(soft music) >> Hello, everyone. Welcome to theCUBE's presentation of the AWS Startup Showcase. AI and Machine Learning: Top Startups Building Foundational Model Infrastructure. This is season 3, episode 1 of the ongoing series covering the exciting stuff from the AWS ecosystem, talking about machine learning and AI. I'm your host, John Furrier and today we are excited to be joined by Luis Ceze who's the CEO of OctoML and Anna Connolly, VP of customer success and experience OctoML. Great to have you on again, Luis. Anna, thanks for coming on. Appreciate it. >> Thank you, John. It's great to be here. >> Thanks for having us. >> I love the company. We had a CUBE conversation about this. You guys are really addressing how to run foundational models faster for less. And this is like the key theme. But before we get into it, this is a hot trend, but let's explain what you guys do. Can you set the narrative of what the company's about, why it was founded, what's your North Star and your mission? >> Yeah, so John, our mission is to make AI sustainable and accessible for everyone. And what we offer customers is, you know, a way of taking their models into production in the most efficient way possible by automating the process of getting a model and optimizing it for a variety of hardware and making cost-effective. So better, faster, cheaper model deployment. >> You know, the big trend here is AI. Everyone's seeing the ChatGPT, kind of the shot heard around the world. The BingAI and this fiasco and the ongoing experimentation. People are into it, and I think the business impact is clear. I haven't seen this in all of my career in the technology industry of this kind of inflection point. And every senior leader I talk to is rethinking about how to rebuild their business with AI because now the large language models have come in, these foundational models are here, they can see value in their data. This is a 10 year journey in the big data world. Now it's impacting that, and everyone's rebuilding their company around this idea of being AI first 'cause they see ways to eliminate things and make things more efficient. And so now they telling 'em to go do it. And they're like, what do we do? So what do you guys think? Can you explain what is this wave of AI and why is it happening, why now, and what should people pay attention to? What does it mean to them? >> Yeah, I mean, it's pretty clear by now that AI can do amazing things that captures people's imaginations. And also now can show things that are really impactful in businesses, right? So what people have the opportunity to do today is to either train their own model that adds value to their business or find open models out there that can do very valuable things to them. So the next step really is how do you take that model and put it into production in a cost-effective way so that the business can actually get value out of it, right? >> Anna, what's your take? Because customers are there, you're there to make 'em successful, you got the new secret weapon for their business. >> Yeah, I think we just see a lot of companies struggle to get from a trained model into a model that is deployed in a cost-effective way that actually makes sense for the application they're building. I think that's a huge challenge we see today, kind of across the board across all of our customers. >> Well, I see this, everyone asking the same question. I have data, I want to get value out of it. I got to get these big models, I got to train it. What's it going to cost? So I think there's a reality of, okay, I got to do it. Then no one has any visibility on what it costs. When they get into it, this is going to break the bank. So I have to ask you guys, the cost of training these models is on everyone's mind. OctoML, your company's focus on the cost side of it as well as the efficiency side of running these models in production. Why are the production costs such a concern and where specifically are people looking at it and why did it get here? >> Yeah, so training costs get a lot of attention because normally a large number, but we shouldn't forget that it's a large, typically one time upfront cost that customers pay. But, you know, when the model is put into production, the cost grows directly with model usage and you actually want your model to be used because it's adding value, right? So, you know, the question that a customer faces is, you know, they have a model, they have a trained model and now what? So how much would it cost to run in production, right? And now without the big wave in generative AI, which rightfully is getting a lot of attention because of the amazing things that it can do. It's important for us to keep in mind that generative AI models like ChatGPT are huge, expensive energy hogs. They cost a lot to run, right? And given that model usage growth directly, model cost grows directly with usage, what you want to do is make sure that once you put a model into production, you have the best cost structure possible so that you're not surprised when it's gets popular, right? So let me give you an example. So if you have a model that costs, say 1 to $2 million to train, but then it costs about one to two cents per session to use it, right? So if you have a million active users, even if they use just once a day, it's 10 to $20,000 a day to operate that model in production. And that very, very quickly, you know, get beyond what you paid to train it. >> Anna, these aren't small numbers, and it's cost to train and cost to operate, it kind of reminds me of when the cloud came around and the data center versus cloud options. Like, wait a minute, one, it costs a ton of cash to deploy, and then running it. This is kind of a similar dynamic. What are you seeing? >> Yeah, absolutely. I think we are going to see increasingly the cost and production outpacing the costs and training by a lot. I mean, people talk about training costs now because that's what they're confronting now because people are so focused on getting models performant enough to even use in an application. And now that we have them and they're that capable, we're really going to start to see production costs go up a lot. >> Yeah, Luis, if you don't mind, I know this might be a little bit of a tangent, but, you know, training's super important. I get that. That's what people are doing now, but then there's the deployment side of production. Where do people get caught up and miss the boat or misconfigure? What's the gotcha? Where's the trip wire or so to speak? Where do people mess up on the cost side? What do they do? Is it they don't think about it, they tie it to proprietary hardware? What's the issue? >> Yeah, several things, right? So without getting really technical, which, you know, I might get into, you know, you have to understand relationship between performance, you know, both in terms of latency and throughput and cost, right? So reducing latency is important because you improve responsiveness of the model. But it's really important to keep in mind that it often leads diminishing returns. Below a certain latency, making it faster won't make a measurable difference in experience, but it's going to cost a lot more. So understanding that is important. Now, if you care more about throughputs, which is the time it takes for you to, you know, units per period of time, you care about time to solution, we should think about this throughput per dollar. And understand what you want is the highest throughput per dollar, which may come at the cost of higher latency, which you're not going to care about, right? So, and the reality here, John, is that, you know, humans and especially folks in this space want to have the latest and greatest hardware. And often they commit a lot of money to get access to them and have to commit upfront before they understand the needs that their models have, right? So common mistake here, one is not spending time to understand what you really need, and then two, over-committing and using more hardware than you actually need. And not giving yourself enough freedom to get your workload to move around to the more cost-effective choice, right? So this is just a metaphoric choice. And then another thing that's important here too is making a model run faster on the hardware directly translates to lower cost, right? So, but it takes a lot of engineers, you need to think of ways of producing very efficient versions of your model for the target hardware that you're going to use. >> Anna, what's the customer angle here? Because price performance has been around for a long time, people get that, but now latency and throughput, that's key because we're starting to see this in apps. I mean, there's an end user piece. I even seeing it on the infrastructure side where they're taking a heavy lifting away from operational costs. So you got, you know, application specific to the user and/or top of the stack, and then you got actually being used in operations where they want both. >> Yeah, absolutely. Maybe I can illustrate this with a quick story with the customer that we had recently been working with. So this customer is planning to run kind of a transformer based model for tech generation at super high scale on Nvidia T4 GPU, so kind of a commodity GPU. And the scale was so high that they would've been paying hundreds of thousands of dollars in cloud costs per year just to serve this model alone. You know, one of many models in their application stack. So we worked with this team to optimize our model and then benchmark across several possible targets. So that matching the hardware that Luis was just talking about, including the newer kind of Nvidia A10 GPUs. And what they found during this process was pretty interesting. First, the team was able to shave a quarter of their spend just by using better optimization techniques on the T4, the older hardware. But actually moving to a newer GPU would allow them to serve this model in a sub two milliseconds latency, so super fast, which was able to unlock an entirely new kind of user experience. So they were able to kind of change the value they're delivering in their application just because they were able to move to this new hardware easily. So they ultimately decided to plan their deployment on the more expensive A10 because of this, but because of the hardware specific optimizations that we helped them with, they managed to even, you know, bring costs down from what they had originally planned. And so if you extend this kind of example to everything that's happening with generative AI, I think the story we just talked about was super relevant, but the scale can be even higher, you know, it can be tenfold that. We were recently conducting kind of this internal study using GPT-J as a proxy to illustrate the experience of just a company trying to use one of these large language models with an example scenario of creating a chatbot to help job seekers prepare for interviews. So if you imagine kind of a conservative usage scenario where the model generates just 3000 words per user per day, which is, you know, pretty conservative for how people are interacting with these models. It costs 5 cents a session and if you're a company and your app goes viral, so from, you know, beginning of the year there's nobody, at the end of the year there's a million daily active active users in that year alone, going from zero to a million. You'll be spending about $6 million a year, which is pretty unmanageable. That's crazy, right? >> Yeah. >> For a company or a product that's just launching. So I think, you know, for us we see the real way to make these kind of advancements accessible and sustainable, as we said is to bring down cost to serve using these techniques. >> That's a great story and I think that illustrates this idea that deployment cost can vary from situation to situation, from model to model and that the efficiency is so strong with this new wave, it eliminates heavy lifting, creates more efficiency, automates intellect. I mean, this is the trend, this is radical, this is going to increase. So the cost could go from nominal to millions, literally, potentially. So, this is what customers are doing. Yeah, that's a great story. What makes sense on a financial, is there a cost of ownership? Is there a pattern for best practice for training? What do you guys advise cuz this is a lot of time and money involved in all potential, you know, good scenarios of upside. But you can get over your skis as they say, and be successful and be out of business if you don't manage it. I mean, that's what people are talking about, right? >> Yeah, absolutely. I think, you know, we see kind of three main vectors to reduce cost. I think one is make your deployment process easier overall, so that your engineering effort to even get your app running goes down. Two, would be get more from the compute you're already paying for, you're already paying, you know, for your instances in the cloud, but can you do more with that? And then three would be shop around for lower cost hardware to match your use case. So on the first one, I think making the deployment easier overall, there's a lot of manual work that goes into benchmarking, optimizing and packaging models for deployment. And because the performance of machine learning models can be really hardware dependent, you have to go through this process for each target you want to consider running your model on. And this is hard, you know, we see that every day. But for teams who want to incorporate some of these large language models into their applications, it might be desirable because licensing a model from a large vendor like OpenAI can leave you, you know, over provision, kind of paying for capabilities you don't need in your application or can lock you into them and you lose flexibility. So we have a customer whose team actually prepares models for deployment in a SaaS application that many of us use every day. And they told us recently that without kind of an automated benchmarking and experimentation platform, they were spending several days each to benchmark a single model on a single hardware type. So this is really, you know, manually intensive and then getting more from the compute you're already paying for. We do see customers who leave money on the table by running models that haven't been optimized specifically for the hardware target they're using, like Luis was mentioning. And for some teams they just don't have the time to go through an optimization process and for others they might lack kind of specialized expertise and this is something we can bring. And then on shopping around for different hardware types, we really see a huge variation in model performance across hardware, not just CPU vs. GPU, which is, you know, what people normally think of. But across CPU vendors themselves, high memory instances and across cloud providers even. So the best strategy here is for teams to really be able to, we say, look before you leap by running real world benchmarking and not just simulations or predictions to find the best software, hardware combination for their workload. >> Yeah. You guys sound like you have a very impressive customer base deploying large language models. Where would you categorize your current customer base? And as you look out, as you guys are growing, you have new customers coming in, take me through the progression. Take me through the profile of some of your customers you have now, size, are they hyperscalers, are they big app folks, are they kicking the tires? And then as people are out there scratching heads, I got to get in this game, what's their psychology like? Are they coming in with specific problems or do they have specific orientation point of view about what they want to do? Can you share some data around what you're seeing? >> Yeah, I think, you know, we have customers that kind of range across the spectrum of sophistication from teams that basically don't have MLOps expertise in their company at all. And so they're really looking for us to kind of give a full service, how should I do everything from, you know, optimization, find the hardware, prepare for deployment. And then we have teams that, you know, maybe already have their serving and hosting infrastructure up and ready and they already have models in production and they're really just looking to, you know, take the extra juice out of the hardware and just do really specific on that optimization piece. I think one place where we're doing a lot more work now is kind of in the developer tooling, you know, model selection space. And that's kind of an area that we're creating more tools for, particularly within the PyTorch ecosystem to bring kind of this power earlier in the development cycle so that as people are grabbing a model off the shelf, they can, you know, see how it might perform and use that to inform their development process. >> Luis, what's the big, I like this idea of picking the models because isn't that like going to the market and picking the best model for your data? It's like, you know, it's like, isn't there a certain approaches? What's your view on this? 'Cause this is where everyone, I think it's going to be a land rush for this and I want to get your thoughts. >> For sure, yeah. So, you know, I guess I'll start with saying the one main takeaway that we got from the GPT-J study is that, you know, having a different understanding of what your model's compute and memory requirements are, very quickly, early on helps with the much smarter AI model deployments, right? So, and in fact, you know, Anna just touched on this, but I want to, you know, make sure that it's clear that OctoML is putting that power into user's hands right now. So in partnership with AWS, we are launching this new PyTorch native profiler that allows you with a single, you know, one line, you know, code decorator allows you to see how your code runs on a variety of different hardware after accelerations. So it gives you very clear, you know, data on how you should think about your model deployments. And this ties back to choices of models. So like, if you have a set of choices that are equally good of models in terms of functionality and you want to understand after acceleration how are you going to deploy, how much they're going to cost or what are the options using a automated process of making a decision is really, really useful. And in fact, so I think these events can get early access to this by signing up for the Octopods, you know, this is exclusive group for insiders here, so you can go to OctoML.ai/pods to sign up. >> So that Octopod, is that a program? What is that, is that access to code? Is that a beta, what is that? Explain, take a minute and explain Octopod. >> I think the Octopod would be a group of people who is interested in experiencing this functionality. So it is the friends and users of OctoML that would be the Octopod. And then yes, after you sign up, we would provide you essentially the tool in code form for you to try out in your own. I mean, part of the benefit of this is that it happens in your own local environment and you're in control of everything kind of within the workflow that developers are already using to create and begin putting these models into their applications. So it would all be within your control. >> Got it. I think the big question I have for you is when do you, when does that one of your customers know they need to call you? What's their environment look like? What are they struggling with? What are the conversations they might be having on their side of the fence? If anyone's watching this, they're like, "Hey, you know what, I've got my team, we have a lot of data. Do we have our own language model or do I use someone else's?" There's a lot of this, I will say discovery going on around what to do, what path to take, what does that customer look like, if someone's listening, when do they know to call you guys, OctoML? >> Well, I mean the most obvious one is that you have a significant spend on AI/ML, come and talk to us, you know, putting AIML into production. So that's the clear one. In fact, just this morning I was talking to someone who is in life sciences space and is having, you know, 15 to $20 million a year cloud related to AI/ML deployment is a clear, it's a pretty clear match right there, right? So that's on the cost side. But I also want to emphasize something that Anna said earlier that, you know, the hardware and software complexity involved in putting model into production is really high. So we've been able to abstract that away, offering a clean automation flow enables one, to experiment early on, you know, how models would run and get them to production. And then two, once they are into production, gives you an automated flow to continuously updating your model and taking advantage of all this acceleration and ability to run the model on the right hardware. So anyways, let's say one then is cost, you know, you have significant cost and then two, you have an automation needs. And Anna please compliment that. >> Yeah, Anna you can please- >> Yeah, I think that's exactly right. Maybe the other time is when you are expecting a big scale up in serving your application, right? You're launching a new feature, you expect to get a lot of usage or, and you want to kind of anticipate maybe your CTO, your CIO, whoever pays your cloud bills is going to come after you, right? And so they want to know, you know, what's the return on putting this model essentially into my application stack? Am I going to, is the usage going to match what I'm paying for it? And then you can understand that. >> So you guys have a lot of the early adopters, they got big data teams, they're pushed in the production, they want to get a little QA, test the waters, understand, use your technology to figure it out. Is there any cases where people have gone into production, they have to pull it out? It's like the old lemon laws with your car, you buy a car and oh my god, it's not the way I wanted it. I mean, I can imagine the early people through the wall, so to speak, in the wave here are going to be bloody in the sense that they've gone in and tried stuff and get stuck with huge bills. Are you seeing that? Are people pulling stuff out of production and redeploying? Or I can imagine that if I had a bad deployment, I'd want to refactor that or actually replatform that. Do you see that too? >> Definitely after a sticker shock, yes, your customers will come and make sure that, you know, the sticker shock won't happen again. >> Yeah. >> But then there's another more thorough aspect here that I think we likely touched on, be worth elaborating a bit more is just how are you going to scale in a way that's feasible depending on the allocation that you get, right? So as we mentioned several times here, you know, model deployment is so hardware dependent and so complex that you tend to get a model for a hardware choice and then you want to scale that specific type of instance. But what if, when you want to scale because suddenly luckily got popular and, you know, you want to scale it up and then you don't have that instance anymore. So how do you live with whatever you have at that moment is something that we see customers needing as well. You know, so in fact, ideally what we want is customers to not think about what kind of specific instances they want. What they want is to know what their models need. Say, they know the SLA and then find a set of hybrid targets and instances that hit the SLA whenever they're also scaling, they're going to scale with more freedom, right? Instead of having to wait for AWS to give them more specific allocation for a specific instance. What if you could live with other types of hardware and scale up in a more free way, right? So that's another thing that we see customers, you know, like they need more freedom to be able to scale with whatever is available. >> Anna, you touched on this with the business model impact to that 6 million cost, if that goes out of control, there's a business model aspect and there's a technical operation aspect to the cost side too. You want to be mindful of riding the wave in a good way, but not getting over your skis. So that brings up the point around, you know, confidence, right? And teamwork. Because if you're in production, there's probably a team behind it. Talk about the team aspect of your customers. I mean, they're dedicated, they go put stuff into production, they're developers, there're data. What's in it for them? Are they getting better, are they in the beach, you know, reading the book. Are they, you know, are there easy street for them? What's the customer benefit to the teams? >> Yeah, absolutely. With just a few clicks of a button, you're in production, right? That's the dream. So yeah, I mean I think that, you know, we illustrated it before a little bit. I think the automated kind of benchmarking and optimization process, like when you think about the effort it takes to get that data by hand, which is what people are doing today, they just don't do it. So they're making decisions without the best information because it's, you know, there just isn't the bandwidth to get the information that they need to make the best decision and then know exactly how to deploy it. So I think it's actually bringing kind of a new insight and capability to these teams that they didn't have before. And then maybe another aspect on the team side is that it's making the hand-off of the models from the data science teams to the model deployment teams more seamless. So we have, you know, we have seen in the past that this kind of transition point is the place where there are a lot of hiccups, right? The data science team will give a model to the production team and it'll be too slow for the application or it'll be too expensive to run and it has to go back and be changed and kind of this loop. And so, you know, with the PyTorch profiler that Luis was talking about, and then also, you know, the other ways we do optimization that kind of prevents that hand-off problem from happening. >> Luis and Anna, you guys have a great company. Final couple minutes left. Talk about the company, the people there, what's the culture like, you know, if Intel has Moore's law, which is, you know, doubling the performance in few years, what's the culture like there? Is it, you know, more throughput, better pricing? Explain what's going on with the company and put a plug in. Luis, we'll start with you. >> Yeah, absolutely. I'm extremely proud of the team that we built here. You know, we have a people first culture, you know, very, very collaborative and folks, we all have a shared mission here of making AI more accessible and sustainable. We have a very diverse team in terms of backgrounds and life stories, you know, to do what we do here, we need a team that has expertise in software engineering, in machine learning, in computer architecture. Even though we don't build chips, we need to understand how they work, right? So, and then, you know, the fact that we have this, this very really, really varied set of backgrounds makes the environment, you know, it's say very exciting to learn more about, you know, assistance end-to-end. But also makes it for a very interesting, you know, work environment, right? So people have different backgrounds, different stories. Some of them went to grad school, others, you know, were in intelligence agencies and now are working here, you know. So we have a really interesting set of people and, you know, life is too short not to work with interesting humans. You know, that's something that I like to think about, you know. >> I'm sure your off-site meetings are a lot of fun, people talking about computer architectures, silicon advances, the next GPU, the big data models coming in. Anna, what's your take? What's the culture like? What's the company vibe and what are you guys looking to do? What's the customer success pattern? What's up? >> Yeah, absolutely. I mean, I, you know, second all of the great things that Luis just said about the team. I think one that I, an additional one that I'd really like to underscore is kind of this customer obsession, to use a term you all know well. And focus on the end users and really making the experiences that we're bringing to our user who are developers really, you know, useful and valuable for them. And so I think, you know, all of these tools that we're trying to put in the hands of users, the industry and the market is changing so rapidly that our products across the board, you know, all of the companies that, you know, are part of the showcase today, we're all evolving them so quickly and we can only do that kind of really hand in glove with our users. So that would be another thing I'd emphasize. >> I think the change dynamic, the power dynamics of this industry is just the beginning. I'm very bullish that this is going to be probably one of the biggest inflection points in history of the computer industry because of all the dynamics of the confluence of all the forces, which you mentioned some of them, I mean PC, you know, interoperability within internetworking and you got, you know, the web and then mobile. Now we have this, I mean, I wouldn't even put social media even in the close to this. Like, this is like, changes user experience, changes infrastructure. There's going to be massive accelerations in performance on the hardware side from AWS's of the world and cloud and you got the edge and more data. This is really what big data was going to look like. This is the beginning. Final question, what do you guys see going forward in the future? >> Well, it's undeniable that machine learning and AI models are becoming an integral part of an interesting application today, right? So, and the clear trends here are, you know, more and more competitional needs for these models because they're only getting more and more powerful. And then two, you know, seeing the complexity of the infrastructure where they run, you know, just considering the cloud, there's like a wide variety of choices there, right? So being able to live with that and making the most out of it in a way that does not require, you know, an impossible to find team is something that's pretty clear. So the need for automation, abstracting with the complexity is definitely here. And we are seeing this, you know, trends are that you also see models starting to move to the edge as well. So it's clear that we're seeing, we are going to live in a world where there's no large models living in the cloud. And then, you know, edge models that talk to these models in the cloud to form, you know, an end-to-end truly intelligent application. >> Anna? >> Yeah, I think, you know, our, Luis said it at the beginning. Our vision is to make AI sustainable and accessible. And I think as this technology just expands in every company and every team, that's going to happen kind of on its own. And we're here to help support that. And I think you can't do that without tools like those like OctoML. >> I think it's going to be an error of massive invention, creativity, a lot of the format heavy lifting is going to allow the talented people to automate their intellect. I mean, this is really kind of what we see going on. And Luis, thank you so much. Anna, thanks for coming on this segment. Thanks for coming on theCUBE and being part of the AWS Startup Showcase. I'm John Furrier, your host. Thanks for watching. (upbeat music)

