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Joseph Nelson, Roboflow | Cube Conversation


 

(gentle music) >> Hello everyone. Welcome to this CUBE conversation here in Palo Alto, California. I'm John Furrier, host of theCUBE. We got a great remote guest coming in. Joseph Nelson, co-founder and CEO of RoboFlow hot startup in AI, computer vision. Really interesting topic in this wave of AI next gen hitting. Joseph, thanks for coming on this CUBE conversation. >> Thanks for having me. >> Yeah, I love the startup tsunami that's happening here in this wave. RoboFlow, you're in the middle of it. Exciting opportunities, you guys are in the cutting edge. I think computer vision's been talked about more as just as much as the large language models and these foundational models are merging. You're in the middle of it. What's it like right now as a startup and growing in this new wave hitting? >> It's kind of funny, it's, you know, I kind of describe it like sometimes you're in a garden of gnomes. It's like we feel like we've got this giant headstart with hundreds of thousands of people building with computer vision, training their own models, but that's a fraction of what it's going to be in six months, 12 months, 24 months. So, as you described it, a wave is a good way to think about it. And the wave is still building before it gets to its full size. So it's a ton of fun. >> Yeah, I think it's one of the most exciting areas in computer science. I wish I was in my twenties again, because I would be all over this. It's the intersection, there's so many disciplines, right? It's not just tech computer science, it's computer science, it's systems, it's software, it's data. There's so much aperture of things going on around your world. So, I mean, you got to be batting all the students away kind of trying to get hired in there, probably. I can only imagine you're hiring regiment. I'll ask that later, but first talk about what the company is that you're doing. How it's positioned, what's the market you're going after, and what's the origination story? How did you guys get here? How did you just say, hey, want to do this? What was the origination story? What do you do and how did you start the company? >> Yeah, yeah. I'll give you the what we do today and then I'll shift into the origin. RoboFlow builds tools for making the world programmable. Like anything that you see should be read write access if you think about it with a programmer's mind or legible. And computer vision is a technology that enables software to be added to these real world objects that we see. And so any sort of interface, any sort of object, any sort of scene, we can interact with it, we can make it more efficient, we can make it more entertaining by adding the ability for the tools that we use and the software that we write to understand those objects. And at RoboFlow, we've empowered a little over a hundred thousand developers, including those in half the Fortune 100 so far in that mission. Whether that's Walmart understanding the retail in their stores, Cardinal Health understanding the ways that they're helping their patients, or even electric vehicle manufacturers ensuring that they're making the right stuff at the right time. As you mentioned, it's early. Like I think maybe computer vision has touched one, maybe 2% of the whole economy and it'll be like everything in a very short period of time. And so we're focused on enabling that transformation. I think it's it, as far as I think about it, I've been fortunate to start companies before, start, sell these sorts of things. This is the last company I ever wanted to start and I think it will be, should we do it right, the world's largest in riding the wave of bringing together the disparate pieces of that technology. >> What was the motivating point of the formation? Was it, you know, you guys were hanging around? Was there some catalyst? What was the moment where it all kind of came together for you? >> You know what's funny is my co-founder, Brad and I, we were making computer vision apps for making board games more fun to play. So in 2017, Apple released AR kit, augmented reality kit for building augmented reality applications. And Brad and I are both sort of like hacker persona types. We feel like we don't really understand the technology until we build something with it and so we decided that we should make an app that if you point your phone at a Sudoku puzzle, it understands the state of the board and then it kind of magically fills in that experience with all the digits in real time, which totally ruins the game of Sudoku to be clear. But it also just creates this like aha moment of like, oh wow, like the ability for our pocket devices to understand and see the world as good or better than we can is possible. And so, you know, we actually did that as I mentioned in 2017, and the app went viral. It was, you know, top of some subreddits, top of Injure, Reddit, the hacker community as well as Product Hunt really liked it. So it actually won Product Hunt AR app of the year, which was the same year that the Tesla model three won the product of the year. So we joked that we share an award with Elon our shared (indistinct) But frankly, so that was 2017. RoboFlow wasn't incorporated as a business until 2019. And so, you know, when we made Magic Sudoku, I was running a different company at the time, Brad was running a different company at the time, and we kind of just put it out there and were excited by how many people liked it. And we assumed that other curious developers would see this inevitable future of, oh wow, you know. This is much more than just a pedestrian point your phone at a board game. This is everything can be seen and understood and rewritten in a different way. Things like, you know, maybe your fridge. Knowing what ingredients you have and suggesting recipes or auto ordering for you, or we were talking about some retail use cases of automated checkout. Like anything can be seen and observed and we presume that that would kick off a Cambrian explosion of applications. It didn't. So you fast forward to 2019, we said, well we might as well be the guys to start to tackle this sort of problem. And because of our success with board games before, we returned to making more board game solving applications. So we made one that solves Boggle, you know, the four by four word game, we made one that solves chess, you point your phone at a chess board and it understands the state of the board and then can make move recommendations. And each additional board game that we added, we realized that the tooling was really immature. The process of collecting images, knowing which images are actually going to be useful for improving model performance, training those models, deploying those models. And if we really wanted to make the world programmable, developers waiting for us to make an app for their thing of interest is a lot less efficient, less impactful than taking our tool chain and releasing that externally. And so, that's what RoboFlow became. RoboFlow became the internal tools that we used to make these game changing applications readily available. And as you know, when you give developers new tools, they create new billion dollar industries, let alone all sorts of fun hobbyist projects along the way. >> I love that story. Curious, inventive, little radical. Let's break the rules, see how we can push the envelope on the board games. That's how companies get started. It's a great story. I got to ask you, okay, what happens next? Now, okay, you realize this new tooling, but this is like how companies get built. Like they solve their own problem that they had 'cause they realized there's one, but then there has to be a market for it. So you actually guys knew that this was coming around the corner. So okay, you got your hacker mentality, you did that thing, you got the award and now you're like, okay, wow. Were you guys conscious of the wave coming? Was it one of those things where you said, look, if we do this, we solve our own problem, this will be big for everybody. Did you have that moment? Was that in 2019 or was that more of like, it kind of was obvious to you guys? >> Absolutely. I mean Brad puts this pretty effectively where he describes how we lived through the initial internet revolution, but we were kind of too young to really recognize and comprehend what was happening at the time. And then mobile happened and we were working on different companies that were not in the mobile space. And computer vision feels like the wave that we've caught. Like, this is a technology and capability that rewrites how we interact with the world, how everyone will interact with the world. And so we feel we've been kind of lucky this time, right place, right time of every enterprise will have the ability to improve their operations with computer vision. And so we've been very cognizant of the fact that computer vision is one of those groundbreaking technologies that every company will have as a part of their products and services and offerings, and we can provide the tooling to accelerate that future. >> Yeah, and the developer angle, by the way, I love that because I think, you know, as we've been saying in theCUBE all the time, developer's the new defacto standard bodies because what they adopt is pure, you know, meritocracy. And they pick the best. If it's sell service and it's good and it's got open source community around it, its all in. And they'll vote. They'll vote with their code and that is clear. Now I got to ask you, as you look at the market, we were just having this conversation on theCUBE in Barcelona at recent Mobile World Congress, now called MWC, around 5G versus wifi. And the debate was specifically computer vision, like facial recognition. We were talking about how the Cleveland Browns were using facial recognition for people coming into the stadium they were using it for ships in international ports. So the question was 5G versus wifi. My question is what infrastructure or what are the areas that need to be in place to make computer vision work? If you have developers building apps, apps got to run on stuff. So how do you sort that out in your mind? What's your reaction to that? >> A lot of the times when we see applications that need to run in real time and on video, they'll actually run at the edge without internet. And so a lot of our users will actually take their models and run it in a fully offline environment. Now to act on that information, you'll often need to have internet signal at some point 'cause you'll need to know how many people were in the stadium or what shipping crates are in my port at this point in time. You'll need to relay that information somewhere else, which will require connectivity. But actually using the model and creating the insights at the edge does not require internet. I mean we have users that deploy models on underwater submarines just as much as in outer space actually. And those are not very friendly environments to internet, let alone 5g. And so what you do is you use an edge device, like an Nvidia Jetson is common, mobile devices are common. Intel has some strong edge devices, the Movidius family of chips for example. And you use that compute that runs completely offline in real time to process those signals. Now again, what you do with those signals may require connectivity and that becomes a question of the problem you're solving of how soon you need to relay that information to another place. >> So, that's an architectural issue on the infrastructure. If you're a tactical edge war fighter for instance, you might want to have highly available and maybe high availability. I mean, these are words that mean something. You got storage, but it's not at the edge in real time. But you can trickle it back and pull it down. That's management. So that's more of a business by business decision or environment, right? >> That's right, that's right. Yeah. So I mean we can talk through some specifics. So for example, the RoboFlow actually powers the broadcaster that does the tennis ball tracking at Wimbledon. That runs completely at the edge in real time in, you know, technically to track the tennis ball and point the camera, you actually don't need internet. Now they do have internet of course to do the broadcasting and relay the signal and feeds and these sorts of things. And so that's a case where you have both edge deployment of running the model and high availability act on that model. We have other instances where customers will run their models on drones and the drone will go and do a flight and it'll say, you know, this many residential homes are in this given area, or this many cargo containers are in this given shipping yard. Or maybe we saw these environmental considerations of soil erosion along this riverbank. The model in that case can run on the drone during flight without internet, but then you only need internet once the drone lands and you're going to act on that information because for example, if you're doing like a study of soil erosion, you don't need to be real time. You just need to be able to process and make use of that information once the drone finishes its flight. >> Well I can imagine a zillion use cases. I heard of a use case interview at a company that does computer vision to help people see if anyone's jumping the fence on their company. Like, they know what a body looks like climbing a fence and they can spot it. Pretty easy use case compared to probably some of the other things, but this is the horizontal use cases, its so many use cases. So how do you guys talk to the marketplace when you say, hey, we have generative AI for commuter vision. You might know language models that's completely different animal because vision's like the world, right? So you got a lot more to do. What's the difference? How do you explain that to customers? What can I build and what's their reaction? >> Because we're such a developer centric company, developers are usually creative and show you the ways that they want to take advantage of new technologies. I mean, we've had people use things for identifying conveyor belt debris, doing gas leak detection, measuring the size of fish, airplane maintenance. We even had someone that like a hobby use case where they did like a specific sushi identifier. I dunno if you know this, but there's a specific type of whitefish that if you grew up in the western hemisphere and you eat it in the eastern hemisphere, you get very sick. And so there was someone that made an app that tells you if you happen to have that fish in the sushi that you're eating. But security camera analysis, transportation flows, plant disease detection, really, you know, smarter cities. We have people that are doing curb management identifying, and a lot of these use cases, the fantastic thing about building tools for developers is they're a creative bunch and they have these ideas that if you and I sat down for 15 minutes and said, let's guess every way computer vision can be used, we would need weeks to list all the example use cases. >> We'd miss everything. >> And we'd miss. And so having the community show us the ways that they're using computer vision is impactful. Now that said, there are of course commercial industries that have discovered the value and been able to be out of the gate. And that's where we have the Fortune 100 customers, like we do. Like the retail customers in the Walmart sector, healthcare providers like Medtronic, or vehicle manufacturers like Rivian who all have very difficult either supply chain, quality assurance, in stock, out of stock, anti-theft protection considerations that require successfully making sense of the real world. >> Let me ask you a question. This is maybe a little bit in the weeds, but it's more developer focused. What are some of the developer profiles that you're seeing right now in terms of low-hanging fruit applications? And can you talk about the academic impact? Because I imagine if I was in school right now, I'd be all over it. Are you seeing Master's thesis' being worked on with some of your stuff? Is the uptake in both areas of younger pre-graduates? And then inside the workforce, What are some of the devs like? Can you share just either what their makeup is, what they work on, give a little insight into the devs you're working with. >> Leading developers that want to be on state-of-the-art technology build with RoboFlow because they know they can use the best in class open source. They know that they can get the most out of