(upbeat music) >> Hey, everyone. Welcome back to New York City. Lisa Martin and John Furrier with theCUBE here live covering the AWS Summit NYC 2022. There's about 15 different summits going on this year, John, globally. We're here with about 10,000 attendees. Just finished the keynote and two guests from SoftwareONE. Please welcome David Torres, the director of cloud services and Asim Khan, a North American AWS services delivery lead at SoftwareONE. Welcome, guys. >> Thank you for having us. >> Thank you for having us. >> Talk to us, David, kick us off. Give the audience an overview of SoftwareONE. What do you guys do? And then tell us a little bit about the AWS partnership. >> Sure, so SoftwareONE, we are one of Microsoft and VMware's largest resellers. We help customers with our IT asset management services, managing their on-premises license real estate, but we're definitely a company that's undergoing a transformation. And when I say that, essentially we're focused on three key pillars with our go to market, supporting the hyperscalers. So we do support AWS, Azure, GCP at modernization because we do see this with a lot of our customers, you know, they're moving from on premises to AWS. They have a lot of technical debt and they're looking at options to modernize that, and mission critical workloads like SAP, Windows, Oracle, and we offer, you know, a suite of professional services, managed services, migrations, quite quite a bit of services. >> Asim, can you kind of double click on the services that SoftwareONE delivers to customers? Maybe some key use cases? >> Yeah, sure. I think in the Amazon space, I would say we're currently focusing in the area of funding programs that Amazon currently has, for example, the Migration Acceleration Program, which is a map with supporting customers basically with the entire cloud journey that they might have, or helping them define that cloud journey. And then we can help the customer in any phase of that journey as well to basically take them a step step above. So that's what our area of focus is right now to basically help enable customers. >> So on the Microsoft, AWS, you mentioned Microsoft, I mean, they've had the enterprise business for years and, you know, developers was their, you know, ecosystem. Back in the day, "Developers, developers, developers" as Steve Ballmer once said, and that was their crown jewel. But then, you know, .NET now has Linux. They got a lot more open source. So those enterprises, their customers are changing. A lot of them are on AWS. So talk about that dynamic of the shift to AWS. And now that Azure's out there, what's the relationship of those hyperscale? How do you guys navigate those waters? >> Sure, I mean, it's always the concept of work backwards from the customer, right? What are the business outcomes they're trying to drive and, you know, define a strategy from that. And it's still a function of change management for a lot of customers, people, process and tools. So, you know, in a lot of cases, our customers are evaluating what's a skillset of our people, do we need to upskill them, the tools that we're using, how do we use those on the multiple clouds, right? And then the processes. So for us, you know, we have some customers that prefer one cloud over another. We have customers that run cross multiple clouds. They deploy different workloads. And then we have some customers that transformation and modernization are really big top of stack for them. So in some cases, those customers are going to AWS and, you know, we're helping them kind of with that journey. It's interesting, Amazon literally won the developer cloud market early on, going back 15 years. >> Absolutely. >> But not all developers, enterprise developers who, you know, in the enterprises, they're stuck in their ways, but are changing. This is a digital transformation moment 'cause cloud native applications, the modernization piece, is developer centric. >> Absolutely. >> That's key, the developers. So I'm interested in your perspective and reaction to what's going on in that developer market right now with DevOps exploding in a great way, the goodness of the cloud coming more and more to the table. >> Sure, no, absolutely, great question. So I think with enterprise developers, you know, we see just the businesses driving a lot of the outcomes, right? So the modernization aspect of needing to get to market faster, needing to deploy applications faster, having a more efficient operating model, more automation. And for your point on the .NET modernization, you know, we work with customers too as well. We made an acquisition a couple years ago, a company, InterGrupo. They actually specialize in this in .NET modernization. So we know we're seeing some customers that are moving to Linux, right? And they want to go .NET Core and, you know, they're kind of standardizing on Linux. So we kind of see a, you know, wide spectrum, but yeah, maybe. >> Where are your customer conversations as things have changed so much in accelerated dramatically in the last couple of years? >> Sure. >> Obviously we've talked about the developers, but talk to me about, you know, business imperatives for businesses in every industry to digitally transform, number one, to survive the last couple of years, but, two, to be at a competitive advantage. >> Sure, no, so I think with businesses, you know, obviously, 2017, innovation, 2022, it's a little bit different, right? There's obviously macro conditions, you have COVID. So, you know, we're seeing where customers are essentially really doing their due diligence, right, when they make their choices more than ever before. And they're trying to maximize, right, their spend and their ROI when they move to cloud and that involves, you know, the licensing advisory, what they can move, what they can modernize, migrations, and just the roadmap and what strategy. But what I see is, it's the business outcomes, what they're trying to drive, and, you know, we're seeing some trends too with maybe a more conservative segments like healthcare, public sector, right, utilities that they are really investing and moving towards the cloud. >> Asim, I got a question from Twitter, a DM, I want to ask. You guys are on the front line. So you see the customers, which is really great 'cause it's primary data. You guys are right there. And you're not biased. You work with whatever hyperscaler. So it's really good. So the question that came up was, "Can you ask them the following, 'What's going on in the data warehouse front, cloud warehouse front, you got Redshift competing with Synapse, Azure Synapse, Google BigQuery, and then you got Snowflake and Databricks out there?'" So you got this new data provider, but it's not a data warehouse. And you got data refactoring on AWS, for instance as well. So, you know, this whole new level of data analytics with how you're doing cloud data. And you call it a data warehouse, I guess for categorically, but it's really not a warehouse. It's a data lake and you got lake front foundation. What are you guys seeing on the front lines with customers as they try to squint through how to deal with the data and which cloud to work with? >> That is a good question. I mean, I've been in the industry a long time. I've worked for some major financial institutions as well and data or big data was big for that industry. (John chuckles) So I've seen how the trends have changed, but from our perspective, because we are an agnostic services company, as you mentioned, we basically can work with any hyperscaler, we initially see what the business needs are for the customer. If the customer is already, for example, using Amazon, we initially want to have the customer use native tooling available within that hyperscaler space. If the customer is open for us to give them any recommendations, of course, we look at the business needs. We look at what type of data is going to be stored. What the industry is. Based on all of those inputs is when we basically give the right recommendation, it could be a third party data warehousing solution. It could be an area one. It all depends on what the business needs of the customer are. >> So for example, and most companies do this they build on say AWS, who is one of the first big clouds. And then they go, "Hey, we got customers over there at Azure, that's Microsoft they got thousands and thousands of customers. Snowflake's done, and they have marketplaces as well." So you guys are kind of agnostic it sounds like. Whatever the architecture is on the stack that they choose. >> Correct, so that's what makes us special. I think we are one of those services companies which is quite unique in the industry. And I don't say that just because I work for SoftwareONE, (John chuckle) that is a fact that gives us a very unique perspective of giving the customer the right piece of advice because we've seen it all and we've done it all. So that's, I think what puts us unique and regarding technology, all the different hyperscalers, they might have a very similar backend technology stack, but what the front end services each hyperscaler is building are very unique. Amazon being the leader in this space, they've been ahead of the curb by a few years, they will always have certain solutions which are above the rest. So I mean, I've always been an Amazon person, so I'm slightly biased, but, hey, I mean, I'm not complaining about that. >> The good news is the customer has choices. >> Right, absolutely. And we do see customers that want to be agnostic, right, >> Yeah. >> With their technology choices. Actually, that's a good segue about our partnership with AWS. We recently signed a strategic collaboration agreement between both parties. So there's going to continue to be big investment from us, scaling out our professional services, our practice areas, and then also key focus area for a fin ops. >> Is that your number one area? >> It's one of the areas, yeah. >> Okay, what your top three practice areas? >> Top three, mission critical workloads. So enterprise workloads like SAP, Microsoft, Oracle, two, app modernization, and, three, definitely fin ops and the hyperscalers, right? Because we see a lot of customers that have already heavily adopted cloud, they're struggling with that cloud financial management aspect. >> So if they're struggling, what are some of the key business outcomes that they come to you, to SoftwareONE, and say, "Help us figure this out. We have to achieve A, B, C." >> Sure, so depending on the maturity of the customer and where they are in the journey, if they're already very heavily adopting cloud, you know, AWS or Azure, we see in a lot of cases that the customers are unsure if they're getting the most out of their cloud spend, and they're looking at their operations, and their governance, and, you know, they're coming to us and basically asking us, "Hey, we feel like our cloud spend is a little bit out of control. Can you help us?" And that's where we can come in, you know, provide the advice, the guidance, the advisory but also give them the tooling, right, to have visibility into their cloud spend and make those conditions. And we also offer a managed fin op service that will end to end do this for the customers to help to manage their resale, their invoicing, their marketplace buy, as well as their cloud spend. >> So obviously the engagement varies customer to customer. What's a typical timeframe? Like how long does it take you to really get in there with a customer, understand the direction they need to go, and create the right plan? >> Sure, again, comes back to the cloud journey. You know, if the customer is still, you know, very much on prem and maybe more, you know, conservative, it may start with licensing assessments just to give them an idea of what it would cost to move those workloads, right? Then it turns into migration modernization, you know, it can be an anywhere from one to six months, you know, of just consulting, right, to get the customer ready. And then we help 'em, you know, obviously with their migration plan. But if they're already heavily adopting cloud, you know, we do remediation work, we do optimization. Obviously, SAP, that's a longer cycle, so. (chuckles) >> So I got to ask you guys, what is the PyraCloud? SoftwareONE as a platform PyraCloud. What is that? >> I might want to answer that. >> Sure. (chuckles) >> It's