>>Hey guys and girls, welcome back to Motor City, Lisa Martin here with John Furrier on the Cube's third day of coverage of Coon Cloud Native Con North America. John, we've had some great conversations over the last two and a half days. We've been talking about identity and security management as a critical need for enterprises within the cloud native space. We're gonna have another quick conversation >>On that. Yeah, we got a great segment coming up from someone who's been in the industry, a long time expert, running a great company. Now it's gonna be one of those pieces that fits into what we call super cloud. Others are calling cloud operating system. Some are calling just Cloud 2.0, 3.0. But there's definitely a major trend happening around how cloud is going Next generation. We've been covering it. So this segment should be >>Great. Let's unpack those trends. One of our alumni is back with us, O Rika Zi, co-founder and CEO of Aerio. Omri. Great to have you back on the >>Cube. Thank you. Great to be here. >>So identity move to the cloud, Access authorization did not talk to us about why you found it assertive, what you guys are doing and how you're flipping that script. >>Yeah, so back 15 years ago, I helped start Azure at Microsoft. You know, one of the first few folks that you know, really focused on enterprise services within the Azure family. And at the time I was working for the guy who ran all of Windows server and you know, active directory. He called it the linchpin workload for the Windows Server franchise, like big words. But what he meant was we had 95% market share and all of these new SAS applications like ServiceNow and you know, Workday and salesforce.com, they had to invent login and they had to invent access control. And so we were like, well, we're gonna lose it unless we figure out how to replace active directory. And that's how Azure Active Directory was born. And the first thing that we had to do as an industry was fix identity, right? Yeah. So, you know, we worked on things like oof Two and Open, Id Connect and SAML and Jot as an industry and now 15 years later, no one has to go build login if you don't want to, right? You have companies like Odd Zero and Okta and one login Ping ID that solve that problem solve single sign-on, on the web. But access Control hasn't really moved forward at all in the last 15 years. And so my co-founder and I who were both involved in the early beginnings of Azure Active directory, wanted to go back to that problem. And that problem is even bigger than identity and it's far from >>Solved. Yeah, this is huge. I think, you know, self-service has been a developer thing that's, everyone knows developer productivity, we've all experienced click sign in with your LinkedIn or Twitter or Google or Apple handle. So that's single sign on check. Now the security conversation kicks in. If you look at with this no perimeter and cloud, now you've got multi-cloud or super cloud on the horizon. You've got all kinds of opportunities to innovate on the security paradigm. I think this is kind of where I'm hearing the most conversation around access control as well as operationally eliminating a lot of potential problems. So there's one clean up the siloed or fragmented access and two streamlined for security. What's your reaction to that? Do you agree? And if not, where, where am I missing that? >>Yeah, absolutely. If you look at the life of an IT pro, you know, back in the two thousands they had, you know, l d or active directory, they add in one place to configure groups and they'd map users to groups. And groups typically corresponded to roles and business applications. And it was clunky, but life was pretty simple. And now they live in dozens or hundreds of different admin consoles. So misconfigurations are rampant and over provisioning is a real problem. If you look at zero trust and the principle of lease privilege, you know, all these applications have these course grained permissions. And so when you have a breach, and it's not a matter of if, it's a matter of when you wanna limit the blast radius of you know what happened, and you can't do that unless you have fine grained access control. So all those, you know, all those reasons together are forcing us as an industry to come to terms with the fact that we really need to revisit access control and bring it to the age of cloud. >>You guys recently, just this week I saw the blog on Topaz. Congratulations. Thank you. Talk to us about what that is and some of the gaps that's gonna help sarto to fill for what's out there in the marketplace. >>Yeah, so right now there really isn't a way to go build fine grains policy based real time access control based on open source, right? We have the open policy agent, which is a great decision engine, but really optimized for infrastructure scenarios like Kubernetes admission control. And then on the other hand, you have this new, you know, generation of access control ideas. This model called relationship based access control that was popularized by Google Zanzibar system. So Zanzibar is how they do access control for Google Docs and Google Drive. If you've ever kind of looked at a Google Doc and you know you're a viewer or an owner or a commenter, Zanzibar is the system behind it. And so what we've done is we've married these two things together. We have a policy based system, OPPA based system, and at the same time we've brought together a directory, an embedded directory in Topaz that allows you to answer questions like, does this user have this permission on this object? And bringing it all together, making it open sources a real game changer from our perspective, real >>Game changer. That's good to hear. What are some of the key use cases that it's gonna help your customers address? >>So a lot of our customers really like the idea of policy based access management, but they don't know how to bring data to that decision engine. And so we basically have a, you know, a, a very opinionated way of how to model that data. So you import data out of your identity providers. So you connect us to Okta or oze or Azure, Azure Active directory. And so now you have the user data, you can define groups and then you can define, you know, your object hierarchy, your domain model. So let's say you have an applicant tracking system, you have nouns like job, you know, know job descriptions or candidates. And so you wanna model these things and you want to be able to say who has access to, you know, the candidates for this job, for example. Those are the kinds of rules that people can express really easily in Topaz and in assertive. >>What are some of the challenges that are happening right now that dissolve? What, what are you looking at to solve? Is it complexity, sprawl, logic problems? What's the main problem set you guys >>See? Yeah, so as organizations grow and they have more and more microservices, each one of these microservices does authorization differently. And so it's impossible to reason about the full surface area of, you know, permissions in your application. And more and more of these organizations are saying, You know what, we need a standard layer for this. So it's not just Google with Zanzibar, it's Intuit with Oddy, it's Carta with their own oddy system, it's Netflix, you know, it's Airbnb with heed. All of them are now talking about how they solve access control extracted into its own service to basically manage complexity and regain agility. The other thing is all about, you know, time to market and, and tco. >>So, so how do you work with those services? Do you replace them, you unify them? What is the approach that you're taking? >>So basically these organizations are saying, you know what? We want one access control service. We want all of our microservices to call that thing instead of having to roll out our own. And so we, you know, give you the guts for that service, right? Topaz is basically the way that you're gonna go implement an access control service without having to go build it the same way that you know, large companies like Airbnb or Google or, or a car to >>Have. What's the competition look like for you guys? I'm not really seeing a lot of competition out there. Are there competitors? Are there different approaches? What makes you different? >>Yeah, so I would say that, you know, the biggest competitor is roll your own. So a lot of these companies that find us, they say, We're sick and tired of investing 2, 3, 4 engineers, five engineers on this thing. You know, it's the gift that keeps on giving. We have to maintain this thing and so we can, we can use your solution at a fraction of the cost a, a fifth, a 10th of what it would cost us to maintain it locally. There are others like Sty for example, you know, they are in the space, but more in on the infrastructure side. So they solve the problem of Kubernetes submission control or things like that. So >>Rolling your own, there's a couple problems there. One is do they get all the corner cases who built a they still, it's a company. Exactly. It's heavy lifting, it's undifferentiated, you just gotta check the box. So probably will be not optimized. >>That's right. As Bezo says, only focus on the things that make your beer taste better. And access control is one of those things. It's part of your security, you know, posture, it's a critical thing to get right, but you know, I wanna work on access control, said no developer ever, right? So it's kind of like this boring, you know, like back office thing that you need to do. And so we give you the mechanisms to be able to build it securely and robustly. >>Do you have a, a customer story example that is one of your go-tos that really highlights how you're improving developer productivity? >>Yeah, so we have a couple of them actually. So there's the largest third party B2B marketplace in the us. Free retail. Instead of building their own, they actually brought in aer. And what they wanted to do with AER was be the authorization layer for both their externally facing applications as well as their internal apps. So basically every one of their applications now hooks up to AER to do authorization. They define users and groups and roles and permissions in one place and then every application can actually plug into that instead of having to roll out their own. >>I'd like to switch gears if you don't mind. I get first of all, great update on the company and progress. I'd like to get your thoughts on the cloud computing market. Obviously you were your legendary position, Azure, I mean look at the, look at the progress over the past few years. Just been spectacular from Microsoft and you set the table there. Amazon web service is still, you know, thundering away even though earnings came out, the market's kind of soft still. You know, you see the cloud hyperscalers just continuing to differentiate from software to chips. Yep. Across the board. So the hyperscalers kicking ass taking names, doing great Microsoft right up there. What's the future? Cuz you now have the conversation where, okay, we're calling it super cloud, somebody calling multi-cloud, somebody calling it distributed computing, whatever you wanna call it. The old is now new again, it just looks different as cloud becomes now the next computer industry, >>You got an operating system, you got applications, you got hardware, I mean it's all kind of playing out just on a massive global scale, but you got regions, you got all kinds of connected systems edge. What's your vision on how this plays out? Because things are starting to fall into place. Web assembly to me just points to, you know, app servers are coming back, middleware, Kubernetes containers, VMs are gonna still be there. So you got the progression. What's your, what's your take on this? How would you share, share your thoughts to a friend or the industry, the audience? So what's going on? What's, what's happening right now? What's, what's going on? >>Yeah, it's funny because you know, I remember doing this quite a few years ago with you probably in, you know, 2015 and we were talking about, back then we called it hybrid cloud, right? And it was a vision, but it is actually what's going on. It just took longer for it to get here, right? So back then, you know, the big debate was public cloud or private cloud and you know, back when we were, you know, talking about these ideas, you know, we said, well you know, some applications will always stay on-prem and some applications will move to the cloud. I was just talking to a big bank and they basically said, look, our stated objective now is to move everything we can to the public cloud and we still have a large private cloud investment that will never go away. And so now we have essentially this big operating system that can, you know, abstract all of this stuff. So we have developer platforms that can, you know, sit on top of all these different pieces of infrastructure and you know, kind of based on policy decide where these applications are gonna be scheduled. So, you know, the >>Operating schedule shows like an operating system function. >>Exactly. I mean like we now, we used to have schedulers for one CPU or you know, one box, then we had schedulers for, you know, kind of like a whole cluster and now we have schedulers across the world. >>Yeah. My final question before we kind of get run outta time is what's your thoughts on web assembly? Cuz that's getting a lot of hype here again to kind of look at this next evolution again that's lighter weight kind of feels like an app server kind of direction. What's your, what's your, it's hyped up now, what's your take on that? >>Yeah, it's interesting. I mean back, you know, what's, what's old is new again, right? So, you know, I remember back in the late nineties we got really excited about, you know, JVMs and you know, this notion of right once run anywhere and yeah, you know, I would say that web assembly provides a pretty exciting, you know, window into that where you can take the, you know, sandboxing technology from the JavaScript world, from the browser essentially. And you can, you know, compile an application down to web assembly and have it real, really truly portable. So, you know, we see for example, policies in our world, you know, with opa, one of the hottest things is to take these policies and can compile them to web assemblies so you can actually execute them at the edge, you know, wherever it is that you have a web assembly runtime. >>And so, you know, I was just talking to Scott over at Docker and you know, they're excited about kind of bringing Docker packaging, OCI packaging to web assemblies. So we're gonna see a convergence of all these technologies right now. They're kind of each, each of our, each of them are in a silo, but you know, like we'll see a lot of the patterns, like for example, OCI is gonna become the packaging format for web assemblies as it is becoming the packaging format for policies. So we did the same thing. We basically said, you know what, we want these policies to be packaged as OCI assembly so that you can sign them with cosign and bring the entire ecosystem of tools to bear on OCI packages. So convergence is I think what >>We're, and love, I love your attitude too because it's the open source community and the developers who are actually voting on the quote defacto standard. Yes. You know, if it doesn't work, right, know people know about it. Exactly. It's actually a great new production system. >>So great momentum going on to the press released earlier this week, clearly filling the gaps there that, that you and your, your co-founder saw a long time ago. What's next for the assertive business? Are you hiring? What's going on there? >>Yeah, we are really excited about launching commercially at the end of this year. So one of the things that we were, we wanted to do that we had a promise around and we delivered on our promise was open sourcing our edge authorizer. That was a huge thing for us. And we've now completed, you know, pretty much all the big pieces for AER and now it's time to commercially launch launch. We already have customers in production, you know, design partners, and you know, next year is gonna be the year to really drive commercialization. >>All right. We will be watching this space ery. Thank you so much for joining John and me on the keep. Great to have you back on the program. >>Thank you so much. It was a pleasure. >>Our pleasure as well For our guest and John Furrier, I'm Lisa Martin, you're watching The Cube Live. Michelle floor of Con Cloud Native Con 22. This is day three of our coverage. We will be back with more coverage after a short break. See that.

