(tranquil music) >> Alation was an early pioneer in solving some of the most challenging problems in so-called big data. Founded early last decade, the company's metadata management and data catalog have always been considered leading examples of modern tooling by customers and analysts alike. Governance is one area that customers identified as a requirement to extend their use of Alation's platform. And it became an opportunity for the company to expand its scope and total available market. Alation is doing just that today, announcing new data governance capabilities, and partner integrations that align with the market's direction of supporting federated governance. In other words, a centralized view of policy to accommodate distributed data in this world of an ever expanding data cloud, which we talk about all the time in theCUBE. And with me to discuss these trends and this announcement is Satyen Sangani, who's the CEO and co-founder of Alation. Satyen, welcome back to the CUBE. Good to see you. >> Thank you Dave, It's great to be back. >> Okay, so you heard my open, please tell us about the patterns that you were seeing in the market and what you were hearing from customers that led you in this direction and then we'll get into the announcement. >> Yeah, so I think there are really two patterns, right? I mean, when we started building this notion of a data catalog, as you said a decade ago, there was this idea that metadata management broadly classified was something that belonged in IT, lived in IT and was essentially managed by IT, right? I always liken it to kind of an inventory management system within a warehouse relative to Amazon.com, which has obviously broadly published for the business. And so, with the idea of bringing all of this data directly to the business and allowing people arbitrarily, depending on their role to use the data. You know, you saw one trend, which was just this massive, shift in how much data was available at any given time. I think the other thing that happened was that at the same time, data governance went through a real transitionary phase where there was a lot of demand often spurred by regulations. Whether that's GDPR, CCPA or more recently than that, certainly the Basel accord. And if you think about all of those regulations, people had to get something in a place. Now what we ended up finding out was when we were selling in to add accounts, people would say, well guess what? I've got this data governance thing going on, but nobody's really using it. I built this business glossary, it's been three years. Nothing's been really very effective. And we were never able to get the value and we need to get value because there are so many more people now accessing and using and leveraging the data. And so with that, we started really considering whether or not we needed to build a formal capability in the market. And that's what we're today that we're doing. >> I liked the way you framed that. And if you think back, we were there as you were in the early big day-to-days. And all the talk was about volume, variety and velocity. And those are sort of IT concepts. How do you deal with all these technical challenges? And then the fourth V which you just mentioned was value. And that's where the line of business really comes in. So let's get into the news. What are you announcing today? >> So we're announcing a new application on top of Alation's Catalog platform, which is an Alations data governance application. That application will be released with our 2021.3 release on September 14th. And what's exciting about that is that we are going to now allow customers to discreetly and elegantly and quickly consume a new application to get data governance regimes off the ground and initiatives off the ground, much more quickly than they've ever been able to do. This app is really all about time to value. It's about allowing customers to be able to consume what they need when they need it in order to be able to get successful governance initiatives going. And so that's what we're trying to deliver. >> So maybe you could talk a little bit about how you think about data governance and specifically your data governance approach. And maybe what's different about Alation's solution. >> Yeah, I think there's a couple of things that are different. I think the first thing that's most critically different is that we move beyond this notion of sort of policy declaration into the world of policy application and policy enforcement, right? I think a lot of data governance regimes basically stand up and say, look you know, it's all about people and then process and then technology. And what we need to do is declare who all the governors are and who all the stewards are. And then we're going to get all our policies in the same place and then the business will follow them. And the reality is people don't change their workflows to go off and arbitrarily follow some data governance policy that they don't know exists, or they don't want to actually have to follow up. And so really what you've got to do is make sure that the policy and the knowledge exists as in where the data exists. And that's why it's so critical to build governance into the catalog. And so what we're doing here is we're basically saying, look, you could declare policies with a new policy center inside of Alation. Those policies will get automatically created in some cases by integrating with technologies like Snowflake. But beyond that, what we're also doing is we're saying, look, we're going to move into the world of taking those policies and applying them to the data on an automated basis using ML and AI and basically saying that now it doesn't have to be some massive boil the ocean three-year regime to get very little value in a very limited business loss rate. Rather all of your data sets, all of your terms can be put into a single place on an automated basis. That's constantly being used by people and constantly being updated by the new systems that are coming online. And that's what's exciting about it. >> So I just want to follow up on that. So if I'm hearing you correctly, it's the humans are in the loop, but it's not the only source of policy, right? The machines are assisting. And in some cases managing end-to-end that policy. Is that right? >> You've got it. I think the the biggest challenge with data governance today is that it basically relies a little bit like the Golden Gate Bridge. You know, you start painting it and by the time you're done painting it, you've got to go back and start painting it again, because it relies upon people. And there's just too much change in the weather and there's too much traffic and there's just too much going on in the world of data. And frankly in today's world, that's not even an apt analogy because often what happens is midway through. You've got to restart painting from the very beginning because everything's changed. And so there's so much change in the IT landscape that the traditional way of doing data governance just doesn't work. >> Got it, so in winning through the press release, three things kind of stood out. I wonder if we could unpack them, there were multi-cloud, governance and security. And then of course the AI or what I like to call machine intelligence in there. And what you call the people centric approach. So I wonder if we could dig in into these and help us understand how they fit together. So thinking about multi-cloud governance, how do you think about that? Why is that so challenging and how are you solving that problem? >> Yeah, well every cloud technology provider has its own set of capabilities and platforms. And often those slight differences are causing differences in how those technologies are adopted. And so some teams optimize for certain capabilities and certain infrastructure over others. And that's true even within businesses. And of course, IT teams are also trying to diversify their IT portfolios. And that's another reason to go multi-cloud. So being able to have a governance capability that spans, certainly all of the good grade called megascalers, but also these new, huge emerging platforms like Snowflake of course and others. Those are really critical capabilities that are important for our customers to be able to get a handle on top of. And so this idea of being cloud agnostic and being able to sort of have a single control plane for all of your policies, for all of your data sets, that's a critical must have in a governance regime today. So that's point number one. >> Okay and then the machine learning piece, the AI, you're obviously injecting that into the application, but maybe tell us what that means both maybe technically and from a business stand point. >> Yeah, so this idea of a data policy, right? Can be sometimes by operational teams, but basically it's a set of rules around how one should and should not be able to use data, right? And so those are great rules. It could be that people who are in one country shouldn't be able to access the data of another country, very simple role, right? But how do you actually enforce that? Like you can declare it, but if there is a end point on a server that allows you to access the data, the policy is effectively moot. And so what you got to go do is make sure that at the point of leverage or at the point of usage, people know what the policy happens to be. And that's where AI come in. You can say let's document all the data sets that happened to be domiciled in Korea or in China. And therefore make sure that those are arbitrarily segregated so that when people want to use that as datasets, they know that the policy exists and they know that it's been applied to that particular dataset. That's somewhere where AI and ML can be super valuable rather than a human being trying to document thousands of databases or tens of thousands of data sets, which is really kind of a (mumbles) exercise. And so, that application of automation is really critical and being able to do governance at the scale that most enterprises have to do it. >> You got it 'cause humans just can't do that at scale. Now what do you mean by people-centric approach? Can you explain that? >> Yeah, often what I find with governance is that there's this notion of kind of there's this heavy notion of how one should deal with the data, right? So often what I find is that there are certain folks who think, oh well, we're going to declare the rules and people are just going to follow them. And if you've ever been well, a parent or in some cases seeing government operate, you realize that that actually isn't how things work. And involve them in how things are run. And if you do that, right? You're going to get a lot more success in how you apply rules and procedures because people will understand that and people know why they exist. And so what we do within this governance regime is we basically say, look, we want to make sure that the people who are using the data, leveraging the data are also the people who are stewarding the data. There shouldn't be a separate role of data steward that is arbitrarily defined off, just because you've been assigned to a job that you never wanted to do. Rather it should be a part of your day job. And it should be something that you do because you really want to do it. And it's a part of your workflow. And so this idea of being people centric is all about how do you engage the analyst, the product managers, the sales operation managers, to document those sales data sets and those product data sets. So that in fact, those people can be the ones who are answering the questions, not somebody off to the side who knows nothing about the data. >> Yeah, I think you've talked in previous CUBE interviews about context and that really fits to this discussion. So these capabilities are part of an application, which is what? it's a module onto your existing platform. And it's sort of it's a single platform, right? I mean, we're not bespoke products. Maybe you can talk about that. >> Yeah, that's exactly right. I mean, it's funny because we've evolved and built a relation with a lot of capability. I mean, interestingly we're launching this data governance application but I would say 60% of our almost 300 customers would say they do a form or a significant part of data governance, leveraging relations. So it's not like we're new to this market. We've been selling in this market for years. What's different though, is that we've talked a lot about the catalog as a platform over the last year. And we think that that's a really important concept because what is a platform? It's a capability that has multiple applications built on top of it, definitionally. And it's also a capability where third party developers can leverage APIs and SDKs to build applications. And thirdly, it has all of the requisite capabilities and content. So that those application developers, whether it's first party from Alation or third party can really build those applications efficiently, elegantly and economically well. And the catalog is a natural platform because it contains all of the knowledge of the datasets. And it has all of the people who might be leveraging data in some fundamental way. And so this idea of building this data governance module allows a very specialized audience of people in governance to be able to leverage the full capabilities of the platform, to be able to do their work faster, easier, much more simply and easily than they ever could have. And that's why we're so excited about this launch, because we think it's one example of many applications, whether it's ourselves building it or third parties that could be done so much more elegantly than it previously could have been. Because we have so much knowledge of the data and so much knowledge of how the company operates. >> Irrespective of the underlying cloud platform is what I heard before. >> irrespective of the underlying cloud platform, because the data as you know, lives everywhere. It's going to live in AWS, it's going to live in Snowflake. It's going to live on-premise inside of an Oracle database. That's not going to be changed. It's going to live in Teradata. It's going to live all over the place. And as a consequence of that, we've got to be able to connect to everything and we've got to be able to know everything. >> Okay, so that leads me to another big part of the announcement, which is the partnership and integration with Snowflake. Talk about how that came about. I mean, why snowflake? How should customers think about the future of data management. In the context of this relationship, obviously Snowflake talks about the data cloud. I want to understand that better and where you fit. >> Yeah, so interestingly, this partnership like most great partnerships was born in the field. We at the late part of last year had observed with Snowflake that we were in scores of their biggest accounts. And we found that when you found a really, really large Snowflake engagement, often you were going to be complementing that with a reasonable engagement with Alation. And so seeing that pattern as we were going out and raising our funding route at the beginning of this year, we basically found that Snowflake obviously with their Snowflake Ventures Investment arm realized how strategic having a great answer in the governance market happened to be. Now there are other use cases that we do with Snowflake. We can certainly get into those. But what we realized was that if you had a huge scale, Snowflake engagement, governance was a rate limiter to customers' ability to grow faster. And therefore also Snowflake's ability to grow faster within that account. And so we worked with them to not only develop a partnership but much more critically a roadmap that was really robust. And so we're now starting to deliver on that roadmap and are super excited to share a lot of those capabilities in this release. And so that means that we're automatically ingesting policies and controls from Snowflake into Alation, giving full transparency into both setting and also modifying and understanding those policies for anybody. And so that gives you another control plane through which to be able to manage all of the data inside of your enterprise, irrespective of how many instances of Snowflake you have and irrespective of how many controls you have available to you. >> And again, on which cloud runs on. So I want to follow up with that really interesting because Snowflake's promise of the data cloud, is it essentially abstracts the underlying complexity of the cloud. And I'm trying to understand, okay, how much of this is vision, how much is is real? And it's fine to have a Northstar, but sometimes you get lost in the marketing. And then the other part of the promise, and of course, big value proposition is data sharing. I mean, I think they've nailed that use case, but the challenge when you start sharing data is federated governance. And as well, I think you mentioned Oracle, Teradata that stuff's not all in the cloud, a lot of that stuff on-prem and you guys can deal with that as well. So help us sort of to those circles, if you can. Where do you fit into that equation? >> I think, so look, Snowflake is a magical technology and in the sense that if you look at the data, I mean, it reveals a very, very clear story of the ability to adopt Snowflake very quickly. So any data team with an organization can get up and running with the Snowflake instance with extraordinary speed and capability. Now that means that you could have scores, hundreds of instances of Snowflake within a single institution. And to the extent that you want to be able to govern that data to your point, you've got to have a single control plane through which you can manage all of those various instances. Whether they're combined or merged or completely federated and distinct from each other. Now, the other problem that comes up on governance is also discoverability. If you have all these instances, how do you know what the right hand is doing if the left hand is working independently of it? You need some way to be able to coordinate that effort. And so that idea of discoverability and governance is really the value proposition that Alation brings to the table. And the idea there is that people can then can get up and running much more quickly because, hey, what if I want to spin up a Snowflake instance, but there's somebody else, two teams over those already solved the problem or has the data that I need? Well, then maybe I don't even need to do that anymore. Or maybe I can build on top of that work to be able to get to even better outcome even faster. And so that's the sort of kind of one plus one equals three equation that we're trying to build with them. >> So that makes sense and that leads me to one of my favorite topics with the notion is this burgeoning movement around the concept of a data mesh in it. In other words, the notion that increasingly organizations are going to push to decentralize their data architectures and at the same time support a centralized policy. What do you think about this trend? How do you see Alation fitting in? >> Yeah, maybe in a different CUBE conversation. We can talk a little bit about my sort of stylized history of data, but I've got this basic theory that like everybody started out what sort of this idea of a single source of truth. That was a great term back in the 90s where people were like, look, we just need to build a single source of truth and we can take all of our data and physically land it up in a single place. And when we do that, it's going to all be clean, available and perfect. And we'll get back to the garden of Eden, right? And I think that idea has always been sort of this elusive thing that nobody's ever been able to really accomplish, right? Because in any data environment, what you're going to find is that if people use data, they create more data, right? And so in that world, you know, like that notion of centralization is always going to be fighting this idea of data sprawl. And so this concept of data mesh I think is, you know, there's formal technical definitions. But I'll stick with maybe a very informal one, which is the one that you offered. Which is just sort of this decentralized mode of architecture. You can't have decentralization if nobody knows how to access those different data points, 'cause otherwise they'll just have copies and sprawl and rework. And so you need a catalog and you need centralized policies so that people know what's available to them. And people have some way of being able to get conformed data. Like if you've got data spread out all over the place, how do you know which is the right master? How do you know what's the right customer record? How do you know what's your right chart of accounts? You've got to have services that exist in order to be able to find that stuff and to be able to leverage them consistently. And so, to me the data mesh is really a continuation of this idea, which the catalog really enabled. Which is if you can build a single source of reference, not a single source of truth, but a single place where people can find and discover the data, then you can govern a single plane and you can build consistent architectural rules so that different services can exist in a decentralized way without having to sort of bear all the costs of centralization. And I think that's a super exciting trend 'cause it gives power back to people who want to use the data more quickly and efficiently. >> And I think as we were talking about before, it's not about just the IT technical aspects, hey, it works. It's about putting power in the hands of the lines of business. And a big part of the data mesh conversation is around building data products and putting context or putting data in the hands of the people who have the context. And so it seems to me that Alation, okay, so you could have a catalog that is of the line of businesses catalog, but then there's an Uber catalog that sort of rolls up. So you've got full visibility. It seems that you've fit perfectly into that data mesh. And whether it's a data hub, a data warehouse, data lake, I mean, you don't care. I mean, that's just another node that you can help manage. >> That's exactly right. I mean, it's funny because we all look at these market scapes where people see these vendor landscapes of 500 or 800 different data and AI and ML and data architecture vendors. And often I get asked, well, why doesn't somebody come along and like consolidate all this stuff? And the reality is that tools are a reflection of how people think. And when people have different problems and different sets of experiences, they're going to want to use the best tool in order to be able to solve their problem. And so the nice thing about having a mesh architecture is you can use whatever tool you want. You just have to expose your data in a consistent way. And if you have a catalog, you can be able to have different teams using different infrastructure, different tools, different fundamental methods of building the software. But as long as they're exposing it in a consistent way, it doesn't matter. You don't necessarily need to care how it's built. You just need to know that you've got good data available to you. And that's exactly what a catalog does. >> Well, at least your catalog. I think the data mesh, it should be tools that are agnostic. And I think there are certain tools that are, I think you guys started with that principle. Not every data catalog is going to enable that, but I think that is the trend Satyen. And I think you guys have always fit into that. It's just that I think you were ahead of the time. Hey, we'll give you the last word. Give us the closing thoughts and bring us home. >> Well, I mean that's exactly right. Like, not all the catalogs are created equal and certainly not all governance is created equal. And I think most people say these words and think that are simple to get into. And then it's a death by a thousand cuts. I was literally on the phone with a chief data officer yesterday of a major distributor. And they basically said, look, like we've got sprawl everywhere. We've got data everywhere. We've got it in every type of system. And so having that sophistication turned into something that's actually easy to use is a super hard problem. And it's the one that we're focused on every single day that we wake up and every single night when we go to sleep. And so, that's kind of what we do. And we're here to make governance easy, to make data discovery easy. Those are the things that we hold our hats on. And we're super excited to put this release out 'cause we think it's going to make customers so much more capable of building on top of the problems that they've already solved. And that's what we're here to do. >> Good stuff, Satyen. Thanks so much, congratulations on the announcement and great to see you again. >> You too, Dave. Great talking. >> All right, thanks for watching this CUBE conversation. This is Dave Vellante, we'll see you next time. (tranquil music)