pronounced PyraCloud. >> How do you pronounce it? >> PyraCloud. >> PyraCloud, okay. I like PyraCloud better. (chuckles) >> With the Y in there. It's basically our spend insight platform. It gives customers an a truly agnostic single pane of glass view into their entire cloud enterprise spend. What I mean by that is with a single login, the customer has access to looking at their enterprise spend on AWS, on Azure, as well as GCP. And in the future, of course, we're going to add other hyperscalers in there as well. Because of the single pin of glass view, the customer has a true or the customer leadership, or, for example, the CTO has a single pane of glass view into the entire spend. We allow the customer to basically have an enterprise level tagging strategy, which is across all the hyperscalers as well as then allowing a certain amount of automated cost management as well, which is again agnostic and enterprisewide. >> Can you share an example of a customer for whom you've given them this single pane of glass through PyraCloud, and by how much they've been able to reduce costs or optimize costs? >> Yes, mostly the customers who would be a very good fit for PyraCloud would be a slightly more mature customer who already has a large amount of spend, or who is already very mature in their different hyperscalers. And usually what we've seen once a customer is mature in the cloud over a certain period of time, controlling costs does become difficult, even though you might have automation in place, but to get to that automation, you have to go through a certain amount of time of basically things breaking and you fixing them. So this is where per cloud becomes very helpful to help control that. And building a strategy, which once in place is repetitive and helps you manage costs and spend in the cloud year after year then. >> One of the things I want to get your guys reaction before we wrap up is this show here has got 10,000 people which is a big number, post COVID, events are coming back but in the past five years, or six years, or seven years, since like 2015, a lot's changed. What's changed the most? Shared to the audience what you think is the biggest step function change that's happening right now? Is it that data's now prime time? Everyone's got a lot of data, hasn't figured out the consequences with it. Is it scale? Is it super cloud? Is it the ecosystem because this is not stopping ,the growth in the enterprise on the digital transformation is expanding, even though GDPs down, and gas prices are high, and inflation, this isn't stopping. Now, some of the unicorns might be impacted by the headwinds, the big overfunded valuations but not the ecosystem. What's changed? What's the big change? >> Well, I think what I see is this cloud is becoming the defacto operating model and customers are working backwards from that as their primary goal, right, to operate in the cloud. And as I mentioned before, they really are doing due diligence, right, to really understand the best approach for seeing kind of maybe some of the challenges other customers have had when they first moved to AWS, so. And I'm, you know, seeing industries that maybe five years ago, you know, were not about moving to cloud, like healthcare. I can tell you a lot of our healthcare customers, they're trying to get to cloud as fast as possible. >> It's a wake up call. >> It's a wake up call. >> Absolutely. Absolutely. >> Asim, what's your reaction? >> In my point of view with what's happened these last few years with a lot of companies having their employees work from home and being remotely, I think end user compute was one of the big booms which happened about two years ago. We support a lot of customer in that space as well. And then overall, I think we actually saw that there was much more business focus with employees working for home for some reason. And we saw that internally in our own organization as well. And with that focus, the whole area of being more lean and agile in the cloud space, I think became much more prevalent for all the enterprises. Everybody wanted to be spend conscious, availing the different tools available in the cloud arena, like autoscaling like using, for example, containerization, using such solutions to basically be more resilient and more lean to basic control costs. >> So necessity is the mother of all inventions >> It is. >> That got forced. So you got wake up call and then a forcing function to like, okay, but exposes the consequences of a modern application, modern environment because they didn't, they're out of business. So then it's like, okay, this is actually working, (chuckles) why don't we like kill that project that we've doubled down on, move it over here." So I see that same pattern. What do you guys see? >> Yeah, no, I mean, we see that pattern as well. Just modernization, efficiency. You could just move faster, more elasticity, you know, and, again, the wake up call, you know, for organizations that people couldn't go to data centers, right? (chuckles) >> Yeah. (chuckles) >> We actually have a customer, that was literally the reason they made the move, right, to AWS. >> And I would add one more thing to that particular point. With the time available, I think customers were able to actually now re-architect their applications slightly better to be able to avail, for example, no server type of solutions or using certain design principles which were much more cost lean in the cloud. That's what we saw. I think customers spent that time available over the past couple of years to be much more cloud centric, I would say. >> Yeah, the forced March was really an accelerant and a catalyst in a lot of ways for good, and there's definitely some silver linings there. Guys, we're out of time. But thank you so much for joining John >> Oh, awesome. >> And me talking about SoftwareONE, what you guys are doing, helping customers, what you're doing with AWS and the hyperscalers. We appreciate your time and your insights. >> Thank you. >> Awesome. Thank you for having us. >> Thanks for having us. >> Really appreciate it. >> All right, for our guests and John Furrier, I'm Lisa Martin. You're watching theCUBE live from New York City at AWS Summit at NYC. Stick around, John and I will be right back with our next guest. (upbeat music) (upbeat music continues)

>> Announcer: From around the globe, it's theCUBE with digital coverage of AWS reInvent 2020 sponsored by Intel, AWS and our community partners. >> Hi, and welcome to theCUBE virtual and our coverage of AWS reInvent 2020. I'm your host Rebecca Knight. Joining me is Sachin Dhoot, he is the vice president for data and platform engineering at Ellie Mae. Thank you so much for coming on theCUBE, Sachin. >> Nice to be here. >> So we are talking today about Ellie Mae's journey towards data monetization. Before we begin though, I want you to give our viewers a little bit, tell our viewers a little bit about yourself and your role at Ellie Mae. >> Sure. So I'm the vice president for data and platform engineering at Ellie Mae. A little bit about Ellie Mae before I talk about myself. So Ellie Mae, which is now part of ICE Mortgage Technology, a division of Intercontinental exchange is the leading cloud based loan origination platform for the mortgage industry. Our technology solutions actually enable lenders to originate more loans, lower origination cost and reduce the time to close. Or when ensuring the highest degree of compliance quality and efficiency. Our mission as we call it here internally is to automate everything 'automatable' for the residential mortgage industry. So that's what we do here. And we take great pride in doing that. >> Everything automatable, I love it. >> Yes. And if you have gone through the mortgage process, you'll see the number of papers you have to sign. And so we are on the journey to automate as much as possible in this. So as part of this, my charter here so I'm the vice president of data and platform engineering. Like I said, I lead and I'm responsible for all AWS based platform and data solutions including our highly secure, scalable data platform and the global, literally. Just to give you a magnitude of how much data we are talking about; so currently Ellie Mae in its platform stores data of nearly 50% of all US for mortgages. So that's the scale which we are talking about and I'm responsible for having the AWS based data platform to support that. >> So in terms of the data monetization journey like most innovations, it starts with a problem. What was the problem that you were trying to solve here? >> Yes, that's a great question. So earlier in our initial design what used to happen is the customers had access to their loan origination system and data in it. And the way they had access to the data was writing some customer SDK applications to actually export our data from their production systems. So this had its own share of challenges. Like for example, if I wrote some inefficient queries to export out the data, since they were acting on the same production database it used to slow down their loan origination system. Plus they did not get access to all of their data. And we had heard it loud and clear from our customers that not only did they need access to the data, but they also wanted us to manage their data. They did not want to get into managing the database or schema changes and all of that. Plus we also had such a rich industry data set. We are talking about 50% of all US home mortgages. So they were also very interested in using that data to get actionable insights about the industry, about their competitive advantages and develop some innovative services on top of it. So those were the challenges which we were trying to solve. >> So what was the original architecture like you're describing what sounds like a very poor experience for Ellie Mae and the lenders themselves. It sounds clunky and cumbersome. And then also leaving a lot on the table because as you said, it was a rich dataset. What was the original architecture? >> So the original architecture was not a cloud-based architecture. We were in our own private data center and every customer had their own database to work with. So, and it wasn't great architecture at that time when the technologies had not evolved. And we had a highly successful product as a result of that but when it came to data it was not a very good experience for them. So why did their loan origination system was working great? The access to the data was not to the extent what we wanted. >> So using best-in-class technologies from AWS tell us a little bit about the new product. >> Yes. So, our journey really started when we heard all of the customer's feedback and the requirements. Then we basically went back to the drawing board. We said, yes, we have a highly successful encompass product in the market, but we also want to solve this problem without affecting their experience with the loan origination system. So that was the challenge which we had taken internally. So what we did was we evaluated quite a bit of cloud providers and technology stacks and the parameters which we had put in that time because of the scale of data was, we needed unlimited scalability and reliability of any provider. We needed a secure data storage including the personally identifiable information protection. So as you can imagine, we deal with loan mortgages, I mean the mortgage and we pretty much have so much of PII data as we call it. Security is on the forefront for us. So we needed a cloud provider which could match up with that expectation. We needed.. >> AWS, was it? >> AWS was definitely it and there were some other parameters which also we were able to check because of that highly scalable and performance data Lake. We needed a big data Lake for this, storage compute separation. We also needed ability to seamlessly import data from any applications internal or external, right? And AWS absolutely gave us all of this. And we did evaluate a lot of cloud vendors and AWS came up on the top. So AWS along with persistent technologies actually helped us with this evaluation and the development of the data platform. >> So tell our viewers a little bit now about data connect and what it is for lenders now. >> Yeah. So what we did was as any cloud technology, we first developed a common platform and then we started building data connect solutions on top of it, right? So