>>Hello, everyone. Welcome to the cubes presentation of the 80 startup showcase marketing technology, emerging cloud scale customer experiences. This is season two, episode three of the ongoing series covering the exciting startups from the, a AWS ecosystem to talk about all the top trends and also featuring the key customers. I'm your host, John ER, today we're joined by Louis Fernando, Denise vice president of peak pay social and John Kim, the CEO of Sandberg to learn about the future of what's going on in fostering deeper customer relationships. Gentlemen, thanks for joining us in the cube showcase, >>Excited to be here. >>So John talk about Sendbird real quick set the table for us. What you guys do, you got a customer here to highlight some of the key things you're doing with customers, the value proposition what's Sendbird and what's the showcase about, >>Yeah, I'm really excited to be here. Uh, I'm John founder, C of Sandberg. So Sandberg is the worst leading conversations platform for mobile applications. We can power user to user conversations in mobile applications, as well as the brand to user conversations such as marketing sales and support. So, uh, today we power over quarter billion users on a monthly basis. Uh, we have, you know, through over 300 employees across seven different countries around the world, we work with some of the world's leading, uh, uh, customers such as big pay that we are going to showcase today, along with other, uh, wonderful customers like DoorDash, Reddit, <inaudible> sports and so forth. We have collectively raised over 200 million in funding. Um, so that's kind of where we are today. >>Well, it's always great to have, uh, one great success. Uh, good funding, more important is the customers. And I love showcases where the customers do the talking, because that means you've got some success stories. Louise, talk about, um, are you happy customer? What's it like working with Sandberg? Give us the, give us the scoop. >>So sandbar is being a great partner with us. So pick pay is a Brazilian payment app. We're at a FinTech here with more than 30 million active users using everyday pick pay to pay everything. So the, the, the majority of the payments are between peers, between people. So sandbar is, is helping us to improve a lot this journey to make it more pleasant between every everyone who are using big, big. So we are here, let's talk and it's a >>Pleasure. Yeah, it's awesome. Well, I great to have you guys on great, great relationship. And one of the things we've been talking about on the cube, if the folks watching that know our audience, no we've been banging the, the drum hard on this new world and this new patterns of user expectations and building relationships in this new digital world is not about the old way, the old MarTech way. There are new new use cases, new expectations by the consumers, John, that are, that are bringing up new opportunities, but also expectations. It's not about, I mean, I mean, if someone's using discord, for example, cuz they're gamers, they're done discord. If they want to communicate with, with slack, they, I do slack, SMS, kind of old hat. You got WhatsApp, you've got all these now peer to peer organic connections, multiple channels. This is all the new world. What's your vision on this new relationship building digital communication world. >>Yeah. So I, I think you brought a really good point there. One of the most frequently used applications in the world today are messaging applications across any countries, any region, any culture, if you look at the most frequently used and most longest used applications are usually some form of a, a messaging application. Now the end users or the customers in the world are so used to using, uh, uh, such a, you know, frictionless ver very responsive, modern experience on those messaging applications. What we want to help with the business around the world, the 99.9% of the business around the world don't have those really te knowledge or user experience expertise in messaging. So we want to help our businesses, help our customers be able to harness the power of modern messaging capabilities and then be able to embed it in their own business so that they can retain their users on their platform, engage with them in the con context that their, uh, what their business is about so that they can not only, uh, control or provide a better user experience, but also be able to, uh, understand their users better, uh, understand what they're doing on their businesses, be able to own and, uh, control the data in a more secure and safe way. >>So really it's uh, we're like the Robin hood of the world trying to keep superpower yeah. Back to the businesses. >>Yeah. Deal from the rich idea, the messaging scale. Bring that to everybody else. I love that. Uh, and you got kind of this double int Robin hood kind of new for the new generation finance. This is about taking the advantage of scalable platforms, monopolies, right. And giving the entrepreneur an opportunity to have that same capability feature, rich Louise PPE. You guys used Sendbird together. You have to level up, you gotta compete with those big monopolies to pride, scalable conversations. Okay. How did you engage this? What was your success path look? What was it look like? >>Yeah. When we look to this majority, the bigger chat apps that we have nowadays in the market, we are looking to them and then Brazilians are using for their daily course, but Brazilians are paying every day millions and millions of payments. And these chat apps are not, uh, able to, to, to deal with these payments. So what we are doing here is that, uh, providing a solution where every conversation that are going to happen before, during, or after a payment between the, the people, they would, uh, uh, have a nice platform that could afford all, all of their emotions and discussions that they have to do before or after the payment. So we are putting together the chat platform and we with the payment platform. So that's, that's what we are doing now. >>Okay. So just so I get this right. You're using Sandberg essentially integrated your mobile payment experience. Okay. Which is your app you're Sandberg to bring that scalability into the, into the social app application into the app itself. Is that right? >>Yes. Perfect. Integrated with the payment journey. So everybody who is going to pay, they need to find the one, the, the one they want to pay and then they can chat and conclude the payment through the platform. Yeah. I >>Mean, why not have it right there at point of, uh, transaction. Right. Um, why did you, um, decide to, um, to use conversations in your mobile wallet? Just curious. >>So it's important to say that we were born social. We born in 2012. So when our main main product was peer to peer payments, so everybody were sending money to a friend requesting or charging their family. So a service provider. And once we, we started as a social platform in that period. In that moment, we are just focusing in likes comments and like public interactions and the word become more private. And as soon we under understood this situation, we decided to move from a public feed to a private, to a private interaction. So that's, uh, that then the, the conversational space was the solution for that moving from a public interaction to a private interaction. So between the peers, which are involved in the, the transaction. So that's why we are providing the chat solution integrated with payments. >>That's a great call. John, just give some context here, again, for the folks watching this is now expected, this integrated experience. What's your, how would you talk to folks out there? I mean, first of all, I, I, I see it clearly, you've got an app, you gotta have all this integration and you need it scaling to reach features. Talk about your view on that. Is that the, is that what's happening here? What's, what's the real dynamic here. What's the, the big trend. >>Yeah. One thing that's, uh, super interesting about, uh, uh, like messaging experience in general, if you think about any kind of conversations that's happening, uh, digitally between human beings, more and more conversations, just like what Louis mentioned earlier are happening between in a private setting, even on applications, whether it be slack or other forms of communication, uh, more hap uh, more conversations happen through either one-on-one conversations or in a private small group settings. And because people feel more secure, uh, safe to have, uh, more intimate conversations. So even when you're making transactions is more, you know, there's a higher trust and, uh, people tend to engage, uh, far better on platforms through these kind of private conversations. That's where we kind of come in, whether it be, you want to set a one-on-one conversations or with a group conversation. And then ultimately if you want to take it public in a large group setting, you can also support, you know, thousands, if not, you know, hundreds of thousands of people, uh, engaging a public forum as well. So all of those capabilities can be implemented using something Ember, but again, the world is, uh, right now the businesses and how the user are, are interacting with this with each other is all happening through digital conversations. And we're seeing more and more of that happening, uh, throughout the life cycle of our company. >>Yeah, just as a sidebar, I was just talking to a venture in San Francisco the other day, and we're talking about the future of security and SAS and cloud scale. And, you know, the conversation went to more of, is it SAS? Is it platform as a service Louis? I wanna get your thoughts because, you know, you're seeing more and more needs for customization, low code, no code. You're seeing these trends. You gotta built in security. So, you know, the different, the old SAS model was softwares a service, but now that's everything in the cloud is softwares a service. So, but you need to have that platform kind of vibe for scale customization, maybe some developer integration, cuz apps are becoming the, the touchpoint. So can you walk us through what your vision was when you decided to integrate, chat into your app and how did you see that chat, changing the customer experience for payments and across your user journey? Cause, I mean, it's obvious now looking at it, but it might not have been for some. What was your, what was your vision? And when you had to do that, >>When you looked to Brazilian reality, we can see those in, uh, payment apps. All of them are focused on the transactional moment. And as soon as we started to think, how could be, how could our journey be better, more pleased than the others and make people want to be here and to use and to open our app every day is just about making the interaction with the peers easier, even with a merchant or even with my friend. So the main point that our first step was just to connect all, all the users between themselves to payments. The second step we are providing now is using the chat platform, the send bird platform as a platform for peak pay. So we are going to provide more best information. We're going to provide a better customer experience through the support and everything. So, um, this, this, this interaction or this connection, this partnership with Sandberg are going to unlock a new level of service for our users. And at the same time, a much more pleasant or a more pleasant journey for them while they are using the, the app for a, a simple payment, or if they are going to look for a group objective or maybe a crowdfund in the future or a group to decide, or just to pay something. So we are then locking a new level of interaction between the peers between the people and the users that are, that are involved into this, this payment or this simple transaction, we are making it more conversational. >>Yeah. You're making the application more valuable. We're gonna get to that in the next segment about, you know, the future of apps one and done, you see a lot of sports apps, oh, this big tournament, you know, and then you use it and then you never use it again until next year. You know, you have very time specific apps, but now you guys are smart to kind of build this in, but I gotta ask you a question because a lot of developers and companies out there always have this buy versus build decision. Why did you decide to use Sendbird versus building it in house? It's always kind of like the big trade off. >>Yeah. First of all, it will take a long, long time for us to achieve a major platform as Sandberg. And we are not a chat platform. So we are going to use this social interaction to improve the payment platform that we have. So when we look to the market and we found Sandberg, then we thought, okay, this guys, they are a real platform. And through the conversations, we are seeing that they are roadmap working in synergy with our roadmap. And then we can, we could start to deliver value to our, to our users in a fastest way. Could you imagine it spending 2, 3, 4 years to develop something like sand? And even when we achieve this point, probably our solution will be, would be weaker than, than Sandberg. So it was like no brainer to do that. Yeah. Because we want to improve the payment journey, not to do a chat, only a chat platform. So that's why we are working together to prove it's >>Really, you start to see these plugins, these, you know, look at Stripe for payments, for instance, right. And here in the success they've had, you know, people want to plug in for services. So John, I gotta ask you about, um, about the, the complexity that goes into it. The trust required that they have for you, you have to do this heavy lifting, you gotta provide the confidence that your service is gonna have to scale the compliance. Talk about that. What do you guys do under the covers that make this easy again, great business model, heavy lifting done by you. Seamless integration provide that value. That's why business is good, but there's a lot going on share what's happening under the, under the covers. >>Yeah. Um, before going to like the technical, like intricacy of what we do just to provide a little bit of background context on why we even started this business is we, uh, this is my second startup. My first company was a gaming company. We had built like chat three, four times just for our own game. So we were basically, we felt like we were reinventing the wheel. And then we actually went on a buyer's journey when we were building a social application, uh, uh, for, for, uh, uh, building our own community. We tried to actually be a buyer to see if we can actually find a solution. We want to use turns out that there weren't a lot of like sophisticated, you know, top notch, modern, uh, uh, chat experience that we can build using some other third party solutions. So we had to build all of that ourselves, which became the foundation for se today. >>And what we realized is that for most companies like using a building, the most sophisticated chat is probably not going to be their highest priority in case a pick pay will be, you know, financial transactions and all the other business that can be built on and hosted by platform like pick pay. But, you know, building the most topnotch chat experience would be a priority for a company like let's say WhatsApp or, or telegram, but it will probably not be the priority for, you know, major gaming companies, food delivery companies, finance companies, chat is not the highest priority. That's kind of where we come in, cuz chat is the highest priority for us. And we also have a privilege of working with some of the other, uh, world industry, uh, industry leaders. So by, uh, having this collective experience, working with the industry leaders, we get, uh, uh, technological superiority, being able to, uh, scale to, you know, hundreds of millions of users on a monthly basis. Also the security and the compliances by working with some of the largest commercial banks on some of the largest FinTech applications across the globe. So we have, you know, security, compliances, all the industry, best practices that are built in and all the new topnotch user experience that we are, uh, building with other customers can be also be, uh, utilized by a customer like pick pay. So you get this collective almost like evolutionary benefit. Yeah. By, uh, working with a company like us, >>You get a lot of economies of scale. Could you mind just sharing the URL for the company? So folks watching can go get, do a deep dive. Cause I'm you guys got a lot of, lot of, um, certifications under the covers, a lot of things you guys do. So you mind just sharing URL real quick. >>Yeah. So our company, uh, you can find everything about our company on sandberg.com like carrot pigeon. So, uh, you're sending a bird to send a message. So, uh, yeah. send.com >>All so let's get it to the application, cuz this is really interesting cuz Chad is table stakes now, but things are evolving beyond Chad. You gotta integrate that user experience. It's data. Now you gotta have scale. I mean, you know, people who wanna roll their own chat will find out there's a lot of client side and backend scale issues. Right. You can have a tsunami river like on Twitch, you know, you chat. I mean that, could you got client side issues, data scale. <laugh> right. You got backend. Um, Louis, talk about that dynamic because you know, as you start to scale, you want to rely on that. Talk about this dynamic, how apps now are integrating all these new features. So is it, are apps gonna go like more multifunctional? Do you see apps one and done? What's the, how do you guys see this app world playing out and where does, does the Sendbird fit in? And >>Just, just let me know better John, about the performance or about the, just, just let me >>Oh, slow with performance. Uh, performance is huge, right? You gotta have no one wants to have lag on, on chat. >>Okay. So, um, big pay when we look to the payments have millions, thousands of, of, of payments happen happening every second. So what we are doing now is moving all the payments through a conversation. So it always happened inside the conversation. So since from the first moment, um, every second counts to convert this client. And since from the first moment we never saw in, on Sandberg, any issue about that. And even when we have a question or something that we need to improve the team we're working together. So that that's, those are the points that are making us to work together and to make things going pretty fast. When we look to the users who are going to use chat, they are, their intention is three times better than the users who are not using payments through the chat. They are average. Average spent is three times higher too. >>So they, they are making more connections. They are chatting with their friends. They are friends are here. So the network effect is stronger. So if they're going to pay and they need to wait one more second, two seconds to conclude the payment, probably they will not go into choose paying through the, again, they will use only the wallet, only the code, only the Alliance of the user. So that's is so important for us to perform really, really fast. And then this is what we are finding. And this is what is happening with the integration with Sandberg. >>And what's interesting is, is that the by build chat with conversation, we just had a minute ago kind of plays in here. You get the benefits of Sandberg, but now your transactional fidelity is in the chat <laugh> that you don't build that you rely on them on. So again, that's an interesting dynamic. This is the future of apps, John, this is where it matters. The engagement. This is what you talk about is the new, the new digital experience who would've thought that five, 10 years ago. I mean, chat was just like, Hey, what's going around direct message. Now it's integral part of the app. What's your reading. >>Yeah. I mean, we're seeing that across, uh, uh, to Lewis's point, not just transactions, but like marketing messages are now being sent through chat. So the marketing is no longer just about like giving discount calls, but you can actually reengage with the brand. Uh, also support is becoming more real time through chat. So you're actually building a relationship. The support agents have a better context about the previous conversations and the transactions, the sales conversations, even like building, uh, building alerts, notification, all those things are now, uh, happening through conversations. And that's a better way for customers to engage with the brand cuz you actually, you're actually building a better relationship and also, uh, being able to trust the brand more because there is a channel for you to communicate and, and, and be seen and be heard, uh, by the brand. So we do believe that that's the future of the business and how more and more, uh, brands will be building relationships with their customers. >>Yeah. I love, I love your business model. I think it's really critical. And I think that stickiness is a real, uh, call out point there and the brand, the co-branding and the branding capability, but also really quickly in the last minute we have John and Luis, if you don't mind talking about security, I mean, I can't go a day now without getting an SMS scam, uh, text, uh, you seeing it now on WhatsApp. I mean, I don't even use telegram anymore. I mean, come on. So like, like this is now a problem. The old way has been infiltrated with spam and security issues. Security has to be there. The trust and security real quick, John, we'll start with you and we all Louis go, go ahead. >>No, no. Just, just to, to say how important is that we are not only a chatting platform. We are a payment platform, so we have money now, the transaction. So here in Brazil, we have all this safe, the, the, the layers, the security layers that we have in, on our app. And then we have the security layers provided from Sandburg. So, and when we look to the features, Sandberg are providing to us a lot of features that help users to feel safer like per refined profiles, like announcements, where it's a profile from peak pay, where the users can recognize. So this is peak pay talking with me. It's not a user trying to pass, trying to use big Bay's name to talk with me. So these issues is something that we are really, really, we really care about here because we are not only a chat platform. As I said before, we are a payment platform. We are a FinTech, we're at a digital bank. So we need to take care a lot and we don't have any complaint about it because Sandberg understood it. And then they, they, they are providing since the first moment with the perfect solutions and the user interface to make it simpler for the users to recognize that we speak, pay who is chatting with them, not a user with, with bad, bad intentions. >>Great, great insight, Louis. Thanks for sharing that, John really appreciate you guys coming on. Great showcase. Real final word. John will give you the final word folks watching out there. How do they engage with Sendbird? I want to integrate, I want to use your chat service. What do I do? Do I have to connect in as it managed service is the line of code. What do I do to get Sendbird? >>Yeah. So if you're a developer building a mobile application, simply come visit our website, we have a open documentation and SDK you can download and simply plug into your application. You can have a chat experience up and running matter of minutes, if not ours using our UI kit. So we want to make it as easy as possible for all the builders in the world to be able to harness the superpower of digital conversations. >>All right, great. Congratulations, John, on your success and all the growth and Louis, thanks for coming in, sharing the customer perspective and great insight. Thanks for coming on the showcase. Really appreciate it. Thanks for your time. >>Yeah. Thank you for having me. >>Okay. The a of us startup showcase season two, episode three here I'm John for your host. Thanks for watching.

>> Narrator: theCUBE presents KubeCon, and CloudNativeCon Europe, 2022, brought to you by Red Hat, the Cloud Native Computing Foundation, and its ecosystem partners. >> Welcome to Valencia, Spain and KubeCon, CloudNativeCon Europe, 2022. I'm Keith Townsend, and we're continuing the conversation with builders, startups, large enterprise, customers, small customers, the whole community. Just got a interesting stat earlier in the day, 7.1 million community members in the CNCF foundation, and we're been interacting with 7,500 of them. But we're bringing the signal, separating the signal from the noise. We have a Kube alum who's been on both sides of the table, Omri Gazitt co-founder and CEO of Aserto. Welcome to the show. >> Thank you so much, Keith. >> So identity management, you know it's, it's critical need to the enterprise cloud native but there's plenty of solutions on the market, what unique problem are you solving you know how are you solving the problem in a unique way that we don't go to some of the big named vendors in this space? >> Yeah, we, my co-founder and I, were veterans of large clouds. We helped start Azure at Microsoft. We in fact helped build what became Azure Active Directory and those solutions entirely focus on one part, the "I" part, the identity part of the problem. They completely ignore the access management part and you could argue that is a larger problem and it is far from solved. So we completely agree. Identity management, a problem that's been solved over the last 15 years and solved well by great companies like Microsoft and Okta and Auth0. And we're best friends with them. We basically pick up where they leave off. We do the access management part. >> So the access management part, what specifically, what what am I getting when I engage with your team and your product? >> Yep. So basically I, authentication is all about proving that you are, who you say you are through a password or something else, you know, biometric. And that part is done. We basically pick up where that leaves off. So once you know who you are, once you've proven to a system that you are Keith. Now, what can Keith do? What roles, what permissions, , what operations can Keith perform on what resources? That's a harder problem. And that's the problem that we focus on. So for example, if you have a SaaS app - let's say you're building, you know an applicant tracking system and you Keith are an owner of some job descriptions and you have some candidates, but  somebody else has a different set of candidates and an admin, maybe has visibility at everything. How do you build that system? That actually is a pretty hard problem. And how do you build it to enterprise grade? That's where we come in. We basically have an end-to-end solution that gives you cloud native, end-to-end authorization that's built to enterprise grade. >> So when I think of this capability, I can't help but to think of AWS IAM and I'm in AWS IAM, I get my security role, and now I can assign to an EC2 instance, the ability to access some other AWS service or identity. So role based identity - are you giving me that type of capability? >> For everything else. So AWS IAM for AWS resources right? Google IAM for Google Resources. Azure has a similar system but they're all infrastructure focused. And what we're trying to do is bring that to your domain specific resources, right? So you, as an application builder, you have the things that correspond  you're not doing VMs, you're not doing storage arrays, you're not doing networks. You have higher level constructs, right. You know, like I said, if you're building Lever or Greenhouse, you have candidates and jobs and reports and things like that. So we basically allow you to create this fine grained access control, but for your own objects. >> So where's the boundaries? Let's say that I have a container or microservice that is a service and it has a role, it has an identity on my network. And there is a cloud based service, let's say a, a cloud SQL. And I want to do authentication across the two or can I only have the boundaries within my private infrastructure or does that boundary extend to the public cloud as well? >> It extends everywhere, right. So basically, you know, if you think about all the different hops here, you know, Zero Trust is the, the rage, right? And that encourages defense in depth. So you have an access proxy that does some type of authorization. Then you have an API Gateway that has a little bit more context, a little bit more authorization. For us we live inside of the application. So the application calls us, we give you a sidecar, you deploy it right next to your application. It gives you, you know, sub-millisecond response time, a hundred percent availability, all the authorization decisions are done with full context about who the user is and what resource they're trying to access. And so our sidecar will give you a response back, allow or deny, and then downstream from us, you could basically talk to another microservice. And at that point you're doing machine identities, right? So you may have a different authorization policy for those, only you know these particular services, are allowed to talk to these other services. And so we solve both the, you know authorization for machine identities as well as authorization for human identities. >> All right Omri are you ready for Q Clock? >> I sure am! >> Oh, I like the energy. >> Bring it on. >> You know, there have been many before you, they have failed the test. >> All right. I mean, they brought, they've brought the energy. You have the energy but do you have the ability to survive the clock? >> I'm going to do my best. >> So I'm going to say start the clock. I haven't said, said start cube clock yet, but when I say it, you have 60 seconds. There's no start overs. There's no repeats. The pressure's on, you ready? >> All right. I'm ready. >> Ready? Start Cube Clock. >> All right. If you are a VP of Engineering or a CTO or run a security or engineering organization what are you doing for roles and permissions? You're building it on your own, right? >> Tough times never last, tough people always do, and you're, you're delaying, you're letting me break you up. >> All right, I'm not going to let you break me up. Great. So you don't want to build it yourself. You don't want to build it yourself. Why would you spend engineering time? Why would you spend, you know, the- >> You deserve a seat at the table. >> No but look, why would you ever spend your time building something that is not differentiating your application? Instead use something like Aserto, just dear God use something, use a developer API. Don't build it yourself because what are you doing? You're reinventing the wheel, you know. You want to get out of the business of reinventing the wheel. >> Crawl before you walk. (Omri laughs) >> You think so? I think, I think you have to go you know, make sure that you spend your engineering resources on the things that matter and the things that matter are. >> Time up. >> Yep. >> You know what? You threw three great curve balls and struck me out. Great job. (Omri laughs) You, you, you just knocked it out the park. Great job Omri, I appreciate you coming in, stopping by, sharing your company's journey about authorization and authorization services and getting kind of this cloud capability, the cloud native. >> I appreciate your time as well Keith, always a pleasure. >> From Valencia Spain, I'm Keith Townsend, and you're watching theCUBE, the leader in high tech coverage. (soft instrumental music)

