>>Okay. Okay. We're back at Caesar's Forum. The Snowflake summit 2022. The cubes. Continuous coverage this day to wall to wall coverage. We're so excited to have the analyst panel here, some of my colleagues that we've done a number. You've probably seen some power panels that we've done. David McGregor is here. He's the senior vice president and research director at Ventana Research. To his left is Tony Blair, principal at DB Inside and my in the co host seat. Sanjeev Mohan Sanremo. Guys, thanks so much for coming on. I'm glad we can. Thank you. You're very welcome. I wasn't able to attend the analyst action because I've been doing this all all day, every day. But let me start with you, Dave. What have you seen? That's kind of interested you. Pluses, minuses. Concerns. >>Well, how about if I focus on what I think valuable to the customers of snowflakes and our research shows that the majority of organisations, the majority of people, do not have access to analytics. And so a couple of things they've announced I think address those are helped to address those issues very directly. So Snow Park and support for Python and other languages is a way for organisations to embed analytics into different business processes. And so I think that will be really beneficial to try and get analytics into more people's hands. And I also think that the native applications as part of the marketplace is another way to get applications into people's hands rather than just analytical tools. Because most most people in the organisation or not, analysts, they're doing some line of business function. Their HR managers, their marketing people, their salespeople, their finance people right there, not sitting there mucking around in the data. They're doing a job and they need analytics in that job. So, >>Tony, I thank you. I've heard a lot of data mesh talk this week. It's kind of funny. Can't >>seem to get away from it. You >>can't see. It seems to be gathering momentum, but But what have you seen? That's been interesting. >>What I have noticed. Unfortunately, you know, because the rooms are too small, you just can't get into the data mesh sessions, so there's a lot of interest in it. Um, it's still very I don't think there's very much understanding of it, but I think the idea that you can put all the data in one place which, you know, to me, stuff like it seems to be kind of sort of in a way, it sounds like almost like the Enterprise Data warehouse, you know, Clouded Cloud Native Edition, you know, bring it all in one place again. Um, I think it's providing, sort of, You know, it's I think, for these folks that think this might be kind of like a a linchpin for that. I think there are several other things that actually that really have made a bigger impression on me. Actually, at this event, one is is basically is, um we watch their move with Eunice store. Um, and it's kind of interesting coming, you know, coming from mongo db last week. And I see it's like these two companies seem to be going converging towards the same place at different speeds. I think it's not like it's going to get there faster than Mongo for a number of different reasons, but I see like a number of common threads here. I mean, one is that Mongo was was was a company. It's always been towards developers. They need you know, start cultivating data, people, >>these guys going the other way. >>Exactly. Bingo. And the thing is that but they I think where they're converging is the idea of operational analytics and trying to serve all constituencies. The other thing, which which also in terms of serving, you know, multiple constituencies is how snowflake is laid out Snow Park and what I'm finding like. There's an interesting I economy. On one hand, you have this very ingrained integration of Anaconda, which I think is pretty ingenious. On the other hand, you speak, let's say, like, let's say the data robot folks and say, You know something our folks wanna work data signs us. We want to work in our environment and use snowflake in the background. So I see those kind of some interesting sort of cross cutting trends. >>So, Sandy, I mean, Frank Sullivan, we'll talk about there's definitely benefits into going into the walled garden. Yeah, I don't think we dispute that, but we see them making moves and adding more and more open source capabilities like Apache iceberg. Is that a Is that a move to sort of counteract the narrative that the data breaks is put out there. Is that customer driven? What's your take on that? >>Uh, primarily I think it is to contract this whole notion that once you move data into snowflake, it's a proprietary format. So I think that's how it started. But it's hugely beneficial to the customers to the users, because now, if you have large amounts of data in parquet files, you can leave it on s three. But then you using the the Apache iceberg table format. In a snowflake, you get all the benefits of snowflakes. Optimizer. So, for example, you get the, you know, the micro partitioning. You get the meta data. So, uh, in a single query, you can join. You can do select from a snowflake table union and select from iceberg table, and you can do store procedures, user defined functions. So I think they what they've done is extremely interesting. Uh, iceberg by itself still does not have multi table transactional capabilities. So if I'm running a workload, I might be touching 10 different tables. So if I use Apache iceberg in a raw format, they don't have it. But snowflake does, >>right? There's hence the delta. And maybe that maybe that closes over time. I want to ask you as you look around this I mean the ecosystems pretty vibrant. I mean, it reminds me of, like reinvent in 2013, you know? But then I'm struck by the complexity of the last big data era and a dupe and all the different tools. And is this different, or is it the sort of same wine new new bottle? You guys have any thoughts on that? >>I think it's different and I'll tell you why. I think it's different because it's based around sequel. So if back to Tony's point, these vendors are coming at this from different angles, right? You've got data warehouse vendors and you've got data lake vendors and they're all going to meet in the middle. So in your case, you're taught operational analytical. But the same thing is true with Data Lake and Data Warehouse and Snowflake no longer wants to be known as the Data Warehouse. There a data cloud and our research again. I like to base everything off of that. >>I love what our >>research shows that organisation Two thirds of organisations have sequel skills and one third have big data skills, so >>you >>know they're going to meet in the middle. But it sure is a lot easier to bring along those people who know sequel already to that midpoint than it is to bring big data people to remember. >>Mrr Odula, one of the founders of Cloudera, said to me one time, John Kerry and the Cube, that, uh, sequel is the killer app for a Yeah, >>the difference at this, you know, with with snowflake, is that you don't have to worry about taming the zoo. Animals really have thought out the ease of use, you know? I mean, they thought about I mean, from the get go, they thought of too thin to polls. One is ease of use, and the other is scale. And they've had. And that's basically, you know, I think very much differentiates it. I mean, who do have the scale, but it didn't have the ease of use. But don't I >>still need? Like, if I have, you know, governance from this vendor or, you know, data prep from, you know, don't I still have to have expertise? That's sort of distributed in those those worlds, right? I mean, go ahead. Yeah. >>So the way I see it is snowflake is adding more and more capabilities right into the database. So, for example, they've they've gone ahead and added security and privacy so you can now create policies and do even set level masking, dynamic masking. But most organisations have more than snowflake. So what we are starting to see all around here is that there's a whole series of data catalogue companies, a bunch of companies that are doing dynamic data masking security and governance data observe ability, which is not a space snowflake has gone into. So there's a whole ecosystem of companies that that is mushrooming, although, you know so they're using the native capabilities of snowflake, but they are at a level higher. So if you have a data lake and a cloud data warehouse and you have other, like relational databases, you can run these cross platform capabilities in that layer. So so that way, you know, snowflakes done a great job of enabling that ecosystem about >>the stream lit acquisition. Did you see anything here that indicated there making strong progress there? Are you excited about that? You're sceptical. Go ahead. >>And I think it's like the last mile. Essentially. In other words, it's like, Okay, you have folks that are basically that are very, very comfortable with tableau. But you do have developers who don't want to have to shell out to a separate tool. And so this is where Snowflake is essentially working to address that constituency, um, to San James Point. I think part of it, this kind of plays into it is what makes this different from the ado Pere is the fact that this all these capabilities, you know, a lot of vendors are taking it very seriously to make put this native obviously snowflake acquired stream. Let's so we can expect that's extremely capabilities are going to be native. >>And the other thing, too, about the Hadoop ecosystem is Claudia had to help fund all those different projects and got really, really spread thin. I want to ask you guys about this super cloud we use. Super Cloud is this sort of metaphor for the next wave of cloud. You've got infrastructure aws, azure, Google. It's not multi cloud, but you've got that infrastructure you're building a layer on top of it that hides the underlying complexities of the primitives and the a p I s. And you're adding new value in this case, the data cloud or super data cloud. And now we're seeing now is that snowflake putting forth the notion that they're adding a super path layer. You can now build applications that you can monetise, which to me is kind of exciting. It makes makes this platform even less discretionary. We had a lot of talk on Wall Street about discretionary spending, and that's not discretionary. If you're monetising it, um, what do you guys think about that? Is this something that's that's real? Is it just a figment of my imagination, or do you see a different way of coming any thoughts on that? >>So, in effect, they're trying to become a data operating system, right? And I think that's wonderful. It's ambitious. I think they'll experience some success with that. As I said, applications are important. That's a great way to deliver information. You can monetise them, so you know there's there's a good economic model around it. I think they will still struggle, however, with bringing everything together onto one platform. That's always the challenge. Can you become the platform that's hard, hard to predict? You know, I think this is This is pretty exciting, right? A lot of energy, a lot of large ecosystem. There is a network effect already. Can they succeed in being the only place where data exists? You know, I think that's going to be a challenge. >>I mean, the fact is, I mean, this is a classic best of breed versus the umbrella play. The thing is, this is nothing new. I mean, this is like the you know, the old days with enterprise applications were basically oracle and ASAP vacuumed up all these. You know, all these applications in their in their ecosystem, whereas with snowflake is. And if you look at the cloud, folks, the hyper scale is still building out their own portfolios as well. Some are, You know, some hyper skills are more partner friendly than others. What? What Snowflake is saying is that we're going to give all of you folks who basically are competing against the hyper skills in various areas like data catalogue and pipelines and all that sort of wonderful stuff will make you basically, you know, all equal citizens. You know the burden is on you to basically we will leave. We will lay out the A P. I s Well, we'll allow you to basically, you know, integrate natively to us so you can provide as good experience. But the but the onus is on your back. >>Should the ecosystem be concerned, as they were back to reinvent 2014 that Amazon was going to nibble away at them or or is it different? >>I find what they're doing is different. Uh, for example, data sharing. They were the first ones out the door were data sharing at a large scale. And then everybody has jumped in and said, Oh, we also do data sharing. All the hyper scholars came in. But now what snowflake has done is they've taken it to the next level. Now they're saying it's not just data sharing. It's up sharing and not only up sharing. You can stream the thing you can build, test deploy, and then monetise it. Make it discoverable through, you know, through your marketplace >>you can monetise it. >>Yes. Yeah, so So I I think what they're doing is they are taking it a step further than what hyper scale as they are doing. And because it's like what they said is becoming like the data operating system You log in and you have all of these different functionalities you can do in machine learning. Now you can do data quality. You can do data preparation and you can do Monetisation. Who do you >>think is snowflakes? Biggest competitor? What do you guys think? It's a hard question, isn't it? Because you're like because we all get the we separate computer from storage. We have a cloud data and you go, Okay, that's nice, >>but there's, like, a crack. I think >>there's uniqueness. I >>mean, put it this way. In the old days, it would have been you know, how you know the prime household names. I think today is the hyper scholars and the idea what I mean again, this comes down to the best of breed versus by, you know, get it all from one source. So where is your comfort level? Um, so I think they're kind. They're their co op a Titian the hyper scale. >>Okay, so it's not data bricks, because why they're smaller. >>Well, there is some okay now within the best of breed area. Yes, there is competition. The obvious is data bricks coming in from the data engineering angle. You know, basically the snowflake coming from, you know, from the from the data analyst angle. I think what? Another potential competitor. And I think Snowflake, basically, you know, admitted as such potentially is mongo >>DB. Yeah, >>Exactly. So I mean, yes, there are two different levels of sort >>of a on a longer term collision course. >>Exactly. Exactly. >>Sort of service now and in salesforce >>thing that was that we actually get when I say that a lot of people just laughed. I was like, No, you're kidding. There's no way. I said Excuse me, >>But then you see Mongo last week. We're adding some analytics capabilities and always been developers, as you say, and >>they trashed sequel. But yet they finally have started to write their first real sequel. >>We have M c M Q. Well, now we have a sequel. So what >>were those numbers, >>Dave? Two thirds. One third. >>So the hyper scale is but the hyper scale urz are you going to trust your hyper scale is to do your cross cloud. I mean, maybe Google may be I mean, Microsoft, perhaps aws not there yet. Right? I mean, how important is cross cloud, multi cloud Super cloud Whatever you want to call it What is your data? >>Shows? Cloud is important if I remember correctly. Our research shows that three quarters of organisations are operating in the cloud and 52% are operating across more than one cloud. So, uh, two thirds of the organisations are in the cloud are doing multi cloud, so that's pretty significant. And now they may be operating across clouds for different reasons. Maybe one application runs in one cloud provider. Another application runs another cloud provider. But I do think organisations want that leverage over the hyper scholars right they want they want to be able to tell the hyper scale. I'm gonna move my workloads over here if you don't give us a better rate. Uh, >>I mean, I I think you know, from a database standpoint, I think you're right. I mean, they are competing against some really well funded and you look at big Query barely, you know, solid platform Red shift, for all its faults, has really done an amazing job of moving forward. But to David's point, you know those to me in any way. Those hyper skills aren't going to solve that cross cloud cloud problem, right? >>Right. No, I'm certainly >>not as quickly. No. >>Or with as much zeal, >>right? Yeah, right across cloud. But we're gonna operate better on our >>Exactly. Yes. >>Yes. Even when we talk about multi cloud, the many, many definitions, like, you know, you can mean anything. So the way snowflake does multi cloud and the way mongo db two are very different. So a snowflake says we run on all the hyper scalar, but you have to replicate your data. What Mongo DB is claiming is that one cluster can have notes in multiple different clouds. That is right, you know, quite something. >>Yeah, right. I mean, again, you hit that. We got to go. But, uh, last question, um, snowflake undervalued, overvalued or just about right >>in the stock market or in customers. Yeah. Yeah, well, but, you know, I'm not sure that's the right question. >>That's the question I'm asking. You know, >>I'll say the question is undervalued or overvalued for customers, right? That's really what matters. Um, there's a different audience. Who cares about the investor side? Some of those are watching, but But I believe I believe that the from the customer's perspective, it's probably valued about right, because >>the reason I I ask it, is because it has so hyped. You had $100 billion value. It's the past service now is value, which is crazy for this student Now. It's obviously come back quite a bit below its IPO price. So But you guys are at the financial analyst meeting. Scarpelli laid out 2029 projections signed up for $10 billion.25 percent free time for 20% operating profit. I mean, they better be worth more than they are today. If they do >>that. If I If I see the momentum here this week, I think they are undervalued. But before this week, I probably would have thought there at the right evaluation, >>I would say they're probably more at the right valuation employed because the IPO valuation is just such a false valuation. So hyped >>guys, I could go on for another 45 minutes. Thanks so much. David. Tony Sanjeev. Always great to have you on. We'll have you back for sure. Having us. All right. Thank you. Keep it right there. Were wrapping up Day two and the Cube. Snowflake. Summit 2022. Right back. Mm. Mhm.

>>mhm. Hello and welcome to the cubes Ducker con coverage. I'm John Ferry, host of the Cube. We've got a great segment here with slim dot AI CEO John Amaral. Stealth mode, SAS Company. Start up in the devops space with tools today and open source around. Supply chain security with containers closed beta with developers. John, Thanks for coming on. Congratulations for being platinum sponsor here, Dr Khan. Thanks for coming on The Cube. >>Thanks so much on my pleasure. >>You know, container analysis, management optimisation. You know, that's super important. But security is at the centre of all the action we're seeing with containers. We've been talking shift left on a lot of cube conversations. What that means? Is it an outcome? Is that the product software supply chain? You seek them? A secure where malware. All these things are part of now the new normal in cloud Native. You guys at the centre of this, the surface areas change. All these things are important. Take a minute to explain what you guys are doing as a as a tools and open source. Some of the things you're doing, I know you got a stealth mode product. You probably can't talk about. But you gotta close, Beta. Can you give us a little bit of a teaser? What slim dot ai about >>sure. So someday I is about helping developers build secure containers fast, and that really plays to a few trends in the marketplace that are really apparent and important right now in a federal mandate and a bunch of really highly publicised breaches that have all been caused by software supply, chain risks and security and software supply, chain security has become a really top of mind concept for people who secure things and people who develop software and runs. SAS so slim that AI has built a bunch of capabilities and tools that allow software developers at their desks to better understand and build secure containers that really reduce software supply. Chain risk as you think about containers being run in production. And we do three things to help developers one, as we help them know everything about their software. It's a kind of a core concept of suffering supply chain security. Just know what software is in your containers to. Another core concept is only ship to production. What you need to run. That's all about risk surface and the ability for you to easily make a container small that has as much a software reduction in it as possible. And three, it's removed as many vulnerabilities as possible to Slim Toolset. Both are open source and our SAS data platform make that easy for developers to do >>so. Basically, you have a nice, clean, secure environment. Know what's in there. Don't only put in production was needed and make sure it's tight and it's trimmed down perfectly. So you're kind of teasing out this concept of slimming, which is in the name of the company. But it really is about surface area of attack around containers and super important as it becomes more and more prominent in the environment these days. What is container slimming and why is it important for supply chain security? >>Sure. So in the in the in the realm of software supply chain security, best practises right, there are three core concepts. One is the idea of an S bahn that you should know the inventory of all the software that runs in your world to its security posture, signing containers, making sure that the authenticity of the software that you use and production is well understood. And the third is, well, managing exactly what shopper you ship. The first two things I said are simply just inventory and basics about knowing what software you have. But no one answers the question. What software do I need? So I run a container and say, It's a gig and it's got all these packages in. It comes from the operating system from note, etcetera. It's got all this stuff in it. I know the parts that I write my code to. But all that other stuff, what is it? Why is it there? What's the risk in it? That slimming part is all about managing the list of things you actually shipped to the absolute minimum and with confidence that you know that that code will actually work when it gets production but be as small as possible. That's what slimming is all about, and it really reduces supply chain risk by lowering the attack surface in your container, but also trimming your supply chain to only the minimum pieces you need, which really causes a lot of improvements in in the operational overhead of having software supply chain security >>It's interesting as you get more more volume and velocity around containers, uh, and automation kicks in. Sometimes things are turning on and off you don't even know. And shift left has been a great trend for getting in the CI CD pipeline for developer productivity. Really cool. What are some of the consequences that's going on with this? Because then you start to get into some of these areas like some stuff happens that the developers have to come shift back and can take care of stuff. So, you know, C. Tus and CSOs are really worried about this container dynamic. What's the What's the new thing that's causing the problems here? What's the issue around the management that CDOs and CDOs care about? >>Sure. And I'll talk about the shift left implications as well for that exact point. So as you start to worry about software supply, chain security and get a handle on all the software you ship to prod well, part of that is knowledge is power. But it's also, um, risk and work as soon as I know about problems with my containers or the risk surface, and I got to do something about it so we're really getting into the age where everyone has to know about the software they ship. As soon as you know about that, say there's a vulnerability or a package that's a little risky or some surface area you don't really understand. The only place that can be evaded is by going back to the developers and asking them. What is that? How do I remove it? Please do that work. So the software supply chain security knowledge turns into developer security work. Now the problem is, is that historically, the knowledge was imperfect, and the developer, you know, involvement in that was, I'd say, at Hawk, meaning that developers had best practises that did the best they could. But the scrutiny we have now on minimising this kind of risk is really high. The beautiful part about containers is their portable, and it's an easily transferrable piece of software. So you have a lot of producers and a lot of consumers of containers. Consumers of containers that care about supply chain risk are now starting to push back on, producers saying, Take those vulnerabilities out, move those packages, make this thing more secure, lower the risk profile this works its way all the way back to the developers who don't really have the tools, capabilities and automation is to do the work I just described easily, and that's an opportunity that Slim is really addressing, making it easy for developers to remove risk. >>And that's really the consequences of shifting left without having the slimming. Because what you're saying is your shift left and that's kind of annulled out because you've got to go back and fix it. The work comes, >>that's right. And yeah, and it's not an easy task for a developer to understand the code that they didn't intentionally put in the container. It's like, Okay, there's a package in that operating system. What does it do? I don't know. Do I even use it? I don't know. So there's like tonnes of analytic and I would say even optimisation questions and work to be done, but they're just not equipped to, because the tooling for that is really immature Slims on a mission to make that really easy for them and do it automatically so they don't have to think about it. We just automatically remove stuff you don't use and voila! You've got this like perfectly pre optimised capability. >>You know, this suffer supply chain is huge, and I remember when open source started when I remember when I was breaking into the business. Now it's such a height in such an escalation of new developers. This it's a real issue that that's going to be resolved. It has to be because supply chain is part of open source, right? As more code comes in, you got to verify. You gotta make sure it's it's slimming where it needs to be slim and optimised. There needs to be optimised, huge trend. Um and so I just love this area. I think it's really innovative and needed. So congratulations on that, you know, have one more question for you before we get into to close out. Um, you guys are part of the Docker Extensions launch and your partner, >>Why >>is this important to participate in this programme and and what do you guys hope to hope it does for slim dot ai, >>First of all, doctors, the ubiquitous platform, their hub has millions and millions of containers. We've got millions and millions of developers using Docker desktop to actually build and work on containers. It's like literally the sandbox for all local work for building containers. It's a fair statement. So inclusion in Dr Khan and the relationship we're building with Docker is really important for developers and that we're bringing these capabilities to the place where developers work and live every day. It's where all the containers live in the world. So we want to have our technology be easy to use with docker tools. We want to keep developers workflows and systems and and tools of record be the same. We just want to help them use those tools better and optimist outputs. From that we've we've worked since our inception to make our tools really, really friendly for darker and darker environments to, um, we are building a doctor extension. Uh, they have, uh, in this darker con. They're launching their doctor extensions programme to the worldwide audience. We have been one of the lucky Cos that's been selected to build one of the early Dr desktop plug ins. It's derived from our capabilities and our Saas platform and an open source, and it's it's effectively an MRI machine, an awesome analytic tool that allows any developer to really understand the composition, security and profile of any container they work with. So it's giving the sight to the blind, so to speak, that it's this new tool to make container analysis easy. >>Well, John, you guys got a great opportunity. Container analysis, management, optimisation key to security, enabling it and maintaining and sustaining it. And it's changing. I know you guys. Your co founder also did a doctor Slim. So you guys are deep in the open source. I Congratulations on that. We'll see a Q. Khan for the remaining time. We have give a plug for the company, obviously in stealth mode price going to come out later this year. You got a developer preview? What's What's the company all about? What's the most important story here? Dr. Khan? >>Sure, just to playback. So we help developers do three important things. Know everything about the software in their containers to only ship stuff to production that you need, and and and three remove as many vulnerabilities as possible. That's really about managing and understanding the risk surface. It ties right back to software supply chain security, and any developer can use these tools today to emit and build containers that are more secure and better production grade containers, and it's easy to do. We have an open source project called Dioxin. Go check it out. Uh, it's not. It's on git Hub. It's easy to find if you go to w w w dot slim that ai you can find access to that. We have tens of thousands of developers, 500,000 plus downloads. We have developers everywhere using those tools today and open source to do the objectives. I just said You can also easily sign up for our data for our Saas platform, you can use the doctor extension, go ahead and do that and really get on your journey to make those outcomes reality for you. And really kind of make those SEC ops people downstream not have to shift anything left. It's super easy for you to be a great participant in software slash insecurity. >>All right. John Amaral, CEO slim dot ai Stealth. Most thanks for coming The Cube Cube coverage of Dr Khan. Thanks for watching. I'm John Kerry hosted the Cube back to more Dr Khan after the short break. Mhm mhm