we created solutions based on the customer's needs. So one solution which we have is what we call as the data connects future products. In this, they can replicate, customers can replicate their data from the cloud, from their private data Lake into their warehouse, or they can access reports and run analytical queries directly on our warehouse which is again in the cloud. So all the solutions that are available depending on the customer's needs but that is all separate from the loan origination system. So we made sure that we are not impacting that existing business while creating this new solutions in the market. And all of these were built on AWS. >> But you also took things a step further and explored what was possible if you aggregated data from all lenders the resulting being insights. Tell our viewers a little bit about insights and what it allows. >> Absolutely. So that was a very cool product which we came up with. So again, because of the rich data set, which we have, right? We are in the position right now to aggregate the data and come up with actionable insights on top of the data. And so we call this product insights. This is our latest offering from Ellie Mae, again based off AWS and the data platform. So this product gives us information about the industry dreams on how the mortgage industry is going in US. It gives the lenders the ability to compare themselves with their peers and with the industry. So they can actually benchmark themselves and decide whether they are doing great, not great, what do they have to change? And this is all in near real time. So this is not like a month old data and all that. So that's the beauty of this product. >> And what are you hearing from customers? Because as you said, that real-time benchmarking and understanding how they're doing relative to their rivals is a game changer. It is and customers are super excited about it. We just launched this few months back and we are seeing amazing adoption for this product. In fact, just not the adoption side of things, we are also seeing so many new use cases and requirements coming from the customer now that they understand we have such a massive data and this data can scale and it's not impacted their business. They just want to add more and more things to it so that it can solve their problem. So it gives a unique opportunity for us where we can monetize more but we can also help solve lenders problems. >> Right. Helping them solve the challenges that they're facing. Talk a little bit more about the primary benefits of the solution, the unlimited scalability, the fact that it's fully managed, the storage compute separation. Tell our viewers a little bit more about the benefits. So the benefits about the solutions are, the customers or lenders don't have to worry about how it is managed. It is all taken care of. They just how to access it when they need it. It is available on demand. It is available 24/7. In this time, this year has been especially very busy for us where the interest rates have dropped and the loan volume and the loan applications have just gone through the roof. But I'm very proud to say that Ellie Mae stack or, all of the data solutions, and in fact, all of our other products, they are able to scale and they have been able to scale to the record volume this year, all because of how we have designed it using the AWS technology stack. So the customers really benefit. They just need to focus on their business. They don't have to worry about underlying infrastructure or how things are going to scale if their volume is going to go up or not or is there any security issues of that? We take care of all of those things and this is all a self provision just web based access for some of our products. So they don't even have to do a lot of customization to get hold of these products. >> So I want to ask what's next for you. You just referenced the fact that Ellie Mae's incredibly busy with record mortgage applications, of course, companies and people around the globe are still grappling with the COVID-19 pandemic. What are some of the big trends you're seeing and what's next for Ellie Mae in the coming coming year? >> We have a exciting and a very rich roadmap coming up. So as I started this interview, I said, Ellie Mae is now part of ICE mortgage technology, which is a Intercontinental exchange division. So as part of this transition, which happened recently, we also have under our umbrella, two companies called MERS and Simplifile, which actually touch so if you take MERS as an example, it touches close to 80% of US loans for home mortgages. So we have such a unique opportunity now to not only expand our data set, make it more rich, and then come up with more additional use cases which are going to help solve customer's problem and also make them competitive in the market. So we have a lot of good opportunity related to data and I feel a lot confident because of the data platform and the technology stack we to use. We will be able to handle all of those things. >> Sachin, tell our viewers a little bit about the partners that are helping you on this data monetization journey. >> So AWS definitely helped us in the initial parts in evaluating the design and the solution architects came in and worked with us. But along with that, I would definitely want to mention Persistent Technologies. They came up with a lot of good design suggestions on how we should develop the data platform and the solutions on top of it. Those insights product, which I talked about is done along with their help. So I'm very happy with the partnership I have with the Persistent Technologies and AWS. >> Excellent, well, Sachin Dhoot, thank you so much for coming on theCUBE. I really appreciate talking to you >> Same here, nice talking to you. >> Stay tuned for more of theCUBE virtual coverage at AWS reInvent. (upbeat music)

>> Hello everyone. On today's panel, the theme is Drug Discovery and how Artificial Intelligence can make a difference. On the panel today, we are honored to have Dr. Ryan Yates, principal scientist at The National Center for Natural Products Research, with a focus on botanicals specifically the pharmacokinetics, which is essentially how the drug changes over time in our body and pharmacodynamics which is essentially how drugs affects our body. And of particular interest to him is the use of AI in preclinical screening models to identify chemical combinations that can target chronic inflammatory processes such as fatty liver disease, cognitive impairment and aging. Welcome, Ryan. Thank you for coming. >> Good morning. Thank you for having me. >> The other distinguished panelist is Dr. Rangan Sukumar, our very own, is a distinguished technologist at the CTO office for High Performance Computing and Artificial Intelligence with a PHD in AI and 70 publications that can be applied in drug discovery, autonomous vehicles and social network analysis. Hey Rangan, welcome. Thank you for coming, by sparing the time. We have also our distinguished Chris Davidson. He is leader of our HPC and AI Application and Performance Engineering team. His job is to tune and benchmark applications, particularly in the applications of weather, energy, financial services and life sciences. Yes so particular interest is life sciences he spent 10 years in biotech and medical diagnostics. Hi Chris, welcome. Thank you for coming. >> Nice to see you. >> Well let's start with your Chris, yes, you're regularly interfaced with pharmaceutical companies and worked also on the COVID-19 White House Consortium. You know tell us, let's kick this off and tell us a little bit about your engagement in the drug discovery process. >> Right and that's a good question I think really setting the framework for what we're talking about here is to understand what is the drug discovery process. And that can be kind of broken down into I would say four different areas, there's the research and development space, the preclinical studies space, clinical trial and regulatory review. And if you're lucky, hopefully approval. Traditionally this is a slow arduous process it costs a lot of money and there's a high amount of error. Right, however this process by its very nature is highly iterate and has just huge amounts of data, right it's very data intensive, right and it's these characteristics that make this process a great target for kind of new approaches in different ways of doing things. Right, so for the sake of discussion, right, go ahead. >> Oh yes, so you mentioned data intensive brings to mind Artificial Intelligence, you know, so Artificial Intelligence making the difference here in this process, is that so? >> Right, and some of those novel approaches are actually based on Artificial Intelligence whether it's deep learning and machine learning, et cetera, you know, prime example would say, let's just say for the sake of discussion, let's say there's a brand new virus, causes flu-like symptoms, shall not be named if we focus kind of on the R and D phase, right our goal is really to identify target for the treatment and then screen compounds against it see which, you know, which ones we take forward right to this end, technologies like cryo-electron, cryogenic electron microscopy, just a form of microscopy can provide us a near atomic biomolecular map of the samples that we're studying, right whether that's a virus, a microbe, the cell that it's attaching to and so on, right AI, for instance, has been used in the particle picking aspect of this process. When you take all these images, you know, there are only certain particles that we want to take and study, right whether they have good resolution or not whether it's in the field of the frame and image recognition is a huge part of this, it's massive amounts of data in AI can be very easily, you know, used to approach that. Right, so with docking, you can take the biomolecular maps that you achieved from cryo-electron microscopy and you can take those and input that into the docking application and then run multiple iterations to figure out which will give you the best fit. AI again, right, this is iterative process it's extremely data intensive, it's an easy way to just apply AI and get that best fit doing something in a very, you know, analog manner that would just take humans very long time to do or traditional computing a very long time to do. >> Oh, Ryan, Ryan, you work at the NCNPR, you know, very exciting, you know after all, you know, at some point in history just about all drugs were from natural products yeah, so it's great to have you here today. Please tell us a little bit about your work with the pharmaceutical companies, especially when it is often that drug cocktails or what they call Polypharmacology, is the answer to complete drug therapy. Please tell us a bit more with your work there. >> Yeah thank you again for having me here this morning Dr. Goh, it's a pleasure to be here and as you said, I'm from the National Center for Natural Products Research you'll hear me refer to it as the NCNPR here in Oxford, Mississippi on the Ole Miss Campus, beautiful setting here in the South and so, what, as you said historically, what the drug discovery process has been, and it's really not a drug discovery process is really a therapy process, traditional medicine is we've looked at natural products from medicinal plants okay, in these extracts and so where I'd like to begin is really sort of talking about the assets that we have here at the NCNPR one of those prime assets, unique assets is our medicinal plant repository which comprises approximately 15,000 different medicinal plants. And what that allows us to do, right is to screen mine, that repository for activities so whether you have a disease of interest or whether you have a target of interest then you can use this medicinal plant repository to look for actives, in this case active plants. It's really important in today's environment of drug discovery to really understand what are the actives in these different medicinal plants which leads me to the second unique asset here at the NCNPR and that is our what I'll call a plant deconstruction laboratory so without going into great detail, but what that allows us to do is through a how to put workstation, right, is to facilitate rapid isolation and identification of phytochemicals in these different medicinal plants right, and so things