>>Okay, welcome back everyone. Cube's coverage here. Live on the floor at AWS summit, 2022, an in person event in San Francisco. Of course, AWS summit, 2022 in New York city is coming up this summer. The cube will be there as well. Make sure you check us out then too, but we day two of coverage had a great guest here. I Han VP of developer relations, Mongo DB, formally of AWS. We've been known each other for a long time doing, uh, developer relations at Mongo DB. Welcome to the queue. Good to see >>You. Thank to be here. Thanks for inviting me, John. It's great >>To, so Mongo DB is, um, first of all, stocks' doing really well right now. Businesswise is good, but I still think it's undervalue. A lot of people think is, is a lot more going huge success with Atlas. So congratulations to the team over there. Um, what's the update? What's the relationship withs, you know, guys have been great partners for years. What's the new thing. Yeah. >>So MongoDB Atlas obviously runs on several different major cloud providers, but AWS is the largest partner that we work with in the public cloud. So the majority of our Atlas workloads for our customers are running on the AWS platform. And just earlier this year, we announced a new strategic collaboration agreement with AWS. That's gonna further strengthen and deepen that partnership that we have with them. >>What's the main product value right now on the scale on, on Atlas, what's the drive in the revenue momentum. >>So, I mean, you know, there's a huge trend in the industry towards cloud managed databases, right? You look back 10, 15 years ago when we first met, most customers were only and operating their own data infrastructure, either running it in their own data centers, or maybe if they were really early using the primitives that cloud providers like AWS offered to run their databases in the cloud when Amazon launched RDS back in 2009, I think it was, we started to see this trend towards cloud managed databases. We followed that with our own Atlas offering back in 2016. And as Andy jazzy from AWS would say very often it's offloading that UND differentiated, heavy lifting, allowing developers to focus on building applications. They don't have to win and operate the data infrastructure. We do it for them, and that has proven incredibly popular amongst our customers. You know, Atlas route right now is growing at 50, sorry, 85% car year on year growth. >>You know, um, I've been following MongoDB for a long, long time. I mean, going back to the lamp stack days, you know, and you think about what Mongo has done as a product because of the developer traction, you know, Mongo can't do this, just keeps getting better every year. And, and the, I think the stickiness with developers is a real big part of that. Can you your view there cuz you're in VE relations. I mean, developers all love Mongo. They're teaching in school. People are picking up a side hustles, they're coding on it, using it all everywhere. I mean it's well known. >>There's a few different reasons for that. I think the main one is the, the document orientated model that we use, the document data models that are used by Mongo DB, just a net way for developers to work with data. And then, uh, we've invested in creating 16 first party drivers that allow developers using various different programming languages, whether that's JavaScript or Python or rust to integrate MongoDB, natively and idiomatic with their software. So it's very, very easy for a developer to pick up MongoDB, grab one of these drivers from their package manager of their choice and then build applications that natively manipulate data inside MongoDB, whether that's MongoDB Atlas or our enterprise edition on their own premises. They get a very consistent and very easy to, I easy to use developer experience with our, with our platform. >>Talk about the go to market with AWS. You guys also have a tightly coupled relationships. There's been announcements there recently. Uh, what's changing most right now that people should pay attention to. Well, >>The first thing is there's a huge amount of technical integration between MongoDB and AWS services. And that's the basis for many of our customers choosing to run Mon Mongo DB on AWS. We're active in 23 AWS regions around the world. And there's many other integration points as well, like cryptographic protection of Mongo MongoDB, stored data using Amazon cryptographic services, for example, or building serverless applications with AWS Lambda and MongoDB servers. So there's a ton of technical integration. Yeah, but what we started to work on now is go to market integration with AWS as well. So you can buy Mongo DB Atlas through AWS's marketplace. You can use the payer, you go offering to pay for it with your AWS bill. And then we're collaborating with AWS on migrations and other joint go to market activities as well. That >>Means get incentives, the sales people at AWS. >>Of course our moreover I mean, it's just really easy for customers, really easy for developers to consume. Yeah, they don't need to contract with MongoDB. They can use their existing AWS contracting, their existing discounting relationships and pre purchasing arrangements with AWS to consume Atlas. >>It's the classic meet the customers where they >>Are exactly right. Meet the developer where they are and meet the customers where they are now with this new model as well. >>Yeah. I love marketplace. I think it's been great. You know, even with its kind of catalog and vibe, I think it's gonna get better and better, uh, over there teams doing good work. Um, and it's easy to consume. That's key. >>Yeah. Super easy. Reduce that friction and make it real easy for developers to adopt this. Right. >>Talk about some of the top customers that you guys share with AWS. What are some of the customers you guys have together and what the benefits of the >>Relationship joint references that we talk about? A lot, one of them is Shutterfly. So in the photographic products area, they built a eCommerce offering with MongoDB and AWS. The second is seven 11 with seven 11. We're doing a lot in the mobile space. So edge applications, we've got a feature in MongoDB Atlas that allows you to synchronize data with databases on mobile devices. Those can be phones point of sale devices or handheld devices that might be used in the parcel industry, for example. So seven 11 using us in that way. And then lastly with Pitney Bowes, we've got a big digital transformation project with Pitney Bowes where they've reimagined their, uh, postage and packaging services, delivering those to their customers, using MongoDB as a data store as well. >>I wanna get in some of the trends, you've got a great per you know, you know, Mongo from Amazon side and now you're there. Um, Mongo's, as you pointed out has, has been around for a long time. What are some of the stats? I mean, how many customers, how many countries? Well, it's pretty massive >>Mind. We've got almost quarter of a billion downloads today, 240 million MongoDB downloads since we launched the first product <laugh>, we've got 33,000 active customers that are using MongoDB Atlas today and we're running well over a million free tier clusters on MongoDB Atlas across all of the different providers where we operate the service as well. So these numbers are, you know, mind blowing in terms of scale. Uh, but of course at the core of that is operational excellence. Customers love Mongo DBS because they don't have to operate it themselves. They don't have to deal with fairly conditions. They don't have to deal with scaling. They don't have to deal with deployment. We all, we do all of those things as part of the service offering and customers get an endpoint that they can use with their applications to store and retrieve data reliably. And with consistently high perform, >>You know, it's, you know, in the media, something has to be dead. Someone's the death of the iPhone, the death of this, nothing that really dies. Mongo DB has always been kind of like talked about, well, it doesn't scale on the high end. Of course, Oracle was saying that, I mean, all the, all the big database vendors were kind of throwing darts at, at Mongo, uh, DB, uh, but it kept scaling. Atlas is a whole nother. Could you just unpack that a little bit more? Why is it so important? Because scale is just, I mean, it's, it's horizontal, but it's also performant. >>Exactly. Right. So with, uh, Mongo DB's document access model that I've described already, you break some of the limitations that exist inside traditional relational databases. So, you know, they don't scale well, if you've got high concurrent and see of data access, and they're typically difficult and expensive to scale because you need to share data. Once you grow beyond individual cluster nodes, and you'll know that all relational databases suffer from these same kinds of issues with non relational systems, no SQL systems like MongoDB, you have to think a little bit more about design at the beginning. So designing database to cater for the different access patterns that you have, but in return for that upfront preparation, that design work, you get near limitless, scalability and performance will scale nearly linearly with that scalability as well. So very much more high performance, very much more simplicity for the developer as their database gets larger and their cluster gets larger to support it. >>Yeah. You know, Amazon web service has always had an a and D jazz. We talk to us all the time, every interview I've done with Swami and Matt wood or whoever on the team and executive levels always said the same thing. There's not one database to rule the world, right? Obvious you're talking about Oracle, but even within AWS customers, they're mixing and matching databases based on use cases. So in distributed environment, they're all working together. So, um, you guys fit nicely into that. So how does that, >>I think strategy slightly counterbalances that so, you know, they would say use the specific tool for the specific task that you have in hand. Yeah. What we try to focus on is creating the simple and most effective developer experience that we can, and then supporting different facets to the product in order to allow developers to different use cases. A really good example with something like MongoDB Atlas search. So we integrated Apache Luine into MongoDB Atlas. Customers can very simply apply Apache Luine search indexes to the data that they've got in MongoDB. And then they can interact with that search data using the same drivers as an API. Yeah, yeah. That they use for regular queries. So if you want to run search on your application data, you don't need a separate open search or elastic search cluster, just turn on MongoDB Atlas search and use that, that search facet. So it's interest and we have other capabilities that it's >>Vertically integrating inside within Mongo, >>Correct? Yes. That's better. Yeah. With the guy, all of creating a really simple and effective developer experience, boosting developer productivity and helping developers get more done in less time. >>You mentioned serverless earlier, what's the serverless angle with AWS when Mongo, >>Is there one? Yeah. So we have MongoDB serverless currently in preview, uh, has the same kind of characteristics that you would, or the characteristics that you would expect from a serverless data base. So consumption based model, you provision an endpoint and that will scale elastically in accordance with your usage and you get billed by consumption units so much like the serverless paradigm that we've seen delivered by AWS, the same kind of model for Mongo, DB, Atlas serverless. >>What, what attracted you to Mongo DBS? So you knew them before, or you moved over there. Um, what's going on there? What's the culture like right now? Oh, >>The culture's great. I mean, it's a much smaller company than AWS where I was before, you know, it's a very large organization. And one of the things that I really like about MongoDB is, as I've said earlier, we can serve the different use cases that a developer might have with a single product, with different aspects, to it, different facets to it. Uh, and it's a really great conversation to have with a, with a developer, with a developer customer, to be able to offer one thing that helps them solve five or six different problems that have traditionally been quite hard for them to wrestle with quite difficult for them to, to deal with. And then we've got this focus on developer experience through these driver packages that we have as well. So it's really great to have as a developer relations pro have that kind of tooling in my kit bag that can help developers become more effective. >>Talk about tooling, cuz you know, I always have, uh, kind of moments where I waffle between more. I love platforms, tools are being over overused, too many tools tool with the tool, you know, the expressions, but we're seeing from developers, the ones that don't want to go into the hood, we serverless plays beautifully. Yep. They want tools. They do. And, and the, the new engineering developers that are coming outta college and universities, they love tools. >>Yeah. And we actually have quite a few of those built into Mongo, DB Atlas. So inside Mongo, DB Atlas, we've got things like an index optimizer, which will suggest the best way that you might index your data for better perform months inside MongoDB, running on Atlas, we've got a data Explorer, which is much like another product that we've got called MongoDB compass that allows you to see and manipulate the data that you have stored within your database natively within the Atlas interface. Uh, and then we also have, uh, whole slew of different metrics, monitoring capabilities built into the platform as well. So these are aspects of Atlas that developers can take advantage of. And then over on the client side, visual studio code plugins. Yeah. So you can manipulate and operate with data directly inside visual studio code, which is obviously the most common and popular IDE out there today, as well as integration with things like infrastructure is code tools. So we support cloud formation for provisioning. We have CDK constructs inside. Yeah. The CDK construct library. We also have a lot of customers using Terraform to provision MongoDB across both AWS and other providers. So having that developer tooling of course is super important. Yeah. Aspect of the developer experience, trying to >>Build out deploying observability is a big one. How does that fit in? Cuz you knew need to talk and not only measure everything here, but talk to other systems. >>Yeah. So we recently announced a provider for Prometheus and Grafana. So we can emit metrics into those providers. Obviously CNCF projects, very common and popular inside customers that are running on Kubernetes. We've got a Kubernetes operator for MongoDB Atlas as well. Good. So you can provision MongoDB Atlas from within Kubernetes as well as having our own native metrics directly within Atlas as well. >>Ian you're crushing it. You got all the, the data, the fingertips. Are you gonna be at Cuban this year? Uh, >>I will be, but some of our team members will definitely be there. >>Yeah, we'll be at, uh, EU. The cube will be there. Great. Thanks for coming on. Appreciate the insight final world. I'll give you the last word. Tell the audience what's going on. What's at Mongo DB. What should they pay attention to? If they've used Mongo and are aware of it? What's the update. What's >>The so you should come to MongoDB world actually in New York at the beginning of June, June 7th, the ninth in the Javit center in New York. Gonna have our own show there. And of course we'd love to see you there. >>Okay. Cube comes here day two of eight, us summit, 2020, this Cub I'm John for your host. Stay with us more. Our coverage as day two winds down. Great coverage.