their data. They know that they can deploy extremely quickly. That's true among students as you mentioned, just as much as as industries. So we welcome students and I mean, we have research grants that will regularly support for people to publish. I mean we actually have a channel inside our internal slack where every day, more student publications that cite building with RoboFlow pop up. And so, that helps inspire some of the use cases. Now what's interesting is that the use case is relatively, you know, useful or applicable for the business or the student. In other words, if a student does a thesis on how to do, we'll say like shingle damage detection from satellite imagery and they're just doing that as a master's thesis, in fact most insurance businesses would be interested in that sort of application. So, that's kind of how we see uptick and adoption both among researchers who want to be on the cutting edge and publish, both with RoboFlow and making use of open source tools in tandem with the tool that we provide, just as much as industry. And you know, I'm a big believer in the philosophy that kind of like what the hackers are doing nights and weekends, the Fortune 500 are doing in a pretty short order period of time and we're experiencing that transition. Computer vision used to be, you know, kind of like a PhD, multi-year investment endeavor. And now with some of the tooling that we're working on in open source technologies and the compute that's available, these science fiction ideas are possible in an afternoon. And so you have this idea of maybe doing asset management or the aerial observation of your shingles or things like this. You have a few hundred images and you can de-risk whether that's possible for your business today. So there's pretty broad-based adoption among both researchers that want to be on the state of the art, as much as companies that want to reduce the time to value. >> You know, Joseph, you guys and your partner have got a great front row seat, ground floor, presented creation wave here. I'm seeing a pattern emerging from all my conversations on theCUBE with founders that are successful, like yourselves, that there's two kind of real things going on. You got the enterprises grabbing the products and retrofitting into their legacy and rebuilding their business. And then you have startups coming out of the woodwork. Young, seeing greenfield or pick a specific niche or focus and making that the signature lever to move the market. >> That's right. >> So can you share your thoughts on the startup scene, other founders out there and talk about that? And then I have a couple questions for like the enterprises, the old school, the existing legacy. Little slower, but the startups are moving fast. What are some of the things you're seeing as startups are emerging in this field? >> I think you make a great point that independent of RoboFlow, very successful, especially developer focused businesses, kind of have three customer types. You have the startups and maybe like series A, series B startups that you're building a product as fast as you can to keep up with them, and they're really moving just as fast as as you are and pulling the product out at you for things that they need. The second segment that you have might be, call it SMB but not enterprise, who are able to purchase and aren't, you know, as fast of moving, but are stable and getting value and able to get to production. And then the third type is enterprise, and that's where you have typically larger contract value sizes, slower moving in terms of adoption and feedback for your product. And I think what you see is that successful companies balance having those three customer personas because you have the small startups, small fast moving upstarts that are discerning buyers who know the market and elect to build on tooling that is best in class. And so you basically kind of pass the smell test of companies who are quite discerning in their purchases, plus are moving so quick they're pulling their product out of you. Concurrently, you have a product that's enterprise ready to service the scalability, availability, and trust of enterprise buyers. And that's ultimately where a lot of companies will see tremendous commercial success. I mean I remember seeing the Twilio IPO, Uber being like a full 20% of their revenue, right? And so there's this very common pattern where you have the ability to find some of those upstarts that you make bets on, like the next Ubers of the world, the smaller companies that continue to get developed with the product and then the enterprise whom allows you to really fund the commercial success of the business, and validate the size of the opportunity in market that's being creative. >> It's interesting, there's so many things happening there. It's like, in a way it's a new category, but it's not a new category. It becomes a new category because of the capabilities, right? So, it's really interesting, 'cause that's what you're talking about is a category, creating. >> I think developer tools. So people often talk about B to B and B to C businesses. I think developer tools are in some ways a third way. I mean ultimately they're B to B, you're selling to other businesses and that's where your revenue's coming from. However, you look kind of like a B to C company in the ways that you measure product adoption and kind of go to market. In other words, you know, we're often tracking the leading indicators of commercial success in the form of usage, adoption, retention. Really consumer app, traditionally based metrics of how to know you're building the right stuff, and that's what product led growth companies do. And then you ultimately have commercial traction in a B to B way. And I think that that actually kind of looks like a third thing, right? Like you can do these sort of funny zany marketing examples that you might see historically from consumer businesses, but yet you ultimately make your money from the enterprise who has these de-risked high value problems you can solve for them. And I selfishly think that that's the best of both worlds because I don't have to be like Evan Spiegel, guessing the next consumer trend or maybe creating the next consumer trend and catching lightning in a bottle over and over again on the consumer side. But I still get to have fun in our marketing and make sort of fun, like we're launching the world's largest game of rock paper scissors being played with computer vision, right? Like that's sort of like a fun thing you can do, but then you can concurrently have the commercial validation and customers telling you the things that they need to be built for them next to solve commercial pain points for them. So I really do think that you're right by calling this a new category and it really is the best of both worlds. >> It's a great call out, it's a great call out. In fact, I always juggle with the VC. I'm like, it's so easy. Your job is so easy to pick the winners. What are you talking about its so easy? I go, just watch what the developers jump on. And it's not about who started, it could be someone in the dorm room to the boardroom person. You don't know because that B to C, the C, it's B to D you know? You know it's developer 'cause that's a human right? That's a consumer of the tool which influences the business that never was there before. So I think this direct business model evolution, whether it's media going direct or going direct to the developers rather than going to a gatekeeper, this is the reality. >> That's right. >> Well I got to ask you while we got some time left to describe, I want to get into this topic of multi-modality, okay? And can you describe what that means in computer vision? And what's the state of the growth of that portion of this piece? >> Multi modality refers to using multiple traditionally siloed problem types, meaning text, image, video, audio. So you could treat an audio problem as only processing audio signal. That is not multimodal, but you could use the audio signal at the same time as a video feed. Now you're talking about multi modality. In computer vision, multi modality is predominantly happening with images and text. And one of the biggest releases in this space is actually two years old now, was clip, contrastive language image pre-training, which took 400 million image text pairs and basically instead of previously when you do classification, you basically map every single image to a single class, right? Like here's a bunch of images of chairs, here's a bunch of images of dogs. What clip did is used, you can think about it like, the class for an image being the Instagram caption for the image. So it's not one single thing. And by training on understanding the corpora, you basically see which words, which concepts are associated with which pixels. And this opens up the aperture for the types of problems and generalizability of models. So what does this mean? This means that you can get to value more quickly from an existing trained model, or at least validate that what you want to tackle with a computer vision, you can get there more quickly. It also opens up the, I mean. Clip has been the bedrock of some of the generative image techniques that have come to bear, just as much as some of the LLMs. And increasingly we're going to see more and more of multi modality being a theme simply because at its core, you're including more context into what you're trying to understand about the world. I mean, in its most basic sense, you could ask yourself, if I have an image, can I know more about that image with just the pixels? Or if I have the image and the sound of when that image was captured or it had someone describe what they see in that image when the image was captured, which one's going to be able to get you more signal? And so multi modality helps expand the ability for us to understand signal processing. >> Awesome. And can you just real quick, define clip for the folks that don't know what that means? >> Yeah. Clip is a model architecture, it's an acronym for contrastive language image pre-training and like, you know, model architectures that have come before it captures the almost like, models are kind of like brands. So I guess it's a brand of a model where you've done these 400 million image text pairs to match up which visual concepts are associated with which text concepts. And there have been new releases of clip, just at bigger sizes of bigger encoding's, of longer strings of texture, or larger image windows. But it's been a really exciting advancement that OpenAI released in January, 2021. >> All right, well great stuff. We got a couple minutes left. Just I want to get into more of a company-specific question around culture. All startups have, you know, some sort of cultural vibe. You know, Intel has Moore's law doubles every whatever, six months. What's your culture like at RoboFlow? I mean, if you had to describe that culture, obviously love the hacking story, you and your partner with the games going number one on Product Hunt next to Elon and Tesla and then hey, we should start a company two years later. That's kind of like a curious, inventing, building, hard charging, but laid back. That's my take. How would you describe the culture? >> I think that you're right. The culture that we have is one of shipping, making things. So every week each team shares what they did for our customers on a weekly basis. And we have such a strong emphasis on being better week over week that those sorts of things compound. So one big emphasis in our culture is getting things done, shipping, doing things for our customers. The second is we're an incredibly transparent place to work. For example, how we think about giving decisions, where we're progressing against our goals, what problems are biggest and most important for the company is all open information for those that are inside the company to know and progress against. The third thing that I'd use to describe our culture is one that thrives with autonomy. So RoboFlow has a number of individuals who have founded companies before, some of which have sold their businesses for a hundred million plus upon exit. And the way that we've been able to attract talent like that is because the problems that we're tackling are so immense, yet individuals are able to charge at it with the way that they think is best. And this is what pairs well with transparency. If you have a strong sense of what the company's goals are, how we're progressing against it, and you have this ownership mentality of what can I do to change or drive progress against that given outcome, then you create a really healthy pairing of, okay cool, here's where the company's progressing. Here's where things are going really well, here's the places that we most need to improve and work on. And if you're inside that company as someone who has a preponderance to be a self-starter and even a history of building entire functions or companies yourself, then you're going to be a place where you can really thrive. You have the inputs of the things where we need to work on to progress the company's goals. And you have the background of someone that is just necessarily a fast moving and ambitious type of individual. So I think the best way to describe it is a transparent place with autonomy and an emphasis on getting things done. >> Getting shit done as they say. Getting stuff done. Great stuff. Hey, final question. Put a plug out there for the company. What are you going to hire? What's your pipeline look like for people? What jobs are open? I'm sure you got hiring all around. Give a quick plug for the company what you're looking for. >> I appreciate you asking. Basically you're either building the product or helping customers be successful with the product. So in the building product category, we have platform engineering roles, machine learning engineering roles, and we're solving some of the hardest and most impactful problems of bringing such a groundbreaking technology to the masses. And so it's a great place to be where you can kind of be your own user as an engineer. And then if you're enabling people to be successful with the products, I mean you're working in a place where there's already such a strong community around it and you can help shape, foster, cultivate, activate, and drive commercial success in that community. So those are roles that tend themselves to being those that build the product for developer advocacy, those that are account executives that are enabling our customers to realize commercial success, and even hybrid roles like we call it field engineering, where you are a technical resource to drive success within customer accounts. And so all this is listed on roboflow.com/careers. And one thing that I actually kind of want to mention John that's kind of novel about the thing that's working at RoboFlow. So there's been a lot of discussion around remote companies and there's been a lot of discussion around in-person companies and do you need to be in the office? And one thing that we've kind of recognized is you can actually chart a third way. You can create a third way which we call satellite, which basically means people can work from where they most like to work and there's clusters of people, regular onsite's. And at RoboFlow everyone gets, for example, $2,500 a year that they can use to spend on visiting coworkers. And so what's sort of organically happened is team numbers have started to pull together these resources and rent out like, lavish Airbnbs for like a week and then everyone kind of like descends in and works together for a week and makes and creates things. And we call this lighthouses because you know, a lighthouse kind of brings ships into harbor and we have an emphasis on shipping. >> Yeah, quality people that are creative and doers and builders. You give 'em some cash and let the self-governing begin, you know? And like, creativity goes through the roof. It's a great story. I think that sums up the culture right there, Joseph. Thanks for sharing that and thanks for this great conversation. I really appreciate it and it's very inspiring. Thanks for coming on. >> Yeah, thanks for having me, John. >> Joseph Nelson, co-founder and CEO of RoboFlow. Hot company, great culture in the right place in a hot area, computer vision. This is going to explode in value. The edge is exploding. More use cases, more development, and developers are driving the change. Check out RoboFlow. This is theCUBE. I'm John Furrier, your host. Thanks for watching. (gentle music)