>>Hello and welcome back to the cubes coverage of Splunk dot com virtual. I'm john Kerry host of the cube we are here in the Splunk studios in Silicon Valley where all the execs are here, it's basically a spunk studio. It's everyone's here telling the stories. We also got some remote guests coming in, customers partners and other Splunk execs. We've got Katie bianchi senior vice president of customer success. Welcome back to the cube. Thank great to see you. >>Thanks john Great to be here. >>Yeah, I love the customer success stories because at the end of the day customers vote with their wallet and when basically like solutions, they'll this customer examples and customer testimonials. There's one thing I've learned covering Splunk over the past decade and done in many dot coms. It's you guys have very happy customers and over the years have continuing to have great customer success organically now have to high end on the enterprise now with cloud scale lots changing, lots growing the world that's going completely cloud. Um, and again, data is at the center of the value proposition as it always was more important than ever. So what's new with the customers? What are some of the successful is that you're seeing what's new in your world? >>Yeah, Thanks for thanks for asking, john I think, You know, we've been talking about how things have been changing over the past 18 months. And if I over simplify our customer obsession means that everything we do is designed to make sure we're helping customers get the most out of their investment was flunk every single day. So we do this across our global team and our partner ecosystem who are providing both the right adoption and technical services and were architected and deploying thousands of Splunk environments to help our customers get to ongoing value. But in the world that we're living with today, I talked to so many customers who are doing amazing things with Splunk but dealing with really tough challenges right? So through the pandemic, everyone is dealing with more complexity, more change in the velocity that we have never seen before. And on top of all this, shifting to a fully digital business model, there's whole new challenges to effectively monitoring infrastructure and applications and maintaining security posture with this to customers that I'm talking to are also having to figure out ways to do a lot more with less. I think we all know it's an incredibly competitive talent market out there. So our customers are relying on Splunk and customer success more and more to make it easier and faster to get to value, to investigate, to monitor, to detect and to remediate. So that pace and all that change of what's happening means that we have to continually check ourselves to be that right strategic partners that can move at the pace of our customers because customers are counting on us to provide right services at the right time for every stage of their journey with us. >>Great point, great insight there. I want to ask you because Splunk has always had this kind of in their D. N. A. Because when Splunk started was always something new and it wasn't a new thing. That new thing never seen before. Now as the world can you guys continue to do that? You bring something new to the market, you operationalize, you bring value to customers then it happens again and again and again. But now more than ever the data rolls of cloud and and customer applications is new for customers. So you have a diverse customer base. I know you're obsessed with customer service but how do you how do you have a customer success? How do you deal with the fact that sometimes things are so new and there may or may not be a benchmark there and you can't go with the proven former. Sometimes you can sometimes you can't how do you solve? It's new to me problem that customers want this new thing. >>Yeah, I think you know a lot of what we see today is that the power as long as a data platform to bring in complex data allows customers to do many different things. Whether it's infrastructure monitoring, whether it's security, use cases or whether its application performance monitoring and all of that is new for our customers. So oftentimes like you said we grew up having customers use us for single use case when we're bringing this much data into the platform and they see what can be unlocked through the value of Splunk, what we have to make sure that they can do is most seamlessly move from use case and value point. So that means from a C. S. Perspective we have to continually make sure that we're doing what customers are asking us to do which is having the right services that deliver the right outcomes that are as prescriptive as possible and that we're doing that across the domain of all of our empire portfolio. So we spend a lot of time making sure that our technical services are scaling to the needs of customers but also everything that we do around success planning and adoption and use case guidance and best practices as well as our education and enablement are as prescriptive as possible for customers whether they are new to Splunk or whether they are scaling Splunk across multiple use cases and multiple areas of their business. >>Certainly a lot of not of multi vendor, multi vendor activities. Modern application development, security is a big part of it. So I have to ask you given all that, what are the top things, top three things for instance that your customers are asking from you guys from C. S perspective customer success >>perspective great question. So I think over, I think what we hear the most frequently is give me a more seamless buying experience with services that are really easy to consume and speed my time to value second and I just mentioned this is I need services that aren't task, just task based to work. I need services that deliver the outcome that I need for the business problem or business opportunity that I am trying to solve for. So make sure that your portfolio lines up with our outcomes And I think 3rd is all about more prescriptive guidance. The world is hard, the world is complex, data is only getting more complex while the opportunity is big, our role is all about prescription and making it as easy as possible. >>So I have to ask you the question that I'm observing, many people are in the industry as well is that Splunk is changing as a company. Um everyone knows the vibe of Splunk is very cool, very chill, very organic, big community vibe, good customer success, everything's going great. You continue to knock it out of the park over the years, but now you're mature company now, Scale is coming in, your customers are getting bigger and bigger. You have existing customers getting new customers, you have new offerings. There's a whole another Splunk coming another level. >>Yeah. How do you, how >>do you view that from a custom respect and you can, you share your reaction to that? >>Yeah, I, you know, I think it's an honor to be part of a company that has such a strong culture and has such great partnership with our customers and it really is all because of who our customers are and I think who are people are internally. But I think growing and scaling and making sure that we are able to deliver the right services at scale is a critical component of what we have to do to help customers along this journey. So the role of you keep saying this, but the role of customer success is to make the complex easy and we do that by making sure that we as an organization have the right data, the right prescription, the right way to serve our customers and the right coverage model no matter where customers are on the journey or who they are and getting and getting the most prescription to them at the right time. And that's that's quite frankly how we scale. But also what our customers asked for. They're asking for more module arised content and they're asking us for more ways that they can drive best practices and use case guidance from right within the product. And those are things that we are working on to help continue to scale out what we're able to do. >>That's a great point. Taking the complexity, make it simple and enable them to be successful. I think data does that you guys are offering that platform which is a great business model by the way, if you can provide those kind of value that's always a winning formula, Make things easy, reduce the steps it takes to do things and make it fast and simple. Uh I have to ask because you mentioned earlier, the top of this interview about digital business, we're here Splunk canceled the conference now is virtual. Were coming in remotely here on site at the studio. They they have a virtual student there now in the media business, which is a data business. You know, you guys are now doing tv with CUBA's here. Um everyone is realizing the pandemic. That digital business now is standard. You're seeing the impact of the instrumentation you mentioned. So as the digital business transformation is accelerated here and this time, not for everybody, it's going to change how customers are behaving. What have you what have you observed at the pandemic? Because it's kind of panel has cleared the runway a little bit for people to to do this properly because you can see what's not working. So what's your thoughts on this whole digital business? Everyone's connected and data is at the center of it. What's your thoughts? >>Yeah, absolutely. I I look, I think, you know what we have seen over the last 12-18 months with this acceleration to a digital business model, is that things and the other dynamics going on or that things are only getting more complex. Right? So strong customers can come to Splunk cloud because we know it reduces complete with complexity in their moves because we are that data platform that allows them to search, investigate and monitor across cloud across multi cloud and across hybrid environments but that's complex. Over the last year we've seen customers get too much quicker value um, in in Splunk cloud right there going through large complex transformation. One of the easiest things you can do is shed the amount of time and money you're spending, managing, monitoring your infrastructure. So coming to Splunk cloud helps accelerate time to value for them in that way. But let's make no mistake, that is really complex. And so part of what we are doing is ramping up our level of focus on those modernization services for customers. So customers who are choosing to come to Splunk cloud for those benefits. We are there from planning and cut over and beyond with more prescriptive tools, more automation and how we move data, more resources and more experts to get customers to Splunk cloud more seamlessly. And that for us from a modernization perspective is one thing that we are hearing clearly customers asking asking for specific in the space so they can take more advantage and move more quickly. >>One of the trends that we're reporting on and I'll get to the headline in silicon angle in a minute, what's reporting on this event is there's more, more surface area, there's more data, there's more tools and tools are important for helping people automate but at the same time if you have more tools you have more blind spots or silos. So when you get into this world of architecture, customers are struggling that we talked to around trying to find the ideal equation of okay balancing architecture platform and tools that's equilibrium if you will by getting access to the data. What's your reaction to that? Because this becomes one of those decisions. I think Splunk shines where you can kind of have the best of a platform at the same time use tooling where relevant to accelerate whether it's automation or other other jobs versus buying tools for everything. >>Yeah and I and so I think part of the part of the thing that we continue to see is with the proliferation of data and data sources and a different degree of complexity in tooling the decisions around what's important and what's not important become much more much more complex for customers and much more difficult for customers to make. So we're changing a lot on the product and pricing side to sort of facilitate that piece. But I think when you're talking about how do I get the most value immediately, what we do across our go to market organization is make sure that we're partnering with customers to say what are the outcomes that you want from you want a need as a priority from a monument infrastructure monitoring for an application performance security perspective and then how do we make sure that we're prioritizing your maturity journey very prescriptively to say here the use cases that are most material here are the data sources that are most material and here's a success plan that helps you get deployed to your priorities so you can start the journey with us and build on that as we go. So again, it's really about how do we make the complex really easy through higher degrees of prescription but really making sure that we're doing our job and tying the prescription to what our customers need most when they need it. >>That's a great segment of my next question. In fact, my final question because because you know the headline on silicon angle dot com that we're reporting for this event is I'll read it to you. Splunk doubles downs on multi cloud data access, observe ability and security at its annual summit. Okay, so balancing the shiny new toy in the North Star Direction vision to practical prescriptive customer journeys is always a balance because you want to talk to customers about the future. Multi cloud, obviously observe ability super important. And honestly if security gonna be built in, okay, we all know that back to the mainstream customer, you're in the customer success. So you want to show them the North Star, show them the headroom, whatever metaphor you want to use at the same time they're dealing with problems and things that they're trying to solve right now. What's your what's your thoughts on on customer success knowing that there's a lot of cool new things coming. >>Yeah, I think our job like I excited, I'll start and in the same sort of started in the same way. Um our job at the end of the day is to help customers get the most out of their current investment was blank and that does and that is all about working on what that maturity journey looks like, prioritizing outcomes that our customers care about and starting and starting that journey. So there's foundational work that needs to be done aligned to priorities. That's where we start and then if we're doing what we need to be doing, creating those prescriptive plans and those success plans, then all of how we deliver to that value is prioritized through what customers need the most when they need it and that is our role and then we believe that by doing that and moving as quickly as we can with customers to get to that value, then we're enabling them to continue on that journey for all the new stuff that's out there that they can explore and get more value from. >>Its always good to have that North star and that china new toy, new technology. So, I have to ask your final final question because I have you here, what have you learned during the pandemic that you could share with other practitioners that are watching or maybe watching this as they look at the best practice because we've seen a lot of evidence where some people have fallen to the side or failed. Didn't weren't prepared. People who were in the cloud experimenting got that tailwind and survived and thrived somewhere re factoring new business were emerging. So you kind of see a pattern, is there anything that you've noticed on your end um that you can share with, you know how to lean into something new? So you don't be left out in the cold if uh the wave comes, a new trend comes that they need to take advantage of like date at the edge or cloud scale. What are some of the things you've you've observed and learned? >>Yeah, that's a great question. So I think, you know, I think for me, my personal learning through the pandemic has been like, we always need to be looking around corners and planning specifically to for our customers and thinking for them in terms of what problems that they will have and we have to anticipate that so that we can pivot and create the right services that help them leverage to do what they need. So very early on. Um even very early on in the pandemic, our professional services team flipped within a two week period doing fully remote and virtual deployments because we knew we couldn't stop time to value given the shift to remote work, our customers were relying on us to deploy so that they could monitor infrastructure um and monitor work from home usage. And I think along with that as we started to see in through the back half digital transformations really pick up and customers move to cloud. We've been working across across the last really 12 to 15 months to really start to plan around what does it take to create the right services and the right capability, not just within Splunk but within our partner ecosystem to effectively move customers to Splunk cloud and help them navigate uh hybrid, multi cloud world with much more speed. And so for me, those are the two things that we really leaned into hard because we were always looking around corners and saying what's next for our customers based on what we're seeing happened in the external environment. >>Great insight, Katie, thank you for coming on the cube. That's awesome. And I think, you know, customers are seeing success formulas and the new ones are emerging and you guys are going the next level is always fun to talk about the future and today at the same time so great to have you on. And certainly at the end of the day the customers, the ones who are deploying and create the innovation with software and data. So thanks for sharing. >>Yeah. Thanks john um really, really happy to spend the time. There's nothing I like to do more than talk about our customers and to all of our customers, huge thank you to you for your partnership and all you're doing to continue to power the world with data. >>It's always good to have a lot of customers to tell the story for you, but I appreciate you. Coming on, congratulations on your success. It's the cube we are here live in the studio of Splunk Studios for their virtual event uh with the remote interview. We're talking all the people in the, in the industry. We can, we're bringing it in. We're going, we're doing the interviews here in person as well as a hybrid event. I'm john for the cube. Thanks for watching. Mm >>mm. Mhm.

>>Mhm Hello and welcome back to the cubes coverage of 80 of his public sector summit live for two days in D. C. In person. CuBA's here is an expo floor that people face to face down here. Adriana guest co founder and Ceo of Girls in tech cube alumni friend of the cube. We've known her for a long time. Watch their success really making an impact. Great to see you. Thanks for coming on. >>Wonderful to see you, john, thanks so much for having me. >>You know, one of the things that Sandy carter talks about matt max Peter talks about all of the Amazonian leadership that's about is skills training. Okay, this is a big deal. Okay, so getting talented to the industry is critical and also diversity and women attacking underrepresented minority groups are key. This has been a look at constant focus, you've been successful and and convincing folks about tech and working hard, what's the update, >>wow. So the reason why we're here, not only as Sandy carter are amazing chairman of the board of six plus years, but I heard we heard so many pain points from several of our partners as well as our good friends over at the White House and the Department of State and many other public sector agencies that there is a deficit. It's been very difficult to find diverse groups of talent and talent period to join their companies and populate those important I. T. Jobs stem jobs, whether it's very very technical or more data driven or more sort of design focus, product development focus across the board it's been very hard for them to find talent for those jobs. So girls in tech has partnered with AWS to create an initiative called the next generation public sector leaders and really focusing on creating awareness on career development opportunities for up and coming talent diverse talent that is curious and interested in job opportunities and educational opportunities within the public sector. So it has multi tiers, right? And it's something that we've devised based on the need and based on a lot of data and a lot of interviews from a lot of our partners and within the A. P. N. Network and we're doing a mentorship program which is a six month long program matching these amazing public sector executives, really accomplished leaders as well as our members from around the world um to connect and expose them and provide that nurturing, fostering mentality so that they can succeed in their careers. So >>eight of us getting behind this mission. Yes. And public sector is really fast growing changing. You start to see a lot of public private partnerships go on. So not just the old school public sector business, I mean the pandemic has shown the impact of society. So what does that do for the melting pot of talent out there? Have you seen anything out there? And how does that relate to this? Is that helped you at all or what's that does that mean for the mission? >>So there is a melting pot of talent. I just think we need to do a better job of creating awareness and really knowing where that talent lives. Like what are the blogs that they read? What are the videos that they watch and listen to? Where are they? Right. And we need to do the hard work and investigating and understanding like taking a more empathetic approach to really finding out what um how we can access them what their needs are. What are the things that interest piqued their interest within these jobs within the public sector um And customize it and market it so that they'll be eager and excited. Um And it would be more appealing to them. >>So I looked at the press release I just want to get your reaction to something you got evening with the experts. It's an in person event. >>Yes. When >>is that? Is that here is that going to be on your own event? What's that about? >>All the events that are going to be in person? Will be in D. C. Um There will be some virtual events as well. Our mentorship program is all virtual six month long program with curriculum and matchmaking on a platform that we use the evening with the experts which is a panel discussion with experts from a A. W. S. And beyond the A. P. N. Network. We'll talk about challenges and technology opportunities within a career development and also jobs. Um Well do recruitment like on the fly type of activities as well. Speed and speed interviewing, speed networking? Um We also have a few other programs, our webinar which is about the next gen public sector opportunities and this is more about the challenges that people face that companies face and the new technologies that will be launched very soon. And we're doing a widget on our jobs board to highlight the new career opportunity, new job opportunities from all of the public sector partners. We work with >>a very comprehensive, >>It's very comprehensive on the six >>month guided mentorship program. How does someone get involved in applications? How what's that going on there? >>It will be an application process and we will promote it to anyone who signs up to our newsletter. So go to Girls in tech dot org. Sign up for our newsletter and we will be posting and sharing more information on how people get involved. But we'll definitely send custom uh E. D. M essentially promoting to the people who are here at the conference and also through our Girls in tech D. C. Chapter as well. >>So I have to ask you, I know you've been really busy, been very successful. You've been out and about what's the trend line looked like? Well >>not for the last few years though, >>you've >>been in lockdown now. >>You've been working hard, you know have not not about now. You >>are not >>about what's the temperature like now in terms of the pulse of the industry relative to progress, what's what's what are you finding, what's the current situation >>progress for women in tech in the industry. So Since I started girls in tech in 2007, we've made A lot of progress, I would say it's a lot slower than I thought it would be, but you do see more and more women and people representing bipac actually apply for those jobs. We it is astronomically different than 2006, when I started in my first startup and there's a lot more mentorship, There are a lot more organizations out there that companies are more accountable with the R. G. Groups and they're changing their policies, are changing their training programs are having more off sites, there's now technologies that focus on tracking uh productivity and happiness of employees so that like all of that did not exist or I should say none of that existed, you know? And so we worked hard, we've worked hard, but it takes a village, it takes a lot of different people to create that change. And now one of girls in text mission is not just providing that education that community, that mentorship, we want to get the corporate involved, we want to teach the corporate about D and I training the importance of diversity, different tactics to recruit uh so on and so forth. And and it's been so amazing, so inspirational, I love, I started working more in partnerships and having our monthly calls with partners because I love it. I love collaborating to >>recruit good peer group around you to accelerate and create more territory of awareness and impact more people can get their hands involved. And I think to me that's what I think you're starting to see that with podcasts and media people are starting to go direct to tell their story, apps are out there now as you mentioned. So, but I feel like we're on a crossover point coming soon, totally thinks it's different. Um, but it's still a >>lot more work to do a lot more. We just got the service. I know, I know you've just scratched the surface, but we're so excited to be here. Aws is a huge supporter thanks to Sandy carter and her team. Um, it's been an amazing experience. >>Sandy's got great vision, she takes risks. So she's actually got the Amazonian concept of experiment, try something double down if it works and that's great to see that you guys have extended that relationship with, with her and the team. I like this idea of the fellowship cohort model of the or that program, you have the mentorship program. I think that's super cool. Um, that's something I think will be very successful. >>Uh, it's been successful so far. We typically over sell our mentorship are mentee spots. Uh, we only have 500 spots and last one we had over 2300 like a crazy amount, so we know that our members are really hungry for it around the world. And we know it will just be as just as popular for the public sector. So >>what's next for you? What's the vision? What's the next step was events are coming back in person? We're here in person. >>Yeah, there's just so much going on. I wish I could clone myself and we're busting at the seams. And I think the things that are really exciting to me are being able to produce our programs internationally, specifically in developing countries. So we're working um we haven't made an official announcement yet or anything, but we are working on expanding in african countries with Aws. They're doing some efforts and making some movements there. So places like Cameroon Ghana Nigeria Egypt. Uh we are looking to create chapters there for Girls in Tech and then expand our programming. Uh we're also, as mentioned earlier, we're working a lot with corporations to provide DNA training. So, training about policies, Inclusive leadership. Making sure they have the tools and policies to succeed and for their employees to feel comfortable, safe and productive in their work environment >>is great to see you. Congratulations Girls in tech dot org. Yes. Is the U. R. L. Check it out a great mission, very successful. Making progress any stats you can throw out there, you can share. >>Yeah, of course, you >>wrap it up. >>Yeah. So right now, girls in tech has 58 active chapters in 38 countries with over 70,000 active members. And by the end of the year we will have close to 100 active members. So hopefully we'll see you next year and that number will double or triple sign >>up. Tell him johN sent, you know, don't say that because you won't get no. Great to see you. >>Thank you. Nice to see you too. Thanks so >>much, john. Great to have you on cube coverage here at AWS public Sector summit in Washington, D. C. Is a live event. Were face to face. We had some remote guests. It's a hybrid event. Everything is being streamed. I'm john Kerry with the cube. Thanks for watching. Mhm. Mhm