>>Hey, welcome back everyone to the cubes coverage of eaters reinvent 2021. So our third day wall-to-wall coverage. I'm my coach, Dave Alonzo. He we're getting all the action two sets in person. It's also a virtual hybrid events with a lot of great content online, bringing you all the fresh voices, all the knowledge, all the news and all the action and got great guests here today. As your renderer, managing director of AWS is Europe, middle east, and Africa also known as EMIA. Welcome to the cube. Welcome, >>Welcome. Thanks for coming on. Lovely to be here. >>So Europe is really hot. Middle east Africa. Great growth. The VC culture in Europe specifically has been booming this year. A lot of great action. We've done many cube gigs out there talking to folks, uh, entrepreneurship, cloud, native growth, and then for us it's global. It's awesome. So first question got to ask you is, is you're new to AWS? What brought you here? >>Yeah, no, John, thank you so much. I've been here about three and a half months now, actually. Um, so what brought me here? Um, I have been in and around the tech world since I was a baby. Um, my father was an entrepreneur. I sold fax machines and microfilm equipment in my early days. And then my career has spanned technology in some form or the other. I was at EMC when we bought VMware. Uh, I was a Colt when we did a FinTech startup joined Schneider in my background, which is industrial tech. So I guess I'm a bit of a tech nerd, although I'm not an engineer, that's for sure. The other thing is I've spent a huge part of my career advising clients. And so while I was at McKinsey on business transformation and cloud keeps coming up, especially post pandemic, huge, huge, huge enabler, right of transformation. So when I got the call from AWS, I thought here's my opportunity to finally take what companies are wrestling with, bring together a pioneer in cloud with our enterprise and start-up and SMB clients connect those dots between business and technology and make things happen. So it real magic. So that's what brought me here. And I guess the only other thing to say is I'd heard a lot of other culture, customer mash, obsession, and leadership principles. >>That's why I'm here. It's been a great success. I got to ask you too, now that your new ostium McKinsey, even seeing the front lines, all the transformation, the pandemic has really forced everybody globally to move faster. Uh, things like connect were popular in EMEA. How, how is that going out? There's at the same kind of global pressure on the digital transformation with cloud? What are you seeing out there? >>I've been traveling since I joined, uh, around 10 of the countries already. So Ben planes, trains, automobiles, and what you definitely see is massive acceleration. And I think it's around reinvention of the business. So people are adopting cloud because it's obviously there's cost reasons. There's MNA reasons. There's really increasingly more about innovating. How do I innovate my business? How do I reinvent my business? So you see that constantly. Um, and whether you're a enterprise company or you're a startup, they're all adopting cloud in different, different ways. Um, I mean, I want to tell a core to stack because it's really interesting. And Adam mentioned this in his keynote five to 15% only of workloads have moved to the cloud. So there's a tremendous runway ahead of us. Um, and the three big things on people's minds helped me become a tech company. So it doesn't matter who you are, you're retail, whether you're life sciences or healthcare. You've probably heard about the Roche, uh, work that we're doing with Roche around accelerating R and D with data, or if you're a shoes Addie desk, how do you accelerate again, your personalized experiences? So it doesn't matter who you have helped me become a tech company, give me skills, digital skills, and then help me become a more sustainable company. Those are the three big things I'm thinking of. >>So a couple of things to unpack there. So think about it. Transformation. We still have a long way to go to your point, whatever 10, 15%, depending on which numbers you look at. We've been talking a lot in the cube about the next decade around business transformation, deeper business integration, and the four smarts to digital. And the woke us up to that, accelerated that as you say, so as you travel around to customers in AMEA, what are you hearing with regard to that? I mean, many customers maybe didn't have time to plan. Now they can sit back and take what they've learned. What are you hearing? >>Yeah. And it's, it's a little bit different in different places, right? So, I mean, if you start, if you look at, uh, you know, our businesses, for example, in France, if you look at our businesses in Iberia or Italy, a lot of them are now starting they're on the, at least on the enterprise front, they are now starting to adopt cloud. So they stepping back and thinking about their overall strategy, right? And then the way that they're doing it is actually they're using data as the first trigger point. And I think that makes it easier to migrate because if you, if you look at large enterprises and if you think of the big processes that they've got and all the mainframes and everything that they need to do, if you S if you look at it as one big block, it's too difficult. But when you think about data, you can actually start to aggregate all of your data into one area and then start to analyze and unpack that. >>So I think what I'm seeing for sure is in those countries, data is the first trigger. If you go out to Israel, well that you've got all, it's really start up nation as you know, right. And then we've got more of the digital natives and they want to, you know, absorb all of the innovation that we're throwing at them. And you've heard a lot here at reinvent on some of the things, whether it's digital twins or robotics, or frankly, even using 5g private network, we've just announcement. They are adopting innovation and really taking that in. So it really does differ, but I think the one big message I would leave you with is bringing industry solutions to business is critical. So rather than just talking it and technology, we've got to be able to bring some of what we've done. So for example, the Goldman Sachs financial cloud, bring that to the rest of financial services companies and the media, or if you take the work we're doing on industrials and IOT. So it's really about connecting what industry use cases with. >>What's interesting about the Goldman Dave and I were commenting. I think we coined the term, the story we wrote on Thursday last week, and then PIP was Sunday superclouds because you look at the rise of snowflake and Databricks and Goldman Sachs. You're going to start to see people building on AWS and building these super clouds because they are taking unique platform features of AWS and then sacrificing it for their needs, and then offering that as a service. So there's kind of a whole nother tier developing in the natural evolution of clouds. So the partners are on fire right now because the creativity, the market opportunities are there to be captured. So you're seeing this opportunity recognition, opportunity, capture vibe going on. And it's interesting. I'd love to get your thoughts on how you see that, because certainly the VCs are here in force. I did when I saw all the top Silicon valley VCs here, um, and some European VCs are all here. They're all seeing this. >>So pick up on two things you mentioned that I think absolutely spot on. We're absolutely seeing with our partners, this integration on our platform is so important. So we talk about the power of three, which is you bring a JSI partner, you bring an ISV partner, you bring AWS, you create that power of three and you take it to our customers. And it doesn't matter which industry we are. Our partner ecosystem is so rich. The Adam mentioned, we have a hundred thousand partners around the world, and then you integrate that with marketplace. Um, and the AWS marketplace just opens the world. We have about 325,000 active customers on marketplace. So sassiphy cation integration with our platform, bringing in the GSI and the NSIs. I think that's the real power to, to, to coming back to your point on transformation on the second one, the unicorns, you know, it's interesting. >>So UK France, um, Israel, Mia, I spent a lot of time, uh, recently in Dubai and you can see it happening there. Uh, Africa, Nigeria, South Africa, I mean all across those countries, you're saying huge amount of VC funding going in towards developers, towards startups to at scale-ups more and more of a, um, our startup clients, by the way, uh, are actually going IPO. You know, initially it used to be a lot of M and a and strategic acquisitions, but they have actually bigger aspirations and they're going IPO and we've seen them through from when they were seed or pre-seed all the way to now that they are unicorns. Right? So that there's just a tremendous amount happening in EMEA. Um, and we're fueling that, you know, you know, I mean, born in the cloud is easy, right? In terms of what AWS brings to the table. >>Well, I've been sacred for years. I always talked to Andy Jassy about this. Cause he's a big sports nut. When you bring like these stadiums to certain cities that rejuvenates and Amazon regions are bringing local rejuvenation around the digital economies. And what you see with the startup culture is the ecosystems around it. And Silicon valley thrives because you have all the service providers, you have all the fear of failure goes away. There's support systems. You start to see now with AWS as ecosystem, that same ecosystem support the robustness of it. So, you know, it's classic, rising tide floats all boats kind of vibe. So, I mean, we don't really have our narrative get down on this, but we're seeing this ecosystem kind of play going on. Yeah. >>And actually it's a real virtuous circle, or we call flywheel right within AWS because a startup wants to connect to an enterprise. An enterprise wants to connect to a startup, right? A lot of our ISV partners, by the way, were startups. Now they've graduated and they're like very large. So what we are, I see our role. And by the way, this is one of the other reasons I came here is I see our role to be able to be real facilitators of these ecosystems. Right. And, you know, we've got something that we kicked off in EMEA, which I'm really proud of called our EMEA startup loft accelerator. And we launched that a web summit. And the idea is to bring startups into our space virtually and physically and help them build and help them make those connections. So I think really, I really do think, and I enterprise clients are asking us all the time, right? Who do I need to involve if I'm thinking IOT, who do I need to involve if I want to do something with data. And that's what we do. Super connectors, >>John, you mentioned the, the Goldman deal. And I think it was Adam in his keynote was talking about our customers are asking us to teach them how to essentially build a Supercloud. I mean, our words. But so with your McKinsey background, I would imagine there's real opportunities there, especially as you, I hear you talk about IMIA going around to see customers. There must be a lot of, sort of non-digital businesses that are now transforming to digital. A lot of capital needs there, but maybe you could talk about sort of how you see that playing out over the next several years in your role and AWS's role in affecting that transfer. >>Yeah, no, absolutely. I mean, you're right actually. And I, you know, maybe I will, from my past experience pick up on something, you know, I was in the world of industry, uh, with Schneider as an example. And, you know, we did business through the channel. Um, and a lot of our channel was not digitized. You know, you had point of sale, electrical distributors, wholesalers, et cetera. I think all of those businesses during the pandemic realized that they had to go digital and online. Right. And so they started from having one fax machine in a store. Real literally I'm not kidding nothing else to actually having to go online and be able to do click and collect and various other things. And we were able with AWS, you can spin up in minutes, right. That sort of service, right. I love the fact that you have a credit card you can get onto our cloud. >>Right. That's the whole thing. And it's about instances. John Adam talked about instances, which I think is great. How do businesses transform? And again, I think it's about unpacking the problem, right? So what we do a lot is we sit down with our customers and we actually map a migration journey with them, right? We look across their core infrastructure. We look at their SAP systems. For example, we look at what's happening in the various businesses, their e-commerce systems, that customer life cycle value management systems. I think you've got to go business by business by business use case by use case, by use case, and then help our technology enable that use case to actually digitize. And whether it's front office or back office. I think the advantages are pretty clear. It's more, I think the difficulty is not technology anymore. The difficulty is mindset, leadership, commitment, the operating model, the organizational model and skills. And so what we have to do is AWS is bringing not only our technology, but our culture of innovation and our digital innovation teams to help our clients on that journey >>Technology. Well, we really appreciate you taking the time coming on the cube. We have a couple more minutes. I do want to get into what's your agenda. Now that you're got you're in charge, got the landscape and the 20 mile stare in front of you. Cloud's booming. You got some personal passion projects. Tell us what your plans are. >>So, um, three or four things, right? Three or four, really big takeaways for me is one. I, I came here to help make sure our customers could leverage the power of the cloud. So I will not feel like my job's been done if I haven't been able to do that. So, you know, that five to 15% we talked about, we've got to go 50, 60, 70%. That that's, that's the goal, right? And why not a hundred percent at some point, right? So I think over the next few years, that's the acceleration we need to help bring in AMEA Americas already started to get there as you know, much more, and we need to drive that into me. And then eventually our APJ colleagues are going to do the same. So that's one thing. The other is we talked about partners. I really want to accelerate and expand our partner ecosystem. >>Um, we have actually a huge growth by the way, in the number of partners signing up the number of certifications they're taking, I really, really want to double down on our partners and actually do what they ask us for, which is join. Co-sell joined marketing globalization. So that's two, I think the third big thing is when you mentioned industry industry industry, we've got to bring real use cases and solutions to our customers and not only talk technology got to connect those two dots. And we have lots of examples to bring by the way. Um, and then for hire and develop the best, you know, we've got a new LP as you know, to strive to be at its best employer. I want to do that in a Mia. I want to make sure we can actually do that. We attract, we retain and we grow and we develop that. >>And the diversity has been a huge theme of this event. It's front and center in virtually every company. >>I am. I'm usually passionate about diversity. I'm proud actually that when I was back at Schneider, I launched something called the power women network. We're a network of a hundred senior women and we meet every month. I've also got a podcast out there. So if anyone's listening, it's called power. Women's speak. It is, I've done 16 over the pandemic with CEOs of women podcast, our women speak >>Or women speak oh, >>And Spotify and >>Everything else. >>And, um, you know, what I love about what we're doing is AWS on diversity and you heard Adam onstage, uh, talk to this. We've got our restock program where we really help under employed and unemployed to get a 12 week intensive course and get trained up on thought skills. And the other thing is, get it helping young girls, 12 to 15, get into stem. So lots of different things on the whole, but we need to do a lot more of course, on diversity. And I look forward to helping our clients through that as well. >>Well, we had, we had the training VP on yesterday. It's all free trainings free. >>We've got such a digital skills issue that I love that we've said 29 million people around the world, free cloud training. >>Literally the th the, the gap there between earnings with cloud certification, you can be making six figures like with cloud training. So, I mean, it's really easy. It's free. It's like, it's such a great thing. >>Have you seen the YouTube video on Charlotte Wilkins? Donald's fast food. She changed her mind. She wanted to take Korea. She now has a tech career as a result of being part of restock. Awesome. >>Oh, really appreciate. You got a lot of energy and love, love the podcast. I'm subscribing. I'm going to listen. We love doing the podcast as well. So thanks for coming on the >>Queue. Thank you so much for having me >>Good luck on anemia and your plans. Thank you. Okay. Cube. You're watching the cube, the leader in global tech coverage. We go to the events and extract the signal from the noise. I'm John furrier with Dave, a lot to here at re-invent physical event in person hybrid event as well. Thanks for watching.

>>Welcome back to the cubes. Continuous live coverage of AWS reinvent 2021 live from Las Vegas. It's I'm Lisa Martin. And it's so great to say that we are doing with AWS and its massive ecosystem of partners. One of the most important hybrid tech events of the year. We've two sets over a hundred guests to remote studios, lots going on. I've got an alumni back with me and a new guest. Please. Welcome back. Sabina. Jo said the GM of technology partners at AWS and Neil Fowler joins her is the GM of micro-focus AMC. And you're going to tell me what AMC stands for >>Application modernization and >>Connectivity. I love it. Awesome guys. It's great. It's great to see you again in person. Thank you for having us. It's great to have the buzz. I know it's gonna be a little bit hard to hear, but great to have. AWS has done a phenomenal job of getting everyone in here safely. I want to give them kudos to that. So being to talk to me with, it's been a while since I've seen you in person, but talk to me about your current role at AWS. What's going on? >>Yeah, so I'm the general manager for technology partnerships globally out of the Americas. We also help partners out of EMEA and APAC grow in the Americas. And one of the great examples of a successful partnership is micro-focus with their solutions across application modernization security, database services, mainframes. >>And so from your perspective, through your lens, how do you think they're performing as a partner? Yes. >>So, um, first of all, kudos to Neil and the entire micro-focus team. They have done a great job leaning in with a cloud first strategy with SAS solutions on AWS and these solutions help customers across application modernization, application, delivery, security, cyber resiliency, database services, and also it performance management. And we've been working with them now for a few years. And in fact, today we have actually 400 customer wins together regulations and then also eight digit annual recurring revenue. They have six active listings in marketplace and all of this is really helping customers move their workloads and modernize their workloads into AWS. >>We've seen that such an acceleration nail in the digital transformation cloud adoption. The pandemic has really been a forcing function for that. There are some silver linings, but talk to me about some of the things that you've seen at micro-focus the last 20 months or so. And how have you helped those 400 customers, you know, getting to that big ARR, how are you helping them with that acceleration? >>Well, I think as you're saying that there's lots of changes in the last 12 to 18 months, some of it brought on by the pandemic and the change in business in business to having to respond, deliver solutions more quickly to the market, as well as remote working. So optimizing and the economic environment of costs, but being there to be more dynamic, it really has caused businesses to have to do something different than just to be able to survive and serve their customers better. That was a >>Big thing that we saw in the very beginning. It was not survival mode. And then of course it wasn't too long when we started seeing those survivors really start to thrive. And you started seeing who were going to be the winners of tomorrow. Cause the thing is every company, these days is a data company. If it's not, it's going to be passed up by competitor, that's right there in the rear view mirror. >>For sure. And so we've got, you know, organizations, so running mainframes, you know, older applications, legacy applications, modernization, where are most industries in terms of adopting that, the mindset, first of all, that they need to change? Well, I think across the whole industry, I mean, it doesn't matter whether it's retail. I mean, if you think about airlines with when the, when the pandemic hit business went down to, unless they've got that elastic nature of flashy to respond to it, but everyone had to bring in new services, new offerings very quickly. So the ability to be able to innovate in their environments and bring more solutions to their customers in a really fast way, you know, they couldn't just sit there and work with what they had. They had to move forward just to be able to stay in the business, but also be able to reduce the costs out of what they're trying to do. So running and transforming at the same time. >>Absolutely. And so how can organizations integrate existing core applications with new technologies to really be able to thrive in today's dynamic market? >>We look at modernization overall. We think of it in sort of three different ways with application process and infrastructure. So with a move to cloud, that's the infrastructure modernization they've immediately got far more access to more scalable dynamic elastic, compute resources, as well as all the technology platforms they have around. And then if you look at the application size and that's where the Microfocus platform comes in, we can help customers actually move those applications forward in terms of making them available through API APIs, maybe as a journey to microservices and cloud native. But once that core business logic and that data is available, it can be integrated into artificial intelligence machine learning and actually rained out the whole solution. So the final part of that from the process modernization, if you, as they're developing these applications with new tools, new ranges, in terms of where they can deploy on the AWS platform, they can automate the build deployment and operations so that all those existing applications and they were running on to contemporary platform with full access to the technologies that were available. >>That's fantastic and so necessary for businesses in any industry. So can you talk about some of the different business units of micro-focus? Are there any ones in particular that you want to call out? >>Yeah, so we work with them across all of their business units, but some of them that come to my mind is of course, Neil and team are doing a great job with application modernization and connectivity, really helping customers modernize the applications. And as customers are modernizing the applications, their cyber resiliency business unit is helping customers secure those applications. And then they also have their it operations management bridge product listed in marketplace. And then just since September are verdict a business unit launch Vertica accelerator on AWS. So I think they have a very holistic story to help customers >>On AWS. Talk to me a little bit, Neil, about cyber resiliency. We have seen such a dramatic change in cybersecurity in the threat landscape the last 20 months. I think I saw a stat recently that ransomware was up almost 11 X in the first half of 2021. Every, every day that companies had had a company, that data is gotta be secure. It's no longer a nice to have. That is a core requirement. How are you helping customers achieve that cyber? >>Well, the thing is, I mean, as you say, across the whole spectrum from cyber, from, from the identity access management through data encryption, through data protection, it's not, it's not a nice to actually say it's not a nice to have Kate take capability. You really have to have an integrated solution to be able to manage access control it, and also generating the events in terms of being able to, if anyone tries to get into the systems and log it because, you know, before, by the time you've discovered something it's too late, so you really need a combined solution for multi-factor authentication to really take it to that next level. >>Absolutely. Right. Once you've detected it, it's too late. And I mean, with ransomware as a service, cyber criminals are getting so much more sophisticated and also more brazen. There's so much money in it that the security front is, is I think even more interesting now than it's ever been. Talk to me about some joint customers and how you've helped them together with AWS with micro-focus achieve some of those key outcomes that you were talking about earlier. Well, I think >>Obviously with AWS as a platform has quite over a technology solutions going in, what we often find with our customers is a lots of, um, they're coming from an existing on-prem solution. So they need that hybrid model. So as part of taking that forward, been able to have that integrated solution that allows them to work both on-prem and as part of the cloud, most of it all being hooked up now, even that from even down to the, uh, as they're developing the applications now to do static code analysis, to help those applications be more secure with things like 40 pound demand, as well as integrating internet security platform for multifactor. So I think as you know, it's a combination of Brunel to bridge between all the different technologies, but have one single view of mail to protect the whole real estate, multiple layers for both external and internal threat. So that's, that's the other thing you also need to take into and can be able to protect all, all layers multi-layered approach. >>Absolutely. But you're right. The internal threats is something that we don't talk about as much, but that is obviously a substantial problem for organizations and most, if not any industries to be, to talk to me a little bit about, let's kind of get into the, the responsibilities that you have a little bit more in there. You've got responsibility for multiple solutions segments at AWS. You told me before we went live, you have 50 meetings this week. My goodness. And since day one, it taught all good. It's fun, fun. It is. Talk to me about AWS approach to partnering. What does it look like? What are some of the things that you think are really critical components? Yeah. >>So as you may have heard, we always start with the, at Amazon and AWS, we start with the customer. We work backwards when we are relaunching our products, our programs or services, you really go and ask the customers, what do you want us to develop? Where do you want us to focus the resources? It takes a lot of discipline to do that, but it's something that where we really want to walk the talk and we use the same approach with our partners when we started to work with micro-focus, we really kind of want to make sure that what we are working on together is what customers want, because we firmly believe that once you lay that foundation of that solution, you can scale your business a lot more quicker. Your story is a lot more simple and the customers are going to find a lot of value in what you are doing together. So it's really all about the customer for us. It is >>Absolutely critical, right? That's the whole point that the whole reason that we're here now, talk to me a little bit about maybe some cultural alignment with AWS, that customer first customer obsession. It sounds like at Microfocus, very similar. >>Absolutely. I mean, the way that we always think about how we're building our products, it's all around customer centric innovation. So that aspect of trying to make sure that we can solve what the business, understanding what the customers are trying to do to then help develop, to deliver solutions that meet that and that combination of a, the way that we look at it from that infrastructure modernization and the range of technologies that are available and that relentless focus on making customer successful is so key. But we have to make sure that that collaboration works together to make sure that the solutions align and we're helping customers get there together >>In your customer conversations. I imagine they've changed quite a bit during the pandemic with so many things being escalated to the C-suite to the board. How have your, how important is that cultural alignment between AWS and Microfocus from your customer's perspective? Is it something that comes up fairly often? Well, >>It's, it's a, I think it, when you actually get a mismatching culture, it's more obvious. So don't think that necessarily people are looking for it to say, I need organizations, but if you're not thinking the same way, you're not behaving the same way and actually partnering. I think that partnering part of it is really important because you're both working together to come up with that desired outcome. So I think it's more, more obvious when it isn't a good match as opposed to what it looking for that particular site. But I think that's a really key aspect in the sense of working together to help that customer be successful. >>Right? That's a great point that you bring up, but it's probably more obvious when it isn't working than when it's beautifully aligned, falling into place and really focused on that customer. So what are some of the things that attendees can, can feel and see and learn at the micro-focus booth at this year's reinvent nail, >>As well as obviously the key Roundup application modernization, where we're looking at the mainframe modernization on the site, we've got the full range of the Microsoft booth in terms of cyber resilience, as well as our, uh, item, my top, uh, it operations management or ADM portfolios. So we've got a lot of technologies which we can learn about in the booth interactive as well as all by experts to understand how we can do all these things and work together as part of the AWS platform to be able to deliver those solutions. >>Excellent. I'm sure there will be plethora of, of knowledge shared at the booth there. Last question, Neil, for you, talk to me about the vision going forward with the partnership. What are some of the things that you're looking forward to as we end 2021 and go into hopefully what is a better year, 2022? >>You know, one of the key things, you know, especially range, no one might, my passionate areas is helping our customers really look in terms of building the platform of the future. We can help solve their customer the problems today, but we're really trying to create that innovation platform to going through. So again, that combination of the technologies that we can bring to help our customers and the breadth and the investment that AWS continue making in the platform, those two combinations really helps us help our customers, not just solve today's problems, who really move into the forward to be the platform for innovation for the next decade. >>And that's really critical that that future ready state that is so undefined most of the time, I mean, none of us saw the pandemic coming, all right. That was a complete shock, but to be able to partner together, to help your customers really set up the foundation to be innovative as things happen that we can't even predict is really critical. So congratulations on your 400 customer wins your eight digit ARR. That's fantastic. Yes, we thank you so much for joining us on the queue, talking about the Microfocus AWS partnership and all of the successes that you guys have had. Great job. And I hope that you have cough drops and a lot of water this week. Sabina. I hope you do too guys. Thanks for joining me. Pleasure for my is I'm Lisa Martin. You're watching the cube, the global leader in live tech coverage.