>> (upbeat music) >> Announcer: From around the globe, it's theCUBE with digital coverage of AWS Public Sector Partner Awards Brought to you by Amazon Web Services. >> Hi, and welcome back. I'm Stu Miniman and this is theCUBE's coverage of Amazon Web Services, Public Sector Awards for their partners. Really interesting, we get to talk to people around the globe, we talked to the vendors, the award winners as well as their customers who have some interesting projects. So happy to welcome to the program coming to us from Argentina. I have Leo Bracco. He is the Latin American Executive Director for CloudHesive and joining him, his customer Carolina Tchintian. She is the Director of the Political Institution Program at CIPPEC. Thank you so much for joining us. >> Thank you. >> Thank you for having us. >> All right, so Leo, first of all, let's start with you if we could. So CloudHesive first of all, congratulations, you were the Nonprofit Sector award winner for cybersecurity solutions. Of course, anybody that knows public sector, there's the government agencies, there's nonprofits there's education. The cybersecurity of course, went from the top priority to the top, top priority here in 2020. So if you could just give us a snapshot of CloudHesive for our customer. >> Well, CloudHesive is a US based company, started six years ago in 2014. And we decide a couple of years ago to move to Latin America and to start working with Latin America customers. Our offices are in Argentina right now. And one of the focus that we have in the solutions that we give to our customers is security. We work on services to help companies to reduce the cost, increase productivity, and what should the security posture? So we've been working a long time ago to many NPOs, and seeing how they can leverage the solutions and how they can give secure, how to be secure in the world. In the internet. >> All right, Carolina, if you could tell us a little bit about the CIPPEC and maybe then key us up as the project that you're working on. >> Okay, thank you. So CIPPEC is a nonprofit think tank, nonprofit organization, independent organization that aims to deliver better public policies in different areas. In economic development, in social protection and state and government. My particular program, the political institutions program goal is, or the mission is basically to promote evidence based decisions to improve democratic processes and to guarantee civil and political rights across all the countries. So we on issues such as improving election administrations, legislative work, representation, and that's our area of work. >> Wonderful. Sounds like a phenomenal project. Leo, if you could help us understand where did CloudHesive get involved in this project? Was there an existing relationship already, or was it for a specific rollout? that tell us about, obviously the security angles are a big piece? >> No, we didn't have a previous engagement with them. They come to us with a very short time to elections and they need a secure solution. So we first have to analyze the actual solution, how it works, acknowledging well the current infra that they have. Then we have to understand the challenge that they're facing. They have a very public site, they need to go public and they need to be very secure. And the last, we have to develop a fast migration strategy. We knew that AWS was the perfect fit for the need. So we just had to align a good strategy with the customer need. And all these it has been done in less than 72 hours. That was our deadline to elections. >> Wow, talk about fast. Okay, Carolina, help us understand a little bit. Had your organization, had you been using a Cloud before? Seventy-two hours is definitely an aggressive timeline. So help us understand a little bit as to what went into making your decision and obviously, 72 hours super short timeframe. >> Super, super short. Yeah, that was a big challenge. So let me tell you more about what we do and the context. So Argentina holds elections, national elections every two years. In each election year CIPPEC tries to generate and systematize analysis of provincial and national elections with the goal of informing key actors in the electoral processes. This is and decision makers, political parties, media, and general population. So as our first experience in 2017, with informed voter project, we had this collaboration with the National Electoral Authorities in which we created a landing page in our website where you could find as the voter, all of the information you need to go and cast your vote throughout the entire election process. Meaning from the campaign stage, election administration details, polling places, electoral offer, participation et cetera. So that was a landing page hosted in our website. And in 2017, we managed to have a button in every eligible voter in Argentina Facebook feed. So you could go click there and go to our website, right. And have all of the information summarize in a very simple way, straightforward way. So what happened in the 2017 election day is that the button was so successful that the landing page made our server to collapse in the first hours of the election day. So we learned a huge lesson there, which was that we had to be prepared in 2019, if we wanted to repeat this experience. And that is how we get to CloudHesive. >> Wonderful, Leo, if you could, help us understand a little bit architecturally what's going on there, what was CoHesive doing, what AWS services were leveraged? >> Perfect. Well we need great reliability, performance, scalability of course and the main thing security. We have no doubt about the Cloud and all the differentials of AWS. Our main question was about how do we align the right services to give the best solution to the customer? So we did kind of strategy with S3, CloudFront, and we, at the same time being monitorizing everything with CloudTrail and securing the public's access to all of these information. That give us a perfect fit for the solution, a very easy solution and very of course scalable, but more than anything, we could improve the customer experience in very small amount of time. So this is a very simple solution, that fits perfect for the customer. >> Wonderful. Carolina, if you could, tell us how did things go? What lessons have you learned? Anything along the way that you would give feedback to your peers or other organizations that were looking to do something similar? >> Yeah, well, the 2017 experience was a very tough experience for us because we've been preparing for election day during the 2016 and 2017. And the infrastructure was the limit we had in that point. So we couldn't afford ... We have a commitment with informing voters and informing key actors on election process. And these key actors are expecting that information on election day, before, and after. The lesson there is, we cannot be limited by the infrastructure. Assuming that in 2019, that the landing page would receive a similar amount or a huge amount of traffic volume visits on the election day, basically, we knew that traditional hosting service couldn't fulfill those needs so we had to go beyond traditional and the partner was critical to help us to the migration, to the Cloud. >> Yeah, Leo, maybe you could speak a little bit to that, the scalability, and of course, nonprofit's very sensitive to costs involved in these solutions. Help us understand that those underpinnings of leveraging, AWS specifically in CloudHesive. How this meets their needs and still is financially, makes sense. >> Perfect. When you have this kind of solutions, of course, your first concern is, okay, how do I make a scalable solution that fits on the, just on this moment that they need the behavior for so many infrastructure involved. And then at the other day, they need no infra at all, but you have another two big things that you have to focus on. One, is the security, you need to monitor all the behaviors of the content and pay attention to any external menace. You have one 24-hour day, so you need to be very responsibility and high sensitive information that the customer has on the set of data there. It's good to say that we have no security incidents, and no security breach during the most public stage of the operation, so that there was very good for us. The next thing is from the delivery perspective. You have a potential pick of people over the side to usually manage the content delivery network to answer all the requirements. You must be able to share the content in CloudFront, and so you have, and you can achieve your goals, right? And what I can say, it's about numbers, we achieve more than 99.5 efficiency hit rate you over the CDN, that's over CloudFront. And we kept server CPU such below 10% all the time. So this was a major success for us. Like we have no trouble, we use things at the most. And most of anything, the customer has the security, everything look from our perspective. (mumbles) >> Leo, what follow up if I could, if you look at 2020 being able to scale and respond to the changes in workload and be able to stay secure when bad actors, many people are working at home, but doesn't mean the bad actors aren't out there. We've actually seen an increase in security attacks. So just, do you have any commentary overall about what's happening more recently in what you see in your space? >> Yeah, well, we're very focused right now and while security is being each time bigger, right? One of the biggest menace in security is our own team, because we have to keep our teams auto align to the process and understanding the security as a first step doing things from the network perspective. Then we have a very good experience over this last two years, with all the security tools that AWS is seeking to the market. So we now have CloudTrail. We can do many things with WAF we're working towers of new good security solutions. And so I think this will be the future. We have to focus ourself in these two pillars. The first pillar is, okay, what we can do on our own network and the other pillar's, all the tools that AWS is giving us so we can manage security from a new perspective. >> Carolina, last question that I have for you is, look forward a little bit, if you will, are there things that you'll be looking to do in future election cycles or anything else from this project that you could expect going forward? >> Yeah, definitely. We're going to repeat this experience in 2021. Trying to think of the success was the 2019 election cycle. And in this particular informed voter project, we might want to keep doing this for the next election cycles, not only 2023 now, but for the future. >> All right then, Leo, last piece for you, first of all, congratulations, again, winning Best Cyber Security Solution for Nonprofit. Just talk a little bit if you would, about your partnership with AWS and specifically, the requirements and what you see in the nonprofit segment. >> Well, we see that the nonprofit are growing large too, they will need very good scalable solutions. We see that all the focus that we have in on security is the next need because we have been working on these towers to the future. The solutions kept growing each time. The networks are growing each time. And the traffic is growing. The focus on the security will be one of the appendix of our work in the future. And I think that's the biggest issue that we are going to have. Having good engineers, good hard work and manage the challenge and consolidate all the solution as a need. Right now, we're working on many projects with different NGO's and we're working towers that they have the solution that fits them. And of course, we try to keep, in all the public sector, we try to keep the cost at a range level that we can afford that our customers can afford. That's I think, a big problem that we're having. >> Well, Carolina, congratulations on the progress with your project. Thank you so much for joining us. And Leo, thank you again for joining us and congratulations to you and the CloudHesive team for winning the award. >> Thanks. >> Thank you very much. >> All right, stay tuned for more coverage, theCUBE, at the AWS Public Sector Partner Awards. I'm Stu Miniman. Thanks for watching. (upbeat music)

(upbeat music) >> Announcer: From theCUBE studios in Palo Alto, in Boston, connecting with thought leaders all around the world. This is a CUBE conversation. >> Hi, and welcome back. I'm Stu Miniman and this is theCUBE's coverage of Amazon Web Services, Public Sector Awards for their partners. Really interesting, we get to talk to people around the globe, we talked to the vendors, the award winners as well as their customers who have some interesting projects. So happy to welcome to the program coming to us from Argentina. I have Leo Bracco. He is the Latin American Executive Director for CloudHesive and joining him, his customer Carolina Tchintian. She is the Director of the Political Institution Program at CIPPEC. Thank you so much for joining us. >> Thank you. >> Thank you for having us. >> All right, so Leo, first of all, let's start with you if we could. So CloudHesive first of all, congratulations, you were the Nonprofit Sector award winner for cybersecurity solutions. Of course, anybody that knows public sector, there's the government agencies, there's nonprofits there's education. The cybersecurity of course, went from the top priority to the top, top priority here in 2020. So if you could just give us a snapshot of CloudHesive for our customer. >> Well, CloudHesive is a US based company, started six years ago in 2014. And we decide a couple of years ago to move to Latin America and to start working with Latin America customers. Our offices are in Argentina right now. And one of the focus that we have in the solutions that we give to our customers is security. We work on services to help companies to reduce the cost, increase productivity, and what should the security posture? So we've been working a long time ago to many NPOs, and seeing how they can leverage the solutions and how they can give secure, how to be secure in the world. In the internet. >> All right, Carolina, if you could tell us a little bit about the CIPPEC and maybe then key us up as the project that you're working on. >> Okay, thank you. So CIPPEC is a nonprofit think tank, nonprofit organization, independent organization that aims to deliver better public policies in different areas. In economic development, in social protection and state and government. My particular program, the political institutions program goal is, or the mission is basically to promote evidence based decisions to improve democratic processes and to guarantee civil and political rights across all the countries. So we on issues such as improving election administrations, legislative work, representation, and that's our area of work. >> Wonderful. Sounds like a phenomenal project. Leo, if you could help us understand where did CloudHesive get involved in this project? Was there an existing relationship already, or was it for a specific rollout? that tell us about, obviously the security angles are a big piece? >> No, we didn't have a previous engagement with them. They come to us with a very short time to elections and they need a secure solution. So we first have to analyze the actual solution, how it works, acknowledging well the current infra that they have. Then we have to understand the challenge that they're facing. They have a very public site, they need to go public and they need to be very secure. And the last, we have to develop a fast migration strategy. We knew that AWS was the perfect fit for the need. So we just had to align a good strategy with the customer need. And all these it has been done in less than 72 hours. That was our deadline to elections. >> Wow, talk about fast. Okay, Carolina, help us understand a little bit. Had your organization, had you been using a Cloud before? Seventy-two hours is definitely an aggressive timeline. So help us understand a little bit as to what went into making your decision and obviously, 72 hours super short timeframe. >> Super, super short. Yeah, that was a big challenge. So let me tell you more about what we do and the context. So Argentina holds elections, national elections every two years. In each election year CIPPEC tries to generate and systematize analysis of provincial and national elections with the goal of informing key actors in the electoral processes. This is and decision makers, political parties, media, and general population. So as our first experience in 2017, with informed voter project, we had this collaboration with the National Electoral Authorities in which we created a landing page in our website where you could find as the voter, all of the information you need to go and cast your vote throughout the entire election process. Meaning from the campaign stage, election administration details, polling places, electoral offer, participation et cetera. So that was a landing page hosted in our website. And in 2017, we managed to have a button in every eligible voter in Argentina Facebook feed. So you could go click there and go to our website, right. And have all of the information summarize in a very simple way, straightforward way. So what happened in the 2017 election day is that the button was so successful that the landing page made our server to collapse in the first hours of the election day. So we learned a huge lesson there, which was that we had to be prepared in 2019, if we wanted to repeat this experience. And that is how we get to CloudHesive. >> Wonderful, Leo, if you could, help us understand a little bit architecturally what's going on there, what was CoHesive doing, what AWS services were leveraged? >> Perfect. Well we need great reliability, performance, scalability of course and the main thing security. We have no doubt about the Cloud and all the differentials of AWS. Our main question was about how do we align the right services to give the best solution to the customer? So we did kind of strategy with S3, CloudFront, and we, at the same time being monitorizing everything with CloudTrail and securing the public's access to all of these information. That give us a perfect fit for the solution, a very easy solution and very of course scalable, but more than anything, we could improve the customer experience in very small amount of time. So this is a very simple solution, that fits perfect for the customer. >> Wonderful. Carolina, if you could, tell us how did things go? What lessons have you learned? Anything along the way that you would give feedback to your peers or other organizations that were looking to do something similar? >> Yeah, well, the 2017 experience was a very tough experience for us because we've been preparing for election day during the 2016 and 2017. And the infrastructure was the limit we had in that point. So we couldn't afford ... We have a commitment with informing voters and informing key actors on election process. And these key actors are expecting that information on election day, before, and after. The lesson there is, we cannot be limited by the infrastructure. Assuming that in 2019, that the landing page would receive a similar amount or a huge amount of traffic volume visits on the election day, basically, we knew that traditional hosting service couldn't fulfill those needs so we had to go beyond traditional and the partner was critical to help us to the migration, to the Cloud. >> Yeah, Leo, maybe you could speak a little bit to that, the scalability, and of course, nonprofit's very sensitive to costs involved in these solutions. Help us understand that those underpinnings of leveraging, AWS specifically in CloudHesive. How this meets their needs and still is financially, makes sense. >> Perfect. When you have this kind of solutions, of course, your first concern is, okay, how do I make a scalable solution that fits on the, just on this moment that they need the behavior for so many infrastructure involved. And then at the other day, they need no infra at all, but you have another two big things that you have to focus on. One, is the security, you need to monitor all the behaviors of the content and pay attention to any external menace. You have one 24-hour day, so you need to be very responsibility and high sensitive information that the customer has on the set of data there. It's good to say that we have no security incidents, and no security breach during the most public stage of the operation, so that there was very good for us. The next thing is from the delivery perspective. You have a potential pick of people over the side to usually manage the content delivery network to answer all the requirements. You must be able to share the content in CloudFront, and so you have, and you can achieve your goals, right? And what I can say, it's about numbers, we achieve more than 99.5 efficiency hit rate you over the CDN, that's over CloudFront. And we kept server CPU such below 10% all the time. So this was a major success for us. Like we have no trouble, we use things at the most. And most of anything, the customer has the security, everything look from our perspective. (mumbles) >> Leo, what follow up if I could, if you look at 2020 being able to scale and respond to the changes in workload and be able to stay secure when bad actors, many people are working at home, but doesn't mean the bad actors aren't out there. We've actually seen an increase in security attacks. So just, do you have any commentary overall about what's happening more recently in what you see in your space? >> Yeah, well, we're very focused right now and while security is being each time bigger, right? One of the biggest menace in security is our own team, because we have to keep our teams auto align to the process and understanding the security as a first step doing things from the network perspective. Then we have a very good experience over this last two years, with all the security tools that AWS is seeking to the market. So we now have CloudTrail. We can do many things with WAF we're working towers of new good security solutions. And so I think this will be the future. We have to focus ourself in these two pillars. The first pillar is, okay, what we can do on our own network and the other pillar's, all the tools that AWS is giving us so we can manage security from a new perspective. >> Carolina, last question that I have for you is, look forward a little bit, if you will, are there things that you'll be looking to do in future election cycles or anything else from this project that you could expect going forward? >> Yeah, definitely. We're going to repeat this experience in 2021. Trying to think of the success was the 2019 election cycle. And in this particular informed voter project, we might want to keep doing this for the next election cycles, not only 2023 now, but for the future. >> All right then, Leo, last piece for you, first of all, congratulations, again, winning Best Cyber Security Solution for Nonprofit. Just talk a little bit if you would, about your partnership with AWS and specifically, the requirements and what you see in the nonprofit segment. >> Well, we see that the nonprofit are growing large too, they will need very good scalable solutions. We see that all the focus that we have in on security is the next need because we have been working on these towers to the future. The solutions kept growing each time. The networks are growing each time. And the traffic is growing. The focus on the security will be one of the appendix of our work in the future. And I think that's the biggest issue that we are going to have. Having good engineers, good hard work and manage the challenge and consolidate all the solution as a need. Right now, we're working on many projects with different NGO's and we're working towers that they have the solution that fits them. And of course, we try to keep, in all the public sector, we try to keep the cost at a range level that we can afford that our customers can afford. That's I think, a big problem that we're having. >> Well, Carolina, congratulations on the progress with your project. Thank you so much for joining us. And Leo, thank you again for joining us and congratulations to you and the CloudHesive team for winning the award. >> Thanks. >> Thank you very much. >> All right, stay tuned for more coverage, theCUBE, at the AWS Public Sector Partner Awards. I'm Stu Miniman. Thanks for watching. (upbeat music)