>>Welcome back to the cubes coverage of AWS public sector summit live in Washington D. C. A face to face event were on the ground here is to keep coverage. I'm john Kerry, your hosts got two great guests. Both cuba alumni Shannon Kellogg VP of public policy for the Americas and john would ceo tell us congratulations on some announcement on stage and congressional john being a public company. Last time I saw you in person, you are private. Now your I. P. O. Congratulations >>totally virtually didn't meet one investor, lawyer, accountant or banker in person. It's all done over zoom. What's amazing. >>We'll go back to that and a great great to see you had great props here earlier. You guys got some good stuff going on in the policy side, a core max on stage talking about this Virginia deal. Give us the update. >>Yeah. Hey thanks john, it's great to be back. I always like to be on the cube. Uh, so we made an announcement today regarding our economic impact study, uh, for the commonwealth of Virginia. And this is around the amazon web services business and our presence in Virginia or a WS as we all, uh, call, uh, amazon web services. And um, basically the data that we released today shows over the last decade the magnitude of investment that we're making and I think reflects just the overall investments that are going into Virginia in the data center industry of which john and I have been very involved with over the years. But the numbers are quite um, uh, >>just clever. This is not part of the whole H. 20. H. Q. Or whatever they call HQ >>To HQ two. It's so Virginia Amazon is investing uh in Virginia as part of our HQ two initiative. And so Arlington Virginia will be the second headquarters in the U. S. In addition to that, AWS has been in Virginia for now many years, investing in both data center infrastructure and also other corporate facilities where we house AWS employees uh in other parts of Virginia, particularly out in what's known as the dullest technology corridor. But our data centers are actually spread throughout three counties in Fairfax County, Loudoun County in Prince William County. >>So this is the maxim now. So it wasn't anything any kind of course this is Virginia impact. What was, what did he what did he announce? What did he say? >>Yeah. So there were a few things that we highlighted in this economic impact study. One is that over the last decade, if you can believe it, we've invested $35 billion 2020 alone. The AWS investment in construction and these data centers. uh it was actually $1.3 billion 2020. And this has created over 13,500 jobs in the Commonwealth of Virginia. So it's a really great story of investment and job creation and many people don't know John in this Sort of came through in your question too about HQ two, But aws itself has over 8000 employees in Virginia today. Uh, and so we've had this very significant presence for a number of years now in Virginia over the last, you know, 15 years has become really the cloud capital of the country, if not the world. Uh, and you see all this data center infrastructure that's going in there, >>John What's your take on this? You've been very active in the county there. Um, you've been a legend in the area and tech, you've seen this many years, you've been doing so I think the longest running company doing cyber my 31st year, 31st year. So you've been on the ground. What does this all mean to you? >>Well, you know, it goes way back to, it was roughly 2005 when I served on the Economic Development Commission, Loudon County as the chairman. And at the time we were the fastest-growing county in America in Loudon County. But our residential real property taxes were going up stratospherically because when you look at it, every dollar real property tax that came into residential, we lose $2 because we had to fund schools and police and fire departments and so forth. And we realized for every dollar of commercial real property tax that came in, We made $97 in profit, but only 13% of the money that was coming into the county was coming in commercially. So a small group got together from within the county to try and figure out what were the assets that we had to offer to companies like Amazon and we realized we had a lot of land, we had water and then we had, you know this enormous amount of dark fiber, unused fibre optic. And so basically the county made it appealing to companies like amazon to come out to Loudon County and other places in northern Virginia and the rest is history. If you look today, we're Loudon County is Loudon County generates a couple $100 million surplus every year. It's real property taxes have come down in in real dollars and the percentage of revenue that comes from commercials like 33 34%. That's really largely driven by the data center ecosystem that my friend over here Shannon was talking. So >>the formula basically is look at the assets resources available that may align with the kind of commercial entities that good. How's their domicile there >>that could benefit. >>So what about power? Because the data centers need power, fiber fiber is great. The main, the main >>power you can build power but the main point is is water for cooling. So I think I think we had an abundance of water which allowed us to build power sources and allowed companies like amazon to build their own power sources. So I think it was really a sort of a uh uh better what do they say? Better lucky than good. So we had a bunch of assets come together that helps. Made us, made us pretty lucky as a, as a region. >>Thanks area too. >>It is nice and >>john, it's really interesting because the vision that john Wood and several of his colleagues had on that economic development board has truly come through and it was reaffirmed in the numbers that we released this week. Um, aws paid $220 million 2020 alone for our data centers in those three counties, including loud >>so amazon's contribution to >>The county. $220 million 2020 alone. And that actually makes up 20% of overall property tax revenues in these counties in 2020. So, you know, the vision that they had 15 years ago, 15, 16 years ago has really come true today. And that's just reaffirmed in these numbers. >>I mean, he's for the amazon. So I'll ask you the question. I mean, there's a lot of like for misinformation going around around corporate reputation. This is clearly an example of the corporation contributing to the, to the society. >>No, no doubt. And you think >>About it like that's some good numbers, 20 million, 30 >>$5 million dollar capital investment. You know, 10, it's, what is it? 8000 9000 >>Jobs. jobs, a W. S. jobs in the Commonwealth alone. >>And then you look at the economic impact on each of those counties financially. It really benefits everybody at the end of the day. >>It's good infrastructure across the board. How do you replicate that? Not everyone's an amazon though. So how do you take the formula? What's your take on best practice? How does this rollout? And that's the amazon will continue to grow, but that, you know, this one company, is there a lesson here for the rest of us? >>I think I think all the data center companies in the cloud companies out there see value in this region. That's why so much of the internet traffic comes through northern Virginia. I mean it's I've heard 70%, I've heard much higher than that too. So I think everybody realizes this is a strategic asset at a national level. But I think the main point to bring out is that every state across America should be thinking about investments from companies like amazon. There are, there are really significant benefits that helps the entire community. So it helps build schools, police departments, fire departments, etcetera, >>jobs opportunities. What's the what's the vision though? Beyond data center gets solar sustainability. >>We do. We have actually a number of renewable energy projects, which I want to talk about. But just one other quick on the data center industry. So I also serve on the data center coalition which is a national organization of data center and cloud providers. And we look at uh states all over this country were very active in multiple states and we work with governors and state governments as they put together different frameworks and policies to incent investment in their states and Virginia is doing it right. Virginia has historically been very forward looking, very forward thinking and how they're trying to attract these data center investments. They have the right uh tax incentives in place. Um and then you know, back to your point about renewable energy over the last several years, Virginia is also really made some statutory changes and other policy changes to drive forward renewable energy in Virginia. Six years ago this week, john I was in a coma at county in Virginia, which is the eastern shore. It's a very rural area where we helped build our first solar farm amazon solar farm in Virginia in 2015 is when we made this announcement with the governor six years ago this week, it was 88 megawatts, which basically at the time quadruple the virginias solar output in one project. So since that first project we at Amazon have gone from building that one facility, quadrupling at the time, the solar output in Virginia to now we're by the end of 2023 going to be 1430 MW of solar power in Virginia with 15 projects which is the equivalent of enough power to actually Enough electricity to power 225,000 households, which is the equivalent of Prince William county Virginia. So just to give you the scale of what we're doing here in Virginia on renewable energy. >>So to me, I mean this comes down to not to put my opinion out there because I never hold back on the cube. It's a posture, we >>count on that. It's a >>posture issue of how people approach business. I mean it's the two schools of thought on the extreme true business. The government pays for everything or business friendly. So this is called, this is a modern story about friendly business kind of collaborative posture. >>Yeah, it's putting money to very specific use which has a very specific return in this case. It's for everybody that lives in the northern Virginia region benefits everybody. >>And these policies have not just attracted companies like amazon and data center building builders and renewable energy investments. These policies are also leading to rapid growth in the cybersecurity industry in Virginia as well. You know john founded his company decades ago and you have all of these cybersecurity companies now located in Virginia. Many of them are partners like >>that. I know john and I both have contributed heavily to a lot of the systems in place in America here. So congratulations on that. But I got to ask you guys, well I got you for the last minute or two cybersecurity has become the big issue. I mean there's a lot of these policies all over the place. But cyber is super critical right now. I mean, where's the red line Shannon? Where's you know, things are happening? You guys bring security to the table, businesses are out there fending for themselves. There's no militia. Where's the, where's the, where's the support for the commercial businesses. People are nervous >>so you want to try it? >>Well, I'm happy to take the first shot because this is and then we'll leave john with the last word because he is the true cyber expert. But I had the privilege of hosting a panel this morning with the director of the cybersecurity and Infrastructure Security agency at the department, Homeland Security, Jenness easterly and the agency is relatively new and she laid out a number of initiatives that the DHS organization that she runs is working on with industry and so they're leaning in their partnering with industry and a number of areas including, you know, making sure that we have the right information sharing framework and tools in place, so the government and, and we in industry can act on information that we get in real time, making sure that we're investing for the future and the workforce development and cyber skills, but also as we enter national cybersecurity month, making sure that we're all doing our part in cyber security awareness and training, for example, one of the things that are amazon ceo Andy Jassy recently announced as he was participating in a White house summit, the president biden hosted in late august was that we were going to at amazon make a tool that we've developed for information and security awareness for our employees free, available to the public. And in addition to that we announced that we were going to provide free uh strong authentication tokens for AWS customers as part of that announcement going into national cybersecurity months. So what I like about what this administration is doing is they're reaching out there looking for ways to work with industry bringing us together in these summits but also looking for actionable things that we can do together to make a difference. >>So my, my perspective echoing on some of Shannon's points are really the following. Uh the key in general is automation and there are three components to automation that are important in today's environment. One is cyber hygiene and education is a piece of that. The second is around mis attribution meaning if the bad guy can't see you, you can't be hacked. And the third one is really more or less around what's called attribution, meaning I can figure out actually who the bad guy is and then report that bad guys actions to the appropriate law enforcement and military types and then they take it from there >>unless he's not attributed either. So >>well over the basic point is we can't as industry hat back, it's illegal, but what we can do is provide the tools and methods necessary to our government counterparts at that point about information sharing, where they can take the actions necessary and try and find those bad guys. >>I just feel like we're not moving fast enough. Businesses should be able to hack back. In my opinion. I'm a hawk on this one item. So like I believe that because if people dropped on our shores with troops, the government will protect us. >>So your your point is directly taken when cyber command was formed uh before that as airlines seeing space physical domains, each of those physical domains have about 100 and $50 billion they spend per year when cyber command was formed, it was spending less than Jpmorgan chase to defend the nation. So, you know, we do have a ways to go. I do agree with you that there needs to be more uh flexibility given the industry to help help with the fight. You know, in this case. Andy Jassy has offered a couple of tools which are, I think really good strong tokens training those >>are all really good. >>We've been working with amazon for a long time, you know, ever since, uh, really, ever since the CIA embrace the cloud, which was sort of the shot heard around the world for cloud computing. We do the security compliance automation for that air gap region for amazon as well as other aspects >>were all needs more. Tell us faster, keep cranking up that software because tell you right now people are getting hit >>and people are getting scared. You know, the colonial pipeline hack that affected everybody started going wait a minute, I can't get gas. >>But again in this area of the line and jenny easterly said this this morning here at the summit is that this truly has to be about industry working with government, making sure that we're working together, you know, government has a role, but so does the private sector and I've been working cyber issues for a long time to and you know, kind of seeing where we are this year in this recent cyber summit that the president held, I really see just a tremendous commitment coming from the private sector to be an effective partner in securing the nation this >>full circle to our original conversation around the Virginia data that you guys are looking at the Loudon County amazon contribution. The success former is really commercial public sector. I mean, the government has to recognize that technology is now lingua franca for all things everything society >>well. And one quick thing here that segues into the fact that Virginia is the cloud center of the nation. Um uh the president issued a cybersecurity executive order earlier this year that really emphasizes the migration of federal systems into cloud in the modernization that jOHN has worked on, johN had a group called the Alliance for Digital Innovation and they're very active in the I. T. Modernization world and we remember as well. Um but you know, the federal government is really emphasizing this, this migration to cloud and that was reiterated in that cybersecurity executive order >>from the, well we'll definitely get you guys back on the show, we're gonna say something. >>Just all I'd say about about the executive order is that I think one of the main reasons why the president thought was important is that the legacy systems that are out there are mainly written on kobol. There aren't a lot of kids graduating with degrees in COBOL. So COBOL was designed in 1955. I think so I think it's very imperative that we move has made these workloads as we can, >>they teach it anymore. >>They don't. So from a security point of view, the amount of threats and vulnerabilities are through the >>roof awesome. Well john I want to get you on the show our next cyber security event. You have you come into a fireside chat and unpack all the awesome stuff that you're doing. But also the challenges. Yes. And there are many, you have to keep up the good work on the policy. I still say we got to remove that red line and identified new rules of engagement relative to what's on our sovereign virtual land. So a whole nother Ballgame, thanks so much for coming. I appreciate it. Thank you appreciate it. Okay, cute coverage here at eight of public sector seven Washington john ferrier. Thanks for watching. Mhm. Mhm.

value in jobs is probably the most rewarding >>things I've ever been involved >>in And I bring that energy to the queue because the cube is where all the ideas are and where the experts are, where the people are And I think what's most exciting about the cube is that we get to talk to people who are making things happen, entrepreneurs ceo of companies, venture capitalists, people who are really on a day in and day out basis, building great companies and the technology business is just not a lot of real time live tv coverage and and the cube is a non linear tv operation. We do everything that the T. V guys on cable don't do. We do longer interviews. We asked tougher questions. We >>ask sometimes some light questions. We talked about the person and what >>they feel about it's not prompted and scripted. It's a conversation authentic and for shows that have the cube coverage and makes the show buzz that creates excitement. More importantly, it creates great content, great digital assets that can be shared instantaneously to the world. Over 31 million people have viewed the cube and that is the result of great content, great conversations and I'm so proud to be part of a Q with great team. Hi, I'm john barrier, Thanks for watching the cube boy. >>Okay, welcome back everyone cube coverage of AWS amazon web services public sector summit in person here in Washington D. C. I'm john Kerry host of the cube with Sandy carter and Lynn martin Vm ware Vice president of government education and healthcare. Great to see you both cube alumni's although she's been on since 2014 your first time in 2018 18 2018. Great to see you. Great to see you. Thanks for coming on. Yeah, thanks for having us. So VM ware and 80 of us have a huge partnership. We've covered that announcement when Andy and Pat nelson was the Ceo. Then a lots happened, a lot of growth. A lot of success. Congratulations. Thank you. What's the big news with AWS this year in >>public sector. So we just received our authorization to operate for Fed ramp high. Um and we actually have a lot of joint roadmap planning. You are kicking off our job today with the Department of Defense and I. L five for the defense customers is also in process. So um a lot of fruits of a long time of labor. So very excited, >>awesome. So explain what does the Fed ramp authority to operate mean? What is >>that all about? So I would say in a nutshell, it's really putting a commercial offering through the security protocols to support the federal government needs. Um and there's different layers of that depending on the end user customers. So Fed ramp i across this, across all the civilian and non classified workloads in the federal government. Um probably applicability for state, local government as well with the new state Gramp focus. Um Fed ramp. I will meet or exceed that. So it will be applicable across the other parts of the government as well and all operated, you know, in a controlled environment jointly. So you get the VM ware software stack on top of the platform from A W. S and all the services that is more VM >>ware, faster deployed usage, faster acceleration. >>Yeah, so I would say um today the government operates on VM ware across all of the government, state, local and federal, um some workloads are still on prem many and this will really accelerate that transformation journey to the cloud and be able to move workloads quicker onto the BMC on AWS platform without free architect in your >>application, without giving away any kind of VM World Secret because that's next week. What is the value proposition of VM ware cloud, on AWS? What is the, what is the, what is the main value proposition you guys see in the public >>sector? So I see three and then Sandy chime in their two, I would say, you know, the costs in general to operate In the Cloud vs on prem or significant savings, we've seen savings over 300% on some customers. Um the speed on the application movement I think is a >>huge >>unique benefit on BMC on AWS. So traditionally to move to native cloud, you have to really do a lot of application were to be able to move those workloads where on BMC on AWS to move them pretty fast. And it also leverages the investments that the government agencies have already made in their operational tools and things of that nature. So it's not like a full reinvestment for something new but really leveraging both the skill sets in the data center in the I. T. Shops and the tools and investments you've bought over the past. And then the third area I would say is really getting the agility and flexibility and speed of a cloud experience. >>What's your, what's your reaction to the partnership? >>You know, we were just talking uh in a survey to our customers and 67% of them said that the velocity of the migration really matters to them. And one of the things that we do really well together is migrate very quickly, so we have workloads that we've migrated that have taken you know weeks months uh as opposed to years as they go over, which is really powerful. And then also tomorrow VM ware is with us in a session on data led migration. We were talking about data earlier and VM ware cloud on Aws also helps to migrate over like sequel server, database oracle databases so that we can also leverage that data now on the cloud to make better decisions and >>real time decisions as >>well. It's been really interesting to watch the partnership and watching VM ware transform as well, not only the migrations are in play with the public sector, there's a lot of them, believe me, healthcare, you name every area. It's all, all those old systems are out there. You know, I'm talking about out there. But now with microservices and containers, you've got tansy and you got the whole cloud, native VM ware stack emerging that's going to allow customers to re factor This is a dynamic that is kind of under reported >>Migration is one thing. But I think, I think that the whole Tan Xue portfolio is one of the most interesting things going on in VM ware. And we also have some integration going on on D. M. C on AWS with tan to we don't have that pentagram. Yeah. For the government market, but it's on the road mapping plans and we have other customers And I would say, you know, some of my non federal government customers were able to move workloads in hours, not even days or weeks. There you go, literally back and forth. And very impressive on the BMC on AWS platform. So, um, as we expand things in with the Tan Xue platform is, you know, Sandy talked about this yesterday and our partners summit, Everyone's talking about containers and things like that. VM ware is doing a lot of investment around the cooper Netease plus the application migration work and things of that nature. >>I'd love to get you guys reaction to this comment because I've seen a lot of change. Obviously we're all seeing it. I've actually interviewed a bunch of aWS and VM ware customers and I would call um some of the categories skeptics the old school cloud holding the line. And then when the pandemic hit those skeptics flip over because they see the value. In fact I actually interviewed a skeptic who became an award winner who went on the record and said I love hey w I love the cloud. I was a skeptic because you saw the value the time to value. This is really a key dynamic. I know it's kind of thrown out a lot of digital transformation or I. T. Modernization but the agility and that kind of speed. It becomes the number one thing. What's your reaction to the skeptics converting? And then what happens >>next? Um So I think there's still a lot of folks in I. T. That our tree huggers or I call him several huggers uh um pick your term. And I think that um there is some concern about what their role will be. So I think one of the differences delivering cloud services to your internal constituents is really understand the business value of the applications and what that delivers from a mission perspective back to your client. And that's a shift for data center owners to really start thinking more from the customer mission perspective than or my servers running you know, do you have enough storage capacity blah blah blah. So I think that creates that skepticism and part of that's around what's my role going to be. So in the cloud transformation of a customer, there's all this old people part that becomes really the catalyst and I think the customers that have been very sad and really leverage that and then retool the business value back to the end users around the mission have done the best job. >>I mean we talk about this all the time, it's really hard to get the best debris partners together and then make it all work cloud, it becomes easier than doing it very bespoke or waterfall way >>Yeah, I have to say with the announcement yesterday, we're going to have a lot more partner with partners. So you and I have talked about this a few times where we bring partners together to work with each other. In fact, Lynn is going to go meet with one of those partners right after the interview um that want to really focus in on a couple of particular areas to really drive this and I think, you know, part of the, you know, as your re factoring or migrating VMro over the other big benefit is skills, people have really strong, these fear skills, the sand skills, >>operation >>operation tools Yeah. And so they want to preserve those, I think that's part of the beauty of doing VM ware cloud on Aws is you get to take those skills with you into the new world as well, >>you know, I was going to just ask the next question ai ops or day two operations, a big buzzword Yeah and that is essentially operation mindset, that devoPS DEVOps two is coming. Emily Freeman gave a keynote with our last event we had with with amazon public showcase revolution and devops devoPS 2.0 is coming which is now faster, security is built in the front end, so all these things are happening so now it's coming into the public sector with the GovCloud. So I have to ask you Lynn what are some of the big successes you've had with on the gulf cloudy, just Govcloud. >>So I would say we've had a lot of customers across the state local side especially um that weren't waiting for fed ramp and those customers were able to move like I mentioned this earlier and you guys just touched on it. So I think the benefit and the benefit, one of our best customers is Emmett Right? Absolutely mitt, God bless them. They've been on every cloud journey with VM ware since 2014 we moved in my three years now and talk about a skeptic. So although Mark is very revolutionary and tries new things, he was like oh who knows and literally when we moved those workloads it was minutes and the I. T shop day one there was no transformation work for them, it was literally using all the tools and things in that environment. So the progress of that and the growth of the applications that have been able to move their things. That took 2 to 3 years before we're all done within six months and really being able to expand those business values back out for the services that he delivers to the customers. So I think you'll see quite a bit across state, local federal government. You know, we have U. S. Marshals, thank them very much. They were our sponsor that we've been working with the last few years. We have a defense customer working with us around aisle five. >>Um you know, if we could also thank Coal Fire because Cold Fire is one of our joint partners talking about partner partners and they were played a critical role in helping BM We're cloud on AWS and get the fed ramp high certifications. >>They were R three p. O. We hired them for their exercise expertise with AWS as well as helping the BMR. >>Well the partnership with the war has been a really big success. Remember the naysayers when that was announced? Um it really has worked out well for you guys. Um I do want to ask you one more thing and we don't mind. Um One of the biggest challenges that you see the blockers or challenges from agencies moving to the cloud cover cloud because you know, people are always trying to get those blockers out of the way but it's an organizational culture is a process technology. What's your what's your take on that land. Um >>I think a lot does have to do with the people and the organizational history. I think somewhere you need a leader and a champion that really wants to change for good. I call Pat, used to call a tech for good. I love that. Right to really, you know, get things moving for the customers. I mean one of the things I'm most proud about supporting the government business in general though is really the focus on the mission is unparalleled, you know, in the sectors we support, you say, education or government or healthcare. Right? All three of those sectors, there's never any doubt on what that focuses. So I think the positives of it are like, how do you get into that change around that? And that could be systems, there's less what's VMC ON AWS as we mentioned, because the tools already in the environment so they know how to use it. But I do think there's a transformation on the data center teams and really becoming moving from technology to the business aspects a little bit more around the missions and things of that. >>What's interesting is that it's so, I mean, I actually love this environment even though it's kind of hard on everyone. Education and health care have been disrupted unprecedented ways and it's never gonna change back? Remember healthcare, hip data silos, silos, education don't spend on it. >>That education was the most remarkable part. Unbelievable. I started working in february before school started with one of the large cities everyone can guess and just the way they were able to pivot so fast was amazing and I don't think anybody, I think we did like five years of transformation in six months and it's never going to go back. >>I completely a great yes education. We just did a piece of work with CTS around the world and education is one of the most disrupted as you said health care and then the third one is government and all three of those are public sector. So the three most disruptive sectors or mission areas are in public sector which has created a lot of opportunity for us and our partnership to add value. I mean that's what we're all about right customer obsession working backwards from the customer and making sure that our partnership continues to add value to those customers >>while we love the tech action on the cube. Obviously we'd like to document and pontificate and talk about it. Digital revolution. Every application now is in play globally. Not just for I. T. But for society, public sector more than ever is the hottest area on the planet. >>Absolutely. And I would say that now our customers are looking at E. S. G. Environmental, they want to know what you're doing on sustainability. They want to know what you're doing for society. We just had a bid that came in and they wanted to understand our diversity plan and then open governance. They're looking for that openness. They're not just artificial intelligence but looking at explainable AI as well. So I think that we have a chance to impact environment societies and governance >>and you mentioned space earlier. Another way I talked with closure. I mean I'm an interview today too, but what's happening with space and what you can monitor disasters, understand how to deploy resources to areas that might have challenges, earthquakes or fires or other things. All new things are happening. >>Absolutely. And all that data people like to say, why are you spending money on space? There's so many problems here, but that data that comes from space is going to impact us here on earth. And so all the things that we're doing, all that data could be used with VM ware cloud on AWS as well. >>Well, you watch closely we got some space coverage coming. I got a big scoop. I'm gonna release soon about something behind the dark side of the moon on in terms of space sovereignty coming a lot of action, cybersecurity in space. That's really heavy right now. But >>aren't you glad that VMC cloud on AWS isn't hidden on the dark side of the moon. It's >>right on the congratulations. Thanks for coming on. You guys are doing great. Thanks for >>thanks for sharing. Congratulations. >>Okay, cube coverage here continues. AWS public sector summit in Washington D. C live for two days of coverage be right back. Thank you. Mhm. Mhm mm mm hmm.