Published Date : Mar 3 2023

SUMMARY :

Welcome to this CUBE conversation You're in the middle of it. And the wave is still building the company is that you're doing. maybe 2% of the whole economy And as you know, when you it kind of was obvious to you guys? cognizant of the fact that I love that because I think, you know, And so what you do is issue on the infrastructure. and the drone will go and the marketplace when you say, in the sushi that you're eating. And so having the And can you talk about the use case is relatively, you know, and making that the signature What are some of the things you're seeing and pulling the product out at you because of the capabilities, right? in the ways that you the C, it's B to D you know? And one of the biggest releases And can you just real quick, and like, you know, I mean, if you had to like that is because the problems Give a quick plug for the place to be where you can the self-governing begin, you know? and developers are driving the change.

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Driving Business Results with Cloud


 

>> If you really want to make an impact to your business, it takes more than just moving your workloads into the cloud. So-called lift and shift is fine to reduce data center footprints and associated costs, but to really drive change, you don't want to simply "pave the cow path," as the saying goes. Rather, you need to think about the operating model, and that requires more comprehensive systems thinking. In other words, how will changes in technology affect business productivity? Or, you know what? Even flip that. What changes in my business process could lower cost, cut elapse times, and accelerate time to market, increase user productivity, and lower operational risks? And what role can technology play in supporting these mandates through modernization, automation, machine intelligence, and business resilience? And that's what we're here to discuss today. Welcome to Driving Business Results with Cloud Transformation, made Possible by Dell and DXC. My name is Dave Vellante, and today we're going to zoom out and explore many aspects of cloud transformation that leading organizations are acting on today. Yeah, sure, we're going to look at optimizing infrastructure, but we'll also dig deeper into cloud considerations, governance, compliance, and security angles, as well as the impact of emerging opportunities around edge and Industry 4.0. Our focus will be on how to remove barriers and help you achieve business outcomes. And to do this, our program features the long-term partnership between Dell and DXC. And we bring to this program six experts in three separate sessions, who are working directly with top organizations in virtually every industry to achieve high impact results. We're going to start with a conversation about cloud, the cloud operating model, and transforming key aspects of your infrastructure. And then we'll look into governance, security, and business resilience. And in our third session, we'll discuss exciting transformations that are occurring in smart manufacturing and facilities innovations. So let's get right into it with our first session. Enjoy the program. (bright music) Hello, and welcome to what is sure to be an insightful conversation about getting business results with cloud transformation. My name is Dave Vellante, and I'm here with James Miller, Chief Technologist for Cloud and Infrastructure Services, and Jay Dowling, Americas Sales Lead for Cloud and Infrastructure Services, both with DXC Technology. Gentlemen, thanks for your time today. Welcome to theCube. >> Great. Thanks for having us. >> Thank you Dave. Appreciate it. >> So let's get right into it. You know, I've talked to a lot of practitioners who've said, "Look, if you really want to drop zeros, like a lot of zeros to the bottom line, you can't just lift and shift." You really got to think about modernizing, the application portfolio. You got to think about your business model, and really think about transforming your business, particularly the operating model. So my first question, Jim, is, What role does the cloud play in modernization? >> Well, there are really three aspects that the, the cloud plays in modernization. You mentioned multiple zeros. One is cost optimization, and that can be achieved through business operations, through environmental, social, and governance. Also being more efficient with your IT investments. But that's not the only aspect. There's also agility and innovation. And that can be achieved through automation and productivity, speed to market for new features and functions, improvements in the customer experience, and the capability to metabolize a great deal more data in your environment, which the end result is an improvement in releasing of new things to the field. And finally, there's resilience. And I'm not really talking about IT resilience, but more of business resilience, to be able, to be able to handle operational risk, improve your securities and controls, deal with some of the talent gap that's in the industry, and also protect your brand reputation. So modernization is really about balancing these three aspects, cost optimization, agility and innovation, and resilience. >> So, so thank you for that. So Jay, I got to ask you, in the current climate, everybody's, you know, concerned, and there's not great visibility on the macro. So, Jim mentioned cost optimization. That seems to be one of the top areas that customers are focused on. The two I hear a lot are consolidating redundant vendors and optimizing cloud costs. So that's, you know, top of mind today. I think everybody really, you know, understands the innovation and, and, and agility piece, at least at a high level, maybe realizing it is different. And then the business resilience piece is really interesting because, you know, prior to the pandemic people, you know, they had a DR strategy, but they realized, "Wow, my business might not be that resilient." So Jay, my question to you is, What are you hearing when you talk to customers? What's the priority today? >> Yeah, the priority is an often overused term of digital transformation. You know, people want to get ready for next generation environments, customer experience, making sure they're improving, you know, how they engage with their clients and what their branding is. And what we find is a lot of clients don't have the underlying infrastructure in place today to get to where they want to get to. So cloud becomes an important element of that. But, you know, with DXC's philosophy, not everything goes to, not everything necessarily needs to go to cloud to be cost optimized, for instance. In many cases, you can run applications, you know, in your own data center, or on-prem, or in other environments, in a hybrid environment, or multi-cloud environment, and, and still be very optimized from a cost spend standpoint and also put yourself in position for modernization and for be able to do the, bring the things to the business that the clients are, you know, that their clients are looking for, like the CMO and the CFO, et cetera. Trying to use IT as a lever to drive business and to drive, you know, business acceleration and drive profitability, frankly. So there's a lot of dependency on infrastructure, but there's a lot of elements to it. And, and we advocate for, you know, there's not a single answer to that. We like to evaluate clients' environments and work with them to get them to an optimal target operating model, you know, so that they can really deliver on what the promises are for their departments. >> So if, let's talk about some of the, the barriers to realizing value in, in a context of modernization. We talked about cost optimization, agility, and, and, and resilience. But there's a business angle, and there's a technical angle here. 'Cause we always talk about people, process, and technology. Technology, oftentimes, CIOs will tell us, "Well, that's the easy part. We'll figured that out," whether it's true or not. But I agree, people and process is sometimes the tough one. So Jay, why don't you start. What do you see as the barriers, particularly from a business standpoint? >> I think people need to let their guard down and be open to the ideas that are, that are out there in the market from, you know, the, the standards that are being built by, you know, best in class models. And, and there's many people that have gone on, you know, cloud journeys and been very successful with it. There's others that have set high expectations with their business leaders that haven't necessarily met the goals that they need to meet or maybe haven't met them as quickly as they promised. So there's a, you know, there's a change management aspect that you'd need to look at with the, you know, with the environments. There's a, you know, there's a skillset set environment that they need to be prepared for. Do they have the people, you know, to deliver with the, you know, with the tools and the skills and the, and the models that that they're putting themselves in place for in the future versus where they are now? There's just a lot of, you know, there's a lot of different elements. It's not just a, "This price is better," or, "This can operate better than one environment over the other." I think we like to try to look at things holistically and make sure that, you know, we're being, you know, as much of a consultative advocate for the client, for where they want to go, what their destiny is, and based on what we've learned with other clients. You know, and we can bring those best practices forward because we've worked, you know, across such a broad spectra of clients versus them being somewhat contained and sometimes can't see outside of their own, you know, their own challenges, if you would. So they need, they need advocacy to help, you know, bring them to the next level. And we like to translate that through, you know, technology advances, which, you know, Jim's really good at doing for us. >> Yeah, Jim, is, is it, is it a, is the big barrier a skills issue, you know, bench strength? Are there other considerations from your perspective? >> Well, we, we've identified a number of factors that inhibit success of, of customers. One is thinking it's only a technology change in moving to cloud when it's much broader than that. There are changes in governance, changes in process that need to take place. The other is evaluating the cloud providers on their current pricing structure and performance. And, and we see pricing and structure changing dramatically every few months between the various cloud providers. And you have to be flexible enough to, to determine which providers you want. And it may not be feasible to just have a single cloud provider in this world. The other thing is a big bang approach to transformation, "I want to move everything, and I want to move it all at once." That's not necessarily the best approach. A well thought out cloud journey and strategy and timing your investments are really important to get at maximizing your business return on the journey to the cloud. And finally, not engaging stakeholders early and continuously. You have to manage expectations in moving to cloud on what business factors will get affected, how you will achieve your cost savings, and, and how you will achieve the business impact over the journey and reporting out on that with very strict metrics to all of the stakeholders. >> You know, mentioned multi-cloud just then. We had, in January 17th, we had our Supercloud 2 event. And Supercloud is basically, it's really multi, what multi-cloud should have been, I, I like to say. So it's this creating a common experience across clouds. And you guys were talking about, you know, there's different governance, there's different security, there's different pricing. So, and, and one of the takeaways from this event in talking to customers and practitioners and technologists is, you can't go it alone. So I wonder if you could talk about your partnership strategy, what do partners bring to the table, and what is, what is DXC's, you know, unique value? >> I'd be happy to lead with that if you'd like. >> Great. >> I, you know, we've got a vast partner ecosystem at DXC, given the size and, and the history of the company. I could use several examples. One of the larger partners in my particular space is Dell Technology, right? They're a great, you know, partner for us across many different areas of the business. It's not just a storage and compute