(upbeat music) >> Announcer: From New York, it's theCUBE. Covering ESCAPE/19. >> Everyone, welcome to theCUBE coverage here in New York City for the ESCAPE Conference 19. This is the inaugural event for multicloud, I think it's the first industry event for, really talking about multicloud and the impact to enterprises and public cloud. My next guest is Steve Mullaney, President and CEO of Aviatrix, storied career in tech, been there done that, seen many waves of innovation. Nicira, Palo Alto Networks, and now Aviatrix. You retired for a while, welcome back! >> I did, yeah, five years, yeah, yeah, yeah. >> Welcome to theCUBE. >> Thank you, thanks for having me. >> It's nice to have you on because I think you have a good perspective on the multicloud because you've been in the industry since the 80s. We've both been broke in at the same time. And we've seen the waves. >> Oh, yeah. >> This wave is bigger than, I think, most of the other waves combined because it brings together so many things, infrastructure, software, cloud scale, and a new modern application environment. And then you complicate everything by throwing IoT out there, edges being pushed to their boundaries, securities equations changed, all this is going on right now, all at the same time. >> No, and that's why I was basically retired for five years, and I was at Nicira, we got bought by VMware, I stayed there for a couple years, and I just said, "Okay, that's it!" I've had a good career and I'm done. And about a year ago, the world changed. And it felt like on a Tuesday morning, I noticed enterprises really, we'd been talking about cloud for 12 years. And five years ago they said, "We're coming in, we're going to do it," but they didn't really mean it. But about a year ago, all in the same day, every enterprise said, "No, now we actually mean it." And I don't know why, I don't know if it was just people retired or just five years of talking about it, they all decided, we're comin' in, and enterprises all moved together. And this wave, as you said, is bigger than, I was around in 1992, in the early 90s, in the movement from mainframe to client server. This is 10 times bigger than that. And more importantly, it's going to happen 10,000 times faster. Because (fingers tapping). What's that? I just deployed 62 data centers around the world. Because if I can leverage the greatest infrastructure built, basic infrastructure of the hyperscalers, AWS, Azure, Google, Alibaba, Oracle, you name it. It's unbelievable the velocity at which you can now start deploying. >> Steve, I think you're onto something big here, and this is why I'm here at this event and why I'm excited, that a lot of the industry thought leaders and practitioners and leaders are doing this event. Small events, inaugural, but I think it has a lot of links. Because there's a lot of tell signs that I like to look at, one is cloud. I've been covering Amazon eight years now, with theCUBE, I've known AWS since it started, and I've done many startups in its launch using AWS. But I've had many conversations with Andy Jassy, one on ones, privately, I got an exclusive coming up for re:Invent with him. I've gotten to know him. It started out, "Everyone's moving to the cloud. "Every data center's not going to exist." And then, you know-- >> Oh, maybe not, yeah, yeah. >> Maybe not, we'll do an output. So I challenged him last year, I said, "Andy, come on, dude, like you were saying like a year ago that." >> Steve: Yeah, it's all AWS or nothing. >> And he said, "John, look I'm not, "I just listen to the customers." And I interviewed him when he did the VMware deal. And he's very customer focused. And when they make these moves with outpost, and I think it's going to be a hybrid message this year at re:Invent, you know it's real. >> Steve: Oh, yeah. >> I think this validates your point, so I got to ask you, what specifically do you see the formula being for multicloud, because certainly everyone's recognized that there's a huge benefit for AWS. But from a scale standpoint, so why not use that? What's going on on the Enterprise on-premise that's making this new thing work? >> I think it all starts with architecture, like anything else. I think right now, enterprises have said, "Okay, we've burned a boat, right? "Now, we're not going to get rid of our data centers, "but in terms of our strategic investment, "we are moving into the cloud. "We are going to leverage "the infrastructure of the hyperscalers. "And whether that is just one hyperscaler, or multiple." And I have not met an enterprise who thinks there only going to be one, right, every single one of them. Now, I don't think they're moving workloads across, I don't think that. I think they see that, I'm going to use Google for AI, I'm going to use AWS because it started there. I'm going to use Azure, for Office 365, and other different things, and everything in infrastructure is always multi. It's never homogeneous, right, it's always that. So I think is going to happen, and I think what people are begging for right now, is, I want to build an architecture that gives me the optionality to be able to deliver a common set of services whether I'm on AWS or multiple clouds. And I want them to be my services and I don't want to have understand the low level abstractions and constructs of each of those clouds, because their all different. One's metric, one's U.S., one's some other weird thing. And I don't have the time, the people, or the resources to be able to do that. Give me a common set of services, that are my services, that I can deploy and abstract away the details of those public clouds. >> Yeah, it's an interesting point there, in fact, I called BS on multicloud last year when it started to kind of rear it's head, I'm like, "Come on, multicloud is bullshit." And I said that on theCUBE. And here's what I meant. Multicloud as an operating model is directionally correct, but the architecture hasn't shown where there's true multicloud. Now, the fact of the matter is, people have Amazon, people have Office and Office 365, that's technically two clouds, >> They're siloed, yeah. >> If they give us Google, that's three clouds. >> I use two or three clouds. >> So, if he have three clouds, I guess they have multiple clouds. But you bring up an interesting point, and going back as a student of the history of tech industry, multi-vendor has been a big deal. >> It is a big deal. >> And like you said, there will be a multi-vendor world, that will happen. The question is how. How do you guys see it happening? >> Well I think what's-- >> Your company is attacking this Aviatrix. >> What's interesting is, so now you think about from a customer perspective which, I do the same thing, same thing with AWS. It's always outside in. Okay, I'm thinking as a enterprise IT person. I'm making the move. Do you believe that your basic infrastructure will lever the hyperscalers, or will you build an on-prem? Everyone says, "I believe that's the way I'm going to go." Great, how do I do that? So, I'm a IT architect, who do I go to to help me? Do I go to CISCO? No. The most shocking thing for me, of the six months I've been at Aviatrix, is that word's never used. It's like it was DEC or IBM in the conversation, when you were talking about client-server, no, why would you? CISCO, Juniper, Arista, any of the networking people, not even in the conversation. VMware, not really in the conversation. So, I don't have any incumbent vendor that I can go to that I used to go to. >> Why aren't they in the conversation? 'Cause of the commodity, they've been extracted away? >> I think it's just because it's the innovation of dilemma. Right, once you're selling a lot of stuff into on-prem, to then go and say, I mean you look at Palo Alto Networks, they're trying to make that transition. Acquiring a bunch of companies, VMware acquiring a bunch of companies. Why are they doing that? Because they know, I got to get off on-prem, everything's going in the cloud. >> So it's a legacy. >> It's a legacy thing, and I think what happens is, there is only one reason, and one reason only, an enterprise customer is not using Aviatrix. 'Cause they never heard of us. That's why, that's the only reason. Once they hear about what they're doing, my God. >> Well, give the plug, talk about the company, what do you guys do-- >> So we deliver, I mean it sounds like I made it up for this conference, but actually this conference was perfect for this. It's networking and security services for the multicloud enterprise. And we're building an architecture, that people can deploy, that will give them this common architecture across all the different clouds. So whether you're just using one cloud or multiple, it doesn't matter, it's the same set of security and networking services. And we do that by embracing and extending the basic constructs that AWS, Google, Azure, and Oracle, and all the other clouds will give you, and to deliver that real enterprise class. Because the other thing we've found is, everyone thinks that the cloud gives you everything and anything you will ever need from networking and security. Let's say AWS, they're going to do everything I need. What the enterprises are figuring out, is once they start going in, what they realize is, it's created for the low-level common basic constructs. And the enterprise starts at, well, I need these BGP feature because guess what, the data center is not going away. And I need more than a hundred route limitations, and I need, all of a sudden there's fifty different limitations AWS will give me. Well, they didn't talk about that! Well, of course they're not going to talk about that. They are just going to go check, check, check, we solve all your problems. As enterprises now move in, with mission critical applications, they're realizing, I need the same level of networking and security services that I had on-prem. I can't get that with the native constructs. So where do I go? That's what we do, so we fill in, we embrace what we can of those constructs, we fill in holes where there are fill in holes. And then we give you the mechanism to be able to orchestrate that across the global network. >> So you operationalize the hyperscale clouds for enterprise, >> Yes. >> that's basically what you do. >> Steve: Exactly, for the enterprise. >> Yeah, exactly. >> On the level that they need. >> So you get the benefits of the cloud, but all those nuances under the cover details like networking and other features you abstract that away and provide an operating model for enterprise compliments. >> And the beautiful thing about it is the velocity, at which we can, we're over the top, effectively over the top. We're integrated into the Cloud Suite, understand what cloud native, we understand all the constructs of accounts, and all the things we need to do. But what we expose to the customer, to the enterprise, is a set of over-the-top services that just work. >> Okay Steve, so I got to ask you, since we are at The Multi-Cloud Conference. What is multicloud, I mean how do you define it, you laid out a pretty compelling architecture of what needs are, levers in the cloud, and on-prem is what Aviatrix does. But what is the definition, how should people understand what is multicloud? >> I think for us, for networking and security in that base, so we're basic infrastructure. We get out there first, right? So, if you're going to build a city, you don't start putting people there first the first thing, if you do it right, is you get sewers, you get electricity, gas, roads, all that. Networking and security, infrastructure, is basic infrastructure goes out first. And you want to create an architecture that's going to live with you for twenty years. You don't want to have to rip up the roads and put the sewers in later. And that architecture needs to be multicloud because, even though you think maybe, most of our customers are 90% AWS right now. But every single one of them say, "But I'm moving to Azure, I'm moving to Google, "I've got retail customers that won't allow me "to put my infrastructure on AWS." Or, "I have machine learning, AI type apps on Google." They all say that same thing. But what they all then say to us, is, "You're going to be the mechanism "upon which I'm going to be able to deploy "this common set of services." So they don't need to know that. >> All right, give an example of a customer you guys have, name a name, we had a customer on stage here-- >> Steve: So, Jefferies. >> John: They did this for a use case. >> Yeah so, Jefferies. Financial Services Institution, lots of requirements, Mark Leon Soon is going to be on stage with me tomorrow. We started working with them about nine months ago. Exactly the same thing, they said, "Okay, you know what? "We need to start moving to the cloud, "we've got to start leveraging the cloud. "But, it's too complicated, right? "Even AWS, says 'Go Build.' "I don't want to go build, I want to consume services. "But they don't have all the service that I needed, "they're too low a level. "They're very high function, high enterprise requirements." So they start using us to orchestrate things, to provide transit networking, to provide egress filtering out to the Internet, we have high performance encryption, AWS will only offer it one gig. We can offer it to 10, 20, 30, 40 gig. So they start deploying, they start realizing all the things we do. Then they go and say, "I want to bring my Palo Alto Networks firewall "into the cloud." When you start looking at that, 'cause then guess what? All my policies, I want the same level that I have on-prem when I'm in the cloud. If I go try to bring in my VM series into AWS the construct that AWS give you, they cause you limitations in performance, in visibility, It's integration hassles, there's performance, sustainability, visibility issues, they force you to use SNAT. And there's all these issues, and they go, "Oh my God, this is a pain in the ass." We solved all that for them. We basically cloudify the VM series for them, so all those limitations go away. So that's just another use case that they use. Now they start looking, and they say, "Okay, now I'm going to start extending into other clouds and I want to use you as the common frame point, the common pane of glass. >> Well Steve, good luck in your venture, you're back in the saddle again. >> Steve: Yeah. >> Another ride here, you feel good about it? >> This is going to be the best, the biggest that I've been, and I was at Palo Alto Networks and VMware Nicira. And this one's going to be bigger than both of those. >> What's your vision for where this is going to be for you, where do you see the company in a few years, what are some of the outcomes you expect to happen? >> Our opportunity, and I look at it as, someone's going to take this opportunity, and the reason I came back is, why not us, someone's going to take it. And the opportunity, honestly, is to become, effectively, what Cisco was in the early 90's. To define the architecture, the networking and the security infrastructure architecture for enterprise customers. They are begging for that right now, that's our opportunity. >> Cloud Interoperability. >> Interoperability, yeah. And so there's so many things that we need to go and do. When you look at also the thing that people are going to say, the operations. So many people think, I want it the same as it was on-prem. I think with the cloud, and across multicloud you can do it right with us, and actually better. Because the visibility that you get is more, than what you get on-prem. >> Well, and the thing that's interesting that's different about this new world that we're talking about is that there is going to be constant improvements in new things which means that the functionality game is going to increase, which means the agility is even more important because the apps are going to have more things to do. >> Yeah. I mean in the end, why do you want to go to cloud? I want to go to cloud 'cause I want it to be self-service and I want agility. I want my developers, I want everybody to be able to do things quicker because all of the sudden they say, "Let's go roll this out", and you want to be able to do it. >> Well, good luck on the new venture, Aviatrix, check 'em out, hot multicloud startup, growing, how many people do you have, put the plug in, >> 100. >> what are you guys looking for, are you hiring, give me a quick plug. >> We just hired a new VP at World Wide Sales, James Winebrenner, who was Viptela CEO, VP Sales in Cisco, hiring a tremendous amount of sales guys right now, we're closing on a $40 million Series C round next week, and we're hiring a lot of people. >> Good luck, we'll be following you Steve, thanks for coming on and sharing your insights. Again, multicloud, this is a shift that's happening, multicloud is just another word for multi-vendor, in a new modern era, this is what it has been in the technology industry, but a whole new world. This is theCUBE coverage here in New York City, ESCAPE/19, I'm John Furrier, thanks for watching. (upbeat music)

>> Is and who we are today as as a country, as a universe. >> Narrator: Congratulations Reggie Jackson, (inspirational music) you are a CUBE alumni. (upbeat music) >> Announcer: Live from Las Vegas it's theCUBE covering Splunk.Conf19. Brought to you by Splunk. >> Okay, welcome back everyone it's theCUBE's live coverage here in Las Vegas for Splunk.Conf19. I am John Furrier host of theCUBE. It's the 10th Anniversary of Splunk's .Conf user conference. Our 7th year covering it. It's been quite a ride, what a wave. Splunk keeps getting stronger and better, adding more features, and has really become a powerhouse from a third party security standpoint. We got a C-SO in theCUBE on theCUBE today. Chief Information Security, John Frushour Deputy Chief (mumbles) New York-Presbyterian The Award Winner from the Data to Everywhere Award winner, welcome by theCube. >> Thank you, thank you. >> So first of all, what is the award that you won? I missed the keynotes, I was working on a story this morning. >> Frushour: Sure, sure. >> What's the award? >> Yeah, the Data Everything award is really celebrating using Splunk kind of outside its traditional use case, you know I'm a security professional. We use Splunk. We're a Splunk Enterprise Security customer. That's kind of our daily duty. That's our primary use case for Splunk, but you know, New York Presbyterian developed the system to track narcotic diversion. We call it our medication analytics platform and we're using Splunk to track opioid diversion, slash narcotic diversions, same term, across our enterprise. So, looking for improper prescription usage, over prescription, under prescription, prescribing for deceased patients, prescribing for patients that you've never seen before, superman problems like taking one pill out of the drawer every time for the last thirty times to build up a stash. You know, not resupplying a cabinet when you should have thirty pills and you only see fifteen. What happened there? Everything's data. It's data everything. And so we use this data to try to solve this problem. >> So that's (mumbles) that's great usage we'll find the drugs, I'm going to work hard for it. But that's just an insider threat kind of concept. >> Frushour: Absolutely. >> As a C-SO, you know, security's obviously paramount. What's changed the most? 'Cause look at, I mean, just looking at Splunk over the past seven years, log files, now you got cloud native tracing, all the KPI's, >> Frushour: Sure. >> You now have massive volumes of data coming in. You got core business operations with IOT things all instrumental. >> Sure, sure. >> As a security offer, that's a pretty big surface area. >> Yeah. >> How do you look at that? What's your philosophy on that? >> You know, a lot of what we do, and my boss, the C-SO (mumbles) we look at is endpoint protection and really driving down to that smaller element of what we complete and control. I mean, ten, fifteen years ago information security was all about perimeter control, so you've got firewalls, defense and depth models. I have a firewall, I have a proxy, I have an endpoint solution, I have an AV, I have some type of data redaction capability, data masking, data labeling capability, and I think we've seen.. I don't think security's changed. I hear a lot of people say, "Oh, well, information security's so much different nowadays." No, you know, I'm a military guy. I don't think anything's changed, I think the target changed. And I think the target moved from the perimeter to the endpoint. And so we're very focused on user behavior. We're very focused on endpoint agents and what people are doing on their individual machines that could cause a risk. We're entitling and providing privilege to end users today that twenty years ago we would've never granted. You know, there was a few people with the keys to the kingdom, and inside the castle keep. Nowadays everybody's got an admin account and everybody's got some level of privilege. And it's the endpoint, it's the individual that we're most focused on, making sure that they're safe and they can operate effectively in hospitals. >> Interviewer: What are some of the tactical things that have changed? Obviously, the endpoint obviously shifted, so some tactics have to change probably again. Operationally, you still got to solve the same problem: attacks, insider threats, etc. >> Frushour: Yeah. >> What are the tactics? What new tactics have emerged that are critical to you guys? >> Yeah, that's a tough question, I mean has really anything changed? Is the game really the game? Is the con really the same con? You look at, you know, titans of security and think about guys like Kevin Mitnick that pioneered, you know, social engineering and this sort of stuff, and really... It's really just convincing a human to do something that they shouldn't do, right? >> Interviewer: Yeah. >> I mean you can read all these books about phone freaking and going in and convincing the administrative assistant that you're just late for meeting and you need to get in through that special door to get in that special room, and bingo. Then you're in a Telco closet, and you know, you've got access. Nowadays, you don't have to walk into that same administrative assistant's desk and convince 'em that you're just late for the meeting. You can send a phishing email. So the tactics, I think, have changed to be more personal and more direct. The phishing emails, the spear phishing emails, I mean, we're a large healthcare institution. We get hit with those types of target attacks every day. They come via mobile device, They come via the phishing emails. Look at the Google Play store. Just, I think, in the last month has had two apps that have had some type of backdoor or malicious content in them that got through the app store and got onto people's phones. We had to pull that off people's phones, which wasn't pretty. >> Interviewer: Yeah. >> But I think it's the same game. It's the same kind to convince humans to do stuff that they're not supposed to do. But the delivery mechanism, the tactical delivery's changed. >> Interviewer: How is Splunk involved? Cause I've always been a big fan of Splunk. People who know me know that I've pretty much been a fan boy. The way they handle large amounts of data, log files, (mumbles) >> Frushour: Sure. >> and then expand out into other areas. People love to use Splunk to bring in their data, and to bring it into, I hate to use the word data leg but I mean, Just getting... >> Yeah >> the control of the data. How is data used now in your world? Because you got a lot of things going on. You got healthcare, IOT, people. >> Frushour: Sure, sure. >> I mean lives are on the line. >> Frushour: Lives are on the line, yeah. >> And there's things you got to be aware of and data's key. What is your approach? >> Well first I'm going to shamelessly plug a quote I heard from (mumbles) this week, who leads the security practice. She said that data is the oxygen of AI, and I just, I love that quote. I think that's just a fantastic line. Data's the oxygen of AI. I wish I'd come up with it myself, but now I owe her a royalty fee. I think you could probably extend that and say data is the lifeline of Splunk. So, if you think about a use case like our medication analytics platform, we're bringing in data sources from our time clock system, our multi-factor authentication system, our remote access desktop system. Logs from our electronic medical records system, Logs from the cabinets that