>>Hello and welcome back to the cubes live coverage of A W. S. Public sector summit. I'm john Kerry hosting CUBA. We're live in Washington D. C. For two days, an actual event with an expo floor with real people face to face and of course we're streaming it digitally on the cube and cube channels. And so our next guest, Mark Francis chief digital health integration officer Electronic caregiver, Mark great to see you tech veteran and former intel back in the day. You've seen your ways of innovation. Welcome to the cube. >>Thanks so much. It's a pleasure to be here. >>So we were talking before we came on camera about all the innovation going back in the computer industry but now with health care and delivery of care telemedicine and how the structural systems are changing and how cloud is impacting that. You guys have an interesting solution on AWS that kind of, to me connect the dots for many tell us what you guys do and take us through the product. >>Sure. Happy to do so uh our company is electronic caregiver were actually founded back in 2009. We're based in Los cruces new Mexico so off the grid. Um but since that time we have been spending a lot of time and money doing foundational R and D pilots and product development work. Really say how do you bridge that chasm between the doctor's office and the patient home in a way that you can put a patient facing device and equipment in a patient's home that's going to drive high level of engagement, obtain actionable curated data that's presented out to caregivers and the caregivers can then act upon that to help direct and deliver high quality care. >>So basically is the future of medicine, >>the future of medicine. Right. Right. We look at medicine, we look at the future of medicine as being a hybrid model of in person care plus remote care. And we really see ourselves at the epicenter of providing a platform to help enable that. >>You know the big story here at the public sector. Some and we've been reporting on a digitally for the previous year is the impact the pandemic has had on the industry and and not just normal disruption, you know technology and start ups, disruption happens, structural changes being forced upon industries by the force majeure. That is the pandemic education, health care and so video and data and connected oriented systems are now the thing structurally that's changing it. That's causing all kinds of business model, innovations and challenges. Yeah. What's your take on that? Because this is real. >>Yeah. It is real. It it's funny that this is actually my third digital health company. Um First one was in in uh Silicon Valley early remote patient monitoring company. We end up selling it to bosh uh when I joined intel to be part of our digital health group, we did that for five years and ended a joint venture with G. E. So people have been playing around in remote patient monitoring telehealth for some time until the pandemic though there wasn't really a strong business model to justify scaling of these businesses. Um uh the pandemic change that it forced adoption and force the government to allow reimbursement coach as well. And as a result of that we've seen this pure if aeration of different product offering service offerings and then payment models around telehealth broadly speaking >>well since you started talking the music started cranking because this is the new music of the industry, we're here on the expo floor, we have face to face conversations going on and uh turn the music down. Hey thanks guys, this is a huge thing and I want to uh highlight even further what is the driver for this? Because is it, I mean actually clouds got some benefits but as you guys do the R. And D. What's going on with what's the key drivers for medicine? >>Yeah, I would take two things from a from a technology perspective, the infrastructure is finally in place to enable this type of charity distance before that it really wasn't there now that's there and the products that folks are used are much more affordable about the provider's side and the patient side. The main driver is um uh there's a lot of underlying trends that were happening that we're just being ignored Whether it was 50% non adherence to treatment plans, massive medication mismanagement um lack of professional and informal caregivers, all those things were kind of happening underneath the surface and then with Kobe, it all hit everybody in the phase. People started using telehealth and then realize, hey, we can deliver high quality care, we can deliver value based care mixed with a hybrid model of tele care plus patient care. And it turned out that, that, that works out well. So I think it's now a realization that tell care not only connects patients but solve some of these other issues around adherents, compliance, staffing and a number of other >>things and that this is a structural change we were talking about. Exactly. All right, So talk about amazon, what do you guys are doing on AWS? How's that all work? >>That's working out great. So as we, as we launch at a 2.0, we built it on 24 foundational aws and Amazon services. It's a serverless architecture, um, uh, which is delivered. What enables us to do is we have a whole bunch of different patients facing devices which we now integrate all into one back end through which we can run our data analytics are machine learning and then present curated actual data to the providers on top of that. We've also been developing a virtual caregiver that's really, really innovative. So we're using the unity engine to develop a very, very realistic virtual caregiver that is with the patient 24 hours a day in their home, they develop a relationship with that individual and then through that they can really drive greater you know more intimate care plan and a more intimate relationship with their human caregivers that's built using basic technology behind Alexa pauline lacks as well as IOT core and a lot of other ai ml services from from amazon as well. >>Not to get all nerdy and kind of seeking out here because under the hood it's all the goodness of amazon. We've got a server list, you got tennis is probably in there doing something who knows what's going on there, You've got polly let's do this and that but it also highlights the edge the ultimate network edges the human and if you've got to care for the patient at home or wherever on the run whatever. Yeah you got to get the access to the data so yeah I can imagine a lot of monitoring involved too. Yeah can you take us through how that works? >>Yeah and for us we like to talk about intelligence as opposed to data because data for data sakes isn't actionable. So really what can we do through machine learning and artificial intelligence to be able to make that data more actionable before the human caregiver because you're never going to take a human out of the equation. Uh But uh we had a lot of data inputs, they're both direct data inputs such as vital signs, we also get subtle data input. So with our with our uh with Addison or virtual caregiver uh the product actually come to the camera away from intel called the real sense cameras. And with that we get to see several signs of changes in terms of gate which might be in the indicative of falls risk of falls. We can see body temperature, pulse, heart rate, signs of stress, lack of sleep. Maybe that's a sign of uh adverse reaction to a new medication. There's a bunch of different direct and indirect inputs. We can take run some analysis against and then say hey there's something here you might want to look at because it might be indicating a change in health. >>So this is where the innovation around these bots and ai come in because you're essentially getting pattern matching on other signals you already know. So using the cameras and or sensors in to understand and get the patients some signaling where they can maybe take action call >>fun or Yeah, that's exactly. And the other thing we get, we get to integrate information related to what are called social determinants of health. So there's a whole body of research now showing that 65% of someone's health is actually driven by non clinical issues. So again issues of food security, transportation, access to care, mental health type issues in terms of stress and stuff like we can start gathering some of that information to based upon people's behaviors or for you to assessments which can also provide insights to help direct care. >>So maybe when I'm doing the Cuban reviews, you guys can go to work and look at me. I'm stressed out right now, having a great time here public sector, this is really cool. So take a minute to explain the vision. What does this go from here? I'll see low hanging fruit, telemedicine, check data, observe ability for patient for optimizing care, check what happens next industry disruption, what how these dominoes have been kind of fall? >>Yeah, for us uh we really are seeing more providers and more payers system. Integrators looking now to say how do I put together a comprehensive solution from the doctor's office to inpatient hospital to home that can remove it. A lot of barriers to care addi which is our platform is designed to be interoperable to plug into electronic health care systems, whether it's Cerner, Epic or Athenahealth, whatever it might be to be able to create that you pick us seamless platform for provider to use. We can push all of the data to their platform if they want to use that or they could use our platform and dashboard as well. We make it available to healthcare providers but also a lot of people are trying to age in place and they're getting treated by private duty providers, senior housing providers and other maybe less clinical caregivers. But if you're there every day with somebody you can pick up signs which might prevent a major health episode down the road. So we want to close that circle our our vision is how do we close the circle of care so that people get the right information at the right time to deliver the right >>care. So it's kind of a health care stack of a new kind of stack. So I have to ask you if there was an eye as pass and sass category um infrastructure as a service platform as a service. And then says it sounds like you guys are kind of combine the lower parts of the stack and enable your partners to develop on top of. Is that how it >>works? Yes it does. Yeah. Yeah. So with addie, the interesting thing that we've done it's designed to have open a P. I. For a lot of modules as well. So if we're working with the american Heart Association and we want to do a uh cardiac care module from using their I. P. We could do that if we want to integrate with Uber health or lift we could do that as well if we want to do something in the amazon and pill pack, it's a plug in that we could do that. So if I'm a patient or or a loved one at home instead of going to 10 different places or use our platform and then pull up four different apps. Everything can be right there at their fingertips. You can either do it by touch or you can use this voice because it's all a voice or a touch of interaction. >>So just because I'm curious and and and for clarification, the idea of going past versus SAS platform versus software as a service is why flexibility or customization? Why not go SAS and be a SAS application? >>Uh we've talked mostly about, we've we've gone back and forth platform as a service or infrastructure as a service. So that's more the debate that we've had. It's more about the scalability that we can offer. Um uh not just in the United States, but globally as well. Um and really that's really the thing that we've been looking at, especially because there's so many different sources of data, if you want to provide high quality care that needs to be integrated. We want to make sure that we created a platform, not just for what we provide but for what others in the environment can provide. >>So you really want to enable other people to create that very much layer on top of you guys, do you have out of the box SAS to get people going or is that just >>With the release of adding 2.0, now we do. So now folks go to our website and they contact our development those tools and and those libraries are available. >>Now, this is an awesome opportunity. So for people out there who are wanting to innovate on you, they can just say, okay, I'll leverage your the amazon web services of healthcare essentially. >>That's a nice bold ambitious statement. Yeah, but I mean kind of but if we if we can achieve that, then we'd be quite happy and we think the industry, you're gonna partner >>benefit of that. It's an ecosystem play. Exactly, yeah. It's kind of like. >>Yeah, yeah, yeah, yeah. And for us, what we do covert is a perfect example going back to that. So when Covid hit um were based in las cruces, new Mexico last winter lost crew system to el paso and overwhelmed. They're at capacity. Different health care systems came to us, they asked if we partner with them to deliver a basically a triage program for folks that were coming into the er with Covid. So we designed a Kobe at home programs. So you get diagnosed, get a kit, go home and using telehealth virtual visits, remote monitoring. Be able to stay healthy at home without doing community spread. And by making sure that you were being watched over by a care professionals 24 hours a day. We did that um worked with 300 people Malcolm would all of them said healthy. We were able to expand uh inpatient capacity by 77%. We saved the system over $6 million in in three months. We've now been asked and we're actually replicating that in Memphis now and then also we've been asked to do so down in Mississippi >>mark, great conversation. Uh real quick. I only I don't have much time left but I want to ask you, does this mean that we're gonna see a clip of proliferation of in home kind of devices to assist? >>Yeah, we will. Uh, what we've seen is a big pivot now towards hospital at home model of care. So you have providers saying, you know, I'll see you in my facility but also extend capabilities so I can see you and treat you at home as well. We've also seen a realization that telehealth is more than a than an occasional video visit because if all you're doing is replacing an occasional in person visit with an occasional video visit. You're not really changing things now. There's a whole different sensors ai other integrations that come together to be able to enable these different models >>for all the business school folks out there and people who understand what's going on with structural change. That's when innovation really changes. Yeah, this is structural change. >>Absolutely. >>Mark, thanks for coming on. Mark Francis chief Digital Health Integration Officer Electronic Caregiver here on the Q. Thanks. Coming >>on. Thank you. My pleasure. >>Okay, more coverage after this short break. I'm john Kerry, your host Aws public Sector summit, We'll be right back mm mm mm

>>Mhm. Mhm Hello and welcome back to the cubes coverage of AWS summit here. Public sector summit here in Washington, D. C. I'm john for your host, We're live at a physical event. People face to face. We're here with the cube on the ground back in business. Of course we have a virtual cube. We got the cube studios in Palo alto in boston. We're gonna bring you all the great coverage and our next guest is parallel casa, Anita Casanova got it. Chief of Channels at Pegasystems, also known as mega official titles, head of global partner ecosystem. But you're known as the Chief of channels. >>Absolutely, thank >>you for coming on. >>Absolutely nice to be here face to face in an event. >>Feel happy, feels good. It feels great. People are happy. I'm still good attendance. Considering what it is about 5, 6000 people roughly give or take maybe up to 7000, who knows. But you guys have a really strong relationship with AWS, you're the chief of the channel. You guys have a great enabling product that crashes itself, as you guys say. So let's get into it before explain what PEG A does. >>Okay, so paga he's a $1 billion dollar company. It's a software company and we call it that software built itself Because we are definitely here to crash customer complexity. So we do it by three doing three things, 1-1 customer engagement customers, customer service and also intelligent automation. So we are a platform and we are helping any single client that has a complex solution to make it simple and to have a good customer experience. >>So I got it wrong. It doesn't crash itself, it crashes complexity, It builds itself okay there it is. All right, I got that out of the way. Software that crashes itself actually doesn't really kind of doesn't sound like a compelling products, but it's not the case. So I gotta ask you So ecosystems are a big part of the cloud amazon has a great ecosystem but the ecosystem has ecosystem is starting to see an expansion of the cloud business with the software model. With cloud scale. What are you guys doing in the channel within the public sector? How do you guys work, how do people engage with you? >>Okay, so first of all we we were always very friendly channel partner but we were using our partners only for implementation because our product is so so uh built for each of the clients, there's a lot of services opportunity and we have very strong peg a practices in the different partners. But last year when I came in I came in almost 16 months ago we decided that we wanted also to improve our our sales with the partners. So we are engaging with partners and to and from the beginning of a sale cycle and brainstorming on what the client needs in order to be more efficient to reduce cost to the moment of the implementation. So we have been working with several uh system integrators, some resellers and with aws as our cloud platform. So we have been moving everything we can to the peg, a cloud that is on aws and clients are are really happy to be modernized in there because there you have the security, the scalability then you the new versions of the product without having to be worrying about it because it's done by our support. >>So it's software on amazon. So customers can buy your software through the marketplace or whatever through a partner or the marketplace and then they can still use the higher level services at in AWS, correct? >>They can use a high services in AWS or with any other partner system Integrator that also works with AWS and we have many cases where we are we we use the power of three. Right. We work with AWS accenture and and for example, Peg or we can use lay does or or booz allen or a parrot on any of the partners that are here in government. >>So you know, the channel equation, you're the chief of the channel. Channel channels love simplicity, simple products to buy. They love products that can throw off gross profit. And you said services, how is that going? Are you guys seeing a good economic equation with your partners? >>Well, our partners do between five and 10 IX of uh, of the revenue that we do on software on services. So that equation definitely works and they love it for that. At the same time we have invested five x the quantity of people that we have supporting the channel. For example, here in government we have invested also two or three times on the rest of the of the business. But there has been definitely good investments for partners. The partners are happy with us because again they not only they can do a good business one off, they can then radiate one. You usually clients one day once they buy peg for one of their use cases or case management as we call it, they usually want to replicate it in other cases and that is where the partners are doing enormous money because they are replicating the same use case in different departments. >>That's the way it's supposed to be, it's their touching the customer, they're adding value on top of your product. So they get to have the best of both worlds high margins on the profits and the services but yet worked with the customer directly to engage, make sure they get the right solution from you and a W. S together. >>Absolutely. Okay, >>what are the key challenges that you find that partners need to solve and overcome to keep this this this equation going. What do you guys focus on? You mentioned more people, what are some of the trends in the public cloud? I mean public sector area? What's this with the dynamics? >>So in in this moment the whole world is with a huge need of digital transformation the every single client but especially in government, they had all digital transformation projects. But they were going at slow motion because of the situation of the pandemic that I don't even want to name it again because everybody's talking about it but it's a reality. These projects have to accelerate 10 times. So whatever it was going to be done in five years has been done in one. So the biggest challenge that we are having is to ensure that we have that capacity to support all these projects that are being done very fast and and for that that's why we also need our partners right Because they have big mega practices. They have been investing as well as we are to ensure that we cover all those needs and but for now we are doing well and so that's that's right. We are growing as a company and with the partners >>carol great to have you on board with the company now kicking some butt now in the channel, Chief of channel good margins happy customers growth. What are some of the use case successes that you've had. Can you name a few customers and what they've done and what's their best practice? >>Well we have, I will name some government because we are in a public secretary event but we have and I will name north America although we also have in the rest of the world. So U. S. Census. That is something that everybody has done right. Even if you did in your mobile, you did it on paper, you did it on the phone. All of that was managed by paga And for the first time ever there was zero than downtime. Not a single problem to access the web. For example, the the US census took us 50% less expense than the one that we did in 2010 just because we use this digital approach And then we also were 50% more efficient because we needed, we didn't need to use all that paper storage that was used in the past. So we taxpayers have to be happy because they really spend less than what they should have spent on this topic. So definitely that was one of the biggest cases that we have in 2020. We have other, we took big big projects like the US and or we do smaller projects and there's one that is not small but that is smaller, that is the New Jersey court that caught my attention because I imagine myself in a situation like that that you are like my mistake taken to the court and you and they are, they are you have to defend yourself that was taking three hours and it's stressful, right? And you don't have to be there if you don't need to And this process got to 20 minutes, that is also reduction and expenses even jail expenses sometimes. So that was one that we did as well. And and that was just by making four legacy systems getting to one having a much faster experience on that. So >>a lot of migrations, a lot of cloud native re factoring going on in the applications sounds like >>yes. What we do is whatever legacy systems you have, we managed to ensure that we connect them all and to have a front line so that you can access information real time and that you can as a user and that you can really have a better experience whatever you do today, whatever company telco company you have, bank you use, I can guarantee you have you have, you speak to you just don't know about >>that. It's under the covers. I gotta ask you my final question. So you guys really doing some good business out here, what if people watching here trying to understand the dynamics of public sector market? What's your take, what's your what do you what would you say, that person? What's the big story happening in public sector? >>Well, to begin with, I'm not a public sector experts, I'm sure that there's a lot of public sector experts out there that can tell me, oh no, you missed this point. But what I have seen in these days that I have been here with the team is that the government needs to act fast in order to digitalized all these projects. So one of our partners yesterday was telling me that there is a mandate in in the army for example to move everything to cloud. How do you do it? They don't even know they're there, there are people that they don't they don't know how to do this. So our partners are building solutions to help them faster get into the cloud because they have to do it by the end of the year. And these are the key things that we are working on with partners to build solutions that can really can access for robust and they can >>escape. It's a very robust ecosystem. Yes, So amazon is an ecosystem you guys and you have an ecosystem. >>It's an ecosystem of ecosystems and that is what works right because Amazon has very good sellers for example, very good people that know the clients and they have a lot of experience but they are not specialized in what to do >>with the channel. These >>other partners have a peg a practice, they are experts and as I told you this is about crushing complexity. So it's making you need to understand the technology and the details behind it to make the best solution to the client. >>Corolla. Great to have you on very dynamic. Love, Love chatting with you Corolla Cazenove >>Cazenove >>Cazenove chief of channels that Pegasystems also known as peg a great to have you on, congratulations on your success. Ecosystems within an ecosystem crushing complexity. Mr que bringing you all the signal out there from the noise. I'm john Kerry. Thanks for watching. Mhm. Mhm.

