level can help set priorities. Because sometimes you want to bring up this application of this class of applications of this class of users of functions before you bring up those so does does apt are apt are going to provide even greater clarity in the crucial restore >> at 70. One of the biggest challenges for >> a lot of companies with restores is actually finding the data. We had a classic use case with a large Fortune 10 company where they had a bunch of service that were being backed up. There were bolted off the tape, and then it was obviously a different backup product they were using. The actually lost the catalog. The data was still there on tape. They had millions of tapes in the vaults, and they used apt title, identify the barcodes and recover that data literally within a matter of hours. And so not only can we find you your freshest copy the most recent copy, if that's what you want, but we can find where is your data? Because in a lot of cases there's multiple replications, multiple copies of the data across all sorts of assets within your >> infrastructure. Interesting. So last thoughts. When we have you back in the Cube in a year, Where you guys going? Big? >> Hey, listen, the two things that I talked about we're going to continue to expand the support of the ecosystem. The world of I t. Whether it's on Prem virtual or in the cloud with Apt are we? We're going to continue to invest in the artificial Intelligence and ML capabilities are not just apt are but all of that tosses ecosystem and you'll see amore integrated approach on the platform based approach on standardization When we come here >> next, guys, thank you so much. Great conversation. Thanks for being here in the Cube to talk about this important relation between data tooling and sources of business value. Rick Clark is the vice president of the outdoor business unit. Used to be the CEO of actor, but now the vice president. The outdoor business unit Veritas. Josie Stroop is vice president of marketing of Veritas. Once again, guys, thanks very much for being here. Thank you so much for having us. And once again, I'm Peter Burgers. You've been listening to another cube conversation until next time.