hold the narcotics that every time you open the door, you know, a log then is created. So, we're bringing in kind of everything that you would need to see. Aside from doing something with actual video cameras and tracking people in some augmented reality matrix whatever, we've got all the data sources to really pin down all the data that we need to pin down, "Okay, Nurse Sally, you know, you opened that cabinet on that day on your shift after you authenticated and pulled out this much Oxy and distributed it to this patient." I mean, we have a full picture and chain of everything. >> Full supply chain of everything. >> We can see everything that happens and with every new data source that's out there, the beauty of Splunk is you just add it to Splunk. I mean, the Splunk handles structured and unstructured data. Splunk handles cis log fees and JSON fees, and there's, I mean there's just, it doesn't matter You can just add that stream to Splunk, enrich those events that were reported today. We have another solution which we call the privacy platform. Really built for our privacy team. And in that scenario, kind of the same data sets. We're looking at time cards, we're looking at authentication, we're looking at access and you visited this website via this proxy on this day, but the information from the EMR is very critical because we're watching for people that open patient records when they're not supposed to. We're the number five hospital in the country. We're the number one hospital in the state of New York. We have a large (mumbles) of very important people that are our patients and people want to see those records. And so the privacy platform is designed to get audit trails for looking at all that stuff and saying, "Hey, Nurse Sally, we just saw that you looked at patient Billy's record. That's not good. Let's investigate." We have about thirty use cases for privacy. >> Interviewer: So it's not in context of what she's doing, that's where the data come in? >> That's where the data come in, I mean, it's advanced. Nurse Sally opens up the EMR and looks at patient Billy's record, maybe patient Billy wasn't on the chart, or patient Billy is a VIP, or patient Billy is, for whatever reason, not supposed to be on that docket for that nurse, on that schedule for that nurse, we're going to get an alarm. The privacy team's going to go, "Oh, well, were they supposed to look at that record?" I'm just giving you, kind of, like two or three uses cases, but there's about thirty of them. >> Yeah, sure, I mean, celebrities whether it's Donald Trump who probably went there at some point. Everyone wants to get his taxes and records to just general patient care. >> Just general patient care. Yeah, exactly, and the privacy of our patients is paramount. I mean, especially in this digital age where, like we talked about earlier, everyone's going after making a human do something silly, right? We want to ensure that our humans, our nurses, our best in class patient care professionals are not doing something with your record that they're not supposed to. >> Interviewer: Well John, I want to hear your thoughts on this story I did a couple weeks ago called the Industrial IOT Apocalypse: Now or Later? And the provocative story was simply trying to raise awareness that malware and spear phishing is just tactics for that. Endpoint is critical, obviously. >> Sure. >> You pointed that out, everyone kind of knows that . >> Sure. >> But until someone dies, until there's a catastrophe where you can take over physical equipment, whether it's a self-driving bus, >> Frushour: Yeah. >> Or go into a hospital and not just do ransom ware, >> Frushour: Absolutely. >> Actually using industrial equipment to kill people. >> Sure. >> Interviewer: To cause a lot of harm. >> Right. >> This is an industrial, kind of the hacking kind of mindset. There's a lot of conversations going on, not enough mainstream conversations, but some of the top people are talking about this. This is kind of a concern. What's your view on this? Is it something that needs to be talked about more of? Is it just BS? Should it be... Is there any signal there that's worth talking about around protecting the physical things that are attached to them? >> Oh, absolutely, I mean this is a huge, huge area of interest for us. Medical device security at New York Presbyterian, we have anywhere from about eighty to ninety thousand endpoints across the enterprise. Every ICU room in our organization has about seven to ten connected devices in the ICU room. From infusion pumps to intubation machines to heart rate monitors and SPO2 monitors, all this stuff. >> Interviewer: All IP and connected. >> All connected, right. The policy or the medium in which they're connected changes. Some are ZP and Bluetooth and hard line and WiFi, and we've got all these different protocols that they use to connect. We buy biomedical devices at volume, right? And biomedical devices have a long path towards FDA certification, so a lot of the time they're designed years before they're fielded. And when they're fielded, they come out and the device manufacturer says, "Alright, we've got this new widget. It's going to, you know, save lives, it's a great widget. It uses this protocol called TLS 1.0." And as a security professional I'm sitting there going, "Really?" Like, I'm not buying that but that's kind of the only game, that's the only widget that I can buy because that's the only widget that does that particular function and, you know, it was made. So, this is a huge problem for us is endpoint device security, ensuring there's no vulnerabilities, ensuring we're not increasing our risk profile by adding these devices to our network and endangering our patients. So it's a huge area. >> And also compatible to what you guys are thinking. Like I could imagine, like, why would you want a multi-threaded processor on a light bulb? >> Frushour: Yeah. >> I mean, scope it down, turn it on, turn it off. >> Frushour: Scope it down for its intended purpose, yeah, I mean, FDA certification is all about if the device performs its intended function. But, so we've, you know, we really leaned forward, our CSO has really leaned forward with initiatives like the S bomb. He's working closely with the FDA to develop kind of a set of baseline standards. Ports and protocols, software and services. It uses these libraries, It talks to these servers in this country. And then we have this portfolio that a security professional would say, "Okay, I accept that risk. That's okay, I'll put that on my network moving on." But this is absolutely a huge area of concern for us, and as we get more connected we are very, very leaning forward on telehealth and delivering a great patient experience from a mobile device, a phone, a tablet. That type of delivery mechanism spawns all kinds of privacy concerns, and inter-operability concerns with protocol. >> What's protected. >> Exactly. >> That's good, I love to follow up with you on that. Something we can double down on. But while we're here this morning I want to get back to data. >> Frushour: Sure. >> Thank you, by the way, for sharing that insight. Something I think's really important, industrial IOT protection. Diverse data is really feeds a lot of great machine learning. You're only as good as your next blind spot, right? And when you're doing pattern recognition by using data. >> Frushour: Absolutely. >> So data is data, right? You know, telecraft, other data. Mixing data could actually be a good thing. >> Frushour: Sure, sure. >> Most professionals would agree to that. How do you look at diverse data? Because in healthcare there's two schools of thought. There's the old, HIPAA. "We don't share anything." That client privacy, you mentioned that, to full sharing to get the maximum out of the AI or machine learning. >> Sure. >> How are you guys looking at that data, diverse data, the sharing? Cause in security sharing's good too, right? >> Sure, sure, sure. >> What's your thoughts on sharing data? >> I mean sharing data across our institutions, which we have great relationships with, in New York is very fluid at New York Presbyterian. We're a large healthcare conglomerate with a lot of disparate hospitals that came as a result of partnership and acquisition. They don't all use the same electronic health record system. I think right now we have seven in play and we're converging down to one. But that's a lot of data sharing that we have to focus on between seven different HR's. A patient could move from one institution to the next for a specialty procedure, and you got to make sure that their data goes with them. >> Yeah. >> So I think we're pretty, we're pretty decent at sharing the data when it needs to be shared. It's the other part of your question about artificial intelligence, really I go back to like dedication analytics. A large part of the medication analytics platform that we designed does a lot of anomaly detections, anomaly detection on diversion. So if we see that, let's say you're, you know, a physician and you do knee surgeries. I'm just making this up. I am not a clinician, so we're going to hear a lot of stupidity here, but bare with me. So you do knee surgeries, and you do knee surgeries once a day, every day, Monday through Friday, right? And after that knee surgery, which you do every day in cyclical form, you prescribe two thousand milligrams of Vicodin. That's your standard. And doctors, you know, they're humans. Humans are built on patterns. That's your pattern. Two thousand milligrams. That's worked for you; that's what you prescribe. But all of the sudden on Saturday, a day that you've never done a knee surgery in your life for the last twenty years, you all of a sudden perform a very invasive knee surgery procedure that apparently had a lot of complications because the duration of the procedure was way outside the bounds of all the other procedures. And if you're kind of a math geek right now you're probably thinking, "I see where he's going with this." >> Interviewer: Yeah. >> Because you just become an anomaly. And then maybe you prescribe ten thousand milligrams of Vicodin on that day. A procedure outside of your schedule with a prescription history that we've never seen before, that's the beauty of funneling this data into Splunk's ML Toolkit. And then visualizing that. I love the 3D visualization, right? Because anybody can see like, "Okay, all this stuff, the school of phish here is safe, but these I've got to focus on." >> Interviewer: Yeah. >> Right? And so we put that into the ML Toolkit and then we can see, "Okay, Dr. X.." We have ten thousand, a little over ten thousand physicians across New York Presbyterian. Doctor X right over here, that does not look like a normal prescriptive scenario as the rest of their baseline. And we can tweak this and we can change precision and we can change accuracy. We can move all this stuff around and say, "Well, let's just look on medical record number, Let's just focus on procedure type, Let's focus on campus location. What did they prescribe from a different campus?" That's anomalous. So that is huge for us, using the ML Toolkit to look at those anomalies and then drive the privacy team, the risk teams, the pharmacy analytics teams to say, "Oh, I need to go investigate." >> So, that's a lot of heavy lifting for ya? Let you guys look at data that you need to look at. >> Absolutely. >> Give ya a (mumbles). Final question, Splunk, in general, you're happy with these guys? Obviously, they do a big part of your data. What should people know about Splunk 2019, this year? And are you happy with them? >> Oh, I mean Splunk has been a great partner to New York Presbyterian. We've done so much incredible development work with them, and really, what I like to talk about is Splunk for healthcare. You know, we've created, we saw some really important problems in our space, in this article. But, we're looking, we're leaning really far forward into things like risk based analysis, peri-op services. We've got a microbial stewardship program, that we're looking at developing into Splunk, so we can watch that. That's a huge, I wouldn't say as big of a crisis as the opioid epidemic, but an equally important crisis to medical professionals across this country. And, these are all solvable problems, this is just data. Right? These are just events that happen in different systems. If we can get that into Splunk, we can cease the archaic practice of looking at spreadsheets, and look up tables and people spending days to find one thing to investigate. Splunk's been a great partner to us. The tool it has been fantastic in helping us in our journey to provide best in-class patient care. >> Well, congratulations, John Frushour, Deputy Chief Information Security Officer, New York Presbyterian. Thanks for that insight. >> You're welcome. >> Great (mumbles) healthcare and your challenge and your opportunity. >> Congratulations for the award winner Data to Everything award winner, got to get that slogan. Get used to that, it's two everything. Getting things done, he's a doer. I'm John Furrier, here on theCube doing the Cube action all day for three days. We're on day two, we'll be back with more coverage, after this short break. (upbeat music)

(upbeat music) >> Announcer: From New York, it's theCUBE. Covering ESCAPE/19. >> Everyone, welcome to theCUBE coverage here in New York City for the ESCAPE Conference 19. This is the inaugural event for multicloud, I think it's the first industry event for, really talking about multicloud and the impact to enterprises and public cloud. My next guest is Steve Mullaney, President and CEO of Aviatrix, storied career in tech, been there done that, seen many waves of innovation. Nicira, Palo Alto Networks, and now Aviatrix. You retired for a while, welcome back! >> I did, yeah, five years, yeah, yeah, yeah. >> Welcome to theCUBE. >> Thank you, thanks for having me. >> It's nice to have you on because I think you have a good perspective on the multicloud because you've been in the industry since the 80s. We've both been broke in at the same time. And we've seen the waves. >> Oh, yeah. >> This wave is bigger than, I think, most of the other waves combined because it brings together so many things, infrastructure, software, cloud scale, and a new modern application environment. And then you complicate everything by throwing IoT out there, edges being pushed to their boundaries, securities equations changed, all this is going on right now, all at the same time. >> No, and that's why I was basically retired for five years, and I was at Nicira, we got bought by VMware, I stayed there for a couple years, and I just said, "Okay, that's it!" I've had a good career and I'm done. And about a year ago, the world changed. And it felt like on a Tuesday morning, I noticed enterprises really, we'd been talking about cloud for 12 years. And five years ago they said, "We're coming in, we're going to do it," but they didn't really mean it. But about a year ago, all in the same day, every enterprise said, "No, now we actually mean it." And I don't know why, I don't know if it was just people retired or just five years of talking about it, they all decided, we're comin' in, and enterprises all moved together. And this wave, as you said, is bigger than, I was around in 1992, in the early 90s, in the movement from mainframe to client server. This is 10 times bigger than that. And more importantly, it's going to happen 10,000 times faster. Because (fingers tapping). What's that? I just deployed 62 data centers around the world. Because if I can leverage the greatest infrastructure built, basic infrastructure of the hyperscalers, AWS, Azure, Google, Alibaba, Oracle, you name it. It's unbelievable the velocity at which you can now start deploying. >> Steve, I think you're onto something big here, and this is why I'm here at this event and why I'm excited, that a lot of the industry thought leaders and practitioners and leaders are doing this event. Small events, inaugural, but I think it has a lot of links. Because there's a lot of tell signs that I like to look at, one is cloud. I've been covering Amazon eight years now, with theCUBE, I've known AWS since it started, and I've done many startups in its launch using AWS. But I've had many conversations with Andy Jassy, one on ones, privately, I got an exclusive coming up for re:Invent with him. I've gotten to know him. It started out, "Everyone's moving to the cloud. "Every data center's not going to exist." And then, you know-- >> Oh, maybe not, yeah, yeah. >> Maybe not, we'll do an output. So I challenged him last year, I said, "Andy, come on, dude, like you were saying like a year ago that." >> Steve: Yeah, it's all AWS or nothing. >> And he said, "John, look I'm not, "I just listen to the customers." And I interviewed him when he did the VMware deal. And he's very customer focused. And when they make these moves with outpost, and I think it's going to be a hybrid message this year at re:Invent, you know it's real. >> Steve: Oh, yeah. >> I think this validates your point, so I got to ask you, what specifically do you see the formula being for multicloud, because certainly everyone's recognized that there's a huge benefit for AWS. But from a scale standpoint, so why not use that? What's going on on the Enterprise on-premise that's making this new thing work? >> I think it all starts with architecture, like anything else. I think right now, enterprises have said, "Okay, we've burned a boat, right? "Now, we're not going to get rid of our data centers, "but in terms of our strategic investment, "we are moving into the cloud. "We are going to leverage "the infrastructure of the hyperscalers. "And whether that is just one hyperscaler, or multiple." And I have not met an enterprise who thinks there only going to be one, right, every single one of them. Now, I don't think they're moving workloads across, I don't think that. I think they see that, I'm going to use Google for AI, I'm going to use AWS because it started there. I'm going to use Azure, for Office 365, and other different things, and everything in infrastructure is always multi. It's never homogeneous, right, it's always that. So I think is going to happen, and I think what people are begging for right now, is, I want to build an architecture that gives me the optionality to be able to deliver a common set of services whether I'm on AWS or multiple clouds. And I want them to be my services and I don't want to have understand the low level abstractions and constructs of each of those clouds, because their all different. One's metric, one's U.S., one's some other weird thing. And I don't have the time, the people, or the resources to be able to do that. Give me a common set of services, that are my services, that I can deploy and abstract away the details of those public clouds. >> Yeah, it's an interesting point there, in fact, I called BS on multicloud last year when it started to kind of rear it's head, I'm like, "Come on, multicloud is bullshit." And I said that on theCUBE. And here's what I meant. Multicloud as an operating model is directionally correct, but the architecture hasn't shown where there's true multicloud. Now, the fact of the matter is, people have Amazon, people have Office and Office 365, that's technically two clouds, >> They're siloed, yeah. >> If they give us Google, that's three clouds. >> I use two or three clouds. >> So, if he have three clouds, I guess they have multiple clouds. But you bring up an interesting point, and going back as a student of the history of tech industry, multi-vendor has been a big deal. >> It is a big deal. >> And like you said, there will be a multi-vendor world, that will happen. The question is how. How do you guys see it happening? >> Well I think what's-- >> Your company is attacking this Aviatrix. >> What's interesting is, so now you think about from a customer perspective which, I do the same thing, same thing with AWS. It's always outside in. Okay, I'm thinking as a enterprise IT person. I'm making the move. Do you believe that your basic infrastructure will lever the hyperscalers, or will you build an on-prem? Everyone says, "I believe that's the way I'm going to go." Great, how do I do that? So, I'm a IT architect, who do I go to to help me? Do I go to CISCO? No. The most shocking thing for me, of the six months I've been at Aviatrix, is that word's never used. It's like it was DEC or IBM in the conversation, when you were talking about client-server, no, why would you? CISCO, Juniper, Arista, any of the networking people, not even in the conversation. VMware, not really in the conversation. So, I don't have any incumbent vendor that I can go to that I used to go to. >> Why aren't they in the conversation? 'Cause of the commodity, they've been extracted away? >> I think it's just because it's the innovation of dilemma. Right, once you're selling a lot of stuff into on-prem, to then go and say, I mean you look at Palo Alto Networks, they're trying to make that transition. Acquiring a bunch of companies, VMware acquiring a bunch of companies. Why are they doing that? Because they know, I got to get off on-prem, everything's going in the cloud. >> So it's a legacy. >> It's a legacy thing, and I think what happens is, there is only one reason, and one reason only, an enterprise customer is not using Aviatrix. 