>>mhm. What the special cube conversation here in Palo alto, I'm john Kerry host of the cube. We're here talking about kubernetes Cloud native and all things Cloud, cloud enterprise amir Sure VP of product and morgan Stanley is with me and we are great to have you on the cube. Thanks for coming on. I appreciate you taking the time, >>appreciate it, john good to be here. You >>know, cloud Native obviously super hot right now as the edges around the corner, you're seeing people looking at five G looking at amazon's wavelength outposts you've got as you got a lot of cloud companies really pushing distributed computing and I think one of the things that people really are getting into is okay, how do I take the cloud and re factor my business and then that's one business side then, the technical side. Okay, How do I do it? Like it's not that easy. Right. So it sounds, it sounds really easy to just go to move to the cloud. This is something that's been a big problem. So I know you guys in the center of all this uh and you've got, you know, microservices, kubernetes at the core of this, take a minute to introduce the company, what you guys do then I want to get into some specific questions. >>Mhm, of course. Well, bob Sani is a startup? Silicon Valley startup and what we do is automate system configuration that's typically worked at an engineer does and take lengthy and if done incorrectly at least to a lot of errors and cost overruns and the user experience problems. We completely automate that using an Ai and ml back end so that the engineering can focus on writing code and not worry about having to tune the little pieces working together. >>You know, I love the, I was talking to a V. C on our last uh startup showcase, cloud startup showcase and uh really prominent VC and he was talking about down stack up stack benefits and he says if you're going to be a down stack um, provider, you got to solve a problem. It has to be a big problem that people don't want to deal with. So, and you start getting into some of the systems configuration when you have automation at the center of this as a table stakes item problems are cropping up as new use cases are emerging. Can you talk about some of the problems that you guys see that you solve for developers and companies, >>of course. So they're basically, they're, the problem expresses itself in a number of domains. The first one is that he who pays the bills is separate from he who consumes the resources. It's the engineers that consume the resources and the incentives are to deliver code rapidly and deliver code that works well, but they don't really care about paying the bills. And then the CFO office sees the bills and there's a disparity between the two. The reason that creates a problem, a business problem is that the developers uh, will over provision stuff, uh to make sure that everything works and uh, they don't want to get caught in the middle of the night. You know, the bill comes due at the end of the month or into the quarter and then the CFO has smoke coming out of his ears because there's been clawed overruns. Then the reaction happens to all right, let's cut costs. And then, you know, there's an edict that comes down that says everything, reduce everything by 30%. So people go across and give a haircut to everything. So what happens next to systems out of balance? There's allocation resource misallocation and uh, systems start uh, suffering. So the customers become unhappy. And ironically, if you're not provisioned correctly, Not ironically, but maybe understandably, customers start suffering and that leads to a revenue problem down the line if you have too many problems unhappy. So you have to be very careful about how you cut costs and how you apportion resources. So both the revenue side is happy and it costs are happy because it all comes down to product experience and what the customers consume. You >>know, that's something that everyone who's done. Cloud development knows, you know, whose fault is it? You know, it's this fall. But now you can actually see the services you leave a switch open or, you know, I'm oversimplifying it. But, you know, you experiment services, you can the bills can just have massive, you know, overruns and then, and then you got to call the cloud company and you gotta call the engineers and say why did you do this? You got to get a refund or or the bad one. Bad apple could ruin it for everyone as you, as you highlighted over the bigger companies. So I have to ask you mean everyone lives this. How do companies have cost overruns? Is their patterns that you see that you guys wrote software 4-1, automate the obvious ones. Is there is there are certain things that you know always happen. Are there areas that have some indications? So why do, first of all, why do companies have cloud cost overruns? >>That's a great question. And let's start with a bit of history where we came from a pre cloud world, you built your own data centers, which means that you have an upfront Capex cost and you spend the money and you were forced to live within the needs that your data center provided. You really couldn't spend anymore. That provided kind of a predictable expenditure bottle it came in big chunks. But you know what, your budget was going to be four years from now, three years from now. And you built for that with the cloud computing, Your consumption is now on on demand basis and it's api enabled. So the developer can just ask for more resources. So without any kind of tools that tell the developer here is x amount of CPU or X amount of memory that you need for this particular service, that for it to deliver the right uh, performance that for the customer. The developers incentivized to basically give it a lot more than the application needs. Why? Because the developer doesn't want to pick up service tickets. He's incentivizing delivering functionality quickly and moving on to next project, not in optimizing costs. So that creates kind of uh an agency problem that the guy that actually controls how research are consumed is not incentivized to control the consumption of these resources. And we see that across the board in every company, engineers, engineering organization is a separate organization than the financial organization. So the control place is different. The consumption place and it breaks down the patterns are over provisions. And what we want to do is give engineers the tools to consume precisely the right amount of resources for the service level objectives that they have, given that you want a transaction rate of X and the literacy rate of Why here's how you configure your cloud infrastructure. So the application delivers according to the sls with the least possible resources consumed. >>So on this tool you guys have in the software you guys have, how how do you guys go to mark with that, you target the business buyer or the developer themselves and and how do you handle the developers say, I don't want anyone looking over my shoulder. I'm gonna go, I'm gonna have a blank check to do whatever it takes, um how do you guys roll that out because actually the business benefits are significant controlling the budget, I get that. Um how do you guys rolling this out? How do people engage with you? What's your strategy? >>Right. Are there, is the application owner, is the guy that owns the PML for the application? It tends to be a VP level or a senior director person that owns a SAAS platform and he or she is responsible for delivering good products to the market and delivering good financial results to the CFO So in that person of everything is rolled up, but that person will always favor the revenue site, which means consume more resources than you need in order to maximize customer happiness, therefore faster growth and uh they do that while sacrificing the cost side. So by giving the product owner the optimization tools autonomous of optimization tools that Sandy has, we allow him or her to deliver the right experience to the customer, with the right sufficient resources and address both the performance and the cost side of equation simultaneously, >>awesome. Can you talk about the impact c I C D s having in the cloud native computing on the optimization cycle? Um Obviously, you know, shifting left for security, we hear a lot of that, you're hearing a lot of more microservices being spun up, spun down automatically. Uh I'll see kubernetes clusters are going mainstream, you start to see a lot more dynamic uh activity if you if you in these new workflows, what is the impact of these new CSC D cloud? Native computing on the optimization cycle? >>C i c D is there to enable a fast delivery of software features basically. Uh So, you know, we have a combination of get get ups where you can just pull down repositories, libraries, open source projects from left and right. And using glue code, developers can deliver functionality really quick. In fact, microservices are there in service of that capability, deliver functionality quickly by being able to build functional blocks and then through a piece you put everything together. So ci cd is just accelerates the software delivery code. Between the time the boss says, give me an application until the application team plus the devops team plus SRE team puts it out in production. Now we can do this really quickly. The problem is though, nobody optimizes in the process. So when we deliver 1.0 in six months or less, we've done zero in terms of optimization and at one point, oh, becomes a way that we go through QA in many cases, unfortunately. And it also becomes a way that we go through the optimization. The customer screams that you eyes Laghi, you know, the throughput is really slow and we tinker and tinker and tinker and by the time it typically goes through a 12 month cycle of maturation, we get that system stability in the right performance with a I and machine learning that a person has enabled. We can deliver that, we can shrink that time out considerably. In fact, uh you know what we're going to announce in q khan is something that be called Kite storm is the ability to uh install our product and kubernetes environment in roughly 20 minutes and within two days you get the results. So before you have this optimization cycle that was going on for a very long time now that it's frank down and because of Ci Cd, you know, you don't have the luxury of waiting and the system itself can become part of the way of contributing system. The system being the uh ai ml service, that the presiding deliveries can be uh part and parcel of the Ci cd pipeline, that optimizes the code and gives you the right configuration and you get to go. So >>you guys are really getting down and injecting in some uh instrumentation for metadata around key areas. That right. Is that kind of how it's working? Are you getting in there with codes going to watch? Um how was it working under the hood? Can you just give me a quick example of, you know, how this would play out and what people might expect, how it would handle, >>of course. So what the way we optimize application performance is we have to have a metric against which we measure performance. That metric is an S L O service level, objective and in a kubernetes environment, we typically tap into Prometheus, which is the metrics gathering place metrics database for kubernetes workloads and we really focus on red metrics, the rate of transactions, the error rate and the for delay or latency. So we focus on these three metrics and what we have to do is inject a small container, it's an open source container into the application work space that we call that a container. Servo. Servo interacts with Prometheus to get the metrics and then it talks to our back end to tell the M L engine what's happening and then L engine and does this analysis and comes back with a new configuration which then servo implements in a canary instance. So the Canary instances where we run our experiments and we compare it against the main line, Which the application is doing after roughly 20 generations or so. The Bellingen Learns what part of the problem space to focus on in order to optimize to deliver optimal results. And then it very quickly comes to the right set of solutions to try and it tries those inside uh inside the canary instance and when it finds the optimal solution, it gives the recommendation back to the application team or alternatively, when you have enough trust in the tiny you can ought to promote it into mainline that >>gets the learning in there is a great example of some cloud native action. I want to get into some examples with your customer, but before we get there, I want to ask you, since I have you here, if you don't mind, what is cloud native mean these days, because you know, cloud native become kind of much cloud computing, um which essentially go move to the cloud, but as people start developing in the cloud where there's real new benefits, people talk about the word cloud native, could you take a quick minute to define? What is cloud Native, Does that even mean? What does cloud native mean? >>I'll try to give you my understanding government, we could get into a bit of philosophy. Uh Yeah, that's good. But basically cloud Native means it's, your application is built for the cloud and it takes advantages of the inherent benefits that a cloud environment can give you, which means that you can grow and shrink resources on the fly, if you built your application correctly, that you can scale up and scale down, you're a number of instances very quickly and uh, everything has taken advantage of a P I S so initially that was kind of done inside of the environment. Uh AWS Ec two is a perfect example of that. Kubernetes shifted cloud native to container its workload because it allows for rapid, more, rapid deployment and even enables or it takes advantage of a more rapid development cycle as we look forward. Cloud Native is more likely to be a surplus environment where you write functions and the backend systems of the cloud service provider, just give you that capability and you don't have to worry about maintaining and managing a fleet of any sort, whether it's VMS or containers, that's where it's gonna go. Currently we are to contain our space >>so as you start getting into the service molly good land, which we've been playing with, loves that as you get into that, that's going to accelerate more data. So I gotta ask you as you get into more of this this month, I will say monitoring or observe ability, how we want to look at it. You gotta get at the data. This becomes a critical part of solving a lot of problems and also making sure the machine learning is learning the right thing. How do you view that you guys over there? Because I think everyone is like getting that cloud native and it's not hard sell to say that's all good, but we can go back, you know, the expression ships created ships and then you have shipwrecks, you know, there's always a double edged sword here. So what's the downside? If you don't get the data right? >>Uh well, so the for us, the problem is not too much data, it's lack of data. So if you don't get data right is you don't have enough data. And the places where optimization cannot be automated is where the transaction rates are slow, where you don't have enough fruit. But coming into the application and it really becomes difficult to optimize that application with any kind of speed. You have to be able to profile the application long enough to know what moves its needle and in order for you to hit the S. L. O. Targets. So it's not too much data, it's not enough data. That seems to be the problem. And there are a lot of applications that are expensive to run but have a low throughput. And I would uh in all cases actually in every customer environment that have been in, where that's been the case if the application is just over provision, if you have a low throughput environment and it's costing too much, don't use ml to solve it. That's a wrong application of the technology. Just take a sledgehammer and back your resources by 50%, see what happens. And if that thing breaks back it again, until you find the baggage point. >>Exactly for you over prison, you bang it back down again. It's like the old school now with the cloud. Take me through some examples when you guys had some success, obviously you guys are in the right area right now, you're seeing a lot of people looking at this area to do that in some cases like changing the whole data center and respect of their business. But as you get it with customers with the app side, what some successes can you share some of the use cases, what you guys are being successful, your customers can get some examples. >>Yeah. So well known financial software for midsize businesses that that does accounting. It's uh there are customer during a large fleet and this product has been around for a while. It's not a container ice product. This product runs on VMS. Angela is a large component of that. So the problem for this particular vendor has been that they run on heterogeneous fleet that the application has been a along around for a very long time. And as new instance types on AWS have come in, developers have used those. So the fleet itself is quite heterogeneous and depending on the time of the day and what kind of reports are being run by organisations, they, the mix of resources that the applications need are different. So uh when we started analyzing the stack, we started we started looking at three different tiers, we looked at the database level, we looked at the job of mid tier and we looked at the web front end. And uh one of the things that became counterproductive is that m L. Discovered that using for the mid tier using larger instances but fear of a lot for better performance and lower cost and uh typically your gut feel is to go with smaller instances and more of a larger fleet if you would. But in this case, what the ML produced was completely counter intuitive And the net result for the customer was 78% cost reduction while agency went down by 10%. So think about it that you're, the response time is less, uh 10% less but your costs are down almost 80% 78% in this case. And the other are the fact that happened in the job of mitt here is that we improve garbage collection significantly and because whenever garbage collection happens on a JV M it takes a pause and that from a customer perspective it reflects as downtime because the machines are not responding so by tuning garbage collection Andrzej VMS across this very large fleet we were able to recover over 5000 minutes and month across the entire fleet. So uh, these are some substantial savings and this is what the right application of machine learning on a large fleet can do for assess business. >>And so talk about this fleet dynamic, You mentioned several lists. How do you see the future evolving for you guys? Where are you skating to where the puck is? As the expression goes? Um obviously with server list is going to have essentially unlimited fleets potentially That's gonna put a lot of power in the hands of developers. Okay. And people building experiences, What's the next five years look like for you guys? >>So I'm looking at the product from a product perspective, the service market depends on the mercy of the cloud service provider and typically the algorithms that they use. Uh basically they keep very few instances warm for you until you're the rate of api calls goes up and they start they start uh start turning on VMS are containers for you and then the system becomes more responsive over time. One place that we can optimize the service environment is give predictability of what the cyclicality of load is. So we can pre provision those instances and warm up the engine before the loads come into the system always stays responsive. You may have noticed that some of your apps on your phone that when you start them up, they may have a start up like a minute or two. Especially if it's a it's a terror gap. What's happening in those cases that you're starting an api calls goes in containers being started up for you to start up that instance, not enough of our warm to give you that rapid response. And that can lead to customer churn. So by by analyzing what the load on the overall load of the system is and pre provision the system. We can prevent the downtime uh prevent the lag to start up black on the downside. Which when you know when the usage goes down, it doesn't make sense to keep that many instances up. So we can talk to the back in infrastructure and the commission of those VMS in order to make to prevent cost creeps basically. So that's one place that we're thinking about extending our technology. >>So it's like, it's like the classic example where people say, oh during black monday everyone searches to do e commerce. You guys are thinking about it on A level that's a user centric kind of use case where you look at the application and be smart about what the expectation is on any given situation and then flex the resources on that. Is that right? That by getting right? So if it's your example, the app is a good one. If I wanted to load fast, that's the expectation. It better load fast. >>Yes, that's exactly but more romantic. So I use valentine's day and flowers my example. But you know, it doesn't have to be annual cycles. It can be daily cycles or hourly cycles. And all those patterns are learning about by an Ml back in. >>Alright, so I gotta ask you love the, this, this this new concept because most people think auto scaling right? Because that's a server concept. Can auto scale or database. Okay. On a scale up, you're getting down to the point where, okay, we'll keep the engines warm, getting more detailed. How do you explain this versus a concept like auto scaling. Is it the same as a cousins? >>They're they're basically the way they're expressed, it's the same technology but their way there expressed is different. So uh in a cooper native environment, the H. B A is your auto scaler basically in response to the need, response more instances and you get more containers going on. What happens as services? Less environment is you're unaware of the underpinnings that do that scale up for you. But there is an auto Scaler in place that does that scale up for you. So the question becomes that we're in a stack from a customer's perspective, are you talking about if you imagine your instances we're dealing with the H. B. A. If you're managing at the functional level we have to have api calls on the service provider's infrastructure to pre warm up the engine before the load comes. >>I love I love this under the hood is kind of love new dynamics kind of the same wine, new bottle but still computer science, still coding, still cool and relevant to make these experiences great. Thanks for coming on this cube conversation. I really appreciate it. Take a minute to put a plug in for the company. What are you guys doing in terms of status funding scale employees, what are you looking for? And if someone's watching this and there should be a customer of you guys, what what's, what's, what's going on in their world? What tells them that they need to be calling you? >>Yeah, so we're serious. Dave we've had the privilege of uh, our we've been privileged by having a very good success with large enterprises. Uh, if you go to our website, you'll see the logos of who we have, we will be at Q khan and there were going to be actively targeting the mid market or smaller kubernetes instances, as I mentioned, it's gonna take about 20 minutes to get started and we'll show the results in two hours. And our goal is for our customers to deliver the best user experience in terms of performance, reliability. Uh, so that they, they delight their customers in return and they do so without breaking the bank. So deliver excellent products, do it at the most efficient way possible, deliver a good financial results for your stakeholders. This is what we do. So we encourage anybody who is running a SAS company to come and take a look at us because we think we can help them and we can accelerate there. The growth at the lower cost >>and the last thing people need is have someone coming breathing down their necks saying, hey, we're getting overcharged. Why are you guys screwing up when they're not? They're trying to make a great experience. And I think this is kind of where people really want to do push the envelope and not have to go back and revisit the cost overruns, which if it's actually a good sign if you get some cost overruns here and there because you're experimenting. But again, you don't want to get out of control. >>You don't want to be a visual like the U. S. Debt. >>Exactly. I'm here. Thank you for coming on. Great. We'll see a coupe con. The key will be there in person is a hybrid event. So uh, coupon is gonna be awesome and thanks for coming on the key. Appreciate it. >>John is a pleasure. Thank you for having me on. >>Okay. I'm john fryer with acute here in Palo alto California remote interview with upsetting hot startup series. I'm sure they're gonna do well in the right spot in the market. Really well poisoned cloud Native. Thanks for watching. Yeah.