>>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

>>Mhm Hello and welcome to today's session of the 2021 aws Global Public Sector partner awards. I'm Natalie early, your host for the cube and I'm delighted to present our guests. They are Jose Montero, ceo logitech the central America and Rafael Ramirez Product manager. Costa rica Ministry of Education. Welcome gentlemen to today's session. >>Think in Italy >>religion and belief. Well, let's start with Rafael. Please tell us about some of the key challenges that are affecting the Ministry of Education in Post A Rekha. >>One of the main challenges was to be able to have a product that is always available to schools that is easy to use for schools and at the same time that the product should be user friendly. That is you don't need so much training for schools to use it more. A few things that we thought of was to consider our client because schools have a very limited connectivity so we could not use very highly tech technologies because that required very huge. Both advanced and our clients, the schools would be subject to a service that was not available to them. One of the main things was to consider the client and how to reach them. Thanks to Ed attack, the ministry made an alliance with a company that thought about the innovation and they recommended different services that we can provide with a cloud through the cloud so that we are able to get to take the service to deliver the service to our clients and then they can use the platform that we are building in an easy way and at the same time to take care of the quality they need. Something important about schools was that while they were using the product, they were getting benefit that made schools to be willing to participate. >>Terrific. Well Jose I'd love it if you could give us some insight on some of the services that you are providing to the ministry. >>Sure. Um, so when, when the ministry approaches and um, and we had the opportunity to work with them um, of course, as an AWS partner, we thought, well, this is couldn't be better, right? And um, so we um, we we started to think on all of the different services that AWS offers in the cloud to provide to the ministry to be able to reach this gap. That has been for a long time where you see still, you know, people using Excel, using access Microsoft access as databases, um, instead of using all of the energy and all of the, the power that the cloud has. So when we approach to them and um, and we were able to um um, to show all of these different services that AWS could um, could provide to the Minister of Education. It was it was a perfect marriage. So, um, we we started to work with uh, with them and I think it's been awesome. This is only the first part of of a project of eight stages, We are currently working on stage two and stage Three, which will come in August and in January of 2020, And, um, but we're we're super happy to to see just in this first face, everything that has come and all of the data that has come to help the Ministry of Education in order to take action in the student's lives. >>Yeah, that's really terrific to hear. Um, you know, I'd love to hear from Rafael further about why he thinks it was so important to have cloud data at the Ministry of Education level. >>Okay, I >>will give you an important example for us in our country. We would rather gather the, collect data in paper and take that to the central office and this would enter into an Excel file. This take around two months to process all this later and make decisions. Mm When we started with the first service, which was to record the number of enrollees of the students, we could pay teachers on time, we could get the number of students and know where we had the biggest needs. So this would make a very innovative solution. And when the pandemic started, we had the first active service. This allowed us to react very quickly and we realized that in the first quarter, 19,000 students were not in in our schools because we were from a face to face service to a virtual service. So we could react very quickly. We plant a strategy with the Ministry of Education that was to come back. That is the idea goes to locate where students were. And in the next four months we could reduce the dropout From 90 students to 18,000 students. After that, we initiated a Another stage to retrieve those 18,000 students back to school. This was thanks to having the information online in some countries that may not have this problem. This might be very little. But for us, this was very, very important because we were able to reach the poll a wrist households so as to bring those students back to the school. >>Terrific. Well, that's really fantastic. Um, you know, in a non covid world, how do you think this technology will really help you, uh, to enhance education within Costa rica? See I can't. The important thing. >>This is important in the idea of this innovative product for us has a strategy of having a single file of the student. This allows us to do a follow up of what the student has done during the different school years and we can identify their lacks the weaknesses and we can see which are the programs that are more appropriate. Was to replicate this in the rest of the country without a centralized file. Like we have now, we are looking to have this traceability of students so as to have strengthened our witnesses and replicate our strength in the rest of the educational system. one of the most important things when you is that this technological unit, this implementation not only reached primary school students, but also preschool kindergarten, primary school, secondary school higher education, technical Education. So we reached every single sector where the Ministry of Education was able to detect where there was a need in the country. >>Yeah, Terrific. Well, I'd love to hear more from our other guest Jose monteiro Ceo of ecotech to central America. Uh, you know, if you could give us a, you know, more insight, more depth on the services that you provide. You, you talked about like an eight step plan. If you could just highlight those eight steps. >>Sure. Um, so part of this aid stages that we're going to be developing and um, and we hope that we'll be working with the Ministry of Education and every single one of them. Um, It causes where it brings a lot of technologies. For example, there's one that were planning on using, which is recognition from AWS. Um, the fact of um, there was, there's a lot of students that come to the country that have no documentation. There's no passports, There's no um, document I. D. There's nothing, right? So it's really hard for a um within the same school system to be able to track these students, right? Because they can they can go, they can come and they can, if they want, they can change their name. They can they can do a lot of things that are maybe are not correct. And um and sometimes it's not even because they want to do something incorrect. It's just that the uh the system or the yeah the the way of doing things manually, it allows us to do these types of changes. So for example, with with the service like recognition have been able to recognize their face or or recognize their um their idea with their with their fingerprints um and and being able to a um to interact and give give an actual recognition as the word says to this student. It's amazing. It's amazing technology that allows the Ministry of Education and the students to have a voice to have a presence even though they don't have their actual documentation because of whatever reason. Um There is something behind this that helps them um b be valuable and the b at the same time, a present in the in the system. Right? And so and and with with not only that, but with the grading with um with the attendance, with with the behavior with um with a lot of things that we're creating within these stages. Uh It's gonna be, for example, let me give you a quick example. Um There's, for example, the system that we've created for the dropouts. Um The student doesn't come one day, two days, three days and automatically. Now it'll, it'll become an alert and it will start to shot emails and alerts to the different people involved in order to see, hey listen, this student has not come for the last week, two classes. Um, we need you to go and see what's going on, Right? So this is maybe it is something very small, but it can, it can change people's life and they can change students lives and um, and, and the fact of, of knowing where they are, how they are, how are they doing, how their grades are, where we can help them and activate these different types of alerts that, um, that the system allows them to, um, to do that. It helps incredibly, the life of the student in the future, of this, of this student. And uh, in that exact, that is exactly what we're trying to do here. At the end. It's not only, um, it's okay, all of the technological and all of the different efforts that we're doing, but at the end, that's what it matters. It's, it's the student, right? It's it's the fact that, um, that he can come and he can finish his school, he can graduate, he can go to college, he can, he can become an, uh, an entrepreneur and, and be some, some day here and I at AWS conference and give him give a conference, and, and and that is exactly what the Ministry of Education is looking at, what we are looking at the project per se. >>Yeah, I mean, that's a really excellent point that you're making. I mean, this technology is helping real people on the ground and actually shaping their lives for the better. So, I mean, it's really incredible, you know, I'd love to hear more now from Rafael, just a bit what insight he can provide to other ministries, who, you know, also, you know, ministers of Education, who also would consider implementing this kind of technology and also his own experience um with this project in the AWS. >>Well, the connectivity for us is really important, not only with within the institutions of the Ministry of Education, but we also have connections with the Ministry of Health, we also have connections with the software called Sienna Julia, which allows the identification of people within the country and the benefits provided by the stage. So the country where all by little is incorporating the pieces and these cloud services, we have found that before we developed everything AWS has a set of services that allow us to focus on the problem and instead of on the solution of the technology, because services are already available. So at the country level, other ministries are incorporating these services nowadays, for covid management, the Minister of Health has a set of applications that allowed to set links between people that has positive. So this has allowed us to associate the situation with that particular student in our classrooms. So little by little services are converting education and other services into a need that allows us to focus on the problem instead of on technological solutions because services are already there for us to consume >>terrific. You know, I'd love to now shift to our other guest um Jose could you give us some insight what is the next phase for your business when you look at 2021? You know, it's gonna be, I mean, we hope it's going to be a wonderful year. Uh post Covid. Uh you know, what's your vision? >>It's it's interesting that you're saying that Natalie um education has changed Covid has um has put an acceleration to um has accelerated the the whole shift of the technological change in in education. It will not, well I hope it will not go back to the same before Covid. Um it's all of these technologies that are being created that are being organized, that are being it developed um for education specifically um an area where everything has been done the same for a long time. Um we need it, it's crazy to say this, but we needed a Covid time in order to accelerate this type of of organizations right in and now like ministry, the ministries of Education, like like the Minister of Education of Costa rica, they've had this for a long time and they've they've been thinking of the importance of making changes and everything, but until now it became a priority. Why? Because they realized that without these technologies with another pandemic, oh boy, we're going to see the effects of this and, and, and it's going to affect a lot of countries and a lot of students. Um, but it's gonna help to accelerate and understand that for example, internet, it has to be a worldwide access, just like water or electricity is in some, in our countries right now. You know, the fact of a student not having internet, um, we're taking away lot of development for this student. So I believe that after this post covid time education is going to continue to do a lot of changes and you and you'll see this and you'll see this in all of the areas in elementary, in preschool, in university, in high school. Um, you're going to see the changes that this is, um, is starting to do and we've seen it and we've seen it, but now it's going to be at a 23 or four X. So we're pretty excited. We're pretty excited what what the world it's gonna what the world's gonna bring to this table and to this specific area which is education. >>Yeah. That's really terrific to hear a silver lining in this pandemic. And just real quick uh final thoughts from rafael, are you looking to ramp up further? Uh you know, in light of what Jose has said, you know, to ramp up the digital transformation process? >>Yes, I believe this is an opportunity. The country is facing the opportunity, the resistance that we had in the sector of education, the current emergency situation. And they need to use virtual tools Have flattened these curves and narratives. Since 2000 and 20, Costa Rica started a very strong uh teach that trainer process that every four years ago it was very difficult to set to involve all teachers. But nowadays all teachers want to get trained. So we are getting there with virtual trainings with new tools, with the implementation and the use of technology in the classroom. So these kinds of emergencies somehow we have to uh, we know the pain but we know that also the gain of this whole idea of this whole situation. So this opportunity for change is something that we have to take advantage of. Thanks to these cloud services, I believe this is nowadays available and the country realized that these things are closer than what we thought of. An innovation is here to stay and I believe we have to exploit this a little by little >>terrific. Well gentlemen, thank you so much for your insights, loved hearing about the innovations taking place in the classroom, especially overseas in Costa rica. And that of course was Rafael Ramirez, the Product Manager, Costa rica, Ministry of Education, as well as Jose monteiro, the ceo of Ecotech D central America. And of course, I'm Natalie ehrlich, your host for the cube for today's session for the 2021 AWS Global Public Sector Partner Awards. Thanks very much for watching. >>Mhm.