play anymore. They're, they're on the edge. They're, you know, they're, they've got intelligence in their networking devices now. And they've really brought, you know, a lot of value to us as a partner. And, you know, there, there's somebody, you could look at Dell technology as somebody that might, you know, have a victim, you know, effect because of all the hyperscale activity and all the cloud activity. But they've really taken an outstanding attitude with this and say, "Listen, not all things are destined for cloud, or not all things would operate better in a cloud environment." And they like to be part of those discussions to see how they can, you know, how we can bring a multi-cloud environment, you know, both private and public, you know, to clients. And let's look at the applications and the infrastructure and, and what's, you know, what's the best optimal running environment, you know, for us to be able to bring, you know, the greatest value to the business with speed, with security, with, you know. And, you know, the things that they want to keep closest to the business are often things that you want to kind of, you know, keep on your premise or keep in your own data center. So they're, they're an ideal model of somebody that's resourced us well, partners with us well in the market. And, and we continue to grow that relationship day in and day out with those guys. And we really appreciate, you know, their support of our strategy, and, and we like to also compliment their strategy and work, you know, work together hand in hand in front of our clients. >> Yeah, you know, Jim, Matt Baker, who's the head of strategic planning at Dell talks about, "It's not a zero sum game." And I think, you know, you're right, Jay. I think initially people felt like, "Oh wow, it's, it is a zero sum game." But it's clearly not, and this idea of of, whether you call it supercloud or ubercloud or multicloud, clearly Dell is headed in in that direction. And I, you know, look at some of their future projects. There's their narrative. I'm curious from a technology standpoint, Jim, what your role is. Is it to make it all work? Is it to, you know, end to end? I wonder if you could help, you know, us understand that. >> Help us figure this out, Jim, here. (group laughing) >> Glad to expand on that. One of my key roles is developing our product roadmap for DXC offerings. And we do that roadmap in conjunction with our partners where we can leverage the innovation that our partners bring to the table. And we often utilize engineering resources from our partners to help us jointly build those offerings that adapt to changes in the market and also adapt to many of our customers changing needs over time. So my primary role is to look at the market, talk to our customers, and work with our partners to develop a product roadmap for delivering DXC products and services to our clients so that they can get the return on investment on their technology journeys. >> You know, we've been working with these two firms for a while now. Even predates, you know, the, the name DXC and that, that transformation. I'm curious as to what's, how you would respond to, "What's unique?" You know, you hear a lot about partnerships. You guys got a lot of competition. Dell has a lot of competition. What's specifically unique about this combination? >> I think, go ahead, Jim. >> I would say our unique approach, we call it cloud right. And that, that approach is making the right investments, at the right time, and on the right platforms. And our partners play a, play a key role in that. So we, we encourage our customers to not necessarily have a cloud first approach, but a cloud right approach where they place the workloads in the environment that is best suited from a technology perspective, a business perspective, and even a security and governance perspective. And, and the right approach might include mainframe. It might include an on-premises infrastructure. It could include private cloud, public cloud, and SaaS components all integrated together to deliver that value. >> Yeah, Jay, please. >> If you were... >> That is a complicated situation for a lot of customers. Chime in here. (Jay chuckles) >> And now, if you were speaking specifically to Dell here, like they, they also walk the talk, right? They invest in DXC as a partnership. They put people on the ground that their only purpose in life is to help DXC succeed with Dell in, you know, arm in arm in front of clients. And it's not, you know, it's not a winner take all thing at all. It's really a true partnership. They, they, they've brought solution resources. We have an account CTO. We've got executive sponsorship. We do regular QBR meetings. We have regular executive touchpoint meetings. It's really important that you keep a high level of intimacy with the client, with the partners, you know, and, and the, and the GSI community. And I, I've been with several GSIs, and, and this is an exceptional example of true partnership and commitment to success with Dell technology. I'm really extremely impressed on, on the engagement level that we've had there and, you know, continue to show a lot of support, you know, both for them. You know, there's other OEM partners, of course, in the market. There's always going to be other technology solutions for certain clients, but this has been a particularly strong element for us in our partnership and in our go-to-market strategy. >> Well, I think too, just my observation, is a lot of it's about trust. You guys have both earned the trust, the kind of, over the, over the years taking your arrows, you know, of over decades. And, and you know, that just doesn't happen overnight. So guys, I appreciate it. Thanks for your time. It's all about getting cloud right, isn't it? >> That's right. (chuckles) (Dave chuckles) >> Thank you Dave. Appreciate it very much. >> Dave, thank you. >> Jay, Jim, great to have you on. Keep it right there for more action on theCube. Be right back. (upbeat guitar music) (keyboard clicks) Welcome back to the program. My name is Dave Vellante, and in this session we're going to explore one of the more interesting topics of the day. IoT for smart factories and with me are Todd Edmunds, the Global CTO of Smart Manufacturing Edge and Digital Twins at Dell Technologies. That is such a cool title. (Todd chuckles) I want to be you. And Dr. Aditi Banerjee who's the Vice President, General Manager for Aerospace Defense and Manufacturing at DXC Technology. Another really cool title. Folks, welcome to the program. Thanks for coming on. >> Thank you. >> Thanks, Dave. Great to be here. >> Nice to be here. So, Todd, let's start with you. We hear a lot about Industry 4.0, smart factories, IIoT. Can you briefly explain like what is Industry 4.0 all about, and why is it important for the manufacturing industry? >> Yeah, sure, Dave. You know, it's been around for quite a while. And it's got, it's gone by multiple different names, as you said, Industry 4.0, smart manufacturing, industrial IoT, smart factory, but it all really means the same thing. Its really applying technology to get more out of the factories and the facilities that you have to do your manufacturing. So being much more efficient, implementing really good sustainability initiatives. And so we really look at that by saying, "Okay, what are we going to do with technology to really accelerate what we've been doing for a long, long time?" So it's really not, it's not new. It's been around for a long time. What's new is that manufacturers are looking at this not as a one-off, two-off, individual use case point of view. But instead they're saying, "We really need to look at this holistically, thinking about a strategic investment in how we do this, not to just enable one or two use cases, but enable many, many use cases across the spectrum." I mean, there's tons of them out there. There's predictive maintenance, and there's OEE, overall equipment effectiveness, and there's computer vision. And all of these things are starting to percolate down to the factory floor. But it needs to be done in a little bit different way. And, and, and really, to really get those outcomes that they're looking for in smart factory, or Industry 4.0, or however you want to call it, and truly transform. Not just throw an Industry 4.0 use case out there, but to do the digital transformation that's really necessary and to be able to stay relevant for the future. You know, I heard it once said that you have three options. Either you digitally transform and stay relevant for the future, or you don't and fade into history like 52% of the companies that used to be on the Fortune 500 since 2000, right? And so really that's a key thing, and we're seeing that really, really being adopted by manufacturers all across the globe. >> Yeah so, Aditi, that's like digital transformation is almost synonymous with business transformation. So is there anything you'd add to what Todd just said? >> Absolutely. Though, I would really add that what really drives Industry 4.0 is the business transformation, what we are able to deliver in terms of improving the manufacturing KPIs and the KPIs for customer satisfaction, right? For example, improving the downtime, you know, or decreasing the maintenance cycle of the equipments, or improving the quality of products, right? So I think these are a lot of business outcomes that our customers are looking at while using Industry 4.0 and the technologies of Industry 4.0 to deliver these outcomes. >> So Aditi, I wonder if I could stay with you. And maybe this is a bit esoteric. But when I first started researching IoT and, and, and Industrial IoT 4.0, et cetera, I felt, you know, while there could be some disruptions in the ecosystem, I kind of came to the conclusion that large manufacturing firms, aerospace defense companies, the firms building out critical infrastructure, actually had kind of an incumbent advantage in a great opportunity. Of course, then I saw on TV, somebody now they're building homes with 3D printers. Its like, blows your mind. So that's pretty disruptive, but, so, but they got to continue. The incumbents have to continue to invest in the future. They're well capitalized. They're pretty good businesses, very good businesses. But there's a lot of complexities involved in kind of connecting the old house to the new addition that's being built, if you will, or this transformation that we're talking about. So my question is, How are your customers preparing for this new era? What are the key challenges that they're facing and the, the blockers, if you will? >> Yeah, I mean the customers are looking at Industry 4.0 for greenfield factories, right? That is where the investments are going directly into building the factories with the new technologies, with the new connectivities, right, for the machines. For example, industrial IoT, having the right type of data platforms to drive computational analytics and outcomes, as well as looking at edge versus cloud type of technologies, right? Those are all getting built in the greenfield factories. However, for the install-based factories, right, that is where our customers are looking at, "How do I modernize these factories? How do I connect the existing machine?" And that is where some of the challenges come in on, you know, the legacy system connectivity that they need to think about. Also, they need to start thinking about cybersecurity and operation technology security, right, because now you are connecting the factories to each other, right? So cybersecurity becomes top of mind, right? So there is definitely investment that is involved. Clients are creating roadmaps for digitizing and modernizing these factories and investments in a very strategic way, right? So perhaps they start with the innovation program, and then they look at the business case, and they scale it up, right? >> Todd, I'm glad Aditi brought up security. Because if you think about the operations technology, you know, folks, historically, they air gapped, you know, the systems. That's how they created security. That's changed. The business came in and said, "Hey, we got to, we got to connect. We got to make it intelligent." So that's, that's got to be a big challenge as well. >> It, it, it absolutely is Dave. And, and you know, you can no longer just segment that because really, to get all of those efficiencies that we talk about, that IoT and Industrial IoT and Industry 4.0 promise, you have to get data out of the factory. But then you got to put data back