>>mhm >>Welcome to this cube conversation here in Palo alto California. I'm john Kerry host of the cube. We've got a great awesome conversation with the Ceo and co founder of harness a hot startup jodi Benson who is the co founder and Ceo but also the co founder of unusual ventures which is a really awesome venture capital firm, doing some great work investment but also they have great content over there for entrepreneurs and for people in the community And of course he's also the founder of big labs, his playground. If you're building out new applications also well known for being the founder of Ap dynamics of super successful billion dollar exit as a startup, Salto, Cisco now doing a lot of things and driving harness, solving big problems. So joe t mouthful intro there, you've done a lot. Congratulations on your an amazing entrepreneur career and now your next uh next next opportunities harness among other things. So congratulations. Thank you for coming. >>Thank you john and glad to be here. >>You guys are solving a big problem in software delivery. Obviously software changing the world. You're seeing open source projects increasing in order of magnitude enterprises jumping on open source in general adoption, large scale with cloud software is being delivered faster than ever before and with cloud scale and now edge this huge challenges around how software deployed, managed maintained. You got, we're talking about space to how do you do break fix in space, all these things are happening at a massive scale across the world. You are solving a big problem. So take a minute to explain what harnesses doing, why you guys exist, why you jumping in into this venture. >>Sure. Yeah. You know what harness mission is to simplify supper delivery and make it uh top notch for everyone. Like if you look at like you know the likes of google and facebook and netflix and amazon these companies are mastered the process of software delivery like and your engineers write code and the code is shipped to the end users and they can do it like multiple times a day at their scale and you know at the complexity that they have but most other business in the world they all want to be software companies but it's extremely, extremely hard for them to get there and I saw this firsthand when I was at epidemics as you know as Ceo last there we're about 12 1300 employees in the company and we had about about 3 50 or so engineers in the company For every 10 or 12 engineers, we had one person whose job was to write automation and scripting and tooling for trying to ships off you know uh you know all kind of scripting kind of stuff. We'll write scripts and chef and puppet and sensible and to deploy in aws and whatnot. And you know one day we're doing the math were like you know we have you know about overall about 30 people whose job was to do devops engineering by writing automation etc to deploy somewhere and I would do the math like you know, one engineer cost is 200 k loaded cost at six million a year that you're spending six million a year just writing deployment, scripting, you know, and even with that we were nowhere close to world class like world class is in like what you would think you could ship every day, we chip on demand, you could, you know, you could deploy software, ship software all of that right? And that was the, you know, I looked at that as a problem inside of dynamics and all they have done with customers, I would talk to like large banks, insurance companies and retailers and telcos and I would hear the same challenge like you know, we hear about devops, we go to the all these devops conferences and events and we see the same 10 companies, you know presenting how the home grew some kind of a devops system for software delivery etc. And you know, I mean that was like, you know, we just, we cannot survive with this like and as the world we need to have uh the right kind of platforms for software delivery and simplify this so that everyone could become as good as a google netflix amazon etcetera that stand of our mission at harness that can we take every business in the world, you know and in a few weeks or a few months, can we get them as sophisticated and good in terms of their dueling for software delivery as a google facebook amazon, those kind of companies would be and that's, that's what we're doing. So >>It's a great ambition and by the way it's a bold move and it's needed. I'll tell you, it's interesting. You mentioned some of those commentary about shipping code at that speed Facebook Google. They had that they had they were forced to do that and again they have all that benefit the mainstream enterprise doesn't. But if you even go back 20 years ago, 15 years ago, that's when Amazon was born. You see two and S three is celebrating their 15th birthday. Software. Yeah, hyper scale has had some good moves there. But the average business went from craft, you know, waterfall QA department go back a little bit slower. I won't say slow motion but manageable now with the speed of shipping and the speed of the scale, that's a huge issue. What kind of pressure do you see that putting on the developer, the individual, not just the system because you got the system of development and the devil and the developers themselves. >>I think the developers have have done quite well to this. I feel like, you know, if you look at the software development part of itself, you know the agile development has been happening for quite some time. So developers have learned how to ship things fast and like in a week sprint or a two week sprint or in in kind of faster cycles. They have moved off from the waterfall kind of models like many years ago now. So that's the suffering development side of things then you have the infrastructure side of things which is the like any province in infrastructure fast. Can you get hardware fast? That's the, you know, the cloud has done that well where the challenges the process, the developers are writing code fast enough these days and you have the, you know, the infrastructure itself could be prov isn't and maintained and and and change fast enough but how do you bring it all together and there is the entire process around it. That's not moving fast enough. So that's where the bottom language. So I feel the, you know, and the process is not good. The developer experience becomes really bad bad because developers are waiting for the process to go and you know, they write some code and the code is sitting on the shelf and they are waiting for things. >>Uh they get all pissed off and mad. What's the holdup? Why what's the process? And then security shifting left, wait a minute to go back and rewrite code. This is huge. I want to just get back and just nail it quickly if you don't mind honing in on the value proposition. What is the harness value proposition? What is the pitch, what are you, what are you offering? What are you solving? Can you nail in on that real quick? >>Sure. So what harness is swallowing is simplifying that software delivery by plane, so developer writes code and that code goes goes through a bunch of steps so a bunch of steps which is uh you know you build the code then you you know test the code, you know, then you do integration tests, then you you know go through your security checks, then you go through a compliance checks, then you go through more dusting, then you're deploying a staging environment, then you go one to do a bunch of things on it. Then you start deploying in production environment but in production you will deploy on like a small part of production, verify everything is working well, it's not working well, you'll roll it back, it's working well then you deploy two more things. This entire process could take like weeks for people to do and this is mostly automated, you know in kind of uh uh you know this kind of random scripts here and there etcetera. So we simplify the entire process that you could describe your process in the language, I just described like you know in a very descriptive declarative kind of way like this is the process I want to achieve and hardness will automatically create your pipelines for this. This kind of process and most of these pipelines have a lot of heavy use of intelligence and um L two, it could go from one step to another, like, so many times, like when you say, you know, deploy the guard and and and 1% of my production environment and see everything is working well and if everything is working well, go to the next 10%. But how do you figure out if everything is working well and that's where the intelligence and um El comes in like, you know, what we learn, what is a normal behavior of your application, how does a normal part of the code works like, you know, there, what's the performance behavior, what is a functional behavior? What errors it is? And if everything is good then you go to the next step so that entire cycle harness automatically, uh you know, uh managers and its automated, you know, if you get governance, you get like, you know, high degree of automation, you get a high degree of, you know, security, you get high degree of like, you know, uh uh you know, quality around him. And so it's it's think of like the, the Ci cd has a lot of developers know and know this process is is ci cd on steroids available to you, Right? So you >>sound like you're making it easier on the Ci cd pipeline process, standing it up, detecting it, prototyping it, if you will, for lack of a better description, get get used to the pipeline and then move it out, roll it out and build your own in a way >>that, is that what is that what you're doing? It's like, you know, a lot of these complex ci city pipelines, what people need, you know, it can take them like three months, six months to to put it uh you know, put it together the harness, it's like an hour, an hour, you could put it together, you know, very, very sophisticated uh Ci cd pipeline and the pipeline is, you know, automated is is, you know, it's it's intelligent around like, you know, what is the normal behavior of your of your applications? Uh It's it's just so phenomenally different than how people have done ci cd before that we simplify the process. Automate the process, you know, and make it manageable and very ready to get involved. >>It's funny you mentioned the three weeks weeks it could take to do the csd pipeline. Of course, that doesn't factor in the what happens when you roll it out, people start complaining, playing with it, breaking it, then you gotta go back and do it again. I mean, that's real and that's a real problem, I mean, can you just going to give a taste of the scar tissue that goes on there. What's some of the what are some of the what some of the pain points that you solve? >>Yeah. So, I think the that is that really becomes the core of the pain point, like, you know, people need, like high amount of dependability, easy to change things, you know, it's we call it like the lack of intelligent automation, you know, and the and this heavy amount of developer toil that the developers have to do so much work around around making all of this work like you know it has to be simplified. So that's that's where our value product comes in like you know, it's it's you know uh you can get like a visual builder and like minutes you can build out the entire process which is your job stability at city pipeline or you could also do like a declarative Yamil interface and just like you know in a few lines just right up whatever process you would want and we would review should be shipped with all kind of integrations with every cloud environment, every monitoring system, every system, every kind of testing process, every kind of security scanning so you can just drag and drop and in minutes eur, europe and running, it just creates so much velocity in this entire process. And also this manageability that people have struggled with >>morale to I mean you can imagine the morale developers go up significantly when you start seeing that the developer productivity has always been a big thing but this intelligent automation conversations huge. Some people have it, some people don't, people say they have it, what is how can you, how can the company figure out uh if someone's really got the real deal when it comes to intelligent automation because again, automation is the is key into devops. >>Yeah, I think I I almost started like you know like if you look at the generational evolution of things like the the first generation was uh you know developer writes code and then it will give you will give it to some some mighty at men who will go and deploy the code, run some commands and do things like tradition to was writing scripts that you're right, a lot of scripts that was automation but it was kind of dumb our dimension and that's how we have, you know that that's where the industry is so actually break now even most of it, the third generation is when the automation is you don't write scripts to you know uh to automate things, you tell our system what you want to achieve and it generates automation for you, right? And that's what we call intelligent automation. Where it's all declarative and all the you don't have to maintain a lot of you know scripts etcetera because they are, you know, they can't keep up with it. You know, you have to change the process all the time and if you change the process, it doesn't work, it becomes completely, you know, uh you know, it becomes very fragile to manage it. So that's that's really where intelligent automation comes in, you know, I look at like, you know, if you can have like uh like you look at like a wrestler, you know, making cars the entire assembly line is automated, but it's, but it's if you want to change something in the assembly line, even that process is automated and it's very simple. Right? So it's and that's what gives them so much uh you know, uh you know, uh let's say control and manageability around the manufacturing process. So the software delivery, uh you know, by assembly line, which is the software software by ci cd piper and really should be a more sophisticated and more intelligent as well now. And that's that's an exhibition, >>jodi. You're also pointing out something that we cover a lot on the cube and we've been writing about is how modern software practices are changing, where this team makeup or whatever its speed is key, but also getting data. Everyone who's successful with cloud and cloud scale and now you got the edge opening up and like I said, even space is going to be programmable, Everything's programmable. And the key is to get the data from the use cases right, get something deployed, look at it, get some data and then double down and make it better. That's a modern approach, not build it and then rebuild it and tear it down and rebuild it, which you're kind of leaning into this idea of let's get some delivery going, let's structure it and then feed it more so that the developers can iterate with with, with the pipeline and this is this again, can scale, can you talk about that? Can you comment on your reaction to that? >>Yeah, definitely. That's exactly how we look at it. Like, you know, you uh you want developers to kind of like say they want to do a, you know, automated process to deploy in their communities infrastructure in matter of minutes, you should be able to get started, but now it's like, you know, there's so much data that comes into it. Like, you know that you have monitoring systems systems like ab dynamics and you're like and data dog and you're logging systems your Splunk and elastic and you know, some logic, you have your, you know, different kind of testing systems here, your security scanning, so there's so much data in it. They're like, you know, terabytes and terabytes of data from it. So when you start doing your deployments, we could also come seem all of the data and see like what was the impact of those deployments or court changes in each of these monitoring, dusting, logging gonna systems and you know, what, how the data changes and then now is that based on that we can learn like, you know, what should be your ideal process and what will break in your process and that's that's the how harness platform works. That's the core of that intelligent automation networks, they're expanding it now to bring a few more of the devops use cases into it Also like the one is cloud cost management because when you, when you, you know, uh you know when we started shipping, there's a lot of people would tell us like, you know, you're you're doing a great job helping us managing the quality, which we always were concerned about like when we're deploying things so you know, security, you know, functionality etcetera. But cloud cost is a big challenge as well. You have your paying like tens and tens of millions of dollars to the cloud providers. And when developers do things in an automated way, it could increase without cost suddenly and we don't know what to do how to manage that. So that's the, you know, we we introduced a new model called cloud cost management to as part of the develops software delivery process that every time you're shipping code and we also figure out like, you know, what with impact on on your on your podcast, you know, can we automate the, you know, uh if there is there is too much impact, can we automate the, you know, the roll back around it, you know, can you get and you can you can we stop the delivery process at that point, can we help you troubleshoot and, you know, reduce the cost down? So that's, you know, that's cost becomes another another another dimension to it. Uh you know, then we recently just added uh you know, the next level that's managing feature Flags. And a lot of the time software developers are adding feature flags to like this feature would be given to this consumer and like, you know, and this feature will be given to this consumer until you test it out through uh test kind of thing and like, you know, what is the impact of, you know, uh turning a feature on versus off, you know, we're bringing that into the same ci cd pipeline. So it's kind of an integrated approach to this uh you know, our intelligently automated biplane instead of these uh small point approaches that just very hard to manage. >>I mean the level of data involved the creature flag for instance, the great is an amazing thing because that allows you to do things that used to be extremely difficult to provision. I mean just picking the color of icon, for instance, this kind of blue, I mean I was just, you hear about this, these kinds of things happening at scale and the date is pretty accurate when it comes in. So I think that's an example of the kind of speed and agility that developers want and the question I want to ask you though on that point because this opens up the whole next conversation, you guys have a modern approach and so much traction and you've recently raised big rounds of funding as you go to the market place, your experienced entrepreneur and uh and Ceo you've seen the waves before. What's the big wave that you're on now? What's the big momentum tailwind for harness? Is it the fact that you're creating value for developers or is it the system that you're integrating into with the intelligence to make things smarter and more scalable? What's the or is it all the above? Can you just share what that that story is? >>Yeah, I think it's, it's, it's really, really both of them. But you know, what are our business case when you go to people who tell them like say, if you're you know, 200 developers. uh, you know, we can give you the world's best software delivery tooling at the cost of half to one developer. Right? So like, you know, so which is like 44, 200 person organization at like 200 to 200 to $300,000 a year. They will get the best software delivery tooling better than a Google Facebook Amazon kind of companies very, very quickly. So our, our entire value prop is built on that like a developer experience gets much better. The productivity gets much better. Developers on an average are spending like 20-30% of the time on deployment, delivery-related toil, like unnecessary stuff that we deal with. So it's only 30% more efficiency gain for the developers. Their quality of life gets better that they don't need to worry about like weekends and nights to babysit your deployments and you know, things breaking and troubleshooting things all the time. Right? So that's that's a that's a big big value. But as a business you get much more velocity your innovation velocity is much higher. You know your risk on your, you know your consumers is much lower because your quality of the of of you know how your ship becomes becomes better. So our business case of like you know at the past of like 1-2 develops engineers will get you the best develops uh you know tooling in the world possible. You know it's not a hard business case for us to make, right? That's that's what we we we look at, it becomes pretty pretty obvious for you know as people try our product, you know the business case >>you don't have to really pass the I. Q. Test to figure this one out, okay everyone's happier and you have more options to scale and make more money in new opportunities not just existing business. I mean the feature flagging these new features you can build a new value and take more territory if you're a business or whatever your objective is so clear value. Can you give an example of some recent successes you've had or or traction points that you think is worth notable that people can get their arms around. >>Yeah definitely like you know we are we're helping a lot of uh you know a lot of customers you know doing uh like completely changing their uh their uh their process of software delivery, you know, 11 recent example, uh nationwide insurance, you know, nationwide insurance, you know, moving from their data center kind of approach to public cloud and to communities and to microservices, like a major cloud native re architecture and in a very ambitious aggressive project to do it, you know, in a in a in a short period of time and harness becomes a platform for them to kind of, you know, uh to remove all the bottom leg around the process, the software delivery process. You know, they obviously they still have to do the developer side of things and they have to do the cloud infrastructure side of things, which is they're doing. But the entire process of how you bring together, you know, harness becomes accelerated around it. So a lot of these kind of stories that we when we kind of create this fundamental transformation for our for our for our customers, you know, uh you know, moving to to a public cloud, you know, moving to microservices, moving to communities, you know, re architect things, but they become much faster. Cloud native higher, you know, a true software company and you know, I would say that's that's something we we we we take a they can take a lot of pride in, I think are always our biggest challenge is uh is to is to is to evangelize and and convince the market that this is possible to do with the product, because historically people have got told like, you know, the only way you can do this kind of software delivery processes and tooling is by engineering it on your own. So everyone wants us on the path of writing their own, you know, and and it's very hard for every, every company in the world to become very good in writing your own software delivery, tooling and processes and systems, etcetera. Right? So it's uh and that's it. So, you know, there is still that that education and evangelism needs to be done, that, you know, there is uh there is no point, you're trying to do it on your own, you can get a platform that can do it all for you and you can focus on the your core business of, you know, what you want to innovate on. >>And I think the Devil's movement hasn't been pioneered and you have to hand roll everything and that's the way it was. But now, as the mainstream market picks this up, you're standing on the shoulders of those pioneers, you are one of them. It's awesome to see this modern approach because it's really playing out in real time again, you've done that before, joe t so it's impressive and, you know, you've seen the movie and developed and the earlier versions pre devops. So, so as cloud native comes and start scaling it's going to be for the rest of us. So, great, great that you're providing the platform and the tools and software. I got to ask you if you don't mind because a lot of people are looking at ways for modern approaches to organizing their teams, how would you define the modern devops movement? You look at devops one point. Oh, we got here. Okay, cloud, cloud native, cloud scale, modern applications, pipe lining. Now, we're looking at a whole another level of confluence of uh of integration and speed. How would you define the modern devops movement? >>Yeah, I think that's a that's a very good question. I think that the core of modern devops, what I would call it develops to point to me is developers self service. It was like the first generation of develops was they create this kind of a devoPS team and then the developers will give all the, you know, delivery related stuff that develops team and the devops team starts to become a bottle, like everywhere now, like in the developed steam job is to build a ci pipeline and the city pipeline and the deployment scripts and you know, do like, you know, you want to do a canary deployment, they have to figure it out how to do it, they have to do, like, you know, you are uh you know, all sort of things that the that needs to be done, you create a central develops team and you give it to them and they become like, you know, uh become a big bottleneck, we look at the modern develops or the next generation and develops has to be done around focusing on the developer experience that and making it all self service for the developers. So you have, you have, let's say you are definitely in for a micro service and it's like, you know 57 engineers, you know, modeling a micro service you want like that, they can go and say this is for our micro service, you know, in a matter of minutes or hours, they can engineer the process without having to lean on a central deVOPS team and to do all the work for them and that's you know, by by maybe a modeler or in some kind of mammal interface or something. That's very easy for them, their experience is so easy that they can manage it themselves without the central deVOPS team have to write it all or cut it all and manage it all. But at the same time the center deVOPS teams, job becomes a bar and governance that can they define the guardrails, that they can define the guardrails on like, you know, you have to have this level of security before something goes into production, you have to have this level of quality before something goes into production, you have to have like, you know, uh this, your cost could not be more than this, right? So you define, so in this instance, instead of the center develops team is doing all the work themselves on writing all the stuff they define the guard rails and it becomes a very easy cell service experience of the developers should do things within those, those guard rails. This is what the modern never actually, >>that's awesome and also accelerate more business value And you're nailing it joe t thank you for coming on and great. Uh, the Ceo on the cube ceo and co founder harness harness dot IO. You guys got free trials, free downloads. You got a great, uh, by as you go model also. Um, you're an entrepreneur at heart. Uh, co founder of unusual ventures, Big Labs appdynamics. Now harness. Congratulations. Thanks for coming on. >>Hey, thank you john. >>Okay, this is a cube conversation. I'm john for here in Palo alto California with the cube. Thanks for watching.

>>Mhm Hello and welcome to the cubes coverage of AWS amazon web services, Global public Sector partner awards program. I'm john for your host of the cube here we're gonna talk about the best covid solution to great guests. Benham or with healthcare and life sciences lead at palantir Ben welcome to the cube SAm Michaels, Director of automation and compound management and Cats. National Center for advancing translational sciences and Cats. Part of the NIH National sort of health Gentlemen, thank you for coming on and and congratulations on the best covid solution. >>Thank you so much john >>so I gotta, I gotta ask you the best solution is when can I get the vaccine? How fast how long it's gonna last but I really appreciate you guys coming on. I >>hope you're vaccinated. I would say john that's outside of our hands. I would say if you've not got vaccinated, go get vaccinated right now, have someone stab you in the arm, you know, do not wait and and go for it. That's not on us. But you got that >>opportunity that we have that done. I got to get on a plane and all kinds of hoops to jump through. We need a better solution anyway. You guys have a great technical so I wanna I wanna dig in all seriousness aside getting inside. Um you guys have put together a killer solution that really requires a lot of data can let's step back and and talk about first. What was the solution that won the award? You guys have a quick second set the table for what we're talking about. Then we'll start with you. >>So the national covered cohort collaborative is a secure data enclave putting together the HR records from more than 60 different academic medical centers across the country and they're making it available to researchers to, you know, ask many and varied questions to try and understand this disease better. >>See and take us through the challenges here. What was going on? What was the hard problem? I'll see everyone had a situation with Covid where people broke through and cloud as he drove it amazon is part of the awards, but you guys are solving something. What was the problem statement that you guys are going after? What happened? >>I I think the problem statement is essentially that, you know, the nation has the electronic health records, but it's very fragmented, right. You know, it's been is highlighted is there's there's multiple systems around the country, you know, thousands of folks that have E H. R. S. But there is no way from a research perspective to actually have access in any unified location. And so really what we were looking for is how can we essentially provide a centralized location to study electronic health records. But in a Federated sense because we recognize that the data exist in other locations and so we had to figure out for a vast quantity of data, how can we get data from those 60 sites, 60 plus that Ben is referencing from their respective locations and then into one central repository, but also in a common format. Because that's another huge aspect of the technical challenge was there's multiple formats for electronic health records, there's different standards, there's different versions. And how do you actually have all of this data harmonised into something which is usable again for research? >>Just so many things that are jumping in my head right now, I want to unpack one at the time Covid hit the scramble and the imperative for getting answers quickly was huge. So it's a data problem at a massive scale public health impact. Again, we were talking before we came on camera, public health records are dirty, they're not clean. A lot of things are weird. I mean, just just massive amount of weird problems. How did you guys pull together take me through how this gets done? What what happened? Take us through the the steps He just got together and said, let's do this. How does it all happen? >>Yeah, it's a great and so john, I would say so. Part of this started actually several years ago. I explain this when people talk about in three C is that and Cats has actually established what we like to call, We support a program which is called the Clinical translation Science Award program is the largest single grant program in all of NIH. And it constitutes the bulk of the Cats budget. So this is extra metal grants which goes all over the country. And we wanted this group to essentially have a common research environment. So we try to create what we call the secure scientific collaborative platforms. Another example of this is when we call the rare disease clinical research network, which again is a consortium of 20 different sites around the nation. And so really we started working this several years ago that if we want to Build an environment that's collaborative for researchers around the country around the world, the natural place to do that is really with a cloud first strategy and we recognize this as and cats were about 600 people now. But if you look at the size of our actual research community with our grantees were in the thousands. And so from the perspective that we took several years ago was we have to really take a step back. And if we want to have a comprehensive and cohesive package or solution to treat this is really a mid sized business, you know, and so that means we have to treat this as a cloud based enterprise. And so in cats several years ago had really gone on this strategy to bring in different commercial partners, of which one of them is Palin tear. It actually started with our intramural research program and obviously very heavy cloud use with AWS. We use your we use google workspace, essentially use different cloud tools to enable our collaborative researchers. The next step is we also had a project. If we want to have an environment, we have to have access. And this is something that we took early steps on years prior that there is no good building environment if people can't get in the front door. So we invested heavily and create an application which we call our Federated authentication system. We call it unified and cats off. So we call it, you know, for short and and this is the open source in house project that we built it and cats. And we wanted to actually use this for all sorts of implementation, acting as the front door to this collaborative environment being one of them. And then also by by really this this this interest in electronic health records that had existed prior to the Covid pandemic. And so we've done some prior work via mixture of internal investments in grants with collaborative partners to really look at what it would take to harmonize this data at scale. And so like you mentioned, Covid hit it. Hit really hard. Everyone was scrambling for answers. And I think we had a bit of these pieces um, in play. And then that's I think when we turned to ban and the team at volunteer and we said we have these components, we have these pieces what we really need. Something independent that we can stand up quickly to really address some of these problems. One of the biggest one being that data ingestion and the harmonization step. And so I can let Ben really speak to that one. >>Yeah. Ben Library because you're solving a lot of collaboration problems, not just the technical problem but ingestion and harmonization ingestion. Most people can understand is that the data warehousing or in the database know that what that means? Take us through harmonization because not to put a little bit of shade on this, but most people think about, you know, these kinds of research or non profits as a slow moving, you know, standing stuff up sandwich saying it takes time you break it down. By the time you you didn't think things are over. This was agile. So take us through what made it an agile because that's not normal. I mean that's not what you see normally. It's like, hey we'll see you next year. We stand that up. Yeah. At the data center. >>Yeah, I mean so as as Sam described this sort of the question of data on interoperability is a really essential problem for working with this kind of data. And I think, you know, we have data coming from more than 60 different sites and one of the reasons were able to move quickly was because rather than saying oh well you have to provide the data in a certain format, a certain standard. Um and three C. was able to say actually just give us the data how you have it in whatever format is easiest for you and we will take care of that process of actually transforming it into a single standard data model, converting all of the medical vocabularies, doing all of the data quality assessment that's needed to ensure that data is actually ready for research and that was very much a collaborative endeavor. It was run out of a team based at johns Hopkins University, but in collaboration with a broad range of researchers who are all adding their expertise and what we were able to do was to provide the sort of the technical infrastructure for taking the transformation pipelines that are being developed, that the actual logic and the code and developing these very robust kind of centralist templates for that. Um, that could be deployed just like software is deployed, have changed management, have upgrades and downgrades and version control and change logs so that we can roll that out across a large number of sites in a very robust way very quickly. So that's sort of that, that that's one aspect of it. And then there was a bunch of really interesting challenges along the way that again, a very broad collaborative team of researchers worked on and an example of that would be unit harmonization and inference. So really simple things like when a lab result arrives, we talked about data quality, um, you were expected to have a unit right? Like if you're reporting somebody's weight, you probably want to know if it's in kilograms or pounds, but we found that a very significant proportion of the time the unit was actually missing in the HR record. And so unless you can actually get that back, that becomes useless. And so an approach was developed because we had data across 60 or more different sites, you have a large number of lab tests that do have the correct units and you can look at the data distributions and decide how likely is it that this missing unit is actually kilograms or pounds and save a huge portion of these labs. So that's just an example of something that has enabled research to happen that would not otherwise have been able >>just not to dig in and rat hole on that one point. But what time saving do you think that saves? I mean, I can imagine it's on the data cleaning side. That's just a massive time savings just in for Okay. Based on the data sampling, this is kilograms or pounds. >>Exactly. So we're talking there's more than 3.5 billion lab records in this data base now. So if you were trying to do this manually, I mean, it would take, it would take to thousands of years, you know, it just wouldn't be a black, it would >>be a black hole in the dataset, essentially because there's no way it would get done. Ok. Ok. Sam take me through like from a research standpoint, this normalization, harmonization the process. What does that enable for the, for the research and who decides what's the standard format? So, because again, I'm just in my mind thinking how hard this is. And then what was the, what was decided? Was it just on the base records what standards were happening? What's the impact of researchers >>now? It's a great quite well, a couple things I'll say. And Ben has touched on this is the other real core piece of N three C is the community, right? You know, And so I think there's a couple