that have historically taken us weeks and sometimes months, think acetylsalicylic acid from salicylic acid as a pain reliever in the willow bark or Taxol, right as an anti-cancer drug, right now we can do that with this system on the matter of days or weeks so now we're talking about activity from a plant and extract down to phytochemical characterization on a timescale, which starts to make sense in modern drug discovery, alright and so now if you look at these phytochemicals, right, and you ask yourself, well sort of who is interested in that and why, right what are traditional pharmaceutical companies, right which I've been working with for 20, over 25 years now, right, typically uses these natural products where historically has used these natural products as starting points for new drugs. Right, so in other words, take this phytochemical and make chemicals synthetic modifications in order to achieve a potential drug. But in the context of natural products, unlike the pharmaceutical realm, there is often times a big knowledge gap between a disease and a plant in other words I have a plant that has activity, but how to connect those dots has been really laborious time consuming so it took us probably 50 years to go from salicylic acid and willow bark to synthesize acetylsalicylic acid or aspirin it just doesn't work in today's environment. So casting about trying to figure out how we expedite that process that's when about four years ago, I read a really fascinating article in the Los Angeles Times about my colleague and business partner, Dr. Rangan Sukumar, describing all the interesting things that he was doing in the area of Artificial Intelligence. And one of my favorite parts of this story is basically, unannounced, I arrived at his doorstep in Oak Ridge, he was working Oak Ridge National Labs at the time, and I introduced myself to him didn't know what was coming, didn't know who I was, right and I said, hey, you don't know me you don't know why I'm here, I said, but let me tell you what I want to do with your system, right and so that kicked off a very fruitful collaboration and friendship over the last four years using Artificial Intelligence and it's culminated most recently in our COVID-19 project collaborative research between the NCNPR and HP in this case. >> From what I can understand also as Chris has mentioned highly iterative, especially with these combination mixture of chemicals right, in plants that could affect a disease. We need to put in effort to figure out what are the active components in that, that affects it yeah, the combination and given the layman's way of understanding it you know and therefore iterative and highly data intensive. And I can see why Rangan can play a huge significant role here, Rangan, thank you for joining us So it's just a nice segue to bring you in here, you know, given your work with Ryan over so many years now, tell I think I'm also quite interested in knowing a little about how it developed the first time you met and the process and the things you all work together on that culminated into the progress at the advanced level today. Please tell us a little bit about that history and also the current work. Rangan. >> So, Ryan, like he mentioned, walked into my office about four years ago and he was like hey, I'm working on this Omega-3 fatty acid, what can your system tell me about this Omega-3 fatty acid and I didn't even know how to spell Omega-3 fatty acids that's the disconnect between the technologist and the pharmacologist, they have terms of their own right since then we've come a long way I think I understand his terminologies now and he understands that I throw words like knowledge graphs and page rank and then all kinds of weird stuff that he's probably never heard in his life before right, so it's been on my mind off to different domains and terminologies in trying to accept each other's expertise in trying to work together on a collaborative project. I think the core of what Ryan's work and collaboration has led me to understanding is what happens with the drug discovery process, right so when we think about the discovery itself, we're looking at companies that are trying to accelerate the process to market, right an average drug is taking 12 years to get to market the process that Chris just mentioned, Right and so companies are trying to adopt what's called the in silico simulation techniques and in silico modeling techniques into what was predominantly an in vitro, in silico, in vivo environment, right. And so the in silico techniques could include things like molecular docking, could include Artificial Intelligence, could include other data-driven discovery methods and so forth, and the essential component of all the things that you know the discovery workflows have is the ability to augment human experts to do the best by assisting them with what computers do really really well. So, in terms of what we've done as examples is Ryan walks in and he's asking me a bunch of questions and few that come to mind immediately, the first few are, hey, you are an Artificial Intelligence expert can you sift through a database of molecules the 15,000 compounds that he described to prioritize a few for next lab experiments? So that's question number one. And he's come back into my office and asked me about hey, there's 30 million publications in PubMag and I don't have the time to read everything can you create an Artificial Intelligence system that once I've picked these few molecules will tell me everything about the molecule or everything about the virus, the unknown virus that shows up, right. Just trying to understand what are some ways in which he can augment his expertise, right. And then the third question, I think he described better than I'm going to was how can technology connect these dots. And typically it's not that the answer to a drug discovery problem sits in one database, right he probably has to think about uniproduct protein he has to think about phytochemical, chemical or informatics properties, data and so forth. Then he talked about the phytochemical interaction that's probably in another database. So when he is trying to answer other question and specifically in the context of an unknown virus that showed up in late last year, the question was, hey, do we know what happened in this particular virus compared to all the previous viruses? Do we know of any substructure that was studied or a different disease that's part of this unknown virus and can I use that information to go mine these databases to find out if these interactions can actually be used as a repurpose saying, hook, say this drug does not interact with this subsequence of a known virus that also seems to be part of this new virus, right? So to be able to connect that dot I think the abstraction that we are learning from working with pharma companies is that this drug discovery process is complex, it's iterative, and it's a sequence of needle in the haystack search problems, right and so one day, Ryan would be like, hey, I need to match genome, I need to match protein sequences between two different viruses. Another day it would be like, you know, I need to sift through a database of potential compounds, identified side effects and whatnot other day it could be, hey, I need to design a new molecule that never existed in the world before I'll figure out how to synthesize it later on, but I need a completely new molecule because of patentability reasons, right so it goes through the entire spectrum. And I think where HP has differentiated multiple times even the recent weeks is that the technology infusion into drug discovery, leads to several aha! Moments. And, aha moments typically happened in the other few seconds, and not the hours, days, months that Ryan has to laboriously work through. And what we've learned is pharma researchers love their aha moments and it leads to a sound valid, well founded hypothesis. Isn't that true Ryan? >> Absolutely. Absolutely. >> Yeah, at some point I would like to have a look at your, peak the list of your aha moments, yeah perhaps there's something quite interesting in there for other industries too, but we'll do it at another time. Chris, you know, with your regular work with pharmaceutical companies especially the big pharmas, right, do you see botanicals, coming, being talked about more and more there? >> Yeah, we do, right. Looking at kind of biosimilars and drugs that are already really in existence is kind of an important point and Dr. Yates and Rangan, with your work with databases this is something important to bring up and much of the drug discovery in today's world, isn't from going out and finding a brand new molecule per se. It's really looking at all the different databases, right all the different compounds that already exist and sifting through those, right of course data is mind, and it is gold essentially, right so a lot of companies don't want to share their data. A lot of those botanicals data sets are actually open to the public to use in many cases and people are wanting to have more collaborative efforts around those databases so that's really interesting to kind of see that being picked up more and more. >> Mm, well and Ryan that's where NCNPR hosts much of those datasets, yeah right and it's interesting to me, right you know, you were describing the traditional way of drug discovery where you have a target and a compound, right that can affect that target, very very specific. But from a botanical point of view, you really say for example, I have an extract from a plant that has combination of chemicals and somehow you know, it affects this disease but then you have to reverse engineer what those chemicals are and what the active ones are. Is that very much the issue, the work that has to be put in for botanicals in this area? >> Yes Doctor Goh, you hit it exactly. >> Now I can understand why a highly iterative intensive and data intensive, and perhaps that's why Rangan, you're highly valuable here, right. So tell us about the challenge, right the many to many intersection to try and find what the targets are, right given these botanicals that seem to affect the disease here what methods do you use, right in AI, to help with this? >> Fantastic question, I'm going to go a little bit deeper and speak like Ryan in terminology, but here we go. So with going back to about starting of our conversation right, so let's say we have a database of molecules on one side, and then we've got the database of potential targets in a particular, could be a virus, could be bacteria, could be whatever, a disease target that you've identified, right >> Oh this process so, for example, on a virus, you can have a number of targets on the virus itself some have the spike protein, some have the other proteins on the surface so there are about three different targets and others on a virus itself, yeah so a lot of people focus on the spike protein, right but there are other targets too on that virus, correct? >> That is exactly right. So for example, so the work that we did with Ryan we realized that, you know, COVID-19 protein sequence has an overlap, a significant overlap with previous SARS-CoV-1 virus, not only that, but it overlap with MERS, that's overlapped with some bad coronavirus that was studied before and so forth, right so knowing that and it's actually broken down into multiple and Ryan I'm going to steal your words, non-structural proteins, envelope proteins, S proteins, there's a whole substructure that you can associate an amino acid sequence with, right so on the one hand, you have different targets and again, since we did the work it's 160 different targets even on the COVID-19 mark, right and so you find a match, that we say around 36, 37 million molecules that are potentially synthesizable and try to figure it out which one of those or which few of those is actually going to be mapping to which one of these targets and actually have a mechanism of action that Ryan's looking for, that'll inhibit the symptoms on a human body, right so that's the challenge there. And so I think the techniques that we can unrule go back to how much do we know about the target and how much do we know about the molecule, alright. And if you start off a problem with I don't know anything about the molecule and I don't know anything about the target, you go with the traditional