in the factory. So no longer is it just firewalling everything is really the answer. So you really have to have a comprehensive approach to security, but you also have to have a comprehensive approach to the cloud and what that means. And does it mean a continuum of cloud all the way down to the edge, right down to the factory? It absolutely does because no one approach has the answer to everything. The more you go to the cloud, the broader the attack surface is. So what we're seeing is a lot of our customers approaching this from a, kind of that, that hybrid, you know, "write once, run anywhere" on the factory floor down to the edge. And one of the things we're seeing, too, is to help distinguish between what is the edge, and that, and, and bridge that gap between, like Dave, you talked about IT and OT. And also help that, what Aditi talked about, is the greenfield plants versus the brownfield plants that they call it, that are the legacy ones and modernizing those. Is, it's great to kind of start to delineate. What does that mean? Where's the edge? Where's the IT and the OT? We see that from a couple of different ways. We start to think about really two edges in a manufacturing floor. We talk about an industrial edge that sits, or some people call it a far edge or a thin edge, sits way down on that plan. It consists of industrial hardened devices that do that connectivity. The hard stuff about, "How do I connect to this obsolete legacy protocol and what do I do with it?" And create that next generation of data that has context. And then we see another edge evolving above that, which is much more of a data and analytics and enterprise grade application layer that sits down in the factory itself that helps figure out where we're going to run this. Does it connect to the cloud? Do we run applications on-prem? Because a lot of times that on-prem application is, is, needs to be done because that's the only way that its going to, it's going to work because of security requirements, because of latency requirements, performance, and a lot of times cost. It's really helpful to build that multiple edge strategy because then you kind of, you consolidate all of those resources, applications, infrastructure, hardware, into a centralized location. Makes it much, much easier to really deploy and manage that security. But it also makes it easier to deploy new applications, new use cases, and become the foundation for DXC's expertise and applications that they deliver to our customers as well. >> Todd, how complex are these projects? I mean, I feel like it's kind of the, the digital equivalent of building the Hoover Dam. I mean, it, it, it's, (chuckles) it, it, so. Yeah, how long does a typical project take? I know it varies, but what, you know, what are the critical success factors in terms of delivering business value quickly? >> Yeah, that's a great question in that, in that we're, you know, like I said at the beginning, we, this is not new. Smart factory and Industry 4.0 is not new. It's been, it's, people have been trying to implement the holy grail of smart factory for a long time. And what we're seeing is a switch, a little bit of a switch, or quite a bit of a switch, to where the enterprise and the IT folks are having a much bigger say and have a lot to offer to be able to help that complexity. So instead of deploying a computer here, and a gateway there, and a server there, I mean, you go walk into any manufacturing plant and you can see servers sitting underneath someone's desk or a, or a PC in a closet somewhere running a critical production application. So we're seeing the enterprise have a much bigger say at the table, much louder voice at the table to say, "We've been doing this at enterprise all the time. We, we know how to really consolidate, bring hyper-converged applications, hyper-converged infrastructure, to really accelerate these kind of applications, really accelerate the outcomes that are needed to really drive that smart factory, and start to bring that same capabilities down into the, on the factory floor." That way, if you do it once to make it easier to implement, you can repeat that. You can scale that. You can manage it much easily. And you can then bring that all together because you have the security in one centralized location. So we're seeing manufacturers, yeah, that first use case may be fairly difficult to implement and we got to go down in and see exactly what their problems are. But when the infrastructure is done the correct way, when that, think about how you're going to run that and how are you going to optimize the engineering. Well, let's take that, what you've done in that one factory, and then set. Let's that, make that across all the factories, including the factory that we're in, but across the globe. That makes it much, much easier. You really do the hard work once and then repeat, almost like a cookie cutter. >> Got it. Thank you. Aditi, what about the skillsets available to apply these, to these projects? You got to have knowledge of digital, AI, data, integration. Is there a talent shortage to get all this stuff done? >> Yeah, I mean definitely, a lot. Different types of skillsets are needed from a traditional manufacturing skillset, right? Of course, the basic knowledge of manufacturing is, is important. But the, the digital skillset sets like, you know, IoT, having a skillset in different protocols for connecting the machines, right, that experience that comes with it, data and analytics, security, augmented virtual reality programming. You know, again, looking at robotics and the digital twin. So you know, it's a lot more connectivity software, data driven skillsets that are needed to smart factory to life at scale. And, you know, lots of firms are, you know, recruiting these types of skill, resources with these skillsets to, you know, accelerate their smart factory implementation, as well as consulting firms like DXC Technology and others. We, we, we recruit. We, we train our talent to, to provide these services. >> Got it. Aditi, I wonder if we could stay on you. Let's talk about the partnership between DXC and Dell. What are you doing specifically to simplify the move to Industry 4.0 for customers? What solutions are you offering? How are you working together, Dell and DXC, to, to bring these to market? >> Yeah, Dell and DXC have a very strong partnership. You know, and we work very closely together to, to create solutions, to create strategies, and how we, we are going to jointly help our clients, right? So areas that we have worked closely together is edge compute, right, how that impacts the smart factory. So we have worked pretty closely in that area. We're also looked at vision technologies, you know. How do we use that at the edge to improve the quality of products, right? So we have several areas that we collaborate in. And our approach is that we, we want to bring solutions to our client, and as well as help them scale those solutions with the right infrastructure, the right talent, and the right level of security. So we bring a comprehensive solution to our clients. >> So, Todd, last question, kind of similar but different. You know, why Dell DXC? Pitch me. What's different about this partnership? You know, where do you, are you confident that, you know, you're going to be, deliver the best value to, to customers? >> Absolutely. Great question. You know, there's no shortage of bespoke solutions that are out there. There's hundreds of people that can come in and do individual use cases and do these things. And just, and, and, and that's, that's where it ends. What Dell and DXC Technology together bring to the table is, we do the optimization, the optimization of the engineering of those previously bespoke solutions upfront, together, right? The power of our scalables, enterprise-grade, structured, you know, industry standard infrastructure, as well as our expertise in delivering package solutions that really accelerate with DXC's expertise and reputation as a global, trusted, trusted advisor. Be able to really scale and repeat those solutions that DXC is so really, really good at. And, and Dell's infrastructure, and our, what, 30,000 people across the globe that are really, really good at that, at that scalable infrastructure, to be able to repeat. And then it really lessens the risk that our customers have and really accelerates those solutions. So it's again, not just one individual solutions, it's all of the solutions that not just drive use cases, but drive outcomes with those solutions. >> Yeah, the, you're right, the partnership has gone, I mean, I first encountered it back in, I think it was 2010, May of 2010, we had you, you guys both on theCube. I think you were talking about converged infrastructure. And I had a customer on, and it was, actually a manufacturing customer, was quite interesting. And back then it was, "How do we kind of replicate what's coming in the cloud?" And, and you guys have obviously taken it into the digital world. Really want to thank you for your time today. Great conversation, and love to have you back. >> Thank you so much. >> Absolutely. >> It was a pleasure speaking with you. >> I agree. >> All right, keep it right there for more discussions that educate and inspire on theCube. (bright music) Welcome back to the program and we're going to dig into the number one topic on the minds of every technology organization. That's cybersecurity. You know, survey data from ETR, our data partner, shows that among CIOs and IT decision makers, cybersecurity continues to rank as the number one technology priority to be addressed in the coming year. That's ahead of even cloud migration and analytics. And with me to discuss this critical topic area are Jim Shook, who's the Global Director of Cybersecurity and Compliance Practice at Dell Technologies, and he's joined by Andrew Gonzalez, who focuses on Cloud and Infrastructure consulting at DXC Technology. Gents, welcome. Good to have you. >> Thanks Dave. Great to be here. >> Thank you. >> Jim, let's start with you. What are you seeing from the front lines in terms of the attack surface, and, and how are customers responding these days? >> It's always up and down and back and forth. The bad actors are smart. They adapt to everything that we do. So we're seeing more and more kind of living off the land. They're not necessarily deploying malware. Makes it harder to find what they're doing. And I think though, Dave, we've, we've adapted, and this whole notion of cyber resilience really helps our customers figure this out. And the idea there goes beyond cybersecurity, it's, "Let's protect as much as possible, so we keep the bad actors out as much as we can. But then, let's have the ability to adapt to and recover to the extent that the bad actors are successful." So we're recognizing that we can't be perfect a hundred percent of the time against a hundred percent of the bad actors. Let's keep out what we can, but then recognize and have that ability to recover when necessary. >> Yeah, thank you. So Andrew, you know, I like what Jim was saying about living off the land, of course, meaning using your own tooling against you, kind of hiding in plain sight, if you will. But, and, and as Jim is saying, you, you can't be perfect. But, so given that, what's your perspective on what good cybersecurity hygiene looks like? >> Yeah, so you have to understand what your crown jewel data looks like, what a good copy of a recoverable asset looks like. When you look at an attack, if it were to occur, right, how you get that copy of data back into production. And not only that, but what that golden image actually entails. So, whether it's networking, storage, some copy of a source code, intellectual property, maybe CMBD data, or an active directory, or DNS dump, right? Understanding what your data actually entails so that you can protect it and that you can build out your recovery plan for it. >> So, and where's that live? Where's that gold copy? You put on a yellow sticky? No, it's got to be, (chuckles) you got to be somewhere safe, right? So you have to think about that chain as well, right? >> Absolutely. Yeah. You, so, a lot of folks have not gone through the exercise of identifying what that golden copy looks like. Everyone has a DR scenario, everyone has a DR strategy, but actually identifying what that golden crown jewel data, let's call it, actually entails is one aspect of it. And then where to put it, how to protect it, how to make it immutable and isolated, that's