>>Welcome to this cube conversation. I'm john Kerry host of the cube here in Palo alto California. We got a hot startup doing new things differently. The new way the cloud native way brendon, Hannigan, Ceo of sun rays securities. They deliver an awesome new solutions platform on all clouds to change the game and how security is done Brendan. Thanks for joining me on this cube conversation. >>Really nice to talk to you today, john >>you know, I loved showcasing companies that are, that are thinking about their entire optimizing their efforts to bring in the new, the new way to do things. And we certainly with the pandemic we've seen and everyone's validating this general global consensus that cloud scale and devops and def sec apps is generating a new kind of modern applications and this is just clearly has been known for a while inside the industry, but now it's mainstream. You guys are building a company around this notion of security. So let's get into it. What do you guys do is get right to it? What's the product? >>Well, firstly to get going And before getting into the specifics of product, john just I like to frame it, which is the ways in which I started out as a software engineer. You know, a long, long time ago built a company based on classic, traditional ways of developing software. The way we develop software has just changed dramatically change from stem to stern. We've gone from monolithic applications to microservices. We've gone from 18 month development cycles to two weeks from business units and I. T. Controlling it to devoPS teams. And then the amazing this is the incredible thing from a security perspective is we used to call up people in traditional networks and data centers to reconfigure the firewall so I could put my application of data center. But now I represented in code infrastructure is code that basically represents the infrastructure I have shows up in of course the cloud. The reason why I'd like to explain this story is we talk about cloud security and the complexities of cloud security. That's just where it all comes together. The reality is everything has changed around it. And we have a simple belief if everything has changed in terms of how it is, you build technology, value, deploy it and operators, we have to change how it is reduced security and it has to be also from stem to stern. So that's what basically that's why we started this business. Our mission is simple. We want to reinvent how it is. People secure new technology in these new environments and we do it by building a service that sits on top of companies usage of cloud amazon as your google cloud. And we help find risks automatically, eliminate them, Make sure they never come back and then deliver incredible new ways of continuously monitor activity to prevent cyber security incidents from happening in the first place. >>So this reinvention is a big, big trend. We've talked about this on the cube, you know, with many guests, even Pat Gelsinger's now the ceo of intel. When was that VM ware told us that you need to do over it in security, got to redo it all, not just incremental improvement. You know, fundamental revolutionary change was you're basically getting out here. So the question is top to bottom reinvention totally get that. How do you do it? Okay, Do you change the airplane engine out of 30,000 ft? It's hard people, it's easier said than done. What are the elements to reinvent security >>in this? We have we have a magical opportunity here because of cloud. So what happens is into traditional data centers and the traditional enterprise networks, There's, there's kind of Control points that are traditionally, which we understand and security John, right. And it's built up over 2030, 50 years. Right. And there's certain ways around which we rotate our security controls and you're familiar with them, right? Firewalls, Endpoint, antivirus security, information, security, event management system. Think of all those things, those control points are not relevant in the cloud. It's not, it's, they're interesting. V p c s and narrow grooves are kind of interesting in the cloud. Totally insufficient. So there's a necessity to reinvent and there's new control points and I will then tell you why it leads with an incredible better result. The new control points of the cloud, we believe and strenuously push when we speak to our customers, our identities. And it's not about Brandon and john, it's nearly always about non people identities, serverless functions, pieces of compute containers, all of these things have rights to like people. The second control point our data. Where is it? We used to have a data center. It's in the word, it says it data center, but in this instance I may have 20 devops teams. Each one of them is using RDS. One of them is using elastic cash. One of them is using a different thing. So data is the second one. The third one is applications. Why is this so important? The service providers have done a great job with core infrastructure. They give us two mechanisms to set up these environments. We need to help our customers organize and reinvent our security around these three pillars. The reason why it's so important, I love what you said is God, we've got to start from scratch. You get to start from scratch and when you do it, you actually can deliver a level of granularity and control and security that is unimaginable in the traditional enterprise network and data center. >>It's like golf, you got an extra Mulligan off the T if you hit it out of bounds and security, you get a do over. This is this is an opportunity. I love that concept because this is I mean it's not many times you get this clean sheet of paper or the opportunity to to pivot or reinvent or refresh re platform re factor whatever word you use. This is a time >>once in our life this transition, we know digital transformation is transforming industries, every industry is feeling it. We can see and understand the significance of the inventions like like AWS, it's an amazing invention, the power of it and what it delivers to us. The opportunity which is a must take opportunity is reinventing security from top to bottom. And by the way if you don't do it, if you just do this kind of half I have asked you end up with a mess on your hands if you do it properly, you end up in a better place than you would have been a traditional enterprise network and data center. >>The old expression you gotta burn the boats to get people motivated to kind of get it done right with the cloud. Let me ask you questions. Identity security and the data secure. Love that perspective because Identity the first thing in terms in my head when you said that was I thought about the identity of the individual their I. D. You know and you could actually get down to the firmware of a phone or you know to fact multifactor authentication. I get that access authentication. You're talking more in terms of other naming spaces and naming systems like specifically around services and applications identity, not just users. Right? >>Can you expand more on that? We we we we understand this as many people now understand this at a superficial level, but they haven't truly understand stood what's under the hood of what's happening inside cloud when you have reinvented applications, microservices, applications, auto scaling applications, it's all cloud is about incredible innovation happening across teams. What happens in the cloud is you have developers, administrators creating workloads. Those work clothes have huge numbers of compute functions which could be a container, a compute instance, a serverless function. They're gaining access to resources, other compute resources, cues and data to give you a sense of scale job you could have a company. It's not unusual. 80,000 pieces of compute 20,000 active at a particular point in time. We've got companies and then they assume these roles which give them access and rights to do things on these cloud services. It's not unusual to have 10,000 rolls in a cloud environment across multiple different accounts. Now, you see the identities, these pieces of compute have rights to do things. That's good because I can restrict what they do. It can be bad because if I don't have a handle on it, it's a mess. By the way, when you talk about this scale, human beings can't process this much information must be able to understand the risks, configure and automate remediation of these risks. The cloud providers give us the tools to build these flexible workloads. They're incredibly flexible. The dark side of it is in experience and basically inefficient deployment of those tools can lead to a whole host of risks that, quite frankly a lot of customers don't fully appreciate yet. >>And then people call that day to operation. But I love this idea of identity, the thousands and thousands of services out there because with microservices and you're seeing coming out of the cloud native world is these these new kinds of services could be stood up and torn down very quickly. So, you know, the observe ability trend is a great indicator in my opinion of this whole, you know, manic focus on data. So, you know, because you need machines to know, you don't know if something could be terminated and and stood up not even knowing about it, it could be errors. How do you log it? Right. So this is just an example. What's your thoughts on that? What's your reaction? Is that right? >>Ephemeral nature is the beauty of cloud. Right. Because, you know, there's problems that even now when we build our, we have a cloud native application ourselves and when we have a problem sometimes, of course we can go in and spin up 400 servers to go solve a problem and spin them back down half an hour later. We couldn't do that before a cloud. We can actually have developers doing this incredible rapid work with serverless functions to go and interrogate data to go out of data. Like to go and do analytics. It's wonderful. But what you said is their ephemeral. Now, just think about an environment. 20,000 pieces of compute 10,000 active, lots of 20 different teams across a 50 amazon accounts. Somebody comes in and basically during a period of time compromises. It compromises something and gets access to data, but it's a federal, it just comes and goes, we have to know that we have to know what's possible. We have to know if it's happened and then we have to basically greatly minimize the possibility of that happened. My promise because I'm security people are always trying to scare everybody which is valid. However, my promise the power of this cloud has created complexity opportunities but actually it also gives us the solution because using analytics machine learning in our case graphing technologies, we can actually find these things and give micro control two workloads so that actually we can see these things and automatically eliminate these risks and that was impossible >>in the the automation is programmable. You can actually set policies around automation. Pretty cool. I gotta ask you about get to the technical and want to understand the graphics and the platform more. But I want to ask you the question on the reinvention. If I follow your your playbook Yes. What's the end results? Can you take me through the all in bet the redo what happens? Can you just take me through the day in the life of an outcome? What's it look like and walk me through that? >>So firstly what the outcome I want to give our clients is they have these complex cloud environment spreading across, you know, any, even a moderate sized enterprise. What I basically want to be able to give our clients and when we have delivered for our clients is they basically managed to break that cloud from being this amorphous thing into specific work clothes. Each and every one of those workloads have specific controls in place that understand how that workload should operate in this environment across staging development and production. And actually we're able to essentially locked down what it is these workloads can do from an identity perspective, a data access perspective, a platform rights perspective and then monitor anything that changes. That's one thing. So the complexity were actually able to push away the complexity leveraged up lower to give that level of granularity at very deep levels. Identity, data platform. The second thing, actually, and this is john again, what's possible will clown? It doesn't it can't be all security teams, its security needs, It could be audit teams, its developers. So we have customers who have onboard tens and tens and tens of teams onto our platform. Why do we do that when we're finding issues and finding things that need to be resolved for directing it directly to the development teams? So we're saying developer to get into production, you're going to have to fix your identity set up in this environment. It's too risky, but it doesn't have to go to the security team. The security team will only hear about it if the developer doesn't fix it. >>Got it. So they're proactive, >>we're involving the teams responsible for creation and resolution of issues. The security and cloud teams are setting up the ground rules for a workload to operate in this environment and now we've got a level of granularity across workloads, whether they're in production or not. That basically is wonderful. That's the that's the ultimate endgame. >>What's the uh status of the vision and product on execution uh where your customers at now? Um how do you feel about it? Where is it going? Can you share a little bit about the roadmap and kind of where the product is? Uh It's a huge vision, it sounds easy to do, but it's not >>it's not actually and, you know, underlying it also, we actually, we've production service, we have wonderful, very large customers who are deployed and operational on our platform. You know, an example of one of them would be world fuel services, fortunate 93 company were the center of their kind of new security environment and operating model for everything they're doing and cloud. It's a beautiful story job. They've gone from in, in, you know, a few years ago. They 22 to the centers today to to yeah, it's unbelievable. And now all that future real estate were the center of that cloud security operating model. What does it mean? A 50 ft plus different teams on boarded onto the platform, following the rules of the road. If they don't follow the rules where all the exceptions are coming in and we're doing a continuous monitoring process underneath it. What is it that we've done? That's interesting. We actually have this incredible, unique way of collecting information from the cloud so that we can gather it in a very uh continuous way. So we're constantly seeing what's happening in addition to interrogating A PS and clouds are actually monitoring logs so we can see all the actions, what you just said. By the way, something comes and goes, we see it. The second thing which we do is we gather the information. We build a graph. This was actually, this was hard because it's not just as simple as sticking things in a graph with all of it to be. But what is the graph doing? The graph is basically understanding the intricacies of all the identity and access management models. I can see everything that can do anything to any other resource in the cloud, right? There is a surplus functioning container or a VM And we boil it down to very simple things. So underneath it's complex. We represented grass with boiling two simple things. Then we run analytics across the graph too, find and eliminate plaque from risk, find and eliminate identity risk. Get customers to the privilege enforced separation of duties, find data that you may not know is there that has incredible amounts of things capable of accessing it and help our customers lockdown that access. And then finally had we getting it into an operational automation kind of pipeline so that basically on an ongoing operational perspective it's efficient. So we're actually doing this for customers. We've got some very large financial institution customers. We've got, you know, large customers like World Fuel Services. And now actually our mission this year is to actually help simplify a lot of what we're describing so that, you know, you know, other companies and maybe companies not as sophisticated as a big financial institution or World Fuel Services is able to just very quickly get the value out of a solution. Like, >>you know, when you have these new technologies, new way of doing things, it's exciting at the same time, you have to kind of vector into an environment where the customer is ready to be operationalized. So, um, I got to ask you about how um teams are forming. I've I've been having a lot of conversation with VPs of engineering, large enterprises and and also big companies and hyper scale as well. And they're all talking about how, because of what you're doing and the kind of the general philosophy that you're you guys have is changing how teams are organized. You have a platform engineer now who can work on a platform and then flex and go work with other say feature engineers. And so it used to be just to do your features, You got your platform guys, you got your networking people. Okay, now you don't have to talk to the networking people because you can abstract away the network. You now have more composite, more compose herbal applications with all the observe ability. And now you can actually build that foundational platform. Redeploy the platform engineers with the other teams. So you seem like and then you got sRS embedded into teams and so you kind of got this new engineering formation going on, new kind of ways to organize the new modern era is here, it's on on this, this how people organize their teams. >>Actually is. There's no, there's no entire recipe at because you go to different customers and customers are basically experimenting with different ways to organize their teams. There's no question. But actually, I think one thing that's changed in the last 18 months is companies realizing we definitely need to change how it is. We've organized our team. I'm going to give you a simple example. Again in the old world, they would have network teams and network security teams you call up, Let me re configure the firewall. That doesn't work. It's just, it's just so broken. It can't work in clarity, can't be calling on people to re configure a firewall. That's an example. Another example which companies are realizing the latest identity. They will go through an approval process and they go through a governance and certification process. Well, these, these teams in the class, they want to get to work out in into, they need to get it in a month in an hour, in an hour. They can take a month and a manual approval processes sort of realizing that you need a skill set antiseptic ground rules and then the teams should be allowed to innovate within the ground rules. That's what the platform teams need to do. And so what we see emerging, which I think is a really best practice, is cloud centers of excellence. They're responsible for what I would call the shared infrastructure of the enterprise. The 250 Amazon accounts for 50 is your subscriptions, whatever it is that is king. Then the devoPS teams are using this shared infrastructure. The question is, how do you interface, how do you help coordinate between these different responsibilities from a security and governance and risk perspective? And that's actually what a big part of what our product is, helping teams coordinate their activities. That's a big part of what our product is, >>love. The first principles, they're sitting those ground rules. I mean there's been a chef and a cook, you know, you know, working with the environment and putting the new ingredients together and then getting that operational. It's a huge opportunity. Great stuff. Brandon. I gotta ask you the final question. Well I got you here, Sunrise Securities, the name Sunray. Where'd that come from? What does it mean? >>It actually means it's a Gaelic word and it means data and it's just so central to you know, what are people trying to steal? Like we can talk about security we're going to face. But at the end of the day they're trying to do damage. You're trying to get access to data. That's the most valuable thing we're trying to protect. So that's why we put it in our name. >>Digital transformation, everything's data now, everything's data, content, data Securities, data, data is everything >>it is. and I did >>great stuff. Brendan. Thank you for sharing the story here on the cube conversation, Brennan Hannigan's ceo of suddenly secure. Thanks for joining me. >>Thank you very much, john, it was a great pleasure. >>Okay. It's the cube from Palo alto California remote. Still. Thanks for watching.

>>from around the globe. It's the Cube with digital coverage of AWS reinvent 2020. Special coverage sponsored by AWS Global Partner Network Welcome to the Cubes. Live coverage of AWS reinvent 2020. I'm Lisa Martin. I've got two guests joining me. Next. Chris Gru's director of Business development, AWS Marketplace Service catalog and Control Tower at AWS. Chris, welcome. >>Thank you. Welcome. Good to see you. >>Likewise. And Matthew Polly is an alumni of the Cube. He is back VP of worldwide business development alliances and channels at Crowdstrike Matthew, Welcome toe. Welcome back. >>Great to be here. Lisa, Thanks for having me. >>And I see you're in your garage, your f one car in the background. Very jealous. So we're gonna be talking a little bit about not f one today, but about what's going on. Some of the the news that's coming from the partner Keynote. So, Chris, let's start with you. What's going on? The AWS marketplace news and also give our audience a real good understanding of what the marketplace is. >>Yeah, sure. So So AWS marketplace is actually an eight year old service within the AWS family, and and our charter is really providing a fine by deploy and manage experience for third party software. And so what our organization does. We work with my issues like Crowdstrike, and we really try to get them to package up their software in that same consumption format that other customers are buying AWS services. It's already the best service already. Those customers are used to buying services like Red Shift, and that's three and a consumption format, and they want to be able to buy third party software in that same manner. And so that's really been our charter since we were launched eight years ago. We've had a lot of great mo mentum since our launch. We now have over 8000 listings available in the catalog, and we have over 1.5 million subscriptions going through the catalog. One of things that we announced earlier today is that we are up to 300,000 active customers. That's actually up from 260,000, which is our previous numbers. So we continue to see really good momentum in terms of adoption, from both our eyes, community publishing listings and then from our customers that are actually buying out of the catalog. We work on all types of formats of software, so we provide machine images in an Amazon machine image format. But we also published and make available SAS products, container products and algorithms and models to run in things like our sage maker environment. And then, as of this morning in the Global Partner Summit, we announced the ability to sell professional services through eight of this marketplace as well. >>So lots of expansion, lots of growth. I'd love to get Chris your take on this expansion into offering professional services. What does that mean? And how have your 300,000 plus customers been influential in that? >>Yeah. And so what we've seen is marketplaces evolved is the transaction sizes have actually gone up dramatically. A couple years ago we launched a feature called Private Offers, which allows eyes views to do a negotiated subscription, submit that to an AWS customer and that they accept that goes right on their bill. We've seen very good adoption that we've got thousands of private offers now going through the system and what we found when the transaction sizes started to grow. Both our eyes V s that we're using the platform, as well as the consulting partners that are partners with US through Amazon Partner Network. They typically attached services to those transactions So pure and eyes V you might wanna package on something like an installation service training services. Or it could just be a bespoke statement of work that goes along with your technology and then on the consulting partner side. Resellers want to attach those same type of services to the software that they re sell, and up until this morning we weren't able to do that. And so it provided a lot of friction to our customers or buyers because what they had to do is they actually had to bottom line those transactions, or they had to do those transactions outside of marketplace. And And that wasn't a good experience for either RSV community or restore community or customers. So now, with this launch, we could actually allow customers to buy those services from those Eyes v partners and those resellers. By virtue of doing that to marketplace and basically how it works. It's similar to our private offer experience. They just submit a private offer to that customer. They could upload a statement of work. And if that customer accept, it goes directly on their AWS bill and they did. This marketplace takes care of all the collection, and the building that goes goes along with that transaction. And so we're really excited about this. We had over 100 launch partners that we're ready to go as of this morning, and we think this is gonna be a great feature, is gonna get a lot of adoption. Crowdstrike, which is a company that Matthews with is one of our launch partners for that feature. And so we just think this is gonna be a game changer for us on a number of levels. It's really gonna open up the type of transactions that we can now do to market place. >>Well, you mentioned Ah, good f word frictionless. That's something that every business really aims to do to make that experience just as seamless as possible. So Matthew talk to us about crowdstrike being part of its professional services, launched the opportunities that that opens up for the marketplace, customers and your customers? >>Sure. So just a quick background on crowdstrike were an endpoint protection cybersecurity company that has historically been protecting laptops desktops on premise, uh, devices from from breaches, basically identifying indications of attack or indications of compromise that that may surface on those end points. We do that by having agents run on those devices and point back to our massive body of data that runs in the cloud A W s. In fact, and so collecting tons and tons of data petabytes upon petabytes of data, literally trillions of events per week were able to easily identify and apply machine learning and artificial intelligence, Um, to that corpus of data to be able to identify when there is adversary activity on those devices. Now we've gone through a bit of a digital transformation ourselves, and we're looking at now. Not only, or we have launched products here recently, that not only protect those on premise devices like the desktops, laptops and on premise servers, but also protect workloads that are running in the cloud E C. Two instances, or RDS instances. What have you in in AWS? Or we've also launched what crowdstrike calls are Falcon Horizon product, which is a cloud security posture management product to be able to give people visibility into configurations that may create risk for their cloud environments. And we've been leveraging marketplace for about two years now. Um, it's been a fantastic opportunity for us to really leverage that frictionless sales motion that Chris talked about reducing sale cycles for us and for our channel partners. We have a number of our channel partners that leverage the CPP Oh capability within within the AWS marketplace toe actually transact business with their customers. It's been a It's been a fantastic, um you know, mechanism for for crowdstrike, for our partners and for our customers. Um, you know, we've been part of the enterprise contract scenarios where we don't have to go through that process of negotiating an end user license contract. We've signed up for the enterprise contract. Many of our customers have signed up for that enterprise contracts with reduces the legal iterations to get a transaction done. So that's been fantastic. And what we're doing now with the you know, the professional services offering is we're standing up a few of our professional services, Um, you know, offerings on the AWS marketplace so that our customers and our channel partners can actually transact business through the AWS marketplace toe, acquire those particular professional services offerings. And the one that I think is most interesting is a kind of cloud security assessment where our professional services team will go in and actually evaluate our their configurations. Are there unmanaged, um, you know, accounts running in AWS or what have you that could represent a security risk and make recommendations about how to improve the overall security posture of that cloud environment, leveraging something like crowd strikes Falcon Horizon, as I mentioned earlier, or our cloud workload protection offering. So it >>really >>is about streamlining the procurement, offering them. You know, the ability to thio, offering customers the ability to acquire through the AWS marketplace, whether that's the crowdstrike product or the Crowdstrike service offerings. >>So, Matthew, I imagine given this year that we're all not sitting together face to face in Las Vegas. The events of this year have also brought a lot of challenges from a security perspective. We've seen Ransomware going up dramatically, but also in this massive pitot to work working remotely. I can imagine your customers big opportunity for Crowdstrike to help them when endpoints just scattered. So in terms of that, as well as the impact with what you're doing with AWS marketplace seems like a great opportunity to provide your customers with faster access to ensuring that they can guarantee the security off their all of their data, which is business critical. >>Yeah, 100%. So the kind of global pandemic and work from anywhere has driven demand for crowd strikes capabilities in two ways. Number one people leaving the office and going home. There's a proliferation of physical devices, laptops for people to actually work from home, which obviously need to be protected. And a lot of times these were people that were working from home for the first time. You know, no longer within the protection of the, you know, the corporate network. Maybe they're using a VPN or what have you? But they needed the added protection of an endpoint protection capability like crowd strikes. And the second is a lot of this digital transformation has been accelerated. We've had a few customers tell us they had a three year plan for for their their digital transformation, and a lot of that is moving on. Premise service involves moving on premise servers to the cloud, and they've had to accelerate that two months or even even weeks in cases. And that's driving. You know, huge demand for understanding how to ensure there maintaining the proper security posture for those cloud environments. So speed is key right now, making sure that you're protected and transacting those those you know, those those sale cycles quickly leveraging native US marketplace all is accelerating. >>Yes, speaking of that acceleration and we've talked about that a lot. Matthew. This acceleration of digital transformation years now crammed into months. Chris, let's wrap with you in light of that acceleration, how has that affected positively? The AWS marketplace Bringing in professional services, allowing your customers to have much more available to them, to transact directly and and in a frictionless way, when speed is so critical? >>Yeah, I mean what it really leads to. It just gives us more selection, right? So if you take a step back and you think about the you know, the infamous Amazon fire, well, one of the key components of what makes a fine we'll go a selection. And there was a lot of solutions that we had. We just couldn't sell through marketplace without having some kind of services attach. While there's a lot of products that you could just point, click and go. There are a lot of technology. Do you need to? Some have some kind of hand holding And so, you know, by virtue launching services, this actually opens up the amateur in terms of selection that we could bring into the catalog. One of things that we've been focused on as a late is bringing in business applications as an example. And a lot of times a business application might need services to go on, actually wrap around that solution cell and, you know, be part of that implementation. And so that's the other great thing about this is it's going to give us more selection, and that's just gonna let our customers buy more and more products out of this market place. But do that in this very easy format, where it literally just lets them put these transactions directly on the AWS bill. So we think it's gonna be a great you know, not only for movie deals faster but also providing more solutions to our customers and just giving a better selection experience of AWS customer >>and being able to do that all remotely, which is these days is table stakes. Chris. Matthew, Thank you so much for joining me today. Talking about what's new with the Amazon marketplace. What you guys are doing with professional services and crowdstrike. We appreciate your time. >>Yep. Thank you. Thanks. Lisa. Yep. >>From my guests. I'm Lisa Martin. You're watching the cubes. Live coverage of aws reinvent 2020.