approaches of docking and molecular dynamics simulations and whatnot, right. But then, you've done so much docking before on the same database for different targets, you'll learn some new things about the ligands, the molecules that Ryan's talking about that can predict potential targets. So can you use that information of previous protein interactions or previous binding to known existing targets with some of the structures and so forth to build a model that will capture that essence of what we have learnt from the docking before? And so that's the second level of how do we infuse Artificial Intelligence. The third level, is to say okay, I can do this for a database of molecules, but then what if the protein-protein interactions are all over the literature study for millions of other viruses? How do I connect the dots across different mechanisms of actions too? Right and so this is where the knowledge graph component that Ryan was talking about comes in. So we've put together a database of about 150 billion medical facts from literature that Ryan is able to connect the dots and say okay, I'm starting with this molecule, what interactions do I know about the molecule? Is there a pretty intruding interaction that affects the mechanism of pathway for the symptoms that a disease is causing? And then he can go and figure out which protein and protein in the virus could potentially be working with this drug so that inhibiting certain activities would stop that progression of the disease from happening, right so like I said, your method of options, the options you've got is going to be, how much do you know about the target? How much do you know the drug database that you have and how much information can you leverage from previous research as you go down this pipeline, right so in that sense, I think we mix and match different methods and we've actually found that, you know mixing and matching different methods produces better synergies for people like Ryan. So. >> Well, the synergies I think is really important concept, Rangan, in additivities, synergistic, however you want to catch that. Right. But it goes back to your initial question Dr. Goh, which is this idea of polypharmacology and historically what we've done with traditional medicines there's more than one active, more than one network that's impacted, okay. You remember how I sort of put you on both ends of the spectrum which is the traditional sort of approach where we really don't know much about target ligand interaction to the completely interpretal side of it, right where now we are all, we're focused on is, in a single molecule interacting with a target. And so where I'm going with this is interesting enough, pharma has sort of migrate, started to migrate back toward the middle and what I mean by that, right, is we had these in a concept of polypharmacology, we had this idea, a regulatory pathway of so-called, fixed drug combinations. Okay, so now you start to see over the last 20 years pharmaceutical companies taking known, approved drugs and putting them in different combinations to impact different diseases. Okay. And so I think there's a really unique opportunity here for Artificial Intelligence or as Rangan has taught me, Augmented Intelligence, right to give you insight into how to combine those approved drugs to come up with unique indications. So is that patentability right, getting back to right how is it that it becomes commercially viable for entities like pharmaceutical companies but I think at the end of the day what's most interesting to me is sort of that, almost movement back toward that complex mixture of fixed drug combination as opposed to single drug entity, single target approach. I think that opens up some really neat avenues for us. As far as the expansion, the applicability of Artificial Intelligence is I'd like to talk to, briefly about one other aspect, right so what Rang and I have talked about is how do we take this concept of an active phytochemical and work backwards. In other words, let's say you identify a phytochemical from an in silico screening process, right, which was done for COVID-19 one of the first publications out of a group, Dr. Jeremy Smith's group at Oak Ridge National Lab, right, identified a natural product as one of the interesting actives, right and so it raises the question to our botanical guy, says, okay, where in nature do we find that phytochemical? What plants do I go after to try and source botanical drugs to achieve that particular end point right? And so, what Rangan's system allows us to do is to say, okay, let's take this phytochemical in this case, a phytochemical flavanone called eriodictyol and say, where else in nature is this found, right that's a trivial question for an Artificial Intelligence system. But for a guy like me left to my own devices without AI, I spend weeks combing the literature. >> Wow. So, this is brilliant I've learned something here today, right, If you find a chemical that actually, you know, affects and addresses a disease, right you can actually try and go the reverse way to figure out what botanicals can give you those chemicals as opposed to trying to synthesize them. >> Well, there's that and there's the other, I'm going to steal Rangan's thunder here, right he always teach me, Ryan, don't forget everything we talk about has properties, plants have properties, chemicals have properties, et cetera it's really understanding those properties and using those properties to make those connections, those edges, those sort of interfaces, right. And so, yes, we can take something like an eriodictyol right, that example I gave before and say, okay, now, based upon the properties of eriodictyol, tell me other phytochemicals, other flavonoid in this case, such as that phytochemical class of eriodictyols part right, now tell me how, what other phytochemicals match that profile, have the same properties. It might be more economically viable, right in other words, this particular phytochemical is found in a unique Himalayan plant that I've never been able to source, but can we find something similar or same thing growing in, you know a bush found all throughout the Southeast for example, like. >> Wow. So, Chris, on the pharmaceutical companies, right are they looking at this approach of getting, building drugs yeah, developing drugs? >> Yeah, absolutely Dr. Goh, really what Dr. Yates is talking about, right it doesn't help us if we find a plant and that plant lives on one mountain only on the North side in the Himalayas, we're never going to be able to create enough of a drug to manufacture and to provide to the masses, right assuming that the disease is widespread or affects a large enough portion of the population, right so understanding, you know, not only where is that botanical or that compound but understanding the chemical nature of the chemical interaction and the physics of it as well where which aspect affects the binding site, which aspect of the compound actually does the work, if you will and then being able to make that at scale, right. If you go to these pharmaceutical companies today, many of them look like breweries to be honest with you, it's large scale, it's large back everybody's clean room and it's, they're making the microbes do the work for them or they have these, you know, unique processes, right. So. >> So they're not brewing beer okay, but drugs instead. (Christopher laughs) >> Not quite, although there are pharmaceutical companies out there that have had a foray into the brewery business and vice versa, so. >> We should, we should visit one of those, yeah (chuckles) Right, so what's next, right? So you've described to us the process and how you develop your relationship with Dr. Yates Ryan over the years right, five years, was it? And culminating in today's, the many to many fast screening methods, yeah what would you think would be the next exciting things you would do other than letting me peek at your aha moments, right what would you say are the next exciting steps you're hoping to take? >> Thinking long term, again this is where Ryan and I are working on this long-term project about, we don't know enough about botanicals as much as we know about the synthetic molecules, right and so this is a story that's inspired from Simon Sinek's "Infinite Game" book, trying to figure it out if human population has to survive for a long time which we've done so far with natural products we are going to need natural products, right. So what can we do to help organizations like NCNPR to stage genomes of natural products to stage and understand the evolution as we go to understand the evolution to map the drugs and so forth. So the vision is huge, right so it's not something that we want to do on a one off project and go away but in the process, just like you are learning today, Dr. Goh I'm going to be learning quite a bit, having fun with life. So, Ryan what do you think? >> Ryan, we're learning from you. >> So my paternal grandfather lived to be 104 years of age. I've got a few years to get there, but back to "The Infinite Game" concept that Rang had mentioned he and I discussed that quite frequently, I'd like to throw out a vision for you that's well beyond that sort of time horizon that we have as humans, right and that's this right, is our current strategy and it's understandable is really treatment centric. In other words, we have a disease we develop a treatment for that disease. But we all recognize, whether you're a healthcare practitioner, whether you're a scientist, whether you're a business person, right or whatever occupation you realize that prevention, right the old ounce, prevention worth a pound of cure, right is how can we use something like Artificial Intelligence to develop preventive sorts of strategies that we are able to predict with time, right that's why we don't have preventive treatment approach right, we can't do a traditional clinical trial and say, did we prevent type two diabetes in an 18 year old? Well, we can't do that on a timescale that is reasonable, okay. And then the other part of that is why focus on botanicals? Is because, for the most part and there are exceptions I want to be very clear, I don't want to paint the picture that botanicals are all safe, you should just take botanicals dietary supplements and you'll be safe, right there are exceptions, but for the most part botanicals, natural products are in fact safe and have undergone testing, human testing for thousands of years, right. So how do we connect those dots? A preventive strategy with existing extent botanicals to really develop a healthcare system that becomes preventive centric as opposed to treatment centric. If I could wave a magic wand, that's the vision that I would figure out how we could achieve, right and I do think with guys like Rangan and Chris and folks like yourself, Eng Lim, that that's possible. Maybe it's in my lifetime I got 50 years to go to get to my grandfather's age, but you never know, right? >> You bring really, up two really good points there Ryan, it's really a systems approach, right understanding that things aren't just linear, right? And as you go through it, there's no impact to anything else, right taking that systems approach to understand every aspect of how things are being impacted. And then number two was really kind of the downstream, really we've been discussing the drug discovery process a lot and kind of the kind of preclinical in vitro studies and in vivo models, but once you get to the clinical trial there are many drugs that just fail, just fail miserably and the botanicals, right known to be safe, right, in many instances you can have a much higher success rate and that would be really interesting to see, you know, more of at least growing in the market. >> Well, these are very visionary statements from each of you, especially Dr. Yates, right, prevention better than cure, right, being proactive better than being reactive. Reactive is important, but we also need to focus on being proactive. Yes. Well, thank you very much, right this has been a brilliant panel with brilliant panelists, Dr. Ryan Yates, Dr. Rangan Sukumar and Chris Davidson. Thank you very much for joining us on this panel and highly illuminating conversation. Yeah. All for the future of drug discovery, that includes botanicals. Thank you very much. >> Thank you. >> Thank you.