'Cause they never heard of us. That's why, that's the only reason. Once they hear about what they're doing, my God. >> Well, give the plug, talk about the company, what do you guys do-- >> So we deliver, I mean it sounds like I made it up for this conference, but actually this conference was perfect for this. It's networking and security services for the multicloud enterprise. And we're building an architecture, that people can deploy, that will give them this common architecture across all the different clouds. So whether you're just using one cloud or multiple, it doesn't matter, it's the same set of security and networking services. And we do that by embracing and extending the basic constructs that AWS, Google, Azure, and Oracle, and all the other clouds will give you, and to deliver that real enterprise class. Because the other thing we've found is, everyone thinks that the cloud gives you everything and anything you will ever need from networking and security. Let's say AWS, they're going to do everything I need. What the enterprises are figuring out, is once they stop going in, what they realize is, it's created for the low-level common basic constructs. And the enterprise starts at, well, I need these BGP feature because guess what, the data center is not going away. And I need more than a hundred route limitations, and I need, all of a sudden there's fifty different limitations AWS will give me. Well, they didn't talk about that! Well, of course they're not going to talk about that. They are just going to go check, check, check, we solve all your problems. As enterprises now move in, with mission critical applications, they're realizing, I need the same level of networking and security services that I had on-prem. I can't get that with the native constructs. So where do I go? That's what we do, so we fill in, we embrace what we can of those constructs, we fill in holes where there are fill in holes. And then we give you the mechanism to be able to orchestrate that across the global network. >> So you operationalize the hyperscale clouds for enterprise, >> Yes. >> that's basically what you do. >> Steve: Exactly, for the enterprise. >> Yeah, exactly. >> On the level that they need. >> So you get the benefits of the cloud, but all those nuances under the cover details like networking and other features you abstract that away and provide an operating model for enterprise compliments. >> And the beautiful thing about it is the velocity, at which we can, we're over the top, effectively over the top. We're integrated into the Cloud Suite, understand what cloud native, we understand all the constructs of accounts, and all the things we need to do. But what we expose to the customer, to the enterprise, is a set of over-the-top services that just work. >> Okay Steve, so I got to ask you, since we are at The Multi-Cloud Conference. What is multicloud, I mean how do you define it, you laid out a pretty compelling architecture of what needs are, levers in the cloud, and on-prem is what Aviatrix does. But what is the definition, how should people understand what is multicloud? >> I think for us, for networking and security in that base, so we're basic infrastructure. We get out there first, right? So, if you're going to build a city, you don't start putting people there first the first thing, if you do it right, is you get sewers, you get electricity, gas, roads, all that. Networking and security, infrastructure, is basic infrastructure goes out first. And you want to create an architecture that's going to live with you for twenty years. You don't want to have to rip up the roads and put the sewers in later. And that architecture needs to be multicloud because, even though you think maybe, most of our customers are 90% AWS right now. But every single one of them say, "But I'm moving to Azure, I'm moving to Google, "I've got retail customers that won't allow me "to put my infrastructure on AWS." Or, "I have machine learning, AI type apps on Google." They all say that same thing. But what they all then say to us, is, "You're going to be the mechanism "upon which I'm going to be able to deploy "this common set of services." So they don't need to know that. >> All right, give an example of a customer you guys have, name a name, we had a customer on stage here-- >> Steve: So, Jefferies. >> John: They did this for a use case. >> Yeah so, Jefferies. Financial Services Institution, lots of requirements, Mark Leon Soon is going to be on stage with me tomorrow. We started working with them about nine months ago. Exactly the same thing, they said, "Okay, you know what? "We need to start moving to the cloud, "we've got to start leveraging the cloud. "But, it's too complicated, right? "Even AWS, says 'Go Build.' "I don't want to go build, I want to consume services. "But they don't have all the service that I needed, "they're too low a level. "They're very high function, high enterprise requirements." So they start using us to orchestrate things, to provide transit networking, to provide egress filtering out to the Internet, we have high performance encryption, AWS will only offer it one gig. We can offer it to 10, 20, 30, 40 gig. So they start deploying, they start realizing all the things we do. Then they go and say, "I want to bring my Palo Alto Networks firewall "into the cloud." When you start looking at that, 'cause then guess what? All my policies, I want the same level that I have on-prem when I'm in the cloud. If I go try to bring in my VM series into AWS the construct that AWS give you, they cause you limitations in performance, in visibility, It's integration hassles, there's performance, sustainability, visibility issues, they force you to use SNAT. And there's all these issues, and they go, "Oh my God, this is a pain in the ass." We solved all that for them. We basically cloudify the VM series for them, so all those limitations go away. So that's just another use case that they use. Now they start looking, and they say, "Okay, now I'm going to start extending into other clouds and I want to use you as the common frame point, the common pane of glass. >> Well Steve, good luck in your venture, you're back in the saddle again. >> Steve: Yeah. >> Another ride here, you feel good about it? >> This is going to be the best, the biggest that I've been, and I was at Palo Alto Networks and VMware Nicira. And this one's going to be bigger than both of those. >> What's your vision for where this is going to be for you, where do you see the company in a few years, what are some of the outcomes you expect to happen? >> Our opportunity, and I look at it as, someone's going to take this opportunity, and the reason I came back is, why not us, someone's going to take it. And the opportunity, honestly, is to become, effectively, what Cisco was in the early 90's. To define the architecture, the networking and the security infrastructure architecture for enterprise customers. They are begging for that right now, that's our opportunity. >> Cloud Interoperability. >> Interoperability, yeah. And so there's so many things that we need to go and do. When you look at also the thing that people are going to say, the operations. So many people think, I want it the same as it was on-prem. I think with the cloud, and across multicloud you can do it right with us, and actually better. Because the visibility that you get is more, than what you get on-prem. >> Well, and the thing that's interesting that's different about this new world that we're talking about is that there is going to be constant improvements in new things which means that the functionality game is going to increase, which means the agility is even more important because the apps are going to have more things to do. >> Yeah. I mean in the end, why do you want to go to cloud? I want to go to cloud 'cause I want it to be self-service and I want agility. I want my developers, I want everybody to be able to do things quicker because all of the sudden they say, "Let's go roll this out", and you want to be able to do it. >> Well, good luck on the new venture, Aviatrix, check 'em out, hot multicloud startup, growing, how many people do you have, put the plug in, >> 100. >> what are you guys looking for, are you hiring, give me a quick plug. >> We just hired a new VP at World Wide Sales, James Winebrenner, who was Viptela CEO, VP Sales in Cisco, hiring a tremendous amount of sales guys right now, we're closing on a $40 million Series C round next week, and we're hiring a lot of people. >> Good luck, we'll be following you Steve, thanks for coming on and sharing your insights. Again, multicloud, this is a shift that's happening, multicloud is just another word for multi-vendor, in a new modern era, this is what it has been in the technology industry, but a whole new world. This is theCUBE coverage here in New York City, ESCAPE/19, I'm John Furrier, thanks for watching. (upbeat music)

(upbeat music) >> Live, from Copenhagen, Denmark. It's theCUBE. Covering Nutanix.NEXT 2019. Brought to you by Nutanix. >> Welcome back everyone to theCUBE's live coverage of Nutanix.NEXT. We are in Copenhagen, Denmark. I'm your host, Rebecca Knight, hosting alongside Stu Miniman. We're joined by Fran Scott. She is a science and engineering presenter. Thanks so much for coming on the show. >> No worries at all. It's good to be here actually. >> So you are a well known face to UK audiences. You are a three times BAFTA nominated science and engineering presenter. Well-known. >> Give her a winner. (laughter) >> You're the Susan Lucci of science. You are the pyrotechnician and you lead the Christmas lectures at the Royal Institute. >> Yeah. I head up the demonstration team at the Royal Institution. We come up with all the science demonstrations, so the visual ways to show the science ideas. I head up that team. We build the demonstrations and we show science to people rather than just tell them about it. >> So mostly, you have a very cool job. (chuckles) >> I love my job. >> I want to hear how you got into this. What was it? What inspired you? >> Oh gosh, two very different questions. In terms of what inspired me, I was very lucky enough to be able to pursue what I love. And I came from a family where answers weren't given out willy-nilly. If you didn't know something, it wasn't a bad thing. It was like a, "Let's look it up. Let's look it up." I grew up in an atmosphere where you could be anything because you didn't have to know what you had to be. You could just have a play with it. I love being hands-on and making things, and I grew up on a farm, so I was quite practical. But I also loved science. Went to university, did neuroscience at university. I enjoyed the learning part but, where I was in terms of the science hierarchy, I found out that once you actually go into a lab, there's a lot of lab work and not much learning straight away, and it was the learning that I loved. And so my friends actually got me into science communication. They took me to the science museum and they were like, "Fran, you will love this." And I was like, "Will I?" And I was like, "You are so right." I got a job at the science museum in London by just approaching someone on that visit and being like, "How do I get a job here?" And they were like, "Well, you got to do this, this, this." I was like, "I can do that." I got the job there and I realized I loved science demonstrations and building stuff. Eventually I just combined that love of science and being practical together. And now I produce and write, build science props and science stage shows. And then it became a thing. (laughter) Hand it to me, I love it. >> So Fran, our audience is very much the technology community. Very supportive of STEM initiatives. Give us a little flavor as to some of the things you're working on. Where is there need for activities? >> I suppose the biggest example of that would be a show that I did a few years ago where there was a big push for new coders within the UK. And I was getting approached time and time again for visual ways to show computer coding. Or programming, as we used to call it back in the day. I didn't have an answer because then, I wasn't a coder. So I was like, "Well, I'll learn. And then I'll figure out a demonstration because this is what I do. So why don't I do it on coding?" And so yeah, I set about. I learnt code. And I came up with an explosions based coding show. Error 404. And we toured around the country with that. Google picked it up and it was a huge success just because it was something that people wanted to learn about. And people were stumped as to how to show coding visually. But because this is what we do day in and day out with different subjects, we could do it with coding just like we do it with physics. >> What do you think is the key? A lot of your audience is kids. >> Yes and family audiences. >> So what is the key to getting people excited about science? >> I think science itself is exciting if people are allowed to understand how brilliant it is. I think some of the trouble comes from when people take the step too big, and so you'd be like, "Hang on but, why is that cool? Why?" Because they don't under... Well they would understand if they were fed to them in a way that they get it. The way I say it is, anyone can understand anything as long as you make the steps to get there small enough. Sometimes the steps are too big for you to understand the amazingness of that thing that's happening. And if you don't understand that amazingness, of course you're going to lose interest. Because everyone around you is going, "Ah, this is awesome, this is awesome!" And you're like, "What? What's awesome?" I think it's up to us as adults and as educators to just try and not patronize the children, definitely not, but just give them those little steps so they can really see the beauty of what it is that we're in awed by. >> One of the things that is a huge issue in the technology industry is the dearth of women in particular, in the ranks of technology and then also in leadership roles. As a woman in science and also showing little girls everywhere all over the UK what it is to be a woman in science, that's a huge responsibility. How do you think of that, and how are you in particular trying to speak to them and say, "You can do this"? >> I've done a lot of research onto this because this was the reason I went into what I'm into. I worked a lot of the time behind the scenes just trying to get the science right. And then I realized there was no one like me doing science presenting. The girl was always the little bit of extra on the side and it was the man who was the knowledgeable one that was showing how to do the science. And the woman was like, "Oh, well that's amazing." And I was like, "Hang on. Let's try and flip this." And it just so happened that I didn't care if it was me. I just wanted a woman to do it. And it just happened that that was me. But now that I'm in that position, one, well I run a business as well. I run a business where we can train other new presenters to do it. It's that giving back. So yes, I train other presenters. I also make sure there's opportunity for other presenters. But I also try, and actually I work with a lot of TV shows, and work on their language. And work on the combination of like, "Okay, so you've got a man doing that, you got women doing this. Let's have a look at more diversity." And just trying to show the kids that there are people like them doing science. There's that classic phrase that, "You can't be what you can't see." So yes, it comes responsibility, but also there's a lot of fun. And if you can do the science, be intelligent, be fun, and just be normal and just enjoy your job, then people go, "Hang on," whether they're a boy or a girl, they go, "I want a bit of that," in terms of, "I want that as my job." And so by showing that, then I'm hopefully encouraging more people to do it. But it's about getting out and encouraging the next generation to do it as well. >> Fran, you're going to be moderating a panel in the keynote later this afternoon. Give our audience a little bit. What brought you to this event? What's going into it? And for those that don't get to see it live, what they're missing. >> I am one lucky woman. So the panel I'm moderating, it's all about great design and I am a stickler for great design. As a scientist, prop-builder, person that does engineering day in and day out, I love something when it's perfectly designed. If there is such a thing as a perfect design. So this panel that we've got, Tobias Manisfitz, Satish Ramachandran, and Peter Kreiner from Noma. And so they all come with their own different aspect of design. Satish works at Nutanix. Peter works at Noma, the restaurant here in Copenhagen. And Tobias, he designs the visual effects for things such as Game of Thrones and Call of Duty. And so yes, they each design things for... They're amazing at their level but in such a different way and for a different audience. I'm going to be questioning them on what is great design to them and what frictionless design means and just sort of picking their amazing brains. >> I love that fusion of technology and design as something they talked about in the keynote this morning. Think of Apple or Tesla, those two things coming together. I studied engineering and I feel like there was a missing piece of my education to really go into the design. Something I have an appreciation for, that I've seen in my career. But it's something special to bring those together. >> Yeah. I think care is brought in mostly because yes, one, I love design. But also I've worked a lot with LEGO. And so I was brought in to be the engineering judge on the UK version of LEGO Masters. Apparently, design in children's builds is the same as questioning the owner of NOMA restaurant. (chuckles) >> So what do you think? Obviously you're doing the panel tomorrow. What is in your mind the key to great design? Because as you said, you're a sucker for anything that is just beautiful and seamless and intuitive. And we all know what great design is when we hold it in our hands or look at it. But it is this very ineffable quality of something that... >> So the panel's later today actually. But in terms of great design, yes, we all know when we have great design. But the trouble comes in creating good design. I think the key, and it's always obvious when you say it out loud, but it's that hand in hand partnership with aesthetics and practicality. You can't have something that's just beautiful. But you can't have something that just works. You need to have it as a mixture of both. It's those engineers talking with the designers, the designers talking with the engineers. The both of them talking with the consumers. And from that, good design comes. But don't forget, good design means they're for different people as well. >> What are some of the most exciting things you're working on, because you are a professional pyrotechnician. We've never had someone like this on theCUBE before. This is amazing. This is a first time ever. >> I was strictly told no fire. >> Yes, thank you. We appreciate that. >> Well at the moment, as I said at the beginning, I'm lucky enough to head up the demo team at the Royal Institution. We are just heading into our Christmas lectures. Now if you don't know these Christmas lectures, they were the first science ever done to a juvenile audience. Back in 1825 was when they started. It's a tradition in the UK and so this year, we're just starting to come up with the demonstrations for them. And this year they presented by Hannah Fry, and so they're going to be on maths and algorithms and how that makes you lucky or does it make you lucky? We've been having some really fun meetings. I can't give away too much, but there definitely be some type of stunt involved. That's all I can say. But there's going to be a lot of building. I really need to get back, get my sore out, get stuff made. >> Excellent. And who is the scientist you most admire? >> Oh my word. >> Living or dead? >> Who is the scientist I most admire? (sighs) I do have... Oh gosh, this is... >> The wheels are churning. >> It's a cheesy one though, but Da Vinci. Just for his multi-pronged approach and the fact that he had so much going on in his brain that he couldn't even get everything down on paper. He'd half draw something and then something else would come to him. >> I had the opportunity of interviewing Walter Isaacson last year, and he loved... It was the, as we talked about, the science and the design and the merging of those. But reading that biography of him, what struck me is he never finished anything because it would never meet the perfection in his mind to get it done. I've seen that in creative people. They'll start things and then they'll move on to the next thing and there. Me as a engineering by training, it's like no, no. You need to finish work. Manufacturing from standpoint, work in progress is the worst thing you could have out there. >> He would be a rubbish entrepreneur. (chuckling) >> Right, but we're so lucky to have had his brain. >> Exactly. I think that's the thing. I think it gives us an insight into what the brain is capable of and what you can design without even knowing you're designing something. >> Well Fran, thank you so much for coming on theCUBE. This was so fun. >> Thanks for having me. >> I'm Rebecca Knight for Stu Miniman. Stay tuned for more of theCUBE's live coverage of .NEXT. (upbeat music)

(upbeat music) >> Welcome back to London everybody, this is Dave Vellante with The Cube, the leader in tech coverage, and we're here at AWS. We wanted to cover deeper the public sector activity. We've been covering this segment for quite some time, with the public sector summit in DC, went to Bahrain last year, and we wanted to extend that to London. We're doing a special coverage here with a number of public sector folks. Anjenesh Babu is here, he's a network manager at Oxford GLAM. Thanks very much for coming on The Cube, it's good to see you. >> Thank you.], thanks. >> GLAM, I love it. Gardens, libraries and museums, you even get the A in there, which everybody always leaves out. So tell us about Oxford GLAM. >> So we are part of the heritage collection side of the University. And I'm here representing the gardens and museums. In the divisions we've got world renown collections, which has been held for 400 years or more. It comprises of four different museums and the Oxford University Botanic Gardens and Arboretum. So in total, we're looking at five different divisions, spread across probably sixteen different sites, physical sites. And the main focus of the division is to bring out collections to the world, through digital outreach, engagement and being fun, bringing fun into the whole system. Sustainment is big, because we are basically custodians of our collections and it has to be here almost forever, in a sense. And we can only display about 1% of our collections at any one point and we've got about 8.5 million objects. So as you can imagine, the majority of that is in storage. So one way to bring this out to the wider world is to digitize them, curate them and present them, either online or in another form. So that is what we do. >> In your role as the network manager is to makes sure everything connects and works and stays up? Or maybe describe that a little more. >> So, I'm a systems architect and network manager for gardens and museums, so in my role, my primary focus is to bridge the gap between technical and the non-technical functions, within the department. And I also look after network and infrastructure sites, so there's two parts to the role, one is a BAU business as usual function where we keep the networks all going and keep the lights on, basically. The second part is bringing together designs, it's not just solving technical problems, so if I'm looking at a technical problem I step out and almost zoom out to see, what else are we looking at which could be connected, and solve the problem. For example, we could be looking at a web design solution in one part of the project, but it's not relevant just to that project. If you step out and say, we could do this in another part of the program, and we may be operating in silence and we want to breakdown those, that's part of my role as well. >> Okay, so you're technical but you also speak the language of the organization and business. We put it in quotes because you're not a business per say. Okay, so you're digitizing all these artifacts and then making them available 24/7, is that the idea? What are some of the challenges there? >> So the first challenge is only 3% of objects are actually digitized. So we have 1% on display, 3% is actually digitized, it's a huge effort, it's not just scanning or taking photographs, you've got cataloging, accessions and a whole raft of databases that goes behind. And museums historically have got their own separate database collection which is individually held different collection systems, but as public, you don't care, we don't care, we just need to look at the object. You don't want to see, that belongs to the Ashmolean Museum or the picture does. You just want to see, and see what the characteristics are. For that we are bringing together a layer, which integrates different museums, it sort of reflects what we're doing in out SIT. The museums are culturally diverse institutions and we want to keep them that way, because each has got its history, a kind of personality to it. Under the hood, the foundational architecture, systems remain the same, so we can make them modular, expandable and address the same problems. So that's how we are supporting this and making it more sustainable at the same time. >> So you have huge volume, quality is an issue because people want to see beautiful images. You got all this meta data that you're collecting, you have a classification challenge. So how are you architecting this system and what role does the Cloud play in there? >> So, in the first instance we are looking at a lot of collections were on premises in the past. We are moving as a SaaS solution at the first step. A lot of it requires cleansing of data, almost, this is the state of the images we aren't migrating, we sort of stop here let's cleanse it, create new data streams and then bring it to the Cloud. That's one option we are looking at and that is the most important one. But during all this process in the last three years with the GLAM digital program there's been huge amount of changes. To have a static sort of golden image has been really crucial. And to do that if we are going down rate of on premise and trying to build out, scale out infrastructures, it would have a huge cost. The first thing that I looked at was, explore the Cloud options and I was interested in solutions like Snowball and the Storage Gateway. Straightforward, loads up the data and it's on the Cloud, and then I can fill out the infrastructure as much as I want, because we can all rest easy, the main, day one data is in the Cloud, and it's safe, and we can start working on the rest of it. So it's almost like a transition mechanism where we start working on the data before it goes to the Cloud anyway. And I'm also looking at a Cloud clearing house, because there's a lot of data exchanges that are going to come up in the future, vendor to vendor, vendor to us and us to the public. So it sort of presents itself a kind of junction, who is going to fill the junction? I think the obvious answer is here. >> So Snowball or Gateway, basically you either Snowball or Gateway the assets into the Cloud and you decide which one to use based on the size and the cost associated with doing that, is that right? >> Yes, and convenience. I was saying this the other day at another presentation, it's addictive because it's so simple and straight forward to use, and you just go back and say it's taken me three days to transfer 30 terabytes into a Snowball appliance and on the fourth day, it appears in in