the other portion of it. >> You know, if I go back to sort of earlier part of last decade, you know, cybersecurity was kind of a checkoff item. And as you got toward the middle part of the decade, and I'd say clearly by 2016, it, security became a boardroom issue. It was on the agenda, you know, every quarter at the board meetings. So compliance is no longer the driver, is, is my point. The driver is business risk, real loss of reputation or data, you know, it's, or money, et cetera. What are the business implications of not having your cyber house in order today? >> They're extreme, Dave. I mean the, you know, the bad actors are good at what they do. These losses by organizations, tens, hundreds of millions into the billions sometimes, plus the reputational damage that's difficult to, to really measure. There haven't been a lot of organizations that have actually been put out of business by an attack, at least not directly on, if they're larger organizations. But that's also on the table, too. So you can't just rely on, "Oh we need to do, you know, A, B and C because our regulators require it." You need to look at what the actual risk is to the business, and then come up with a strategy from there. >> You know, Jim, staying with you, one of the most common targets we hear of attackers is to go after the backup corpus. So how should customers think about protecting themselves from that tactic? >> Well, Dave, you hit on it before, right? Everybody's had the backup and DR strategies for a long time going back to requirements that we had in place for physical disaster or human error. And that's a great starting point for resilience capability. But that's all it is, is a starting point. Because the bad actors will, they also understand that you have those capabilities, and, and they've adapted to that. In every sophisticated attack that we see, the backup is a target. The bad actors want to take it out, or corrupt it, or do something else to that backup so that it's not available to you. That's not to say they're always successful, and it's still a good control to have in place because maybe it will survive. But you have to plan beyond that. So the capabilities that we talk about with resilience, let's harden that backup infrastructure. You've already got it in place. Let's use the capabilities that are there like immutability and other controls to make it more difficult for the bad actors to get to. But then as Andrew said, that gold copy, that critical systems, you need to protect that in something that's more secure, which commonly we, we might say a cyber vault. Although, there's a lot of different capabilities for cyber vaulting, some far better than others, and that's some of the things that we focus on. >> You know, it's interesting, but I've talked to a lot of CIOs about this, is prior to the pandemic, they, you know, had their, as you're pointing out, Jim, they had their DR strategy in place, but they felt like they weren't business resilient. And they realized that when we had the forced march to digital. So Andrew, are there solutions out there to help with this problem? Do you guys have an answer to this? >> Yeah, absolutely. So I'm glad you brought up resiliency. We, we take a position that to be cyber resilient, it includes operational resiliency. It includes understanding at the C level what the implication of an attack means, as we stated, and then, how to recover back into production. When you look at protecting that data, not only do you want to put it into what we call a vault, which is a Dell technology that is an offline immutable copy of your crown jewel data, but also how to recover it in real time. So DXC offers a, I don't want to call it a turnkey solution since we architect these specific to each client needs, right, when we look at what client data entails, their recovery point, objectives, recovery time objectives, what we call quality of the restoration. But when we architect these out, we look at not only how to protect the data, but how to alert and monitor for attacks in real time, how to understand what we should do when a breach is in progress, putting together with our security operations centers, a forensic and recovery plan and a runbook for the client, and then being able to cleanse and remediate so that we can get that data back into production. These are all services that DXC offers in conjunction with the Dell solution to protect, and recover, and keep bad actors out. And if we can't keep them out to ensure that we are back into production in short order. >> You know, this, this discussion we've been having about DR kind of versus resilience, and, and you were just talking about RPO and RTO. I mean, it used to be that a lot of firms wouldn't even test their recovery 'cause it was too risky. Or, you know, maybe they tested it on, you know, July 4th or something like that. But, but it, I'm inferring that's changed. I wonder if we could, you know, double click on recovery? How hard is it to, to, to test that recovery, and, and how quickly are you seeing organizations recover from attacks? >> So it depends, right, on the industry vertical, what kind of data. Again, a financial services client compared to a manufacturing client are going to be two separate conversations. We've seen it as quickly as being able to recover in six hours, in 12 hours. In some instances we have the grace period of a day to a couple of days. We do offer the ability to run scenarios once a quarter where we can stand up in our systems the production data that we are protecting to ensure that we have a good recoverable copy. But it depends on the client. >> I really like the emphasis here, Dave, that you're raising and that Andrew's talking about. It's not on the technology of how the data gets protected. It's focused on the recovery. That's all that we want to do. And so the solution with DXC really focuses on generating that recovery for customers. I think where people get a little bit twisted up on their testing capability is, you have to think about different scenarios. So there are scenarios where the attack might be small. It might be limited to a database or an application. It might be really broadly based like the NotPetya attacks from a few years ago. The regulatory environment, we call those attacks severe but plausible. So you can't necessarily test everything with the infrastructure, but you can test some things with the infrastructure. Others, you might sit around on a tabletop exercise or walk through what that looks like to really get that, that recovery kind of muscle, muscle memory so that people know what to do when those things occur. But the key to it, as Andrew said before, have to focus down, "What are those critical applications? What do we need, what's most important? What has to come back first?" And that really will go a long way towards having the right recovery points and recovery times from a cyber disaster. >> Yeah, makes sense. Understanding the value of that data is going to inform you how to, how to respond and how to prioritize. Andrew, one of the things that we hear a lot on theCube, especially lately, is around, you know, IOT, IIOT, Industry 4.0, the whole OT security piece of it. And the problem being that, you know, traditionally, operations technologies have been air gapped, often by design. But as businesses, increasingly they're driving initiatives like Industry 4.0, and they're connecting these OT systems to IT systems. They're, you know, driving efficiency, preventative maintenance, et cetera. So a lot of data flowing through the pipes, if you will. What are you seeing in terms of the threats to critical infrastructure and how should customers think about addressing these issues? >> Yeah, so bad actors, you know, can come in many forms. We've seen instances of social engineering. We've seen, you know, a USB stick dropped in a warehouse. That data that is flowing through the IoT device is as sensitive now as your core mainframe infrastructure data. So when you look at it from a protection standpoint, conceptually, it's not dissimilar from what we've been been talking about where you want to understand, again, what the most critical data is. Looking at IoT data and applications is no different than your core systems now, right? Depending on what your, your business is, right? So when, when we're looking at protecting these, yes, we want firewalls, yes, we want air gap solutions, yes, we want front end protection, but we're looking at it from a resiliency perspective. Putting that data, understanding what what data entails to put in the vault from an IoT perspective is just as critical as as it is for your core systems. >> Jim, anything you can add to this topic? >> Yeah, I think you hit on the, the key points there. Everything is interconnected. So even in the days where maybe people thought the OT systems weren't online, oftentimes the IT systems are talking to them, or controlling them, SCADA systems, or perhaps supporting them. Think back to the pipeline attack of last year. All the public testimony was that the OT systems didn't get attacked directly. But there was uncertainty around that, and the IT systems hadn't been secured. So that caused the OT systems to have to shut down. It certainly is a different recovery when you're shutting them down on your own versus being attacked, but the outcome was the same that the business couldn't operate. So you really have to take all of those into account. And I think that does go back to exactly what Andrew's saying, understanding your critical business services, and then the applications and data and other components that support those and drive those, and making sure those are protected. You understand them, you have the ability to recover them if necessary. >> So guys, I mean, you made the point. I mean, you're right. The adversary is highly capable. They're motivated 'cause the ROI is so, it's so lucrative. It's like this never ending battle that cybersecurity pros, you know, go through. It really is kind of frontline sort of technical heroes, if you will. And so, but sometimes it just feels daunting. Why are you optimistic about the future of, of cyber from the good guy's perspective? >> I think we're coming at the problem the right way, Dave. So that, that focus, I'm so pleased with the idea that we are planning that the systems aren't going to be hundred percent capable every single time, and let's figure that out, right? That's, that's real world stuff. So just as the bad actors continue to adapt and expand, so do we. And I think the differences there, the common criminals, it's getting harder and harder for them. The more sophisticated ones, they're tough to beat all the time. And of course, you've raised the question of some nation states and other activities. But there's a lot more information sharing. There's a lot more focus from the business side of the house and not just the IT side of the house that we need to figure these things out. >> Yeah, to, to add to that, I think furthering education for the client base is important. You, you brought up a point earlier. It used to be a boardroom conversation due to compliance reasons. Now, as we have been in the market for a while, we continue to mature the offerings. It's further education for not only the business itself, but for the IT systems and how they interconnect, and working together so that these systems can be protected and continue to be evolved and continue to be protected through multiple frameworks as opposed to seeing it as another check the box item that the board has to adhere to. >> All right, guys, we got to go. Thank you so much. Great conversation on a, on a really important topic. Keep up the good work. Appreciate it. >> Thanks Dan. >> Thank you. >> All right, and thank you for watching. Stay tuned for more excellent discussions around the partnership between Dell Technologies and DXC Technology. We're talking about solving real world problems, how this partnership has evolved over time, really meeting the changing enterprise landscape challenges. Keep it right there. (bright music) Okay, we hope you enjoyed the program and learned some things about cloud transformation and modernizing your business that will inspire you to action. Now if you want to learn more, go to the Dell DXC partner page shown here, or click on the URL in the description. Thanks for watching everybody and on behalf of our supporters, Dell and DXC, good luck. And as always, get in touch if we can be of any assistance. (bright music)