>> live from San Francisco, celebrating 10 years of high tech coverage. It's the Cube covering Veum World 2019 brought to you by the M Wear and its ecosystem partners. >> I am Stew Minimum and my co host, Justin Warren. And you're watching The Cube live from VM World 2019 here in Moscow North. Actually, the 10th year that we've had the cubit this event joining me on the program, I have Brad Anderson and Keith Norby, both with Netapp. Brad is an executive vice president, and Keith is director of strategic alliances. Gentlemen, thanks so much for joining us. >> Thank you. So, Brad, I've had >> the pleasure of working with the, um where since 2002 it's one of the highlights of my career in Tech has been watching that growth of virtual ization a company that, you know. It was about 100 people when I first started watching them. And that wave, a virtualization that had ripples throughout the industry, was really impressive. But >> I didn't actually >> get to come to this show until 2010 Asai said. Our 10th year of the show, you were one of the few that were at the inaugural event that it's the 16th year of it. So >> just give us a >> little bit of ah ah, look back in. You know what you've seen changing Netapp, of course. You know, long longtime partner of ah of Via Mers. >> Absolutely. He was like 3 4000 for it was at a hotel in San Diego. And there's probably about 1000 people there, but I don't think they were planning 1000. So is the longest kind of room. And we had people that were just kind of a mile down. And finally, uh uh, the comment was, Hey, could we knock down a wall and kind of get people a little bit closer? So, no, that was a long time ago. And in fact, it was Diane Mendel. I had an opportunity of Aquino, and I think there was another key note from IBM. >> Yeah, well, you know, I'm sorry they didn't invite you back on stage this morning, but, you know, >> a little big, bigger show today. >> A little bigger. I think we're somewhere the ballpark. 20 thousands. What? This show's been for about the last five years. Conversations very different today. As I made commentary were in the post VM era. Today, V EMS are no longer the center of the conversation. And you know, multi cloud is something that they put out there, which is the story I've been hearing from net out for many years software company, living in all of these cloud environment. So talk to us a little bit about how that relationship with VM wear and what we're not upsets in the ecosystem is >> changing. I mean, you know, Veum, where has never happened, then where has been a great partner for a long, long time? And, uh, and net have strategies Clearly hybrid multi cloud. When you think about private clouds today, VM where has a huge footprint in that space, So they continue be super important. We probably have a more expansive definition of hybrid to us. Hybrid is private cloud and public cloud in all kinds of combinations. And but we also so strongly believe the multi cloud and so we are. You know, we're driving very hard for the hybrid multi cloud, letting customers basically start anywhere they want to with any cloud provider on Prem in the cloud, and have that you know that control of data irrespective of and move at their own pace. >> Yes, sir. Vienna, Where has long been one of those places where everybody can meet? So you mentioned knocking down walls. VM. Where is one of the few companies that actually succeeded in doing that and having people be able to work with partners in other eras? There was often a lot of fighting between different vendors, or it's here. It's whatever you as a customer wants to do, we will be there to do that with you. And that's another one of those companies. All right, if you have some data, we will help you manage it, no matter where it is. So what tell it tells about something that what are you doing right now in this Is New World, where a stew mentions it's a post of'em world. So in this post of'em world, how do you manage your data in that post VM world? >> Well, it's it's it's Ah, it's managing first of all, I mean, we really strongly believe place, and so we're gonna manage, you know, you know the data and start where the customer starts. I mean, we're not advocating that they have to start in cloud. They have to be on prim. There's an orderly path because depending on the customer, they're all going to take a very different path. And and so what we want to do is give him control. Their data, irrespective of the path, allow them to move on that path. But we're seeing at Netapp that it's it's the but the data is beyond the data that's increasingly about applications. And so, you know, you heard a little bit about Ah Kubernetes. That's That's something we've strongly feel as well on providing a set of tools to provide choice where, you know, you know, independent the cloud, you know, same kubernetes service, same different tools, same tool set. Same service is on prim or in the cloud. >> Yeah, Ned has a strong cloud. President's summer things like cloud volumes. Some of the other acquisitions that you've made that help you with the cloud journey, like some of them have sufferings, are really strong, >> know very much so. And and we think we can provide Ah ah, the superior customer experience. But then, if the customer wants to use, you know, a variety interesting set of tools we support that as well. We are supporting the customer on his journey with the tools as they ah determined. >> So, Keith, tell us about some of the strategic partnerships that helped net up. To be able to partner with these different customers and to bring different vendors together to help themselves. Customer problems? >> Yeah, well takes a lot of them. Thio, meet the customer needs, as you saw today in the landscape folks that are on the solutions exchange floor. It takes not just a partnership between net up and VM wear, but net up in Vienna, where plus v m net up in Vienna, where plus ah ton of other folks, Cisco has an example longtime partner of ours and flex pot. Then you know the fact that we're doing memory accelerator flex pod takes, you know, something that has had a long tradition of the, um where excellence with Cisco and is now the order of magnitude faster than anything you want for APS that need scale, performance, all the service capabilities of on tap for things like Metro Cluster and beyond. >> So you remember back years ago it was you know, you know who has the most integrations and with the M wear. And you know, if you know all the A I and Viv balls and all of those pieces and netapp always, you know, was right at the top of the list. You know, working in those environments may be brought if you want to enter this. But, you know, today, how do you give us some examples That kind of that joint engineering work that goes on between Netapp and VM, where obviously there's bundle solutions like flex pod, that's, you know, the sphere plus netapp in there. But you know that engineering level, you know, where does rubber with road? >> Yeah, it's funny because I've been at every vehicle except to, And so I've been with you. In the sense I've seen the landscape of these innovations where Steve Haired and some others would talk about the movie previews of things like the aye aye and bossy providers all coming. And that was the big thing you'd focus on. Now it's less about that, and I think it's more about what Brad is kind of brought to net happened in the focus on simplicity. Now the funny part about simplicity is that to deliver simplicity, much like the engineering detail to deliver Tesla or an iPhone is extraordinary, so the work isn't less. In fact, the work is Maur and you pre configuring or pre what you were wearing as much as possible. The work we started to do over a year ago between George Curry in our CEO and Sanjay Poon got together. We started planning on some multi cloud plans, and, uh, that's where you see a lot of our persistence and cloud volumes on VMC. You see us having a view more vow, didn't design Aneta Page C. I for your Private Cloud VD I solutions. And these air meant to draw NSX a kn and when his net I've ever had in NSX immigration all said, Now we have had a sex and integrations to make that easier to bring on board. We have the realized integration so you could build a self serve portal catalog just like it talked about today, and the list goes on and on, so it's funny how it's less. The features are important. But what's more important is trying to make this a simple it's possible for you to consume and then for the folks that need things like scale of maps and service is or they need the same cloud volumes in this data fabric on any one of the hyper scale er's. We have really the only end in story on that, and that's what makes the via More plus net up thing worked really well. >> So how do you balance the flexibility of being able to solve multiple customer problems? And they all have different needs. How do you balance the simplicity with that? With that complexity? And it was mentioned by Pat, make a note as well that you've got this kind of tension between. I need to be able to do everything flexibly, but that can sometimes lead the complexity. So how do you change that? To become simple for customers to use? >> I mean, I think the biggest thing it Z it's a design input. I mean, if if you start out with just trying to make the technology all it can be with a end of you know, one particular cloud or one particular partner, then it becomes very difficult. As he tried to expand it to multiple partners and because it's about choice. We're kind of think about that right up front. And so if it's a design input, it puts, it puts, as he said, to put some burden on the technical team. But it is a much more powerful solution if we if you can pull it off, and that's been a big part, and I think it kind of starts with this mentality that you know, it's about choice, and we gotta make simplicity. And now part of the value proposition, rather than after for thought as it has, may be historically has been. What if >> we could talk a little bit about customers? Because, you know the message I hear this morning is you know, you talk multi cloud, a cloud native. There's a lot of change in the industry, you know, I'm participating in couple of career advice events because remember back 10 years ago, it was Oh, my gosh, if I'm a server admin, I need to learn to be virtualization than it was cloud. You know, architects, but way know that change in the industry is constant. So, you know, what are some of the key drivers when you're talking to customers in general and specifically when you talk about in engaging in part with the M where, >> Yeah, I mean, I I think it starts with people just recognizing. Even if people haven't moved the cloud today, that tends to be their primary strategy. In a recent survey, I think we found 98% of the customers, said Cloud is her strategy. However, 53% said still on Prem is their primary compute centers. So you know they're not there yet. And so But because that's their strategy, then you know we have to respect that. And so So, uh, you know, increasingly you're seeing at Netapp Waleed with clout, even though we know customers aren't quite ready there. But we align to that long term vision. But then our strange made up helping the modernize What they have currently on prim helping build private clouds for the same service is they have him public cloud, and then let them have the complete absolute choice. What public cloud or multiple public clouds they want and designed with with, you know, that