my packets, so what are we missing? Nothing. Let's do it again next week. So you got the Snowball for 10 days, bring it in transfer, so it's much more straightforward than transferring it over the network, and you got to keep and eye on things. Not that it's not hard, so for example, the first workloads we transferred over to the file gateway, but there's a particular server which had problems getting things across the network, because of out dated OS on it. So we got the Snowball in and in a matter of three days the data was on the Cloud, so to effect every two weeks up on the Snowball, bring it in two weeks, in three days it goes up back on the Cloud. So there's huge, it doesn't cost us any more to keep it there, so the matter of deletions are no longer there. So just keep it on the Cloud shifting using lifecycle policies, and it's straight forward and simple. That's pretty much it. >> Well you understand physics and the fastest way to get from here to there is a truck sometimes, right? >> Well, literally it is one of the most efficient ways I've seen, and continues to be so. >> Yeah, simple in concept and it works. How much are you able to automate the end-to-end, the process that you're describing? >> At this point we have a few proof of concept of different things that we can automate, but largely because a lot of data is held across bespoke systems, so we've got 30 terabytes spread across sixteen hard disks, that's another use case in offices. We've got 22 terabytes, which I've just described, it's on a single server. We have 20 terabytes on another Windows server, so it's quite disparate, it's quite difficult to find common ground to automate it. As we move forward automation is going to come in, because we are looking at common interface like API Gateways and how they define that, and for that we are doing a lot of work with, we have been inspired a lot by the GDS API designs, and we are just calling this off and it works. That is a road we are looking at, but at the moment we don't have much in the way of automation. >> Can you talk a bit more about sustainability, you've mentioned that a couple of times, double click on that, what's the relevance, how are you achieving sustainability? Maybe you could give some examples. >> So in the past sustainability means that you buy a system and you over provision it, so you're looking for 20 terabytes over three years, lets go 50 terabytes. And something that's supposed to be here for three years gets kept going for five, and when it breaks the money comes in. So that was the kind of very brief way of sustaining things. That clearly wasn't enough, so in a way we are looking for sustainability from a new function say, we don't need to look at long-term service contracts we need to look at robust contracts, and having in place mechanisms to make sure that whatever data goes in, comes out as well. So that was the main driver and plus with the Cloud we are looking at the least model. We've got an annual expenditure set aside and that keeps it, sustainability is a lot about internal financial planning and based on skill sets. With the Cloud skill sets are really straightforward to find and we have engaged with quite a few vendors who are partnering with us, and they work with us to deliver work packages, so in a way even though we are getting there with the skills, in terms of training our team we don't need to worry about complex deployments, because we can outsource that in sprints. >> So you have shipped it from a CAPX to an OPX model, is that right? >> Yes >> So what was that like, I mean, was that life changing, was it exhilarating? >> It was exhilarating, it was phenomenally life changing, because it set up a new direction within the university, because we were the first division to go with the public Cloud and set up a contract. Again thanks to the G-Cloud 9 framework, and a brilliant account management team from AWS. So we shifted from the CAPX model to the OPX model with an understanding that all this would be considered as a leased service. In the past you would buy an asset, it depreciates, it's no longer the case, this is a leased model. The data belongs to us and it's straight forward. >> Amazon continues to innovate and you take advantage of those innovations, prices come down. How about performance in the cloud, what are you seeing there relative to your past experiences? >> I wouldn't say it's any different, perhaps slightly better, because the new SDS got the benefit of super fast bandwidth to the internet, so we've got 20 gigs as a whole and we use about 2 gigs at the moment, we had 10 gig. We had to downgrade it because, we didn't use that much. So from a bandwidth perspective that was the main thing. And a performance perspective what goes in the Cloud you frankly find no different, perhaps if anything they are probably better. >> Talk about security for a moment, how early on in the Cloud people were concerned about security, it seems to have attenuated, but security in the Cloud is different, is it not, and so talk about your security journey and what's your impression and share with our audience what you've learned. >> So we've had similar challenges with security, from security I would say there's two pots, one's the contractual security and one is the technical security. The contractual security, if we had spun up our own separate legal agreement with AWS or any other Cloud vendor, it would have taken us ages, but again we went to the digital marketplace, used the G-Cloud 9 framework and it was no brainer. Within a week we had things turned around, and we were actually the first institution to go live with and account with AWS. That is the taken care of. SDS is a third party security assessment template, which we require all our vendors to sign. As soon as we went through that it far exceeds what the SDS requires, and it's just a tick box exercise. And things like data encryption at rest, in transit it actually makes it more secure than what we are running on premise. So in a way technically it's far more secure than what we could ever have achieved that's on premise, and it's all taken care of, straight forward. >> So you've a small fraction of your artifacts today that are digitized. What's the vision, where do you want to take this? >> We're looking at, I'm speaking on behalf of gardens, this is not me, per say, I'm speaking on behalf of my team, basically we are looking at a huge amount of digitization. The collection should be democratized, that's the whole aspect, bringing it out to the people and perhaps making them curators in some form. We may not be the experts for a massive collection from say North America or the Middle East, there are people who are better than us. So we give them the freedom to make sure they can curate it in a secure, scalable manner and that's where the Cloud comes in. And we backend it using authentication that works with us, logs that works with us and roll-back mechanisms that works with us. So that's were we are looking at in the next few years. >> How would you do this without the Cloud? >> Oh. If you're doing it without the Cloud-- >> Could you do it? >> Yes, but we would be wholly and solely dependent on the University network, the University infrastructure and a single point. So when you're looking at the bandwidth it's shared by students using it network out of the university and our collection visitors coming into the university. And the whole thing, the DS infrastructure, everything's inside the university. It's not bad in its present state but we need to look at a global audience, how do you scale it out, how do you balance it? And that's what we're looking at and it would've been almost impossible to meet the goals that we have, and the aspirations, and not to mention the cost. >> Okay so you're going to be at the summit, the Excel Center tomorrow right? What are you looking forward to there for us from a customer standpoint? >> I'm looking at service management, because a lot of our work, we've got a fantastic service desk and a fantastic team. So a lot of that is looking at service management, how to deliver effectively. As you rightly say Amazon is huge on innovation and things keep changing constantly so we need to keep track of how we deliver services, how do we make ourselves more nimble and more agile to deliver the services and add value. If you look at the OS stack, that's my favorite example, so you look at the OS stack you've got seven layers going up from physical then all the way to the application. You can almost read an organization in a similar way, so you got a physical level where you've got cabling and all the way to the people and presentation layer. So right now what we are doing is we are making sure we are focusing on the top level, focusing on the strategies, creating strategies, delivering that, rather than looking out for things that break. Looking out for things that operationally perhaps add value in another place. So that's where we would like to go. >> Anjenesh, thanks so much for coming on The Cube. >> Thank you >> It was a pleasure to have you. All right and thank you for watching, keep right there we'll be back with our next guest right after this short break. You're watching The Cube, from London at Amazon HQ, I call it HQ, we're here. Right back. (upbeat music)

>> live from Boston, Massachusetts. It's the you covering your red hat. Some twenty nineteen rots. You buy bread hat. >> Well, good afternoon. Welcome back here on the Cube as we continue our coverage of the Red Hat Summit and you know, every once in a while you come across one of these fascinating topics. It's what's doing I get so excited about when we do the Cube interviews is that you never know where >> you're >> going to go, the direction you're going to take. And I think this next interview has been a fit into one of those wow interviews for you at home. Along was to minimum. I am John Walls, and we're joined by Dr Ellen Grant, who was the director of the fetal neo NATO Neuroimaging and Developmental Science Center of Boston Children's Hospital. So far, so good, right? And the professor, Radiology and pediatrics at the Harvard Medical School's Dr Grant. Thank you for joining us here on the Cube and Dr Rudolph Pienaar, who is the technical director at the F n N D. S. C. And an instructor of radiology at the Harvard Medical School. So Dr Rudolph Pienaar, thank you for joining us as well. Thank you very much. All right. Good. So we're talking about what? The Chris Project, which was technically based. Project Boston Children's Hospital. I'm going to let you take from their doctor Grant. If you would just talk about the genesis of this program, the project, what its goal, wass And now how it's been carried out. And then we'LL bring in Dr PNR after that. So if you would place >> sure, it's so The goal of the Chris Project was to bring innovated imaging, announces to the bedside to the front end where clinicians are not like high are working all the time but aren't sophisticated enough or don't have enough memory to remember how to do, you know, line code in Lenox. So this is where initially started when I was reading clinical studies and I wanted to run a complex analysis, but there was no way to do it easily. I'd have tio call up someone to log into a different computer, bring the images over again lots of conflict steps to run that analysis, and even to do any of these analysis, you have to download the program set up your environment again. Many many steps, said someone. As a physician, I would rather deal with the interpretation and understanding the meaning of those images. Then all that infrastructure steps to bring it together. So that was the genesis of Chris's trying to have a simple Windows point and click way for a physician such as myself, to be able to rapidly do something interesting and then able to show it to a clinician in a conference or in the at the bedside >> and who's working on it, then, I mean, who was supplying what kind of manpower, If you will root off of the project >> kind of in the beginning, I would say maybe one way to characterize it is that we wanted to bring this research software, which lives mostly online, ex onto a Windows world, right? So the people developing that software researchers or computational researchers who do a lot of amazing stuff with image processing. But those tools just never make it really from the research lab outside of that. And one of the reasons is because someone like Ellen might not ever want to fire paternal and typing these commands. So people working on it are all this huge population of researchers making these tools on what we try to do. What I try to help with, How do we get those tools really easily usable in excess of one and, you know, to make a difference? Obviously. So that was a genesis. I was kind of need that we had in the beginning, so it started out, really, as a bunch of scrips, shell scripts, you slight a type of couple stuff, but not so many things on gradually, with time, we try to move to the Web, and then it began to grow and then kind of from the Web stretching to the cloud. And that's kind of the trajectory in the natural. As each step moved along, more and more people kind of came in to play. >> Dr Grant, I think back, you know, I work for a very large storage company and member object storage was going to transform because we have the giant files. We need to be able to store them and manage them and hold them up. But let's talk about the patient side of things. What does this really mean? You know, we had a talk about order of magnitude that cloud can make things faster and easier. But what? What does this mean to patient care? Quality service? >> Well, I think what it means or the goal for patient care is really getting to specialized medicine or individualized medicine on to be able to not just rely on my memory as to what a normal or abnormal images or the patients I may have seen just in my institution. But can we pull together all the knowledge across multiple institutions throughout the country and use more rigorous data announces to support my memory? So I want to have these big bridal in front lobes that air there, the cloud that helped me remember things into tidies connections and not have to remind just rely on my visual gestalt memory, which is obviously going to have some flaws in it. So and if I've never seen a specific disorder, say, for example, at my institution, if they've seen it at other institutions who run these comparisons all of sudden, I made be aware of a new treatment that otherwise I may not have known about >> All right, so one of my understanding is this is tied into the mass open cloud which I've had the pleasure of talking on the program at another show back here in Boston. Talk about a little bit about you know how this is enable I mean massive amounts of data you need to make sure you get that. You know the right data and it's valuable information and to the right people, and it gets updated all the time, so give us a little bit of the inner workings. >> Exactly. So thie inner workings, That's it can be a pretty big story, but kind of the short >> story time Theo Short >> story is that if we can get data in one place, and not just from one institution, from many places, that we can start to do things that are not really possible otherwise so, that's kind of the grand vision. So we're moving along those steps on the mass Open cloud for us makes perfect sense because it's there's a academic linked to Boston University. And then there's thie, Red Hat, being one of the academic sponsors as well in that for this kind of synergy that came together really almost perfectly at the right time, as the cloud was developing as where that was moving in it as we were trying to move to the cloud. It just began to link all together. And that's very much how we got there at the moment on what we're trying to do, which is get data so that we can cause medicine. Really, it's amazing to me. In some ways there's all these amazing devices, but computational e medicine lag so far behind the rest of the industry. There's so little integration. There's so little advanced processing going on. There's so much you can do with so little effort, you could do so much. So that's part of the >> vision as well. So help me out here a little bit, Yeah, I mean, maybe it before and after. Let's look at the situation may be clinically speaking here, where a finding or a revelation that you developed is now possible where it wasn't before and kind of what those consequences might have been. And then maybe, how the result has changed now. So maybe that would help paint up a practical picture of what we're talking about. >> I could use one example we're working on, but we haven't got fully to the clouds. All of these things are in their infancy because we still have to deal with the encryption part, which is a work in progress. But for example, we have mind our clinical databases to get examples of normal images and using that I can run comparisons of a case. It comes up to say whether this looks normal or abnormal sweat flags. The condition is to whether it's normal or abnormal, and that helps when there's trainees are people, not is experienced in reading those kinds of images. So again we're at the very beginnings of this. It's one set of pictures. There's many sets of pictures that we get, so there's a long road to get to fully female type are characterized anyone brain. But we're starting at the beginning those steps to very to digitally characterize each brain so we can then start to run. Comparisons against large libraries of other normals are large libraries of genetic disorders and start to match them up. And >> this is insecure. You working in fetal neural imaging as well. So you're saying you could take a an image of ah baby in a mother's womb and many hundreds thousands, whatever it is and you developed this basically a catalogue of what a healthy brain might look like. And now you're offering an opportunity to take a image here on early May of twenty nineteen. And compared to that catalogue, look and determine whether might be anabel normality that otherwise could have been spotted before. >> Correct and put a number to that in terms of a similarity value our probability values so that it's not just Mia's a collision, say Well, I think it's a little abnormal because it is hard to interpret that in terms of how severe is the spectrum of normal. How how? Sure you. So we put all these dated together. We can start to get more predictive value because we couldn't follow more kids and understand if it's that a a sima that too similar what's most likely disorder? What's the best treatment? So it gives you better FINA typing of the disorders that appear early and fetal life, some of which are linked to we think he treated, say, for example, with upcoming gene therapies and other nutritional intervention so we could do this characterization early on. We hope we can identify early therapies that our target to targeted to the abnormalities we detect. >> So intervene well ahead of time. Absolutely. >> I don't know. The other thing is, I mean Ellen has often times said how many images she looks at in the day on other radiologist, and it's it's amazing. It's she said, the number hundred thousand one point so you can imagine the human fatigue, right? So it Matt, imagine if you could do a quick pre processing on just flag ones that really are abnormal by you know they could be grossly abnormal. But at least let's get those on the top of the queue when you can look at it when you are much more able to, you know, think, think, think these things through. So there's one good reason of having these things sitting on an automated system. Stay out of the cloud over it might be >> Where are we with the roll out of this? This and kind of expansion toe, maybe other partners. >> So a lot of stuff has been happening over the last year. I mean, the the entire platform is still, I would say, somewhat prototypical, but we have a ll the pipelines kind of connected, so data can flow from a place like the hospital flowed to the cloud. Of course, this is all you know, protected and encrypted on the cloud weaken Do kind of weaken. Do any analysis we want to do Provided the analysis already exists, we can get the results back. Two definition we have the interface is the weapon to faces built their growing. So you can at this point, almost run the entire system without ever touching a command line. A year ago, it was partially there. A year ago, you had to use a command line. Now you don't have to. Next year will be even more streamlined. So this is the way it's moving right now and was great for me personally. About the cloud as well is that it's not just here in Boston where you, Khun benefit from using these technologies, you know, for the price of a cellphone on DH cell signal. You can use this kind of technology anywhere. You could be in the bush in Africa for argument's sake, and you can have access to these libraries of databases imaging that might exist. You, khun compare Images are collected wherever it might be just for the price of connecting to the Internet. >> You just need a broadband connection >> just right. Just exactly. >> Sometimes when you think about again about you know, we've talked about mobile technology five g coming on as it is here in the U. S. Rural health care leveling that and Third World, I was thinking more along the lines of here in the States and with some memories that just don't have access to the kind of, like, obviously platinum carry you get here in the Boston area. But all those possibilities would exist or could exist based on the findings that you're getting right now with Chris Project. So >> where does the Chris project go from here? >> Well, what we'd like to do is get more hospitals on board, uh, thinking pediatrics, we have a lot of challenge because there are so many different rare disorders that it's hard to study any one of them from one hospital. So we have to work together. There's been some effort to bring together some genetic databases, but we really need to being also the imaging bait databases together. So hopefully we can start to get a consortium of some of the pediatric hospitals working together. We need that also because normal for normal, you need to know the gender, the age, the thie ethnicity. You know, so many demographics that are nice to characterize what normal is. So if we all work together, we can also get a better idea of what is normal. What is normal variants. And there's a lot of other projects that are funded by N. H. Building up some of those databases as well, too. But we could put him into all into one place where we can actually now query on that. Then we could start to really do precision medicine. >> And the other thing, which we definitely are working on and I want to do, is build a community of developers around this platform because, you know, there's no way our team can write all of these tools. No, no, no, we want to. But we want everyone else who wants to make these tools very easily hop onto this platform. And that's very important to us because it's so much easier to develop to christen it just about the Amazon. There's almost no comparison. How much easier >> we'Ll Definitely theme, we hear echoing throughout Red Hat summit here is that Does that tie into, like, the open shift community? Or, you know, what is the intersection with red hat? >> It definitely does, because this is kind of the age of continue ization, which makes so many things so much easier on DH. This platform that we've developed is all about container ization. So we want to have medical by medical or any kind of scientific developers get onto that container ization idea because when they do that and it's not that hard to do. But when you do that, then suddenly you can have your your analysis run almost anywhere. >> And that's an important part in medicine, because I run the same analysis on different computers, get different results. So the container ization concept, I think, is something that we've been after, which is a reproduce ability that anybody can run it along there, use the same container we know we're going. Same result. And that is >> critical. Yes, especially with what you're doing right, you have to have that one hundred percent certainty. Yep. Standardisation goes along, Ray. Sort of fascinating stuff. Thank you both for joining us. And good luck. You're an exciting phase, that's for sure. And we wish you all the best going forward here. Thank you so much. Thank you both. Back with more from Boston. You're watching Red Hat Summit coverage live here on the Q t.