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

>>from around the globe. It's the cue with digital coverage of active EO data driven 2020. Brought to you by activity. We're back. This is the cubes coverage. Our ongoing coverage of active FiOS data driven. Of course, we've gone virtual this year. Ash. Ashutosh is here. He's the founder, president and CEO of Active Eo. Great to see you again. >>Likewise, They always always good to see you. >>We have We're in a little meet up, You and I in Boston. I always enjoy our conversations. Little did we know that, You know, a few months later, we would only be talking at this type of distance and, uh and of course, it's sad. I mean, a data driven is one of our favorite events is intimate, its customer content driven. The theme this year is you call it the next normal. Some people call it the new abnormal, the next normal. What's that all about? >>I think it's pretty pretty fascinating to see when we walked in in March, all of us were shocked by the effect of this pandemic. And for a while we all scrambled around trying to figure out How do you react to this one, and everybody reacted very differently. But most people have this tendency to think that this is going to be a pretty broom environment with lots of unknown variables, and it is important for us to try to figure out how to get a get our hands on this. By the time we came on. For six weeks into that, almost all of us have figured out this is Ah, this is not something you fight again. This is not something you wait, what, it to go away? But this is one. Did you figure out how to live in and you figured out how to work around it? And that, we believe, is the next long. It's not about trying to create a new abnormal. It's not about creating a new normal, but it's truly one that basically says that is it. That is a way, perhaps packed forward. There's a is a way to create this next normal, and you just figured out how to live with the environment, behalf and the normal outcomes of companies that have done remarkably well as a result of these actions. Fact. If you're being one of them, >>it's quite amazing isn't it? I mean, I've talked to a lot of tech companies, CEOs and their customers, and it's almost like they feel the first reaction was course they cared about their there, their employees and their broader families. Number one number two was many companies, as you know, saw a tailwind, and it initially didn't want to be seen as ambulance chasing. And then, of course, the entrepreneurial spirit kicked in and they said, Okay, we can only control what we can control and tech companies in particular just exceedingly Well, I don't think anybody really predicted that early >>on. Yeah, I, um I think of the heart, We're all human beings, and the first reaction was to take it off. Four constituencies, right? One. Take care of your family. Take it off your community, take care of your employees, take care of your customers. And that was the hardest part. The first 4 to 6 weeks was to figure out How do you do each of those four. Once you figured that part out or you figured out ways to get around to making sure you can take it off those you really found the next mom, you really start forgetting our out of continue to innovate Could, you know to support each of those four constituencies and people have done different things. I know it's amazing how, um, Cuba continues to operate As far as a user is concerned, they're all watching anymore. Yes, we don't have the wonderful desk, and we all get to chat and look in the eye. But the content of the messages asked powerful as what it waas a few months ago. So I'm sure this is how we're all going to figure out how to make through this new next normal >>and digital transformation kind of went from from push to pull. I mean, every conference you go to, they say, Well, look at uber, you know, look at Airbnb and it put up the examples you have to do this to, and then all of sudden the industry dragged you along. Some Curis esta is toe. How and and I guess the other point there is digital means data. We've said that many, many times. If you didn't have a digital strategy during the height of the lock down, you couldn't transact business and still many restaurants is still trying to figure this out, But so how did it affect you and your customers? >>Yeah, it's very interesting. And I we spend a lot of time with several of our customers were managing some of the largest I T organizations. We talk about very interesting phenomena that happened some better beginning of this year. About 20 years ago, we used to worry about this thing called the Digital Divide, those who have access the network and Internet and those who don't. And now there is this beta divide, the divide between organizations that know how to leverage, exploit and absolutely excellent the business using data and those adorable. I think we're seeing this effect so very clearly among organizations that unable to come back and address some of this stuff. And it's fascinating. Yes, we all have the examples off the lights off. People are doing delivery. People are doing retailing, but there are so many little things you're seeing organizations. And just the other day, he had a video from Century Days Is Central Data System, which is helping accelerate Cohen 19 research because it will get copies of the data faster than they would get access to data so that these are just much, much faster. Sometimes you know, several days to a few minutes. It's that that level of effect, it's not just down to some seven. You know, you almost think of it as nice to have, but it's must have life threatening stuff. Essential stuff or just addressing. Korea was running a very pretty in a wonderful article about this supercomputer in That's Doing an Aristo covert 19 and how it's figured out most of these symptoms they're able to figure out by just crunching a ton of data. And almost every one of those symptoms that the computer has predicted Supercomputer is predicted has being accurate. It's about data. It is absolutely about data, which is why I think this is a phenomenal time for companies. Toe Absolutely go change. Make this information about data exploration, data leverage, exploitation. And there's a ton of it all over all around us. >>Yeah, and and part of that digital transformation, the mandate is to really put data at the core. I mean, we've we've certainly seen this with the top market cap companies. They've got dated at the core, and and now, as they say it's it's become a A mandate. And, you know, there's been several things that we've clearly noticed. I mean, you saw the work from home required laptops and, you know, endpoint security and things of that. VD. I made a comeback, and certainly Cloud was there. But I've been struck by the reality of multi Cloud. I was kind of a multi cloud skeptic early on. >>Yeah, >>I said many times I thought it was more of a symptom than it was a strategy, but it's that's completely flipped. Ah, recently in r e t r surveys, we saw multi cloud popping up all over the place. I wonder what you're seeing when you talk to your customers and other CEOs. >>Yeah, So fascinating, though really is the first flower part of sometime in 2018. End of 2018 >>Go right, Yeah, >>the act if you'll go on world, which is a phenomenal way to completely change the way you think about the using object storage in the flower for two years that we saw about 20% of our business. By the end of two years, the beginning of this year, 20% of our business was built on never it in the cloud since March. So that was end of our almost ended the Q one. So now we just limit left you three in six months. We added 12 more percent of the business literally weeded in six months. What we did not do before for 18 months before that, right? Significantly more than what we did for a year and a half before that. And there are really three reasons and we see this old nor again, we have a large customer. We closed in January. Ironically, were deploying out of UK, a very large marketing organization. Got everything deployed, running the they're back up and beyond and a separate data center. And they had a practical problem of not being able to access the second sight literally in the middle of deployment. Mystere that customer, Did you see me Google Cloud? Because they were simply no way for them to continue protecting their data, being able to develop new applications with that data that simply had no access. So there was. This was the number one reason the inability for already physically access, but put their their employees at rest and have before the plow would be the infrastructure. That's number one, so that first of all, drove the reason for the cloud. And then there's a second reason there are practical reasons. And why some clerk platforms that good one working the other ones are not. So where, uh, some other more fuels. And so if I'm an organization that has that spans everything, I've got no power PC and X 86 machine A vm I got container platforms. I got Oracle. They got a C P. There is no single cloud platform that supports all my work loaders efficiently. It's available in all the agents I want. So inevitably I have to go at our different about barefoot. So that's a second practical visa. And then there's a strategic reason. No, when no customer what's really locked into anyone card back at least two. You're gonna go pear more likely? Three. So those are the reasons. And then, interestingly enough, have you were on a panel with as global Cee Io's and in addition to just the usual cloud providers of you all know and love inside the U. S. Across the world, in Europe, in Asia, there's a rise off the regional flower fire. See you take all this factor. So have you got absolute physical necessity? You got practical constraints of what can the club provided support the strategic reasons on why either Because I don't want to be locked into a part for better or because there is a rise off data nationalism that's going on, that people want to keep their data within the country bombs all of these reasons. But the foundations or why multiplier is almost becoming a de facto. It's impossible. What a decent size organization to assume. They were just different on one car ready. >>The big trend we're seeing, I wonder if you could comment. Is this this notion of the data life cycle of the data pipeline? It's a very complex situation for a lot of organizations, their data siloed. We hear that a lot. They have data scientists, data engineers, developers, data quality engineers, just a lot of different constituencies and lines of business. And it's kind of a mess. And so what they're trying to do is bring that together. So they've done that data. Scientists complain they spend all their time wrangling data, but but ultimately the ones that are succeeding to putting data at the core is, we've just been discussing are seeing amazing outcomes by being able to have a single version of the truth, have confidence in that data, create self serve for their for their lines of business and actually reduce the end and cycle times. It's driving your major monetization, whether that's cost cutting or revenue. And I'm curious as to what you're seeing. You guys do a lot of work. Heavy work in Dev ops and hard core database those air key components of that data Lifecycle. Yeah, you're seeing in that regard regarding that data pipeline. >>Yeah, it's a It's a phenomenal point if you really want to go back and exploit data within an organization. If you really want to be a data driven organization, the very first thing you have to do is break down the silos. Ironically, every organization has all the data required to make the decisions they want to. They just can't either get to it or it's so hard to make the silos. That is just not what trying to make it happen. And 10 years ago we set out on this mission rather than keep this individual silos of data. Why don't we flip it open and making it a pipeline, which looks like a data cloud where essentially anybody who's consuming it has access to it based on the governance rules based on the security rules that the operations people have said and based on the kind of format they want to see data. Not everyone even want to see the data in a database. Former, maybe you want the database for my convert CSP for my before you don't analytics And this idea of making data, the new infrastructure, this idea of having the operations people provide this new layer for data, it's finally come to roost. I mean, it's it's fascinating. I was the numbers last quarter. We just finished up. You do now. 45% of our customer base is uses activity or for reuse is the back of data for things that excellent. The business things that make the business move faster, more productive or you will survive. That was the mission. That was what we set out to do 10 years ago. We were talking to an analyst this morning, and now this is question off. You know, it looks like there's a team of backup data being reused, said Yeah, that's kind of what we've been saying for 10 years. Backup cannot be an insurance back up in order to your destination. It has to be something that you could use as an asset and that I think it's finally coming to the point with you can use back up a single source of truth only if you designed it right from the beginning. For that purpose, you cannot just lots of lots of ways to fake it. Make it try to pretend like you're doing it. But that was a trooper was off making date of the new infrastructure, making it a cloud, making it something that is truly an ask. And it's fascinating to see our businesses. You take any of our larger counts and the way they've gone about transforming not just basic backup. India. Yes, we are the world's glasses back up in most Kayla will be our solution. That's that's a starting point. But do we will be used after Devil applications 8, 10 times faster? Ron Analytics, 100 ex pastor. The more data you have, the more people who use data you have, the better this return makeups. >>You know, that is interesting to hear you talk about that because that has been the holy Grail of backup. Was toe go beyond insurance to actually create business value. And you're actually seeing some underlying trends We talked about that data pipeline in one of the areas that is the most interesting is in database, which was so boring for so many years. Ah, and you're seeing new workloads emerge. Take the data warehouse beyond your reporting. Never really lived up to its Ah, it's promise of 360 degree view. You mentioned analytics. That's really starting toe happen. Ah, and it's all about data John, for Used to say that your data is that is the new development kit. You call it the new infrastructure, and it's sort of the same same type of theme. So maybe some of the trends you're seeing in ah in database enoughto talk about that for a little bit and then pick your brains and some other tech like object storage is another one that we've really seen takeoff? >>Yeah. So I think our journey with object story began in 16 4017 as we started or Doctor Cloud platform in response to the user requirements, Uh, we did more like most companies have done and unfortunately continue to do to take the in print product. And then it's smooth under the cloud. And one of the things we saw was there was a fundamental difference off how the design points of flower engineering is all about what they're designed it for object story, that one of those one of those primitives fundamental stories, primitives that the cloud providers actually produced that we know really exploited. There was. It was used as a graveyard for data. It's a replacement for me, please, where data goes to die. And then we look at it really closely and say, Well, this is actually a massively scalable, very low cost storage, but it has some problems. It has an interface that you cannot use with traditional servers. Uh, it has some issues around not being able to read, modify right the data. So it feels like a consuming a lot of stories. So we're going to solve those problems because a good two years to come back with something on world that fundamentally creeds objects the lady like this massive use capable high performer disk? Yes, except it is ridiculously low cost and optimize the capacity. So this finger on world that patented has really become the foundation of how everything in our works without using CPU Ray, that is simply nothing at a lower PCO that if you wanted to basic backup, the, uh, more importantly, use that to do this a massive analytics and you don't know more data warehouse data leaks. It is not a good deal of Lake House aladi. All of these are still silent. All of these are people trying to take some data from somewhere put into one of the new construct and have it being controlled by somebody else. This is artist thing. It's just you just move the silos from some place to another place instead of creating a pipeline. If you want to really create a pipeline object story has been integral part of the pipeline, not a separate bucket by itself. And that's what we did. And same thing with databases, you know, most business, most of the critical business and I was on a daily basis, and the ability to find a way to leverage those. Move them on our leverage in terms of whichever format databases access. Which location or Saxes doesn't know how big it is. Lots of work has gone into trying to figure figure that one out. And we we had some very, very good partners in some of the largest customers who help take the journey with us. I'm pretty much all of the global 2000 accounts you see across the board, but an integral part of a process. >>You mentioned the word journey and triggered a thought. Is your discussion with Robbie, the CEO of of Seeing >>A. It was a customer years. >>Ah, and what he said. I liked what he said. He course he used the term journey. We all do. But he said, You know what? I kind of don't like that term because I want to inject the sense of urgency essentially what he was saying. I want speed, you know, journeys like Okay, kids get in the car, were in a drive across country. We're gonna make some stops. And so, while there's a journey, he also was was really trying to push the organization hard and he talked about culture. Ah, as some of the most difficult things and it goes like many. See, I said, Now the technology is almost the easy part. It's true when it works. Oh, I thought that was a great discussion that you had. What were some of your takeaways >>with thinking? Robbie's is very astute. Ah, I t executive was being around the block for so long and one of the fascinating things, but a asking this question about what's the biggest challenge was just gone through this a couple of times. What is the biggest challenge? Taking an organization as vulnerable as well known A C gate is. I mean, this is a data company. This is This is the heart of the Oliver Half the world's data is on seeing stuff. How are you today was, or company has been around for long in the middle of Silicon Valley and make it into ah into a fast growing transformation company that's responding to the newer challenges. And I thought he was going to come back with Well, you know, I gotta go to the abuses. I picked this technology that techno in. Surely that is exactly what I expected he would end up with. There's nothing through technology in this day and age when you can have an Elon Musk and send a card of Mars. It's not many technologies that we can really solve many covered 19 ism. Next one Do we gotta go solve? Well, frankly, he kid upon the one thing that matters to every company. It is the fundamental culture to create a biased of action. It's a fundamental culture where you have to come back and have a deliverable that moves the ball forward every day, every month, every quarter, as opposed to have this CDs off. Like you said, a journey that say's and we all know this right? People talk about, we're going to do this in face one. We're gonna do this and face to and good food release and face three nothing and what happens Invasive. Nobody gets a number feast. I think he did a great job of saying I fundamentally had to go change the culture that was my biggest take away, and this I've heard this so many times the most effective I D execs wait a transformation. It actually shows in the people that they have. It's not the technology, it's the people. And some. This history is replete with organizations that have done remarkably well, not by leveraging the heck out of the technology, but truly by leveraging the change in the people's mindset. And, of course, that at that point that leverages technology where a proper here. But Robbie's a insightful person, always such a They lied to talk them, said they like for him to have chosen us as a its information technology for him to go pull his data warehouses and completely transformed how I was doing manufacturing across the globe. >>You know, I want to have some color of what you just said because some key keep takeaways that from what you just said, ashes is You know, you're right when you look back at the history of the computer industry used to be very well known processes, but the technology was the big mystery and the and the big risk and you think about with Cove it were it not for Technology Way didn't know what was coming. We were inventing new processes literally every day, every week, every month. It's so technology was pretty well understood. It and enabled that. And when you when you think when we talked earlier about putting data at the core, it was interesting to hear Robbie. He basically said, Yeah, we had a big data team in the U. S. A big tainted TV in Europe. We actually organized around silos and and so you guys played a role you were very respectful about, you know, touting active video with him. You did ask him, You know what role you play, But it is interesting to hear and talk about how he had to address that both culturally. And of course, there's technology underneath to enable that unification of data that silo busting, if you will. And you guys played a role in that. >>Yeah, I always enjoy, um, conversation with folks who have taken a problem, identified what needs to be done and then just get it done. And its That's more fascinating than you. Of course, I video plays a small part in a lot of things, and we're proud to have played a small part in his big initiative, and that's true of know the thousands of customers we talk about. But it's such a fascinating story to have leaders who come back and make this transformation happen, and to understand how they went about making those decisions, how they identified where the problem with these are so hard. We all see them in our own life, right? We see there is a there's a problem, but sometimes it takes a wider don't understand. How do you identify them and what do you have to do and more importantly, actually do it? And so whenever use, whenever I get an opportunity with people like Robbie, I think understanding that there's a way to help, uh, we always make sure that we play our own small part, and we're privileged to be a part of those kinds of journeys. >>Well, I think what's interesting about activity on the company that you created is essentially that. We're talking about the democratisation of data, that whole data pipeline, that discussion, that we had the self service of that data to the lines of business and, you know, you guys clearly play a role there. The multi cloud discussion fits into that. I mean that these air all trends that are tail winds for companies that can that can help sort of you know, flattened the data globe. If you if you will, your final thoughts. >>Yeah, I know you said something that is so much at the heart of every idea Exactly that you're talking to, if they truly is. The fundamental asset that I finally end up with is an organization. The democratization of data. Where I do not lock this into another silo, another platform, another ploughed. Another application has to be part of my foundation design and therefore my ability to use each of this cloud platform for the services they provide. While I and they were to move the data to where I needed to be. That is so critical. So you almost start to think about the one possession and organization now has. And we talked about this with a group of CEOs. They might be some pretty soon. Not too far off, but data stolen asset. I might actually have our data mark data market, just like you. I was stopped working, but I can start to sell my data. You know, imagine a coup in 19. There's so many organization that have so much data, and many of them have contributed to this research because this is an existence of issue. But you can see this turning into a next level. So, yes, we've got activities, will move the data toe one level higher where it's become a foundation construct for the organization. The next part is gonna actually done. This is the one asset would actually monetize someone stuff. And it will be not too long when you need to talk about how there's this new exchange and what's the rate of data for this company? Was, is that company in the future trading options? Who knows is gonna be really interesting. >>Well, I think you're right on this notion of a data. Marketplaces is coming, and it's not not that far away, Blash. It's always great to talk to you. I hope next year a data driven weaken we could be face to face. But I mean, look, this has been we we've dealt with it. It's it's actually created opportunities for us toe to reinvent ourselves. So congratulations on the success that you've had and ah, and thank you for coming on the Cube. >>No, thank you for hosting us and always a big fan off Cube. You guys, you engage with you since early days, and it is fascinating to see how this company has grown. And it's probably many people don't even know how much you've grown behind the seats, technologies and culture that you created yourself. So it's hopefully one day we'll strict the table that I would be another side and asking of our transformation. Digital transformation of Cuban cell >>I would love to. I'd love to do that index again. And thank you, everybody for watching our continuous coverage of active fio data driven keeper Right there. We'll be back with our next guest right after this short break. >>Thank you.

>>from around the globe. It's the cue with digital coverage of active Eo data driven 2020 Brought to you by activity. >>Hi, everybody. My name is David Chang. I'm the chief product officer and co founder of Active Fio. Extremely excited to have you joined Active feels data driven where it's the only event. Customer essentially is on the center stage telling you what they're using active before, excited to have you looking forward to the event.

>>from around the globe. It's the queue with digital coverage of active EO data driven 2020 brought to you by activity. >>However, this is Dave Volante for the Cube and appear to really tell you how excited we are about active CIOs. Data driven. We're partnering with active again this year. Of course, the conference has gone virtual. Data driven is a great event. It's a very customer oriented event. Active CEO is a company that deals with some really gnarly data problems at scale. They started in the space of copy data Management and have extended into Dev Ops and Analytics and Cloud. And so the Cube will be there. It's September 15th and 16th, 16th goto active geo dot com. Sign up. There's a free e book on Dev Ops. It's always a great program. We'll see you there. >>Yeah, yeah, yeah, yeah

>>from around the globe. It's the queue with digital coverage of active eo data driven 2020 Brought to you by activity. >>Hi, I'm Brian Reagan from Active Seo. And I'd like to welcome you to join us at Data Driven 2020 this year. Online as in years past, it's all about the customer from the bear voice to you talking about how they're solving their cloud Dev Ops Analytics and data protection challenges using the activity of platform and helping move their business forward this year. We're also excited to welcome Gene Kim Noted Dev Ops author in Guru on his E book. The Unicorn Project is available for free if you register today, so join us September 15th and 16th for data driven 2020. We look forward to seeing you online. >>Yeah, yeah, yeah, yeah, yeah