full spectrum in mind, knowing they could start anywhere on that on that scale. >> Yeah, the customers ultimately are gonna dictate to the market What Israel and I think over time, Pios sort of vet who is right on this stuff. And so history's a great lesson teacher of all those things, you know, for me, it seems less less about how many different things you can offer. And as you see whether we're at Veum World or at Red Hat Summit were made obvious. Reinvent or, um, coup con every every every vector, turn of the customers. Prism on this will say something different. But I think in general, categorically, if you look at it, you could start to just, you know, glean what you think are the real requirements. And by the way, the rule carpets are not all technical. You know, I think what what gets lost on folks is that there is a lot of operational political factors, probably political factors, a lot more than what a lot of people think. You know, they're just talking about what the what The speed is to re factor APs or to migrate APS. Frankly, there's just a lot of politics that goes with that. There's a lot of just stuff to work through, >> and that's where I think simplicity is so important because of those non technical reason. Simplicity resonates across the board. >> But I would say you have to have simplicity with capabilities. >> I mean, just one of the things you talk about, right? If I modernize some application, well, the people that were using that application, they were probably complaining about that old one. But at least they do have to relearn >> that. Have that that new one. So we're gonna have some exciting announcements tomorrow. So I'm kind of check out tomorrow's stuff that will announce with VM, where with Netapp tomorrow We're here at the show floor will be showcasing some of those things. We can't give away too much of that today. But, you know, we think the future is bright and together with with Veum Or, you know, this partnership, I think, has a lot of upside. Like you said, we've had We've had a 17 year history with, you know, hundreds of thousands of customers together and installed base that goes back to like you said to be very beginning. Um, I remember back to the very beginning of the ecosystem. Net up was one of the strongest players in that market on dhe Since then, it's evolved beyond just NFS. >> Well, hopefully bread. We can get you on a keynote for in another 10 years. Waken Knock that wall down Exactly. Exactly. >> All right, great. Want to give you both the final word? You know, so so many big themes going on, you know, takeaways that you want people to have from the emerald 2019 bread >> I think the biggest takeaway is that just like the show today you didn't hear a whole lot about virtualization. It's moving to contain her eyes and and we had netapp view that, you know, we support all virtualized environments on from across the cloud, moving to supporting all containerized application environments on premises and cloud. And it's about choices in combinations of both, but keeping data control. >> Yeah, I'd say for me, it's it's really the power of the of of the better together, you know, to me, it's nobody's great apart. It takes really an ecosystem of players to kind of work together for the customer benefit and the one that we've demonstrated of'em. Where with that plus Veum, where has been a powerful one for well, well over 17 years and the person that putting in terms of joint customers that have a ton of loyalty to both of us, and they want us just to work it out. So you know, whether you're whether your allegiance on one side of the Cooper natty criminals battle or another or you're on one side of anyone's stores. Choice or another. I think customers want Netapp on via mortar work. It's out and come up with solutions that we've done that. And now what? We wait for the second act of this to come out. We'll start that tomorrow. Teeth and >> Brad, thank you so much if you couldn't tell by the sirens on the street. We are live here at San Francisco at Mosconi, north of lots more coverage. Three days wall to wall coverage for Justin Warren. I'm stew. Minimum is always thank you for watching the cue

extracting the signal from the noise it's the cube covering vmworld 2015 brought to you by vmware and its ecosystem sponsors now your host John furrier and Dave vellante okay welcome back everyone we are here live in San Francisco for vmworld 2015 SiliconANGLE media's the cube star flagship program we go out to the event and extract the students from noise i'm john furry the founders looking angle to of my coast and partner david lonte co-founder Wikibon calm slipping angles research are my next guess is sanjay poonen executive vice president general manager of vmware's end-user computing great to see you again welcome back to the cube John's pleasure to be here but I got to say one thing I'm waiting for the day when you have the tie and dave has the non-tidal I mean seriously you gotta quit that purple tile no I'm just getting a pleasure to be on your show I happy to wear tie but people would know it's phony baloney but I'm happy cape looks good d looks good in the neck but I'm California gotta be chillax a little bit here are you relaxed you feeling good I'm feeling great okay so you get a big body through your anniversary at vm work this month Wow excited to be here at the show so choice so give us the state of the union au CSAP to vmware now two years air wash huge acquisition we saw your an event you had here in San Francisco with all the top customers you have big name box big time player is working with you guys cloud needs a theme that you guys are really driving hard what's this all about where are we right now in your group and user computing is all the rage developer attraction and DevOps kind of connects the dots where are we with this yeah no I think it's been a fabulous two years we've hired a fantastic team I talked about this in my last show your some of the new people that joined us summative on Bob Jules no awasum were some of the people we promoted from within kit Kohlberg Eric Freiburg and then many of the people in the field we really really put together I think the best end-user computing team in the industry bar none it always starts to the people you know my people values where it's all started secondly we really started to innovate on product that differentiates us from the competition and made the bold move and mobile because mobile is the new desktop we joked internally that you could end user computing without a strategy you got that Josh yes yeah you know so that's in essence what we've done to be invisible and taking up the complexities away that's really the key will you yeah absolutely and making yourself relevant to where the world is going in this digitization of the workplace so we see this as a phenomenal opportunity for us to become the de facto brand in a Switzerland set of proposition you've got apple iOS you've got google android about windows microsoft OS 10 VMware's propositions via Switzerland type of company that can manage and secure all of those devices in very transparent fashion then lead and lead with that mobile story right I mean isn't that part of it yeah no absolutely mobile is the new desktop so it does become the key outcome the people are looking for and our proposition that we talked about last year working at the speed of life being able to go all the way from desktop to Tesla many of those things are really starting to resonate now as we talked to CIOs and so you know 10 at 2010 when we first did the cube six years ago Palmer its laid out the whole manifesto and user computing had a lot of disparate parts some of gods and have left explain to the folks out there and clarify the positioning of end-user computing visa V all the turmoil in the marketplace with customers cloud has got obviously hybrid cloud people I try to get their arms around that virtualization a lot of plumbing going on with SD and Isis and growth there a lot of stuff going on underneath your layer that's going to affect you how do you manage that clarify the positioning and then talk about how you respond to the growth that's going to come out of underneath you and the infrastructure yeah I think Paul Maritz had it right down he's one of the visionaries of our time and as he talked in 2010 that was around the time we actually coined the term workspaces the inwards 12 companies had coined the term mobile workspace and now many of those technologies are coming to bear so much of the demos that Paul actually noah was here at the time Steve Herod showed you know I'm actually sort of sitting on the shoulders of many of those giants in terms of driving this so the time has come now where the desktop virtualization market now is less costly and less complex so we've taken cost and complexity out and that's why now we're taking market share from Citrix and other players in that market in the mobile place we weren't moving fast enough we acquire the leader AirWatch in mobile security and we've now created an ecosystem out of that of the leading application providers that are all partnering at a Salesforce workday Adobe SI p everyone in the app space the telco providers players like a TMT vodafone singtel partnering with us and then the security players like palo alto networks of all embraced AirWatch and then we actually created some blue technologies that really bring the desktop and the mobile together like identity management identity as a service is becoming one of those very critical like critical items that's a life blood that ties desktop and mobile together because you're your device now becomes your second factor of authentication right you can use your fingerprint or retina scan all of these now really coming in a mature fashion so we're seeing huge growth out of particularly AirWatch side I think sixty percent last last quarter path to profitability I believe in 2016 no Pat's talking about it Carl's talking about at jonathan's talking about Joe Tucci's talk of everybody's talking about your business so what's driving that growth you just talked about that ecosystem that's got to be a lot of the leverage but maybe help us unpack deck wrote a little bit I think it has been and I'm biased so obviously next to VMware being acquired by emc one of the best acquisitions of modern you know last 18 months in enterprise software we were diligent just the same way EMC a treated VMware to be somewhat separate and independent we kept AirWatch fairly dependent for the first six months and gradually began the integration because there was a motion that Alain de Biron John Marshall had in the context the way they ran their what's that we did not want to break and then over time in the second half of last year in the first half of this year we began to get two parts of VMware that we do well in to play the value side of big deals so we start to participate in elas now where larger conversations with customers the big accounts the volume site are the transaction partners our channel partners 75,000 partners of VMware now have an opportunity to take this mobile solution as a door-opener the CIO but remember now we're bringing together horizon on the desktop site air watching the mobile side with glue types of technologies like identity so the proposition just got like one plus one equals like 111 and that's a huge often you mentioned he'll I mean huge year renewal year in 2016 so that's going to be a tailwind it cloud-based solution around one of the reasons with why I watch it was there