>> From the Salesforce Tower in downtown San Francisco, it's theCUBE covering Accenture TechVision 2019. Brought to you by SiliconANGLE Media. (electronic music) >> Welcome back everybody, Jeff Frick here with theCUBE. We're in downtown San Francisco at the Salesforce Tower, the 33rd floor, brand new Accenture Innovation Hub, five stories here in the building, the ribbon cutting this morning, and we're really excited to have our next guest. He's been on many times, I think the first time in 2013. Fresh off the plane from Davos, Paul Daugherty, great to see you. >> It's great to be here Jeff and thanks for joining us at this event. It's a really big day for us here. >> Absolutely, now I didn't get your title in, I give you Chief Technology and Innovation Officer. You're really at kind of the forefront, so let's jump into the TechVision. This is something you guys do every year. You pick five kind of big trends that we should be taking a look at. There's a lot of detail. People can (laughs) take their time to read through it. But, I just want to touch on some of the highlights. What are some of the big changes from when we sat down a year ago? >> We have five trends this year. The number of trends varies a little bit, but the, you know, I think the one key takeaway and highlight from the Vision this year is this idea, the big idea, that we're entering the post-digital era, and I think many people will be surprised by that. They'll go what do ya mean post-digital? >> When you said that earlier today, I'm like post? We're just right in the meat of it aren't we? >> Right, but just to contextualize that a little bit, last year companies spent 1.1 trillion dollars on digital transformation. 94% of companies are doing some stage of digital transformation. 68% of them said they're pretty well set with their digital transformation. >> They said they're set? >> They're in good shape. Now you can question it. >> Does that surprise you? >> I question it, yes, it surprises me, and we're not sure that that's entirely-- >> Accurate? >> Representative, >> That's okay. >> But nonetheless, what is true is that every organization is adopting digital, and the question we're asking in the Vision is if everybody's doing digital, what's going to differentiate you? And, we believe that that's the characteristics of the post-digital environment where what you did leading up to now isn't going to be enough to differentiate you and lead to success in the future. In the post-digital era, it's about some new business concepts about how you shape your business and new technologies and some new corporate obligations that are going to be instrumental in your success as an organization. >> I want to dig into that a little bit 'cause I think it's a really interesting conversation. At the ribbon cutting this morning, we had representatives from the city and county of San Francisco, a representative from, I think, San Francisco State academic institution, and you said in some earlier remarks today that the responsibility for the company has moved beyond kind of stewardship for their customers, stewardship for their employees and their shareholders, but really they've got to be kind of active contributors to the community. And, that's been kind of called out over the last couple years especially in the tech industry that hey, you can't just do this stuff willy-nilly. You got to kind of take responsibility for what you can do. >> Yeah, well put, and that's one of the key things that we've been talking about in prior Visions, if you'll recall. This year, it's a big theme. The importance of this is, it's not just because it feels good. It's not just because you want to create good headlines. It's instrumental to your business success to be responsible, to create trust with your workers, employees, consumers and citizens and people in the communities you live in, and I'll explain why. What's happening is, we're creating increasingly intimate technology-enabled experiences for consumers. Think about implantable medical devices to prevent epileptic seizures. Think about the monitoring devices we use. Think about the information that's collected on us. People swipe on Tinder 1.1 million times per second, 3.7 million Google searches per second, 178 million emails per second, 266,000 hours of Netflix tracking every pause, play, fast forward, yeah per second, 266,000 hours. There's so much information collected on us out there. Our information is being used in so many different ways, and the technology is enabling companies to create individualized services for you that are great for consumers, but they're only going to be great if companies build the trust with their customers to get that data from them and if they honor the boundaries of responsibility to make sure they can sustain those products and services. >> But Paul, you scare me to death because every day we hear this breach, that breach, this breach, that breach. It's almost now-- >> Three billion identities in 2018 alone stolen. >> That's half the world, right, or almost. So, it's almost like okay, that's going to happen. And now that you're getting all this additional information, now you can tie the information from my phone that I'm takin' eight trips to 7-Eleven a day and spending way too much time on my couch not movin' around and how those things are going to tie together. One, for kind of the ethics of how the information is used when they have it, and two, it is probably going to get breached. An amazing concept you talked about earlier today, a digital twin. We hear about it from GE all the time for a jet engine, but to have a digital twin of me in some data base, that's, uh, you know, it's with everything, right? There's a good side and a scary side. >> There is, but I think this is where the idea of trust becomes very important. We need to think about, companies need to think about these services and their consumers in different ways. A lot of people, including myself, in the past have used phrases like data is the new oil. Data's the gold of artificial intelligence in this digital age we're living. I think that's dead wrong, and we got to change the mindset. Data isn't fuel or gold. Each piece of data is a fragment of a person and represents a part of a person's activity and identity, and I think if you change your thinking that way, and if you take a view that it's not all about optimizing the use of data, but it's about carefully using data in the right way that builds trust and provides value for the consumer, and you get that equitable exchange of value, that's what the future's all about. >> Right, so one of the topics, and again, we don't have time to go through all of 'em here, and you're going to give a presentation later, it's kind of just the whole machine and human interaction and how that's evolving. Specifically, I want to ask in terms of the work world. We hear about RPA, and everybody should have their own bots, and you can have bionic legs, so that you don't hurt your back if you're doing lifting. So, as you guys kind of look at how these things are melding, it's going to be an interesting combination of people with machines that are going to enable this kind of next gen of work. >> Yeah, no it'll be interesting. I think the important thing that we need to really think about is that like anything else, all these technologies are being designed by us, and we're deciding how to use them. We're deciding the principals around it, so this is about how do we design the world we want which gets back to the theme around responsibility and such. If you look at it, we find that workers are actually optimistic about the technology. Two thirds of workers are positive and optimistic about how all this technology's going to improve their job to even increase career prospects, but only half of those workers believe that their companies are going to provide them with the right training and learning. When we're talking about the human plus trend in here, the human plus worker trend is that it's not a nice to have for companies to provide learning platforms and train their employees. It's critical to their success because the jobs are changing so fast, roles are changing so fast, that if you as a company don't invest in a learning platform to continuously advance your people to fill the new jobs as they're being redefined every day, you as a company are going to get left behind, and that's what we're talking about in the human plus trend of the Vision. >> Right, another thing we hear all the time in terms of how technology's advancing on accelerating curves and people aren't so good at accelerating curves, but very specifically how no one person in one particular industry really has visibility as to what's happening in all these tangential. What's happening in health care? What's happening in drugs? What's happening in logistics? I'm in the media business, so I don't know. You guys are really sitting in an interesting catbird seat because you can see the transformation and the impacts of technology across this huge front, and it's that movement across that front which is really accelerating this thing way faster than people realize I think. >> Yeah it is, and it's a great position to be in to be able to look across like that. The thing I would say though is that unlike other eras of technology earlier, we're seeing remarkably broad industry adoption of these concepts. It's a little different in each industry as you just said, but every industry is looking at this. The interesting thing to me is one of the most common requests that I get from CEOs and from the C-Suite is they want to pull together a workshop, and they want to talk about their strategy and where they're going, and very often, more often than not now, they're saying, and I want to hear from people outside my industry. I want to hear what's happening over there. If I'm in insurance, I might want to hear what's happening in retail, or you know, they want to hear about different industries because they understand that the change is happening differently. They want to make sure they're not missing a pattern that they could apply in their own industry. >> Right, so last question before I let you go. You're speaking all the time. You're talkin' to customers. You go to cool shows like Davos and get to hang out with other big-brained people, but you get to participate in all these things, and now you have this facility. What does the Innovation Hub and these resources enable you to do with the clients that you couldn't do as we sit here in this beautiful new facility? >> Yeah, that's a great question. It's something we've worked on really hard over the last four or five years. It's creating what we call our Innovation Architecture, and it's, what we think, a unique way of putting together capability from research and thought leadership to our Accenture Ventures which is our venture capital investing arm to Accenture Labs which is our R and D and inventors to our studios where we co-create with clients to our industry professionals, the 2,000 people here in Northern California that are working with our clients everyday, and we can put all that together to turn the idea, the research, into results very quickly for our clients, and I don't think anybody can do it in the same way we can by co-like-heading all this and by the sheer investment we put into this. We invest over 800 million dollars a year in research and development, over a billion dollars a year in training for our people, and that results in things like 6,500, 6,500 patents that we generate, more than anybody else in our sector, and 1,400 of those come from our people right here in the San Francisco Innovation Hub, so it's an amazing place for innovation right here. >> All right, well Paul, thanks again for taking a few minutes. I know it's a busy day. You're gettin' ready to go present the findings for people. Where should they go to learn more about the TechVision? >> Go to accenture.com dot, uh, accenture.com/techvision. I think at midnight tonight Pacific Time it'll be out there, but by the time they see this, they'll probably have access to it, thanks. >> Paul, thanks for takin' a minute and good luck tonight. >> Always fun, thanks Jeff. >> He's Paul, I'm Jeff, you're watchin' theCUBE. We're at the Accenture Innovation Hub in downtown San Francisco in the Salesforce Tower. Thanks for watchin'. (electronic music)

live from Las Vegas it's the cube covering AWS reinvent 2018 brought to you by Amazon Web Services Intel and their ecosystem partners hey welcome back everyone we're live here in Las Vegas with AWS Amazon webster's reinvent our 6th year I'm Jeff our table what they did six years two sets people rolling out of the keynote so much action we got another day coming tomorrow they're two great guests here we got dr. feci philomon is the general manager the machine learning and AI at Amazon Web Services and dr. Taha costs senior leader at healthcare and AI at Amazon guys welcome to the cube Thank You thanks itíd that you're here because I've been waiting to have this conversation Dave and I have been we just had an analysis of the distractions and glued up the stack around machine learning so much value now coming online that's been in the works around AI are really mainly machine learning that's creating a I like benefits and II just had to spend a lot of time with key nuts they almost a third of it around a I like capabilities and how Amazon integrates in from you know chipsets with elastic inference beautiful it's just good stuff so congratulations so what does it mean what does it mean for customers right now who want to kind of grok what's going on with Amazon and AI is that new sense the services coming online is that how long has been the works explaining yeah our mission at AWS has always been to take technologies that have been traditionally available for a few special technology companies and take that and make it available to all developers and we've done that I should say that we've done that fairly well when it comes to compute when it comes to storage when it comes to databases the analytics and we're doing the same thing for machine learning and AI and what we're doing because it's a new field is we've got to innovate at three layers of our stack to the bottom most layer as you saw in the keynote earlier has to do with frameworks and infrastructure so this is more for the people that fully understand how to deal with machine learning models and like to go in and tweak these models the middle layer then is for everyday developers and the data scientists and that's sort of where sage maker fits in and finally at the top layer of the stack is where we have our application services and this is meant for developers that don't want to get into the weeds of machine learning but they still want to use make use of all of these technologies to make their applications more smarter so they get the insight benefits get the insights have the day that without getting in town on the weeds exactly who want to get down in the weeds you can get down and dirty with all this other stuff yeah look at that right yeah and typically what we do with the top layer of the stack as we try and solve really hard problems and so customers can now take advantage of it because we've solved it for them and they can just take that and integrate it into their Apple quick what what's the hardest problem that you guys solve I mean traditionally speech recognition is a very hard problem that's one of the hard problems the other one is NLP natural language processing but I would say speech recognition is probably a hard problem and we just launched streaming transcription so you can now transcribe live as somebody speaks and of course you can connect it to translate and translate it as well live so great for our cute beers looking forward to having that on as a health care practitioner how does this all apply to that industry what kind of projects are you guys working on in that regard of course yeah so I mean to to posses point is want to continue to innovate on behalf of the customers across all layers of the stack machine learning in particular this week we launched Amazon comprehend medical particularly in a hardier heart problem where the majority of healthcare data is captured conversation and observations and unstructured formality so petabytes of data is stored across entire healthcare system that's a nun structure for form so to drive actionable insights and to be able to find the right elements to treat patients or to manage a population or even to do accurate billing it's been really an important that we can empower our customers with building blocks for them to build the right solutions to take advantage of that so Amazon comprehend Medical is able to understand the medical language and the context similar how clinicians understand the medical language and context for example if you're looking at a patient medical note Amazon campaign medicals able to with high accuracy extract medical conditions medications tests procedures being done on the patients as well as the relationship between those and understanding that context at this condition and this treatment go together as well as the nuances for example you know a patient has no family history of X or there's no smoking history all those are things in relation in the past or in the future or other members and this is really what we're really proud about launched an Amazon comprehend medical talk about how it works because you know I Healthcare has been a great field around where a is old-fashioned a is a queer when I wasn't doing it in the 80s early 90s ontologies were really popular and it's linguistics is kind of known but now that but you need that linguistics guru to do that he mentioned streaming the transcribed got metadata how do you guys get this kind of benefit when the balls moving so fast around these rapidly changing and verticals like healthcare because healthcare is got a big problem like other verticals where it's too many notifications what I pay attention to so much data how do you put the puzzle together let me first give you some context here as you probably we're at last reinvent we launched Amazon comprehend right comprehend is a text analytics service it helps you look into text and understand what's in there right we started out with general things that we could detect like people places things sentiment the language the text is written in and so on but when we started customers are picked on it and they're using it a lot but as they keep using it they came back to us and said hey it's great that you guys have this this you're giving us the capability to understand general language but some of our domains have some special language like jargon like yeah like take the legal domain for example right it's got charges and defendants and very particular things that are very relevant to the legal domain so they were asking us for a capability to sort of extend the comprehend to include their custom domain terms and phrases as well right so last week we actually launched a custom custom entities feature that allows them to bring in their custom domain into comprehend so the comprehend be extended to include their domain the so legal language is difficult to understand but medical language on the other hand is even more harder to understand that quick right acronyms jargon absolutely what is an entity looks like extracting that and extracting it uses alone yeah miss spells right but relating those entities together is super important because you could in one clinical note you could have multiple drugs in there with different dosages different frequencies and so you need to be able to relate those entities together right and that's the sort of thing that comprehend Medical allows our customers to do to solve some really so you're doing one of that entity extraction is under the covers is that right has it were I mean how does comprehending the medical work I mean just out of the box you have to train it there's no training meet needed know machine learning expertise needed so the algorithm extract these entities as well as the relationship between those entities and then also extracts any attributes that might be related such as negation or past and future or what's anatomy of the body relates one now all that is done out of the box and that's super important you want to know whether the patient's stopped taking a medication right yeah so negation things like that you want to know because that gives you the context just getting the terms alone doesn't really tell you much it each has had a great video about the f1 point of ethics imagine that for personal that's right you're not doing good right now take a break yeah so I feel like we're kind of now scratching the service of stress in the surface of health care yeah information yeah think about the health care industry for years it's been compliance-driven yeah whether it's hip Affordable Care Act yeah EMR and meaningful use right but the industry hasn't been you know dramatically transformed and disrupted and it kind of needs to be yeah how do you guys see that evolving I feel like you're now beginning to see that see change and that's going to take a while it's a high-risk business obviously but what's your sort of prognosis for that transformation and what's the vision as to the outcome yes now that's a really great question I mean one thing I mean one great things happen over the last decade is the digitization of your medical record so and that's really wonderful because before was all paper-based primarily unless you were an acute setting so now the majority of the US for example and globally there's this huge adopt adoption and propagation of these electronic medical records the issue there remains now when the majority of that data is observations and conversations as well as unstructured that that creates a different kind of roadblock for our customers and this is what we're hoping for service like Amazon comprehend medical that's HIPPA eligible means a lot of the early the compliance or help our customer meet their compliance needs that we'll be able to remove the heavy lifting of this undepreciated task about you know having in a large amount of time being spent on analyzing this text and extracting very low we're now with Amazon company and medical be able to really fast track that and be able to elevate it hit the nail on the head of the undifferentiated heavy lifting right that's the ethos of DevOps is that yeah let me give you some stats actually there are one point two billion medical documents that are generated every year in the US and 80% of them it's unstructured text so to make sense of that it's going to enable our customers to do some really amazing things one of the things one of the use cases that we see is its clinical trial recruitment so Fred Hutchinson which is one of the yeah the nation's top cancer research centers they recruit patients for clinical trials if you go to clinical trials.gov you'll see like 290 thousand four and 50 clinical trials open and typically from history we know that most of these clinical trials don't end up recruiting they don't end up meeting their recruiting goals because it's very hard to figure out which patients fit the clinical trial that you're actually trying to perform so comprehend medical helps these customers to very quickly narrow it down expand on the involvement of people in the community mentioned Fred hutch Roach has also been involved what I heard yeah what who was involved in this project sound it was a collaboration take a minute to explain that right I mean it's very similar to a lot of other services that we put it into the market we collaborate a lot with customers 90% of what we do is really coming from customers so we've collaborated with people like Fred hutch and some of the nation's top institutions to help us validate the service that we've built to actually make sure that its meeting sort of the requirements for those use cases that they