Published Date : Feb 14 2023

SUMMARY :

and help you achieve business outcomes. Thanks for having us. You really got to think about modernizing, in releasing of new things to the field. So Jay, my question to you is, and to drive, you know, the barriers to realizing value to deliver with the, you know, on the journey to the cloud. you know, unique value? I'd be happy to lead to kind of, you know, keep on your premise And I think, you know, you're right, Jay. Help us figure this out, Jim, here. that our partners bring to the table. Even predates, you know, the, the name DXC And, and the right approach Chime in here. the partners, you know, And, and you know, that just That's right. Thank you Dave. Jay, Jim, great to have you on. Great to be here. Nice to be here. that you have to do your manufacturing. add to what Todd just said? the downtime, you know, and the, the blockers, if you will? that they need to think about. they air gapped, you know, the systems. on the factory floor down to the edge. I know it varies, but what, you know, in that we're, you know, You got to have knowledge of So you know, it's a lot to simplify the move and the right level of security. that, you know, you're going to be, it's all of the solutions love to have you back. to be addressed in the coming year. What are you seeing from the front lines and have that ability to So Andrew, you know, I and that you can build out how to make it immutable and isolated, of last decade, you know, "Oh we need to do, you know, A, B and C to go after the backup corpus. for the bad actors to get to. they, you know, had their, and then being able to on, you know, July 4th We do offer the ability to But the key to it, as Andrew said before, to inform you how to, how to We've seen, you know, a USB So that caused the OT you know, go through. and not just the IT side of the house that the board has to adhere to. Thank you so much. that will inspire you to action.

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Ankur Shah, Palo Alto Networks | AWS re:Invent 2022


 