of things you mentioned with this, johN is the way we execute this is, it was very nimble, it was very agile and there's something to be said on that piece from a procurement perspective, the government had many covid authorities that were granted to make very fast decisions to get things procured quickly. And we were able to turn this around with our acquisition shop, which we would otherwise, you know, be dead in the water like you said, wait a year ago through a normal acquisition process, which can take time, but that's only one half the other half. And really, you're touching on this and Ben is touching on this is when he mentions the research as we have this entire courts entire, you know, research community numbering in the thousands from a volunteer perspective. I think it's really fascinating. This is a really a great example to me of this public private partnership between the companies we use, but also the academic participants that are actually make up the community. Um again, who the amount of time they have dedicated on this is just incredible. So, so really, what's also been established with this is core governance. And so, you know, you think from assistance perspective is, you know, the Palin tear this environment, the N three C environment belongs to the government, but the N 33 the entire actually, you know, program, I would say, belongs to the community. We have co governance on this. So who decides really is just a mixture between the folks on End Cats, but not just end cast as folks at End Cats, folks that, you know, and I proper, but also folks and other government agencies, but also the, the academic communities and entire these mixed governance teams that actually set the stage for all of this. And again, you know, who's gonna decide the standard, We decide we're gonna do this in Oman 5.3 point one um is the standard we're going to utilize. And then once the data is there, this is what gets exciting is then they have the different domain teams where they can ask different research questions depending upon what has interest scientifically to them. Um and so really, you know, we viewed this from the government's perspective is how do we build again the secure platform where we can enable the research, but we don't really want to dictate the research. I mean, the one criteria we did put your research has to be covid focused because very clearly in response to covid, so you have to have a Covid focus and then we have data use agreements, data use request. You know, we have entire governance committees that decide is this research in scope, but we don't want to dictate the research types that the domain teams are bringing to the table. >>And I think the National Institutes of Health, you think about just that their mission is to serve the public health. And I think this is a great example of when you enable data to be surfaced and available that you can really allow people to be empowered and not to use the cliche citizen analysts. But in a way this is what the community is doing. You're doing research and allowing people from volunteers to academics to students to just be part of it. That is citizen analysis that you got citizen journalism. You've got citizen and uh, research, you've got a lot of democratization happening here. Is that part of it was a result of >>this? Uh, it's both. It's a great question. I think it's both. And it's it's really by design because again, we want to enable and there's a couple of things that I really, you know, we we clamor with at end cats. I think NIH is going with this direction to is we believe firmly in open science, we believe firmly in open standards and how we can actually enable these standards to promote this open science because it's actually nontrivial. We've had, you know, the citizen scientists actually on the tricky problem from a governance perspective or we have the case where we actually had to have students that wanted access to the environment. Well, we actually had to have someone because, you know, they have to have an institution that they come in with, but we've actually across some of those bridges to actually get students and researchers into this environment very much by design, but also the spirit which was held enabled by the community, which, again, so I think they go they go hand in hand. I planned for >>open science as a huge wave, I'm a big fan, I think that's got a lot of headroom because open source, what that's done to software, the software industry, it's amazing. And I think your Federated idea comes in here and Ben if you guys can just talk through the Federated, because I think that might enable and remove some of the structural blockers that might be out there in terms of, oh, you gotta be affiliate with this or that our friends got to invite you, but then you got privacy access and this Federated ID not an easy thing, it's easy to say. But how do you tie that together? Because you want to enable frictionless ability to come in and contribute same time you want to have some policies around who's in and who's not. >>Yes, totally, I mean so Sam sort of already described the the UNa system which is the authentication system that encounters has developed. And obviously you know from our perspective, you know we integrate with that is using all of the standard kind of authentication protocols and it's very easy to integrate that into the family platform um and make it so that we can authenticate people correctly. But then if you go beyond authentication you also then to actually you need to have the access controls in place to say yes I know who this person is, but now what should they actually be able to see? Um And I think one of the really great things in Free C has done is to be very rigorous about that. They have their governance rules that says you should be using the data for a certain purpose. You must go through a procedure so that the access committee approves that purpose. And then we need to make sure that you're actually doing the work that you said you were going to. And so before you can get your data back out of the system where your results out, you actually have to prove that those results are in line with the original stated purpose and the infrastructure around that and having the access controls and the governance processes, all working together in a seamless way so that it doesn't, as you say, increase the friction on the researcher and they can get access to the data for that appropriate purpose. That was a big component of what we've been building out with them three C. Absolutely. >>And really in line john with what NIH is doing with the research, all service, they call this raz. And I think things that we believe in their standards that were starting to follow and work with them closely. Multifactor authentication because of the point Ben is making and you raised as well, you know, one you need to authenticate, okay. This you are who you say you are. And and we're recognizing that and you're, you know, the author and peace within the authors. E what do you authorized to see? What do you have authorization to? And they go hand in hand and again, non trivial problems. And especially, you know, when we basis typically a lot of what we're using is is we'll do direct integrations with our package. We using commons for Federated access were also even using login dot gov. Um, you know, again because we need to make sure that people had a means, you know, and login dot gov is essentially a runoff right? If they don't have, you know an organization which we have in common or a Federated access to generate a login dot gov account but they still are whole, you know beholden to the multi factor authentication step and then they still have to get the same authorizations because we really do believe access to these environment seamlessly is absolutely critical, you know, who are users are but again not make it restrictive and not make it this this friction filled process. That's very that's very >>different. I mean you think about nontrivial, totally agree with you and if you think about like if you were in a classic enterprise, I thought about an I. T. Problem like bring your own device to work and that's basically what the whole world does these days. So like you're thinking about access, you don't know who's coming in, you don't know where they're coming in from, um when the churn is so high, you don't know, I mean all this is happening, right? So you have to be prepared two Provisions and provide resource to a very lightweight access edge. >>That's right. And that's why it gets back to what we mentioned is we were taking a step back and thinking about this problem, you know, an M three C became the use case was this is an enterprise I. T. Problem. Right. You know, we have users from around the world that want to access this environment and again we try to hit a really difficult mark, which is secure but collaborative, Right? That's that's not easy, you know? But but again, the only place this environment could take place isn't a cloud based environment, right? Let's be real. You know, 10 years ago. Forget it. You know, Again, maybe it would have been difficult, but now it's just incredible how much they advanced that these real virtual research organizations can start to exist and they become the real partnerships. >>Well, I want to Well, that's a great point. I want to highlight and call out because I've done a lot of these interviews with awards programs over the years and certainly in public sector and open source over many, many years. One of the things open source allows us the code re use and also when you start getting in these situations where, okay, you have a crisis covid other things happen, nonprofits go, that's the same thing. They, they lose their funding and all the code disappears. Saying with these covid when it becomes over, you don't want to lose the momentum. So this whole idea of re use this platform is aged deplatforming of and re factoring if you will, these are two concepts with a cloud enables SAM, I'd love to get your thoughts on this because it doesn't go away when Covid's >>over, research still >>continues. So this whole idea of re platform NG and then re factoring is very much a new concept versus the old days of okay, projects over, move on to the next one. >>No, you're absolutely right. And I think what first drove us is we're taking a step back and and cats, you know, how do we ensure that sustainability? Right, Because my background is actually engineering. So I think about, you know, you want to build things to last and what you just described, johN is that, you know, that, that funding, it peaks, it goes up and then it wanes away and it goes and what you're left with essentially is nothing, you know, it's okay you did this investment in a body of work and it goes away. And really, I think what we're really building are these sustainable platforms that we will actually grow and evolve based upon the research needs over time. And I think that was really a huge investment that both, you know, again and and Cats is made. But NIH is going in a very similar direction. There's a substantial investment, um, you know, made in these, these these these really impressive environments. How do we make sure the sustainable for the long term? You know, again, we just went through this with Covid, but what's gonna come next? You know, one of the research questions that we need to answer, but also open source is an incredibly important piece of this. I think Ben can speak this in a second, all the harmonization work, all that effort, you know, essentially this massive, complex GTL process Is in the N three Seagate hub. So we believe, you know, completely and the open source model a little bit of a flavor on it too though, because, you know, again, back to the sustainability, john, I believe, you know, there's a room for this, this marriage between commercial platforms and open source software and we need both. You know, as we're strong proponents of N cats are both, but especially with sustainability, especially I think Enterprise I. T. You know, you have to have professional grade products that was part of, I would say an experiment we ran out and cast our thought was we can fund academic groups and we can have them do open source projects and you'll get some decent results. But I think the nature of it and the nature of these environments become so complex. The experiment we're taking is we're going to provide commercial grade tools For the academic community and the researchers and let them use them and see how they can be enabled and actually focus on research questions. And I think, you know, N3C, which we've been very successful with that model while still really adhering to the open source spirit and >>principles as an amazing story, congratulated, you know what? That's so awesome because that's the future. And I think you're onto something huge. Great point, Ben, you want to chime in on this whole sustainability because the public private partnership idea is the now the new model innovation formula is about open and collaborative. What's your thoughts? >>Absolutely. And I mean, we uh, volunteer have been huge proponents of reproducibility and openness, um in analyses and in science. And so everything done within the family platform is done in open source languages like python and R. And sequel, um and is exposed via open A. P. I. S and through get repository. So that as SaM says, we've we've pushed all of that E. T. L. Code that was developed within the platform out to the cats get hub. Um and the analysis code itself being written in those various different languages can also sort of easily be pulled out um and made available for other researchers in the future. And I think what we've also seen is that within the data enclave there's been an enormous amount of re use across the different research projects. And so actually having that security in place and making it secure so that people can actually start to share with each other securely as well. And and and be very clear that although I'm sharing this, it's still within the range of the government's requirements has meant that the, the research has really been accelerated because people have been able to build and stand on the shoulders of what earlier projects have done. >>Okay. Ben. Great stuff. 1000 researchers. Open source code and get a job. Where do I sign up? I want to get involved. This is amazing. Like it sounds like a great party. >>We'll send you a link if you do a search on on N three C, you know, do do a search on that and you'll actually will come up with a website hosted by the academic side and I'll show you all the information of how you can actually connect and john you're welcome to come in. Billion by all means >>billions of rows of data being solved. Great tech he's working on again. This is a great example of large scale the modern era of solving problems is here. It's out in the open, Open Science. Sam. Congratulations on your great success. Ben Award winners. You guys doing a great job. Great story. Thanks for sharing here with us in the queue. Appreciate it. >>Thank you, john. >>Thanks for having us. >>Okay. It is. Global public sector partner rewards best Covid solution palantir and and cats. Great solution. Great story. I'm john Kerry with the cube. Thanks for watching. Mm mm. >>Mhm

>>from the cube studios >>in Palo alto in >>boston connecting with thought leaders all around the world. This >>is a cute >>conversation. Hello welcome to the cubes coverage of HPD discovered 2021 virtual. I'm john for your host of the cube we're here with CUBA alumni. One of the original cube guests 2020 11 back in the day kurt president and chief architect of Hewlett Packard labs. He's also a Hewlett Packard enterprise fellow and vice president. Great to see you and you're in Vegas. I'm in Palo Alto. We've got a little virtual hybrid going on here. Thanks for spending time. >>Thanks john it's great to be back with you >>so much going on. I love to see you guys having this event kind of everyone in one spot. Good mojo. Great CHP, you know, back in the saddle again. I want to get your, take, your in the, in the, in the action right now on the lab side, which is great disruptive innovation is the theme. It's always been this year, more than ever coming out of the pandemic, people are looking for the future, looking to see the signs, they want to connect the dots. There's been some radical rethinking going on that you've been driving and in the labs, you hope you look back at last, take us through what's going on, what you're thinking, what's the, what's the big trends? >>Yeah, John So it's been interesting, you know, over the last 18 months, all of us had gone through about a decade's worth of advancement in decentralization, education, healthcare, our own work, what we're doing right now suddenly spread apart. Uh, and it got us thinking, you know, we think about that distributed mesh and as we, as we try and begin to return to normal and certainly think about all that we've lost, we want to move forward, we don't want to regress. And we started imagining, what does that world look like? And we think about the world of 20 2500 and 35 zeta bytes, 100 and 50 billion connected things out there. And it's the shape of the world has changed. That's where the data is going to be. And so we started thinking about what's it like to thrive in that kind of world. We had a global Defense research institute came to us, Nasa's that exact question. What's the edge? What do we need to prepare for for this age of insight? And it was kind of like when you had those exam questions and I was one of those kids who give you the final exam and if it's a really good question, suddenly everything clicked. I understood all the material because there was that really forcing question when they asked us that for me, it it solidified what I've been thinking about all the work we've done at labs over the last the last 10 years. And it's really about what does it take to survive and thrive. And for me it's three things. One is, success is going to go to whoever can reason over more information, who can gain the deepest insights from that information in time that matters and then can turn that insight into action at scale. So reason, insight and action. And it certainly was clear to me everything we've been trying to push for in labs, all those boundaries. We've been pushing all those conventions we've been defying are really trying to do that for, for our customers and our partners to bring in more information for them to understand, to be able to allow them to gain insight across departments across disciplines and then turn that insight into action at scale where scale is no longer one cloud or one company or one country, let alone one data center >>lot there. I love the dot I love that metadata and meta reasoning incites always been part of that. Um and you mentioned decentralization. Again, another big trend. I gotta ask you where is the big opportunity because a lot of people who are attending discover people watching are trying to ask what should they be thinking about. So what is that next big opportunity? How would you frame that and what should attendees look for coming out at HP discover. >>So one thing we're seeing is that this is actually a ubiquitous trend, whether we're talking about transportation or energy or communications, they all are trying to understand and how will they admit more of that data to make those real time decisions? Our expectation in the middle of this decade when we have the 125 petabytes, You know, 30% of that data will need real time action out of the edge where the speed of light is now material. And also we expect that at that point in time three out of four of those 185 petabytes, they'll never make it back to the data center. So understanding how we will allow that computation, that understanding to reach out to where the data is and then bringing in that's important. And then if we look at at those, all of those different areas, whether it's energy and transportation, communications, all that real time data, they all want to understand. And so I I think that as many people come to us virtually now, hopefully in person in the future when we have those conversations that labs, it's almost immediate takes a while for them and then they realize away that's me, this is my industry too, because they see that potential and suddenly where they see data, they see opportunity and they just want to know, okay, what does it take for me to turn that raw material into insight and then turn that insight into >>action, you know, storage compute never goes away, it gets more and more, you need more of it. This whole data and edge conversations really interesting. You know, we're living in that data centric, you know, everyone's gonna be a date a couple, okay. That we know that that's obvious. But I gotta ask you as you start to see machine learning, um cloud scale cloud operations, a new Edge and the new architecture is emerging and clients start to look at things like AI and they want to have more explain ability behind I hear that all the time. Can you explain it to me? Is there any kind of, what is it doing? Good as our biases, a good bad or you know, is really valuable expect experimental experiential. These are words are I'm hearing more and more of >>not so much a speeds >>and feeds game, but these are these are these are these are outcomes. So you got the core data, you've got a new architecture and you're hearing things like explainable ai experiential customer support, a new things happening, explain what this all means, >>You know, and it's it's interesting. We have just completed uh creating an Ai ethical framework for all of Hewlett Packard enterprise and whether we're talking about something that's internal improving a process, uh something that we sell our product or we're talking about a partnership where someone wants to build on top of our services and infrastructure, Build an AI system. We really wanted to encompass all of those. And so it was it was challenging actually took us about 18 months from that very first meeting for us to craft what are some principles for us to use to guide our our team members to give them that understanding. And what was interesting is we examined our principles of robustness of uh making sure they're human centric that they're reliable, that they are privacy preserving, that they are robust. We looked at that and then you look at where people want to apply these Ai today's AI and you start to realize there's a gap, there's actually areas where we have a great challenge, a human challenge and as interesting as possibly efficacious as today's A. I. S. R. We actually can't employ them with the confidence in the ethical position that we need to really pull that technology in. And what was interesting is that then became something that we were driving at labs. It began gave us a viewpoint into where there are gaps where, as you say, explica bility, you know, as fantastic as it is to talk into your mobile phone and have it translated into another one of hundreds of languages. I mean that is right out of Star trek and it's something we can all do. And frankly, it's, you know, we're expecting it now as efficacious as that is as we echo some other problems, it's not enough. We actually need to be explainable. We need to be able to audit these decisions. And so that's really what's informed now are trustworthy ai research and development program at Hewlett Packard Labs. Let's look at where we want to play. I I we look at what keeps us from doing it and then let's close the technology gap and it means some new things. It means new approaches. Sometimes we're going back back back to some of the very early ai um that things that we sort of left behind when suddenly the computational capability allowed us to enter into a machine learning and deep neural nets. Great applications, but it's not universally applicable. So that's where we are now. We're beginning to construct that second generation of AI systems where that explica bility where that trustworthiness and were more important that you said, understanding that data flow and the responsibility we have to those who created that data, especially when it's representing human information, that long term responsibility. What are the structures we need to support that ethically? >>That's great insight, Kirk, that's awesome stuff. And it reminds me of the old is new again, right? The cycles of innovation, you mentioned a I in the eighties, reminds me of dusting off and I was smiling because the notion of reasoning and natural language that's been around for a while, these other for a lot of Ai frame which have been around for a while But applied differently becomes interesting. The notion of Meta reasoning, I remember talking about that in 1998 around ontology and syntax and data analysis. I mean, again, well formed, you know, older ways to look at data. And so I gotta ask you, you know, you mentioned reasoning over information, getting the insights and having actions at scale. That doesn't sound like an R and D or labs issue. Right? I mean that that should be like in the market today. So I know you, there's stuff out there, what's different around the Hewlett Packard labs challenge because you guys, you guys are working on stuff that's kind of next gen, so why, what's next gen about reasoning moreover, information and getting insights? Because you know, there's a zillion startups out there that claim to be insights as a service, um, taking action outcomes >>and I think there were going to say a couple things. One is the technologies and the capabilities that God is this far. Uh, they're actually in an interesting position if we think of that twilight of moore's law is getting a little darker every day. Um, there's been such a tail wind behind us tremendous and we would have been foolish not to take advantage of it while it lasted, but as it now flattens out, we have to be realistic and say, you know what that ability to expect anticipate and then planned for a doubling and performance in the next 18 to 24 months because there's twice as many transistors in that square of silicon. We can't count on that anymore. We have to look now broader and it's not just one of these technology inflection points. There's so many we already mentioned ai it's voraciously vowing all this data at the same time. Now that data is all at the edge is no longer in the data center. I mean we may find ourselves laughing chuckling at the term itself data center. Remember when we sent it all the data? Because that's where the computers were. Well, that's 2020 thinking right, that's not even 2025. Thinking also security, that cyber threat of Nation State and criminal enterprises, all these things coming together and it's that confluence of discontinuities, that's what makes a loud problem. And the second piece is we don't just need to do it the way that we've been doing it because that's not necessarily sustainable. And if something is not sustainable is inherently inequitable because we can't afford to let everyone enjoy those benefits. So I think that's all those things, the technology confluence of technology, uh, disruptions and this desire to move to really sustainable, really inherently inequitable systems. That's what makes it a labs problem. >>I really think that's right on the money. And one of things I want to get your thoughts on, cause I know you have a unique historic view of the trajectory arc. Cloud computing that everyone's attention lift and shift cloud scale. Great cloud native. Now with hybrid and multi cloud clearly happening, all the cloud players were saying, oh, it's never gonna happen. All the data set is going to go away. Not really. The, the data center is just an edge big age. So you brought up the data center concept and you mentioned decentralization there, it's a distributed computing architecture, There is no line anymore between what's cloud and what's not the cloud is just the cloud and the data center is now a big fat edge and edges are smaller and bigger. Their nodes distribute computing now is the context. So this is not a new thing for Hewlett Packard enterprise. I mean you guys been doing distributed computing paradigms, supplying software and hardware and solutions Since I can remember since it was founded, what's new now, what do you say that folks are saying, what is HP doing for this new architecture? Because now an operating system is the word, the word that they want. They want to have an operating model, deV ops to have sex shops, all this is happening. What's the what's the state of the art from H. P. E. And how does the lab play into that vision? >>And it's so wonderful that you mentioned in our heritage because if you think about it was the first thing that Bill and they did, they made instruments of unparalleled value and quality for engineers and scientists. And the second thing they did was computerized that instrument control. And then they network them together and then they connect to the network measurement sensing systems to business computing. Right. And so that's really, that's exactly what we're talking about here. You know, and yesterday it was H. B. I. B. Cables. But today it is everything from an Aruba wireless gateway to a green Lake cloud that comes to you to now are cray exa scale supercomputing. And we wanted to look at that entire gamut and understand exactly what you said. How is today's modern developer who has been distinct in agile development in seven uh and devops and def sec ops. How can we make them as comfortable and confident deploying to any one of those systems or all of them in conjunction as confident as they've been deploying to a cloud. And I think that's really part of what we need to understand. And as you move out towards the edge things become interesting. A tiny amount of resources, the number of threats, physical and uh um cyber increased dramatically. It is no longer the healthy happy environment of that raised floor data center, It is actually out in the world but we have to because that's where the data is and so that's another piece of it that we're trying to bring with the labs are distributed systems lab trying to understand how do we make cloud native access every single bite everywhere from the tiniest little Edge embedded system, all the way up through that exa scale supercomputer, how do we admit all of that data to this entire generation and then the following subsequent generation, who will no longer understand what we were so worried about with things being in one place or another, they want to digest all the world's data regardless of where it is. >>You know, I was just having a conversation, you brought this up. Uh that's interesting around the history and the heritage, embedded systems is changing the whole hardware equations, changes the software driven model. Now, supply chain used to be constrained to software. Now you have a software supply chain, hardware, now you have software supply chain. So everything is happening in these kind of new use cases. And Edge is a great example where you want to have compute at the edge not having pulled back to some central location. So, again, advantage hp right, you've got more, you've got some solutions there. So all these like memory driven computing, something that you've worked on and been driving the machine product that we talked about when you guys launched a few years ago, um, looks like now a good R and D project, because all the discussions, I'm I'm hearing whether it's stuff in space or inside hybrid edges is I gotta have software running on an embedded system, I need security, I gotta have, you know, memory driven architecture is I gotta have data driven value in real time. This is new as a kind of a new shift, but you still need to run it. What's the update on the machine and the memory driven computing? And how does that connect the dots for this intelligent Edge? That's now super important in the hybrid equation. >>Yeah, it's fantastic you brought that up. You know, it's uh it's gratifying when you've been drawing pictures on your white board for 10 or 15 years and suddenly you see them printed uh and on the web and he's like, OK Yeah, you guys were there were there because we always knew it had to be bigger than us. And for a while you wonder, well is this the right direction? And then you get that gratification that you see it repeated. And I think one of the other elements that you said that was so important was talking about that supply chain uh and especially as we get towards these edge devices uh and the increasing cyber threat, you know, so much more about understanding the provenance of that supply chain and how we get beyond trust uh to prove. And in our case that proof is rooted in the silicon. Start with the silicon establish a silicon root of trust, something that can't be forged that that physically uncomfortable function in the silicon. And then build up that chain not of trust but a proof of measurable confidence. And then let's link that through the hardware through the data. And I think that's another element, understanding how that data is flowing in and we establish that that that provenance that's provable provenance and that also enables us to come back to that equitable question. How do we deal with all this data? Well, we want to make sure that everyone wants to buy in and that's why you need to be able to reward them. So being able to trace data into an AI model, trace it back out to its effect on society. All these are things that we're trying to understand the labs so that we can really establish this data economy and admit the day that we need to the problems that we have that really just are crying out for that solution bringing in that data, you just know where is the data, Where is the answer? Now I get to work with, I've worked for several years with the German center for your Degenerative Disease Research and I was teasing their director dr nakata. I said, you know, in a couple of years when you're getting that Nobel prize for medicine because you cracked Alzheimer's I want you to tell me how long was the answer hiding in plain sight because it was segregated across disciplines across geography and it was there. But we just didn't have that ability to view across the breath of the information and in a time that matters. And I think so much about what we're trying to do with the lab is that that's that reasoning moreover, more information, gaining insights in the time that matters and then it's all about action and that is driving that insight into the world regardless of whether it has to land in an exa scale supercomputer or tiny little edge device, we want today's application development teams to feel that degree of freedom to range over all of those that infrastructure and all of that data. >>You know, you bring up a great call out there. I want to just highlight that cause I thought that was awesome. The future breakthroughs are hiding in plain sight. It's the access to the people and the talent to solve the problems and the data that's stuck in the silos. You bring those together, you make that seamless and frictionless, then magic happens. That's that's really what we're talking about in this new world, isn't it? >>Absolutely, yeah. And it's one of those things that sometimes my kids as you know, why do you come in every day? And for me it is exactly that I think so many of the challenges we have are actually solvable if the right people knew the right information at the right time and that we all have that not again, not trust, but that proof that confidence, that measurable conference back to the instruments that that HP was always famous for. It was that precision and they all had that calibration tag. So you could measure your confidence in an HP instrument and the same. We want people to measure their confidence when data is flowing through Hewlett Packard Enterprise infrastructure. >>It's interesting to bring up the legacy because instrumentation network together, connecting to business systems. Hey, that sounds like the cloud observe ability, modern applications, instant action and actionable insights. I mean that's really the the same almost exact formula. >>Yeah, For me that's that, that the constant through line from the garage to right now is that ability to handle and connect people to the information that they need. >>Great, great to chat. You're always an inspiration and we could go for another hour talking about extra scale, green leg, all the other cool things going on at H P E. I got to ask you the final question, what are you most excited about for h B and his future and how and how can folks learn more to discover and what should they focus on? >>Uh so I think for me um what I love is that I imagine that world where the data you know today is out there at the edge and you know we have our Aruba team, we have our green Lake team, we have are consistent, you know, our core enterprise infrastructure business and now we also have all the way up through X scale compute when I think of that thriving business, that ability to bring in massive data analytics, machine learning and Ai and then stimulation and modeling. That's really what whether you're a scientist and engineer or an artist, you want to have that intersectionality. And I think we actually have this incredible, diverse set of resources to bring to bear to those problems that will span from edge to cloud, back to core and then to exit scale. So that's what really, that's why I find so exciting is all of the great uh innovators that we get to work with and the markets we get to participate in. And then for me it's also the fact it's all happening at Hewlett Packard Enterprise, which means we have a purpose. You know, if you ask, you know, when they did ask Dave Packer, Dave, why hp? And he said in 1960, we come together as a company because we can do something we could not do by ourselves and we make a contribution to society and I dare anyone to spend more than a couple of minutes with Antonio Neary and he won't remind you. And this is whether it is here to discover or in the halls at labs remind me our purpose, that Hewlett Packard Enterprise is to advance the way that people live and work. And for me that's that direct connection. So it's, it's the technology and then the purpose and that's really what I find so exciting about HPV. >>That's a great call out, Antonio deserves props. I love talking with him, he's the true Bill and Dave Bill. Hewlett Dave package spirit And I'll say that I've talked with him and one of the things that resident to me and resonates well is the citizenship and be interesting to see if Bill and Dave were alive today, that now it's a global citizenship. This is a huge part of the culture and I know it's still alive there at H P E. So, great call out there and props to Antonio and yourself and the team. Congratulations. Thanks for spending the time, appreciate it. >>Thank you john it's great to be with you again. >>Okay. Global labs. Global opportunities, radical. Rethinking this is what's happening within HP. Hewlett Packard Labs, Great, great contribution there from Kirk, have them on the cube and always fun to talk so much, so much to digest there. It's awesome. I'm john Kerry with the cube. Thanks for watching. >>Mm >>mhm Yeah.