are thinking of so we collaborate closely with them to get the service to where this today and we announced it as generally available yesterday ok so what's the use case I'll go ahead yeah I can expand a little bit some of the customers as well their use cases we're talking anywhere from hospital systems that when I use or take advantage of their unstructured text for things such as identify people who are for their follow-up appointments or stopping treatments or find an alternative routes to billers we're trying to identify it is accurate procedures were done if we account for all the procedures or care for all the billing which often time is hidden in those unstructured text and require a lot of manual process and often time the rules that can't really scale to things such as clinical trials recruitment how can you if example in Fred Hutchinson Cancer Institute use case for identify a patient and match them to the right clinical trial these patients often time have Harry Potter's worth of clinical notes down on the minute their longitudinal journey and to go from one institution another another and be able to really find it's no longer needed a haystack it's like a needle in the bottom of Atlantic Ocean and then be able to really do that match from hours and months down to a few seconds and that's really the beauty about the service John likes to talk about the 20 mile stare and I wonder if we could just look ahead how far can we take AI and machine learning in in healthcare and how far should we take it and maybe a more specific question as as a practitioner you know when do you think machines might make better diagnosis than doctors if ever how do you feel about that where do you see this all going I think I mean the whole idea about machine learning the beauty about it I mean the seta scope was introduced or how the thermometer was introduced in medicine and these are tools that we use to our advantage to really provide better care and and better outcomes and that's really what we're that's the mission that our health IT and customers and wanna are really driving tower's machine learning can do a lot of great things for routine things that human being can't can go and focus their attention to other things such as the Fred Hutchinson instead of going and mining these diagnoses in mountain amounts of data a machine learning will be able to identify that with a clinical staff can focus on care and that's really where I think I mean over the next decade and so we can see a lot of this advancement in in these building blocks as well as what Amazon's offering from forecasting and prediction algorithms Rana will be able to find you know fine-tune our capabilities to help customers achieve even precision medicine real-world impact because you're changing the workflow I mean someone's within the wrong line or the wrong process based upon their history yeah HIPPA HIPPA requirements really cause a lot of this record sharing thing to be a problem from what we've been reporting over the years it's kind of a solution to that so if I move to a service medical service I get all that records with me it's just kind of how you see going and how does other regulations that are holding you back that are blockers is that clear now how does that solve the industry challenge it's of privacy and if you look at the healthcare system today there are lots of inefficiencies in there right in the end this is all about improving patient outcomes and making sure that we reduce costs and that's what this boils down to and these are tools that allow our customers to do exactly that well guys thanks for sharing this insight comprehend medicals really awesome opportunities I think it's early days day one is you guys think right I think there's so much more that could be there I'd love to see the industry just from the personal is decided change it's just get out of the way of all these pretty broad hurdles get the data out there expose the data check the privacy box would be good right this is gonna change the game yeah maybe we should say a little bit about the how we built the service in terms of that right as you know at AWS security and privacy is number one for us right so this service is HIPAA eligible it's a stateless service what that means is nothing gets stored this is not the data is not used to improve the models or anything like that the only person that can actually see the data is the customer he's got the keys he's the only one that's sending the data to the endpoint and whatever he gets back only he can decrypt it so we've taken care to make sure that we can remove some of those hurdles that people have always been worried about well doctors take you so much for sharing thank you so much for having us here we are bringing you all the action here from 80s reinvent again as the compute power is increased as software is written with new apps a eyes changing the game of course the cube a lot of video we don't need some of these services to make these transcribes on the fly they succumb and I really appreciate it you think back on the more after this short break [Music]

>> Announcer: Live from Washington D.C., it's the Cube. Covering .conf2017. Brought to you by Splunk. >> Welcome back, here on the Cube along with Dave Vellante, I am John Walls. We're live at .conf2017, as Splunk continues with day two of its get together here the nation's capital, Washington D.C. Home game for me, I love it. Dave's up the road in Boston, so, hey, you had to hit the road a little bit, but not as bad as it can be sometimes for you. >> No, I'll take D.C. over Vegas. Sorry, Vegas. >> Yeah, but you travel a lot, man, you do, you're on the road. Chris Kurtz travels a lot, too. He's come with us from Arizona State University, he's a systems architect out there. Chris, always good to see you, we had a chance to visit last year for the first time. >> Yep. >> A member of the Splunk trust. And a gentleman with quite a diverse background, I mean. You supported Mars missions. As far as the... >> The Spirit and Opportunity. >> Facilitated out in Phoenix. Working now, as you said, at Arizona State, but also the Trust. Let's talk about that a little bit, because there was some conversation yesterday from the keynote stage about expanding that group? >> Absolutely. >> Adding 14 new members. And for a lot of people at home, who might not be familiar with the Splunk trust, talk about the concept and how you put it into practice. >> Absolutely, so, the Splunk trust is the organization that Splunk set up as a community leader, as a community activist. Our, kind of, watch word is, is that, "We're not the smartest people in the room, "but we'll be the most helpful." and, so, our purpose is... >> John: I'm not sure about that first part, too, by the way. >> Thank you, very much. >> John: I think you're short-changing yourself. >> So, our organization preface is we act as members of the community to help direct community people who have issues and help them externally, but also, to help Splunk and what direction they should go. "Hey, we see this pain point from a lot of the customers, "this is something that maybe Splunk should concentrate on." We're often given access to betas or even earlier, or, you know, even potential products. It's, "How should we build this, is this something that "you would use? "Is this something that you would like?" Table data sets was a feature that I worked on for a year, that was released last year. You know, "Is this something that you would use, "is this something that you would want?" and, sometimes, you know, users fall through the cracks in the support system and they don't know how to get support help, or they don't know where to get directed, and we can volunteer and say, you know, "Show them where the Splunk answers group is very powerful." There's an app for that, we can show them Splunkbase and help them when those things fall through the cracks. So, we provide community enrichment and support, but we're not an official representative of Splunk, even though we're appointed by Splunk on a year-to-year basis. >> John: There aren't that many of ya, right? >> Well, there's a couple, 42 this time. And, you serve for a year and it can be renewed each year, you reapply. Or you can be volunteered, you know, somebody else can... >> Nominate you. >> Can nominate for us. And there's no guarantee. We, the members of the trust vote and then that goes to Splunk and Splunk makes the final decision. Some companies allow that, some don't, it depends. ASU is very generous and let's me participate and give them my time to the organization. >> And I said ASU, Arizona State University. >> That's what I was thinking. >> I never fully introduced that, I'm sorry. >> What do you have to do to qualify and what's the hurdle? >> So, be the most helpful person in the room, that's what you need to do to qualify. So you need to be a part... You can't work for Splunk, you have to be a partner or a customer, and you need to give to the community in some way. So, you need to give back to the community. You participate on Answers, which is the online, kind of, self-support forum. You need to speak in the community, maybe run a user group, a lot of us do run the user groups. I run the user group in Arizona. And, you need to be respected amongst the community and, people go, you know, "I want to go to them, "they'll help me or at least get me to the right person." >> Is it predominantly or exclusively technical practitioners, or not necessarily? >> This year, they divided us in to, kind of, organizational units, so there's architects, and practitioner, and developer. So, we're all technical, but, this year we're going to have the ability to focus a little more on a specific area. You know, "What do you do for a living, "what do you do with Splunk? "Do you architect with Splunk internally, "do you just provide Splunk practice? "Are you a Splunk developer that makes apps? "How do you use Splunk on a daily basis?" And, again, there are partners as well. So, Aplura and Defense Point, I think, are both tied with four members a piece. So that's one of those things that, you know, they're going out to individual customers and helping them everyday. >> So, it's really taking this notion of a customer advisory board to a whole another level. I mean, it's not a passive, you know, group of people that, maybe, meets once a year. >> Right. >> It's an ongoing, active, organic institution essentially. >> Absolutely, we have quarterly meetings online and at those meetings a different Splunk, sometimes executives, sometimes product managers or engineering managers, you know, come and speak to us. And it can be anything from, "Hey, we're developing this "internal product and are we interested, you know, "is that useful to you?" Or, "What enhancements do you feel the product need?" Or, you know, "This is a new feature we're working on "to look and feel." I was consulted about the conf logo. "Hey, Chris, you're an average customer, "which of these four logos do you think really, you know, "kind of helps set the mood?" And, you know, did they take my advice? Does it really matter, no, but they were willing to just... I'm not associated, I'm not in the bowels of the company. >> So this isn't your logo over here? >> That is actually the one that I chose. >> Oh, excellent, I would assume so, right. >> Who organizes the quarterly meetings? >> So, the quarterly meetings are organized by Splunk in the community. There's a community group that's underneath Brian Goldfarb, who's the Chief Marketing Officer. So, he organizes the quarterly meetings. He gets to herd all the cats, because we're all across the world. You know, you have to figure out a time zone, you have to figure out where, you have to figure out when. But, most of the time, there's some suggestions. "Hey, you know, the engineering manager "for section x would like to speak." But, sometimes it's like, "Yeah, we would like to talk "to the person in charge of Search Head Clustering," for example. "We see some pain points in the community," or something like that, so, it's wide-ranging. But, you know, we're not just a group to rubber stamp anything that Splunk does, but we're also not a group to just sit there and complain about things we don't like. It's really very much a give and take. Splunk is generous and open enough to give us that access, and we take that very seriously. To be able to help guide Splunk in making their product the best it can be. It's an amazing product, I'm an evangelist, have been since I started using it. But, also, to help the customers. If the customers are having a pain point, we're probably going to hear about that first. >> Dave: When did you start using? >> I've been using Splunk for about five years. And when I started using Splunk at ASU, it had been a 50GB license and they'd just bought another 100GB, and it needed re-working, it needed architecting. So, when I came in, our chief information security officer and our VP for operations are the ones who directed me. And I said, "What do you want to grow for?" And they said, "Architect it for a terabyte, "assume it's going to take us several years to get there." So, I rebuilt the current environment and we architected it for a terabyte and here we are, four-and-a-half, five years later, we're at a terabyte. And, we're still growing and we're looking at Cloud, you know, we're looking at other use-cases. I think the biggest ship for us is that, we talked about this briefly last year, is that I work for John Rome, who's the Deputy CIO for Arizona State, and he's in charge of business intelligence and analytics. So, it is an enterprise application for data at ASU. It is not part of the security office, it's not part of operations, it's not part of depth. Those are all customers. And, so, internally those are customers and I think that's an amazing opportunity to say that, "Those are customers of mine." So, I'm not beholden to, you know, building the system so it's only useful for security, or building it so it's only useful for operations. They're my customers, and we avoid any appearance of, "Oh, I don't want to put my data in a security product. "I don't want to put my data in an operations product." Nobody questions putting their data in the data warehouse, that's the appropriate place for the data to go. So, that's the beauty of the system that we've developed, is they're both customers of mine. >> All right, so let's talk about your work at Arizona State, little bit. I don't know the size now, I'm trying to think of it, a huge... >> Chris: We're the largest single university in the United States. >> Probably what, 60,000-70,000? >> Total enrollment 104-110,000. A lot of that's online, I think we have about 78,000 or more at the main campus. But, we're the single largest university in the U.S. There are groups like the University of California that's larger overall, but not single institution. >> So, you know... >> Massive. >> Big project, yeah. Where are you now, then? What have you been using Splunk for that maybe you weren't last year when you and I had a chance to visit? >> Yeah, so, we started using it as a security product. It was brought in to make security more agile in getting that information from the operations and the networking groups, firewalls was the first thing we were brought in for. Now, we're starting to look at other use-cases, we're starting to look at edge cases. "Are we using it for academic integrity?" So, the very beginning so that we're looking at, "If a student is taking a test, are they the person "taking the test?" We're looking at it to make sure the students' accounts are safe and not compromised. We're looking at rolling out multi-factor to the university and being able to protect that. And, we're taking a lot of those functions and pushing them down to our help desk, so the help desk has all of the tools they need to be able to support the student and take care of their issue on the first call. That's really important, we have an amazing help desk organization, amazing care organization. And that's the goal is, it doesn't matter how long the call takes, you do that on the first call. And Splunk is a key portion of that to be able to provide them with the right information. And they don't have to go and try to get somebody from network engineering just to solve the student problem, they can see what the problem is from the beginning. >> Academic integrity, explain that. >> Yeah, so, you know, I don't think that there's any student who doesn't want to do their own work and do the best possible thing they can. But, sometimes, students get in a position where they need some help and, maybe, that isn't always exactly what they should do. So, you need to make sure that the student is taking the test that they're signed up for, that they didn't have any assistance, especially in online classes. We need to keep our degree important and valid, and, obviously, none of our students want to, but occasionally you find somebody who hasn't done exactly what they're supposed to. And we need to be able to validate that. So, we need to be able to validate that someone did what they said they did or did the work that they said they did. It's just like, nobody wants to plagiarize, but, occasionally it does happen and we need to protect ourselves and protect the students. >> And you can do that with data? >> We can absolutely do. >> You can ensure that integrity, how? Explain that a little bit. >> A little bit, yeah. So, we look at where the student logs in from. If the login routinely from Tempe, Arizona and then, suddenly there's a login from someplace else. Oftentimes, that has nothing to do with academic integrity, that has to do with there is an account compromise. We need to protect the students' personal information, both HIPAA and FIRPA. We need to protect their privacy information, just generally available PII. So we look at when they logged in, where they logged in, how they logged in. Did the how-to factor worked? I think academic integrity is really a much smaller portion of that, I think the more thing is we need to protect those students. So, we look at how they logged in, when they logged in, what type of machine they logged in from. I mean, if you're using a Surface and you've been using a Surface to login for months and then, all of a sudden, you login from an iPhone, you might have gotten a new iPhone, but, you know, you might not have. So, we put all those pieces of information, all those launch together to build a case that, "Do we need to reset this user's password for safety?" >> But I think academic integrity's important from the brand as well, because the consumers of your students, the employers out there, they may be leery of online courses. So, to the extent that you can say, "Hey, we've got this covered, we actually can ensure "that academic integrity through data." That enhances the value of the degree and the ASU brand, right? >> Absolutely, we don't think that any student wants to do anything that they're not supposed to. It does happen, you know. >> But even if it's one, right, or even if it's the perception of the employer that it can happen? >> John: The possibility. >> Yeah, and I think that's a really good point, is that we need to protect that brand and we need to protect the students. I think protecting students is the number one thing, protecting employees is the number one thing. Everything else falls from that. >> Okay, what about other student behaviors? I mean, you're sort of trafficking around campus, maybe, food consumption, dorm living, I mean, all these kinds of things that with sensors or, what have you, you could extract reams of data? >> We're doing a lot of that. We're partnering with Amazon to look at the Amazon Echo and using them in dorms to provide them voice interface. "Echo, where is my next class?" Or, "What time does the Memorial Union open?" Or, "How late can I get a pizza," and that type of thing. We want to build an environment that's not only fun for the students, but very powerful, and uses the latest technology. >> Pricing, I want to talk pricing, all right? I dig for the one little wart in Splunk and it's hard to find. But, I've heard some chirping about pricing because pricing is a function of the volume of data. The data curve is growing, it's reshaping. What are your thoughts? What do you tell Splunk about pricing? >> So, a lot of people say, "Man, Splunk is expensive." And, I don't think Splunk is expensive. Once you've achieved a volume, it's got a good pricing structure. I think that anything that Splunk tries to do to change the pricing model is a bad direction. >> Dave: So you like it the way it is? >> I like it the way it is. I believe that we've made an investment in a perpetual-licensed product and I certainly don't think that what we're spending on it, for a maintenance year is a bad thing. And i think that we get a good value for the product. And we're going to continue to use it for years to come. >> I've always felt, like, "Your price is too high," has never been a deal-breaker for software companies. They've generally navigated through that criticism. And it's been, you know, ultimately an indicator of success more than anything else. But, your point is if the values there, you pay for it. Are you able to find ways to save money using Splunk that essentially pay for that premium? >> Absolutely, so one of the very first things we did with Splunk, is we looked at our employee direct deposit, we talked about this briefly last year. We looked at employee direct deposit and we were being targeted by a Malaysian hacking group who was using phishing emails to phish credentials from us. You know, you send an email that looks very much like a university login and says, "You need to login "and change your password or you're not going to be able "to work in an hour." A lot of employees, especially employees in areas that aren't high tech, you know, in the psychology department, they may fill-in that information and then the hackers login and change their direct deposit. And then the university ends up paying the employee again and eating those costs. Our original use-case was on-the-fly, we saved $30,000 in a single payroll run. Pretty easy to pay for Splunk when you do that. And so, that was our very original use-case. And that came from just looking at the data. "Is this useful, where are these people logging in from?" There's a change, you know, and I think that that's very important. The thing I love about Splunk is, because it's schema on demand, because there's no hard schema, and that it's use-case on demand. Is that, every single good use-case in the very beginning was standing around the water cooler, having a drink and saying, "I wonder if combine data set A, "we combine data set B, we come up with something that "nobody was asking about." And now when we something that we can help fix, we can help grow, we can make more efficient. To the question of how you deal with all that data is, you tune, you decide what data is important, you decide what data is unimportant, you clean up the logs that you don't care about. And we spent a year, we didn't buy Splunk for one year, we didn't buy a new license, or didn't buy an expansion license, because we took a year to compact and say, "Okay, all the data we're getting "from this firewall, is that all necessary, "is there anything redundant?" "Does it have redundant dates, does it have redundant "time stamps, et cetera." >> Right. >> And I pulled that information out and that just gave us a little bit of breathing room, and then we're going to turn around and take another chunk. >> Help. >> No schema on right sounds icky but it's profound. >> You mentioned the word, help, again, big word, key word. Chris Kurtz, one of the most helpful guys in the community of the Splunk. >> Thank you very much. >> Thanks for being with us, Chris Kurtz. Back with more, Dave and I are going to take a short break, about a half-hour, we'll continue our coverage here live at .conf2017. (upbeat music)