with a leader in cloud-based mobile John and Alan were very smart and creating a cloud-based solution not to say that they can't deploy on premise but its cloud first so think Salesforce in a world where everyone else looks like a siebel so we were very astute basically saying we want to look at a way by which the subscription revenue starts to become a flywheel yeah so I want to ask you about business mobility that's a theme that you guys have been big big on your ace application configuration I think it's called or yeah happy creating for the enterprise you had Salesforce box cisco workday and a bunch of other partners showing nsx identity the hard stuff the stuff that you will think about i was there at the event and I want you to compare that visa V some news at hit today with apple and cisco partnering on iOS traffic and prioritizing traffic for iOS apps on cisco hardware yeah which is essentially deep packet inspection looking at the routes and giving them a fast lane if you will that seems to be the trend this consumerization where new Apple examples saying okay differentiate with apple stuff versus Android are the business people thinking about that that way are we looking at nsx innovating under the hood explain the consumerization of business mobility why that's relevant and how hard it is when some things that you guys are doing we coined the term john consumer simple meets and a prize secure and you hear about that more tomorrow in my keynote which i encourage all your viewers to come to tomorrow the clock at nine o'clock there's some very special in huge news hint at and little bit but let's bring that together because who is one of the best at consumers simplicity today Apple okay and we basically are Google and much of what they do too but we took basically a strong partnership with apple and dialed it further and and his apples talked about publicly they have a group of enterprise partners where one among a very few 30 40 50 that they're working with in the EMM space and we investigated meaning enterprise mobile manager okay guy and as we we did that we also then looked at all the apps players that were very key to this mobile cloud ecosystem box you know native people exactly these are folks who are building a cloud-based mobile set of applications and we signed all of them up to this need of integration called app config with enterprise that the device operating system vendors like Apple and Google and us invented now what's happening is you're starting to see that ecosystem getting stronger so actually it's awesome because the apps that were announced today in the cisco apple announcement were WebEx spark the same applications i build laughs and fig yes for so we actually copying you guys well no they actually joining the ecosystem so i think it's awesome when you have an IBM in the ecosystem of vmware in the ecosystem now is cisco on the ecosystem it's amazing there you know there's lots of players we partner with SI PE last you're gonna see us doing more with them so our goal is to ensure that the lead players whether it's an applications world whether it's the networking world what's the security world start plugging into appropriate platform I remember the proposition of vmware though is to be Switzerland so we have to build strong relationships with apple with Google and Microsoft Windows 10 because they're all viable ecosystems in the post-pc world well of course you want to be neutral because you want to have you know rising tide as you said but your announcement also highlighted box docusign was in their AT&T you talk about some cool things I can split outspent reports by having an iphone so the rant random example but the but it highlights a new way of doing things right but i thought i asked her the question those are cloud native companies mean box workday mean they were born in the cloud if you will but what about the enterprises that aren't they have a lot of legacy that's a problem right so it's not easy to be cloud- talk about the challenges there and the opportunities how you guys are addressed i love that word because the each side of that coin is a challenging the opportunity so when we go to traditional enterprises they have client server applications or all browser applications that they want us to real deployment and you'll hear my keynote tomorrow a very key phrase any application on any device so you've got a client-server application and old browser application or native mobile app we can deliver into any device you pick your device you've got a traditional windows laptop at in client a mac OS and Android and iOS or a tesla with running some kind of you know maybe android inside it we can deploy those applications on any device and that requires the combination the technology we have from a horizon and AirWatch so what do we do in those traditional applications we virtualize them we can either virtualize the desktop or the app and deploy them onto at incline we think john the future is thin client computing where you know your glass that you present on is going to be like the glass the Corning makes us projectable and this phone becomes your remote control into your entire life so I love this conversation because there's so much talk in this business Gardner has bimodal IT IDC has the third platform and and but what you just described is doesn't doesn't say old stuff over here and new stuff over there it says extend the client-server apps the 19-year old legacy apps and allow them to participate in this cloud native cloud native doesn't mean throw away the old stuff and start with a blank piece of paper I wonder if you could first of all do you agree with that and what if you could talk about that as a strategy it's a very important strategy because if you are a new company like an uber or Netflix you don't have legacy infrastructure you can start completely new on a cloud native all cloud apps but for the majority of global 2000 companies they have existing applications client-server primarily some running in all browsers ie8 ie9 and you've got to bring those apps to the new world so we see the world moving clearly to mobile and html5 long term but there's still going to be many of those applications 3d applications for example you go to many of our large manufacturing customers they've got jet engine parts or parts of various different manufacturing processes that are still not yet html5 or mobile apps so bringing those old world of apps to a Chromebook or to an iOS device is something we can magically do but for these native mobile apps you want to make it one touch so the benefit of what we had with app configures now with one-touch secured by air watch you can now automatically get access to Salesforce or DocuSign or box this is the best of both worlds for the new apps single touch easy seamless access those apps for the old world world of apps you can seamlessly virtualize them in other words abstract them and then send them over to the ecosystem is critical in all of this and and a lot of times we see this trend toward vertical integration we watch what Oracle's do and you see what Amazon's doing the e così i'm hearing the ecosystem is still vital to your strategy absolutely and the ecosystem takes various different forms the device operating system players the system integrators the security players people like Paul all tanks and then in this world apps players are really really important I talked last year about SI p we had many new apps in that and you know just a small little hint tomorrow at nine o'clock you're going to see a major ecosystem player on stage with us never in the history of the world I don't want to blow the cat out of the bag and I want every one of your viewers gonna be big my lap gonna be huge so you got to come there okay so ecosystem just real quick profitable good economics people making money how's that economics work yeah you know via MERS all about ecosystem right you go to the show floor and vmworld has got thousands including companies that compete with us what you got to do is ensure that you're open and you allow even competitors to integrate with you ok I've got competitors that I compete with in my part of the business they've got to integrate with vsphere vice versa I've got to make sure that I can play in a heterogeneous world with a variety of companies that might compete in the STD sea world and part of the magic of doing this is to ensure that the ecosystem is proliferating but you have some platform player that's what's made vm VMware successful 600,000 greatest infrastructure company balls out I have box again to wrap here so I have a final question then I have a final final question because I need to get two questions in first api api f occasion as a term that we've been kicking around the openstack cloud community coined by google's Craig mcluckie on the cube it's been kicking around but API making your api's available if you overdo it you could cause some problems but you're mentioning interacting with of all these apps your take on that and the second final final question is how do you view DevOps do you care you're looking down at it saying go faster or you're agnostic what are you guys doing specifically around this API ification trend yeah i mean the devops in particular they're both of a related questions let me cover them in sort of a quick sequence everything that we should do as a platform you're a platform if you create a service-oriented architecture that allows others to plug into you so when we talk about app config for the enterprise part of what we did was created an API set with the device operating system players like Apple Google is an open it's an open standard that all EMS can can embrace and now then we natively integrate sales force or workday or essay p into that so the api's are absolutely important in every layer of vmware whether it's the desktop side was the mobile side with its SDDC we live by those principle as a platform company no doubt then as you think about DevOps there's aspects of now the management complexity in the cloud world that needs rethought because this isn't systems management the old way in which the client-server were looked at it DevOps really has a very key way which you can go from tested Evra production where you've got multiple clouds you've got federated clouds and we've got to make sure and this is something that we use internally a lot of our AirWatch solutions that are deployed because they're cloud first have DevOps built into them build an integration built between AirWatch and the management tools of vmware their customers who asked us to integrate in the service now this whole management platform the next generation mobile cloud management platform is going to have DevOps at the key at the heart of it and we think that's a huge opportunity for VMware and for our ecosystem so yes or no question senior management's behind DevOps we are absolutely behind everything that drives in the ecosystem DevOps is one key part of it but there are many other aspects this is one key part where the management platform is going and we're very very committed to making that I know you got to run to your meeting thanks so much Sanjay put in the general man and your EVP of then use a computer big announcement tomorrow watch his keynote tomorrow at 9am I nair on SiliconANGLE TV the cube is going to be covering all the keynotes then keep watching we'll be right back more with live coverage from San Francisco vmworld 2015 this is the cube with John fair and Dave vellante we'll be right back thanks John