>>mhm Yes. >>Hello and welcome back to the cubes coverage of dr khan 2021 virtual. I'm john Kerry hosted the Q got a great cube segment here. Simon Maple Field C T Oh it's technique. Great company security shifting left great to have you on Simon. Thanks for thanks for stopping by >>absolute pleasure. Thank you very much for having me. >>So you guys were on last year the big partnership with DR Conn remember that interview vividly because it was really the beginning at the beginning but really come to me the mainstream of shifting left as devops. It's not been it's been around for a while. But as a matter of practice as containers have been going super mainstream. Super ballistic in the developer community then you're seeing what's happening. It's containers everywhere. Security Now dev sec apps is the standard. So devops great infrastructure as code. We all know that but now it's def sec ops is standard. This is the real deal. Give us the update on what's going on with sneak. >>Absolutely, yeah. And you know, we're still tireless in our approach of trying to get make sure developers don't just have the visibility of security but are very much empowered in terms of actually fixing issues and secure development is what we're really striving for. So yeah, the update, we're still very, very deep into a partnership with DACA. We have updates on DR desktop which allows developers to scan the containers on the command line, providing developers that really fast feedback as as early as possible. We also have uh, you know, new updates and support for running Docker scan on Lennox. Um, and yeah, you know, we're still there on the Docker hub and providing that security insights um, to, to users who are going to Docker hub to grab their images. >>Well, for the folks watching maybe for the first time, the sneak Docker partnership, we went in great detail last year was the big reveal why Docker and sneak partnership, what is the evolution of that partnership over the year? They speak highly of you guys as a developer partner. Why Doctor? What's the evolution looked like? >>It's a it's a really great question. And I think, you know, when you look at the combination of DACA and sneak well actually let's take let's take each as an individual. Both companies are very, very developer focused. First of all, right, so our goals and will be strife or what we what we tirelessly spend their time doing is creating features and creating, creating an environment in which a developer you can do what they need to do as easily as possible. And that, you know, everyone says they want to be developer friendly, They want to be developer focused. But very few companies can achieve. And you look at a company like doctor, you're a company like sneak it really, really provides that developer with the developer experience that they need to actually get things done. Um, and it's not just about being in a place that a developer exists. It's not enough to do that. You need to provide a developer with that experience. So what we wanted to do was when we saw doctor and extremely developer friendly environment and a developer friendly company, when we saw the opportunity there to partner with Yoko, we wanted to provide our security developer friendliness and developer experience into an already developed a friendly tool. So what the partnership provides is the ease of, you know, deploying code in a container combined with the ease of testing your code for security issues and fixing security issues in your code and your container and pulling it together in one place. Now, one of the things which we as a as a security company um pride ourselves on is actually not necessarily saying we provide security tools. One of what our favorite way of saying is we're a developer tooling company. So we provide tools that are four developers now in doing that. It's important you go to where the developers are and developers on DACA are obviously in places like the Docker hub or the Docker Cli. And so it's important for us to embed that behavior and that ease of use inside Dhaka for us to have that uh that that flow. So the developer doesn't need to leave the Docker Cli developer that doesn't need to leave Docker hub in order to see that data. If you want to go deeper, then there are probably easier ways to find that data perhaps with sneak or on the sneak site or something like that. But the core is to get that insight to get that visibility and to get that remediation, you can see that directly in in the in the Dhaka environment. And so that's what makes the relationship so so powerful. The fact that you combine everything together and you do it at source >>and doing it at the point of code. >>Writing >>code is one of the big things I've always liked about the value proposition is simple shift left. Um So let's just step back for a second. I got to ask you this question because this I wanted to make sure we get this on the table. What are the main challenges uh and needs to, developers have with container security? What are you seeing as the main top uh A few things that they need to have right now for the challenges uh with container security? >>Yeah, it's a it's a very good question. And I think to answer that, I think we need to um we need to think of it in a couple of ways. First of all, you've just got developers security uh in general, across containers. Um And the that in itself is there are different levels at which developers engage with containers. Um In some organizations, you have security teams that are very stringent in terms of what developers can and can't do in other organizations. It's very much the developer that that chooses their environment, chooses their parent image, et cetera. And so there when a developer has many, many choices in which they need to need to decide on, some of those choices will lead to more issues, more risk. And when we look at a cloud native environment, um uh Let's take let's take a node uh image as an example, the number of different uh images tags you can choose from as a developer. It's you know, there are hundreds, probably thousands. That you can actually you can actually choose. What is the developer gonna do? Well, are they going to just copy paste from another doctor file, for example, most likely. What if there are issues in that docker file? They're just gonna copy paste that across mis configurations that exist. Not because the developer is making the wrong decision, but because the developer very often doesn't necessarily know that they need to add a specific directive in. Uh So it's not necessarily what you add in a conflict file, but it's very often what you admit. So there are a couple of things I would say from a developer point of view that are important when we think about cloud security, the first one is just that knowledge that understanding what they need to do, why they need to do it. Secure development doesn't need to be, doesn't mean they need to be deep in security. It means they need to understand how they can develop securely and what what the best decisions that could come from guard rails, from the security team that they provide the development team to offer. But that's the that's an important error of secure development. The second thing and I think one of the most important things is understanding or not understanding necessarily, but having the information to get an act on those things early. So we know the length of time that developers are uh working on a branch or working on um some some code changes that is reducing more and more and more so that we can push to production very, very quickly. Um What we need to do is make sure that as a developer is making their changes, they can make the right decision at the right time and they have the right information at that time. And a lot of this could be getting information from tools, could be getting information from your team where it could be getting information from your production environments and having that information early is extremely important to make. That decision. May be in isolation with your team in an autonomous way or with advice from the security team. But I would say those are the two things having that information that will allow you to make that action, that positive change. Um uh and and yeah, understanding and having that knowledge about how you can develop security. >>All right. So I have a security thing. So I'm a development team and by the way, this whole team's thing is a huge deal. I think we'll get to that. I want to come back to that in a second but just throw this out there. Got containers, got some security, it's out there and you got kubernetes clusters where containers are coming and going. Sometimes containers could have malware in them. Um and and this is, I've heard this out and about how do how that happens off container or off process? How do you know about it? Is that infected by someone else? I mean is it gonna be protected? How does the development team once it's released into the wild, so to speak. Not to be like that, but you get the idea, it's like, okay, I'm concerned off process this containers flying around. What is it How do you track all >>and you know, there's a there's a few things here that are kind of like potential potential areas that, you know, we can trip up when we think about malware that's running um there are certain things that we need to that we need to consider and what we're really looking at here are kind of, what do we have in place in the runtime that can kind of detect these issues are happening? How do we block that? And how do you provide that information back to the developer? The area that I think is, and that is very, very important in order to in order to be able to identify monitor that those environments and then feed that back. So that that that's the kind of thing that can be that can be fixed. Another aspect is, is the static issues and the static issues whether that's in your os in your OS packages, for example, that could be key binaries that exist in your in your in your docker container out the box as well or of course in your application, these are again, areas that are extremely important to detect and they can be detected very very early. So some things, you know, if it's malware in a package that has been identified as malware then absolutely. That can be that can be tracked very very early. Sometimes these things need to be detected a little bit later as well. But yeah, different tools for different for different environments and wear sneak is really focused. Is this static analysis as early as possible. >>Great, great insight there. Thanks for sharing that certainly. Certainly important. And you know, some companies classes are locked down and all of sudden incomes, you know, some some malware from a container, people worried about that. So I want to bring that up. Uh The other thing I want to ask you is this idea of end to end security um and this is a team formation thing we're seeing where modern teams have essentially visibility of their workload and to end. So this is a huge topic. And then by the way it might integrate their their app might integrate with other processes to that's great for containers as well and observe ability and microservices. So this is the trend. What's in it for the developer? If I work with sneak and docker, what benefits do I get if I want to go down that road of having these teams began to end, but I want the security built in. >>Mhm. Yeah, really, really important. And I think what's what's most important there is if we don't look end to end, there are component views and there are applications. If we don't look into end, we could have our development team fixing things that realistically aren't in production anyway or aren't the key risks that are potentially hurting us in our production environment. So it's important to have that end to end of you so that we have the right insights and can prioritize what we need to identify and look at early. Um, so I think, I think that visibility into end is extremely important. If we think about who, who is re fixing uh certain issues, again, this is gonna depend from dog to walk, but what we're seeing more and more is this becoming a developer lead initiative to not just find or be given that information, but ultimately fixed. They're getting more and more responsible for DR files for for I see for for their application code as well. So one of the areas which we've looked into as well is identifying and actually running in cuba Netease workloads to identify where the most important areas that a developer needs to look at and this is all about prioritization. So, you know, if the developer has just a component view and they have 100 different images, 100 different kubernetes conflicts, you know, et cetera. Where do they prioritize, where do they spend their time? They shouldn't consider everything equal. So this identification of where the workloads are running and what um is causing you the most risk as a business and as an organization, that is the data. That can be directly fed back into your, your your vulnerability data and then you can prioritize based on the kubernetes workloads that are in your production and that can be fed directly into the results in the dashboards. That's neat. Can provide you as well. So that end to end story really provides the context you need in order to not just develop securely, but act and action issues in a proper way. >>That's a great point. Context matters here because making it easy to do the right thing as early as possible, the right time is totally an efficiency productivity gain, you see in that that's clearly what people want. It's a great formula, success, reduce the time it takes to do something, reduced the steps and make it easy. Right, come on, that's a that's a formula. Okay, so I gotta bring that to the next level. When I ask you specifically around automation, this is one the hot topic and def sec ops, automation is part of it. You got scale, you got speed, you've got a I machine learning, you go out of all these new things. Microservices, how do you guys fit into the automation story? >>It's a great question. And you know, one of the recent reports that we that we did based on a survey data this year called the state of a state of cloud, native applications security. We we asked the question how automated our people in their in their deployment pipelines and we found some really strong correlations between value from a security point of view um in terms of in terms of having that automation in it, if I can take you through a couple of them and then I'll address that question about how we can be automated in that. So what we found is a really strong correlation as you would expect with security testing in ci in your source code repositories and all the way through the deployment ci and source code were the two of the most most well tested areas across the pipeline. However the most automated teams were twice as likely to test in I. D. S. And testing your CLS in local development. And now those are areas that are really hard to automate if at all because it's developers running running their cli developers running and testing in their I. D. So the having a full automation and full uh proper testing throughout the sclc actually encourages and and makes developers test more in their development environment. I'm not saying there's causation there but there's definite correlation. A couple of other things that this pushes is um Much much more likely to test daily or continuously being automated as you would expect because it's part of the bills as part of your monitoring. But crucially uh 73% of our respondents were able to fix a critical issue in less than a week as opposed to just over 30% of people that were not automated, so almost double people are More likely to fix within a week. 36% of people who are automated can fix a critical security issue in less than a day as opposed to 8% of people who aren't automated. So really strong data that correlates being automated with being able to react now. If you look at something like Sneak what if our um goals of obviously being developer friendly developer first and being able to integrate where developers are and throughout the pipeline we want to test everywhere and often. Okay, so we start as far left as we can um integrating into, you know, CLS integrating into Docker hub, integrating into into doctors can so at the command line you type in doctors can you get sneak embedded in DHAKA desktop to provide you those results so as early as possible, you get that data then all the way through to to uh get reposed providing that testing and automatically testing and importing results from there as well as as well as other repositories, container repositories, being at a poor from there and test then going into ci being able to run container tests in C I to make sure we're not regressing and to choose what we want to do their whether we break, whether we continue with with raising an issue or something like that, and then continuing beyond that into production. So we can monitor tests and automatically send pull requests, etcetera. As and when new issues or new fixes occur. So it's about integrating at every single stage, but providing some kind of action. So, for example, in our ui we provide the ability to say this is the base level you should be or could be at, it will reduce your number of vulnerabilities by X and as a result you're going to be that much more secure that action ability across the pipeline. >>That's a great, great data dump, that's a masterclass right there on automation. Thanks for sharing that sign. I appreciate it. I gotta ask you the next question that comes to my mind because I think this is kind of the dots connect for the customer is okay. I love this kind of hyper focus on containers and security. You guys are all over it, shift left as far as possible, be there all the time, test, test, test all through the life cycle of the code. Well, the one thing that is popping up as a huge growth areas, obviously hybrid cloud devops across both environments and the edge, whether it's five G industrial or intelligent edge, you're gonna have kubernetes clusters at the edge now. So you've got containers. The relationship to kubernetes and then ultimately cloud native work clothes at, say, the edge, which has data has containers. So there's a lot of stuff going on all over the place. What's your, what's your comment there for customer says, Hey, you know, I got, this is my architecture that's happening to me now. I'm building it out. We're comfortable with kubernetes put in containers everywhere, even on the edge how to sneak fit into that story. >>Yeah, really, really great question. And I think, you know, a lot of what we're doing right now is looking at a developer platform. So we care about, we care about everything that a developer can check in. Okay, so we care about get, we care about the repositories, we care about the artifact. So um, if you look at the expansion of our platform today, we've gone from code that people uh, third party libraries that people test. We added containers. We've also added infrastructure as code. So Cuban eighties conflicts, Terror form scripts and things like that. We're we're able to look at everything that the developer touches from their code with sneak code all the way through to your to your container. And I see, so I think, you know, as we see more and more of this pushing out into the edge, cuba Nitties conflict that that, you know, controls a lot of that. So much of this is now going to be or not going to be, but so much of the environment that we need to look at is in the configurations or the MIS configurations in that in those deployment scripts, um, these are some of the areas which which we care a lot about in terms of trying to identify those vulnerabilities, those miS configurations that exist within within those scripts. So I can see yeah more and more of this and there's a potential shift like that across to the edge. I think it's actually really exciting to be able to see, to be able to see those uh, those pushing across. I don't necessarily see any other, any, you know, different security threats or the threat landscape changing as a result of that. Um there could be differences in terms of configurations, in terms of miS configurations that that that could increase as a result, but, you know, a lot of this and it just needs to be dealt with in the appropriate way through tooling through, through education of of of of how that's done. >>Well, obviously threat vectors are all gonna look devops like there's no perimeter. So they're everywhere right? Looking at I think like a hacker to be being there. Great stuff. Quick question on the future relationship with DR. Obviously you're betting a lot here on that container relationship, a good place to start. A lot of benefits there. They have dependencies, they're going to have implications. People love them, they love to use them, helps old run with the new and helps the new run better. Certainly with kubernetes, everything gets better together. What's the future with the DACA relationship? Take us through how you see it. >>So yeah, I mean it's been an absolute blast the doctor and you know, even from looking at some of the internal internal chats, it's been it's been truly wonderful to see the, the way in which both the doctor and sneak from everything from an engineering point of view from a marketing, from a product team. It's been a pleasure to, it's been a pleasure to see that relationship grow and flourish. And, and I think there's two things, first of all, I think it's great that as companies, we, we both worked very, very well together. I think as as as users um seeing, you know, doctor and and and sneak work so so seamlessly and integrated a couple of things. I would love to see. Um, I think what we're gonna see more and more and this is one of the areas that I think, um you know, looking at the way sneak is going to be viewing security in general. We see a lot of components scanning a lot, a lot of people looking at a components can and seeing vulnerabilities in your components. Can I think what we need to, to to look more upon is consolidating a lot of the a lot of the data which we have in and around different scans. What I would love to see is perhaps, you know, if you're running something through doctors can how can you how can you view that data through through sneak perhaps how can we get that closer integration through the data that we that we see. So I would love to see a lot more of that occur, you know, within that relationship and these are kind of like, you know, we're getting to that at that stage where we see integration, it just various levels. So we have the integration where we have we are embedded but how can we make that better for say a sneak user who also comes to the sneak pages and wants to see that data through sneak. So I would love to see at that level uh more there where as I mentioned, we have we have some some additional support as well. So you can run doctors can from from Lenox as well. So I can see more and more of that support rolling out but but yeah, in terms of the future, that's where I would love to see us uh to grow more >>and I'll see in the landscape side on the industry side, um, security is going beyond the multiple control planes out there. Kubernetes surveillance service matches, etcetera, continues to be the horizontally scalable cloud world. I mean, and you got you mentioned the edge. So a lot more complexity to rein in and make easier. >>Yeah, I mean there's a lot more complexity, you know, from a security point of view, the technology is the ability to move quickly and react fast in production actually help security a lot because you know, being able to spin a container and make changes and and bring a container down. These things just weren't possible, you know, 10 years ago, 20 years ago. Pre that it's like it was it's insanely hard compared trying to trying to do that compared to just re spinning a container up. However, the issue I see from a security point of view, the concerns I see is more around a culture and an education point of view of we've got all this great tech and it's it's awesome but we need to do it correctly. So making sure that as you mentioned with making the right decision, what we want to make sure is that right decision is also the easy decision and the clear decision. So we just need to make sure that as we as we go down this journey and we're going down it fast and it's not gonna, I don't see it slowing down, we're going fast down that journey. How do we make, how do we prepare ourselves for that? We're already seeing, you know, miss configurations left, right and center in the news, I am roles as three buckets, etcetera. These are they're they're simpler fixes than we than we believe, right? We just need to identify them and and make those changes as needed. So we just need to make sure that that is in place as we go forward. But it's exciting times for sure. >>It's really exciting. And you got the scanning and right at the point of coding automation to help take that basic mis configuration, take that off the table. Not a lot of manual work, but ultimately get to that cloud scale cool stuff. >>Simon, thank you >>for coming on the cube dr khan coverage. Really appreciate your time. Drop some nice commentary there. Really appreciate it. Thank you. >>My pleasure. Thank you very much. >>Simon Maple Field C T. O. A sneak hot startup. Big partner with Docker Security, actually built in deVOPS, is now dead. Say cops. This is dr khan cube 2021 virtual coverage. I'm sean for your host. Thanks for watching. Mm.