>>Good afternoon from the Venetian Expo, center, hall, whatever you wanna call it, in Las Vegas. Lisa Martin here. It's day four. I'm not sure what this place is called. Wait, >>What? >>Lisa Martin here with Dave Ante. This is the cube. This is day four of a ton of coverage that we've been delivering to you, which, you know, cause you've been watching since Monday night, Dave, we are almost at the end, we're almost at the show wrap. Excited to bring back, we've been talking about security, a lot about security. Excited to bring back a, an alumni to talk about that. But what's your final thoughts? >>Well, so just in, in, in the context of security, we've had just three in a row talking about cyber, which is like the most important topic. And I, and I love that we're having Palo Alto Networks on Palo Alto Networks is the gold standard in security. Talk to CISOs, they wanna work with them. And, and it was, it's interesting because I've been following them for a little bit now, watch them move to the cloud and a couple of little stumbling points. But I said at the time, they're gonna figure it out and, and come rocking back. And they have, and the company's just performing unbelievably well despite, you know, all the macro headwinds that we love to >>Talk about. So. Right. And we're gonna be unpacking all of that with one of our alumni. As I mentioned, Anker Shaw is with us, the SVP and GM of Palo Alto Networks. Anker, welcome back to the Cub. It's great to see you. It's been a while. >>It's good to be here after a couple years. Yeah, >>Yeah. I think three. >>Yeah, yeah, for sure. Yeah. Yeah. It's a bit of a blur after Covid. >>Everyone's saying that. Yeah. Are you surprised that there are still this many people on the show floor? Cuz I am. >>I am. Yeah. Look, I am not, this is my fourth, last year was probably one third or one fourth of this size. Yeah. But pre covid, this is what dream went looked like. And it's energizing, it's exciting. It's just good to be doing the good old things. So many people and yeah. Amazing technology and innovation. It's been incredible. >>Let's talk about innovation. I know you guys, Palo Alto Networks recently acquired cyber security. Talk to us a little bit about that. How is it gonna compliment Prisma? Give us all the scoop on that. >>Yeah, for sure. Look, some of the recent, the cybersecurity attacks that we have seen are related to supply chain, the colonial pipeline, many, many supply chain. And the reason for that is the modern software supply chain, not the physical supply chain, the one that AWS announced, but this is the software supply chain is really incredibly complicated, complicated developers that are building and shipping code faster than ever before. And the, the site acquisition at the center, the heart of that was securing the entire supply chain. White House came with a new initiative on supply chain security and SBO software bill of material. And we needed a technology, a company, and a set of people who can really deliver to that. And that's why we acquired that for supply chain security, otherwise known as cicd, security, c >>IDC security. Yeah. So how will that complement PRIs McCloud? >>Yeah, so look, if you look at our history lease over the last four years, we have been wanting to, our mission mission has been to build a single code to cloud platform. As you may know, there are over 3000 security vendors in the industry. And we said enough is enough. We need a platform player who can really deliver a unified cohesive platform solution for our customers because they're sick and tired of buying PI point product. So our mission has been to deliver that code to cloud platform supply chain security was a missing piece and we acquired them, it fits right really nicely into our portfolio of products and solution that customers have. And they'll have a single pin of glass with this. >>Yeah. So there's a lot going on. You've got, you've got an adversary that is incredibly capable. Yeah. These days and highly motivated and extremely sophisticated mentioned supply chain. It's caused a shift in, in CSO strategies, talking about the pandemic, of course we know work from home that changed things. You've mentioned public policy. Yeah. And, and so, and as well you have the cloud, cloud, you know, relatively new. I mean, it's not that new, but still. Yeah. But you've got the shared responsibility model and not, not only do you have the shared responsibility model, you have the shared responsibility across clouds and OnPrem. So yes, the cloud helps with security, but that the CISO has to worry about all these other things. The, the app dev team is being asked to shift left, you know, secure and they're not security pros. Yeah. And you know, kind audit is like the last line of defense. So I love this event, I love the cloud, but customers need help in making their lives simpler. Yeah. And the cloud in and of itself, because, you know, shared responsibility doesn't do that. Yeah. That's what Palo Alto and firms like yours come in. >>Absolutely. So look, Jim, this is a unable situation for a lot of the Cisco, simply because there are over 26 million developers, less than 3 million security professional. If you just look at all the announcement the AWS made, I bet you there were like probably over 2000 features. Yeah. I mean, they're shipping faster than ever before. Developers are moving really, really fast and just not enough security people to keep up with the velocity and the innovation. So you are right, while AWS will guarantee securing the infrastructure layer, but everything that is built on top of it, the new machine learning stuff, the new application, the new supply chain applications that are developed, that's the responsibility of the ciso. They stay up at night, they don't know what's going on because developers are bringing new services and new technology. And that's why, you know, we've always taken a platform approach where customers and the systems don't have to worry about it. >>What AWS new service they have, it's covered, it's secured. And that's why the adopters, McCloud and Palo Alto Networks, because regardless what developers bring, security is always there by their side. And so security teams need just a simple one click solution. They don't have to worry about it. They can sleep at night, keep the bad actors away. And, and that's, that's where Palo Alto Networks has been innovating in this area. AWS is one of our biggest partners and you know, we've integrated with, with a lot of their services. We launch about three integrations with their services. And we've been doing this historically for more and >>More. Are you still having conversations with the security folks? Or because security is a board level conversation, are your conversations going up a stack because this is a C-suite problem, this is a board level initiative? >>Absolutely. Look, you know, there was a time about four years ago, like the best we could do is director of security. Now it's just so CEO level conversation, board level conversation to your point, simply because I mean, if, if all your financial stuff is going to public cloud, all your healthcare data, all your supply chain data is going to public cloud, the board is asking very simple question, what are you doing to secure that? And to be honest, the question is simple. The answer's not because all the stuff that we talked about, too many applications, lots and lots of different services, different threat vectors and the bad actors, the bad guys are always a step ahead of the curve. And that's why this has become a board level conversation. They wanna make sure that things are secure from the get go before, you know, the enterprises go too deep into public cloud adoption. >>I mean there, there was shift topics a little bit. There was hope or kinda early this year that that cyber was somewhat insulated from the sort of macro press pressures. Nobody's safe. Even the cloud is sort of, you know, facing those, those headwinds people optimizing costs. But one thing when you talk to customers is, I always like to talk about that, that optiv graph. We've all seen it, right? And it's just this eye test of tools and it's a beautiful taxonomy, but there's just too many tools. So we're seeing a shift from point tools to platforms because obviously a platform play, and that's a way. So what are you seeing in the, in the field with customers trying to optimize their infrastructure costs with regard to consolidating to >>Platforms? Yeah. Look, you rightly pointed out one thing, the cybersecurity industry in general and Palo Alto networks, knock on wood, the stocks doing well. The macro headwinds hasn't impacted the security spend so far, right? Like time will tell, we'll, we'll see how things go. And one of the primary reason is that when you know the economy starts to slow down, the customers again want to invest in platforms. It's simple to deploy, simple to operationalize. They want a security partner of choice that knows that they, it's gonna be by them through the entire journey from code to cloud. And so that's why platform, especially times like these are more important than they've ever been before. You know, customers are investing in the, the, the product I lead at Palo Alto network called Prisma Cloud. It's in the cloud network application protection platform seen app space where once again, customers that investing in platform from quote to cloud and avoiding all the point products for sure. >>Yeah. Yeah. And you've seen it in, in Palo Alto's performance. I mean, not every cyber firm has is, is, >>You know, I know. Ouch. CrowdStrike Yeah. >>Was not. Well you saw that. I mean, and it was, and and you know, the large customers were continuing to spend, it was the small and mid-size businesses Yeah. That were, were were a little bit soft. Yeah. You know, it's a really, it's really, I mean, you see Okta now, you know, after they had some troubles announcing that, you know, their, their, their visibility's a little bit better. So it's, it's very hard to predict right now. And of course if TOMA Brava is buying you, then your stock price has been up and steady. That's, >>Yeah. Look, I think the key is to have a diversified portfolio of products. Four years ago before our CEO cash took over the reins of the company, we were a single product X firewall company. Right. And over time we have added XDR with the first one to introduce that recently launched x Im, you know, to, to make sure we build an NextGen team, cloud security is a completely net new investment, zero trust with access as workers started working remotely and they needed to make sure enterprises needed to make sure that they're accessing the applications securely. So we've added a lot of portfolio products over time. So you have to remain incredibly diversified, stay strong, because there will be stuff like remote work that slowed down. But if you've got other portfolio product like cloud security, while those secular tailwinds continue to grow, I mean, look how fast AWS is growing. 35, 40%, like $80 billion run rate. Crazy at that, that scale. So luckily we've got the portfolio of products to ensure that regardless of what the customer's journey is, macro headwinds are, we've got portfolio of solutions to help our customers. >>Talk a little bit about the AWS partnership. You talked about the run rate and I was reading a few days ago. You're right. It's an 82 billion arr, massive run rate. It's crazy. Well, what are, what is a Palo Alto Networks doing with aws and what's the value in it to help your customers on a secure digital transformation journey? >>Well, absolutely. We have been doing business with aws. We've been one of their security partners of choice for many years now. We have a presence in the marketplace where customers can through one click deploy the, the several Palo Alto Networks security solutions. So that's available. Like I said, we had launch partner to many, many new products and innovation that AWS comes up with. But always the day one partner, Adam was talking about some of those announcements and his keynote security data lake was one of those. And they were like a bunch of others related to compute and others. So we have been a partner for a long time, and look, AWS is an incredibly customer obsessed company. They've got their own security products. But if the customer says like, Hey, like I'd like to pick this from yours, but there's three other things from Palo Alto Networks or S MacCloud or whatever else that may be, they're open to it. And that's the great thing about AWS where it doesn't have to be wall garden open ecosystem, let the customer pick the best. >>And, and that's, I mean, there's, there's examples where AWS is directly competitive. I mean, my favorite example is Redshift and Snowflake. I mean those are directly competitive products, but, but Snowflake is an unbelievably great relationship with aws. They do cyber's, I think different, I mean, yeah, you got guard duty and you got some other stuff there. But generally speaking, the, correct me if I'm wrong, the e the ecosystem has more room to play on AWS than it may on some other clouds. >>A hundred percent. Yeah. Once again, you know, guard duty for examples, we've got a lot of customers who use guard duty and Prisma Cloud and other Palo Alto Networks products. And we also ingest the data from guard duty. So if customers want a single pane of glass, they can use the best of AWS in terms of guard duty threat detection, but leverage other technology suite from, you know, a platform provider like Palo Alto Networks. So you know, that that, you know, look, world is a complicated place. Some like blue, some like red, whatever that may be. But we believe in giving customers that choice, just like AWS customers want that. Not a >>Problem. And at least today they're not like directly, you know, in your space. Yeah. You know, and even if they were, you've got such a much mature stack. Absolutely. And my, my frankly Microsoft's different, right? I mean, you see, I mean even the analysts were saying that some of the CrowdStrike's troubles for, cuz Microsoft's got the good enough, right? So >>Yeah. Endpoint security. Yeah. And >>Yeah, for sure. So >>Do you have a favorite example of a customer where Palo Alto Networks has really helped them come in and, and enable that secure business transformation? Anything come to mind that you think really shines a light on Palo Alto Networks and what it's able to do? >>Yeah, look, we have customers across, and I'm gonna speak to public cloud in general, right? Like Palo Alto has over 60,000 customers. So we've been helping with that business transformation for years now. But because it's reinvented aws, the Prisma cloud product has been helping customers across different industry verticals. Some of the largest credit card processing companies, they can process transactions because we are running security on top of the workloads, the biggest financial services, biggest healthcare customers. They're able to put the patient health records in public cloud because Palo Alto Networks is helping them get there. So we are helping accelerated that digital journey. We've been an enabler. Security is often perceived as a blocker, but we have always treated our role as enabler. How can we get developers and enterprises to move as fast as possible? And like, my favorite thing is that, you know, moving fast and going digital is not a monopoly of just a tech company. Every company is gonna be a tech company Oh absolutely. To public cloud. Yes. And we want to help them get there. Yeah. >>So the other thing too, I mean, I'll just give you some data. I love data. I have a, ETR is our survey partner and I'm looking at Data 395. They do a survey every quarter, 1,250 respondents on this survey. 395 were Palo Alto customers, fortune 500 s and P 500, you know, big global 2000 companies as well. Some small companies. Single digit churn. Yeah. Okay. Yeah. Very, very low replacement >>Rates. Absolutely. >>And still high single digit new adoption. Yeah. Right. So you've got that tailwind going for you. Yeah, >>Right. It's, it's sticky because especially our, our main business firewall, once you deploy the firewall, we are inspecting all the network traffic. It's just so hard to rip and replace. Customers are getting value every second, every minute because we are thwarting attacks from public cloud. And look, we, we, we provide solutions not just product, we just don't leave the product and ask the customers to deploy it. We help them with deployment consumption of the product. And we've been really fortunate with that kind of gross dollar and netten rate for our customers. >>Now, before we wrap, I gotta tease, the cube is gonna be at Palo Alto Ignite. Yeah. In two weeks back here. I think we're at D mgm, right? We >>Were at D MGM December 13th and >>14th. So give us a little, show us a little leg if you would. What could we expect? >>Hey, look, I mean, a lot of exciting new things coming. Obviously I can't talk about it right now. The PR Inc is still not dry yet. But lots of, lots of new innovation across our three main businesses. Network security, public cloud, security, as well as XDR X. Im so stay tuned. You know, you'll, you'll see a lot of new exciting things coming up. >>Looking forward to it. >>We are looking forward to it. Last question on curf. You, if you had a billboard to place in New York Times Square. Yeah. You're gonna take over the the the Times Square Nasdaq. What does the billboard say about why organizations should be working with Palo Alto Networks? Yeah. To really embed security into their dna. Yeah. >>You know when Jim said Palo Alto Networks is the gold standard for security, I thought it was gonna steal it. I think it's pretty good gold standard for security. But I'm gonna go with our mission cyber security partner's choice. We want to be known as that and that's who we are. >>Beautifully said. Walker, thank you so much for joining David in the program. We really appreciate your insights, your time. We look forward to seeing you in a couple weeks back here in Vegas. >>Absolutely. Can't have enough of Vegas. Thank you. Lisa. >>Can't have in Vegas, >>I dunno about that. By this time of the year, I think we can have had enough of Vegas, but we're gonna be able to see you on the cubes coverage, which you could catch up. Palo Alto Networks show Ignite December, I believe 13th and 14th on the cube.net. We want to thank Anker Shaw for joining us. For Dave Ante, this is Lisa Martin. You're watching the Cube, the leader in live enterprise and emerging tech coverage.

Published Date : Dec 2 2022

SUMMARY :

whatever you wanna call it, in Las Vegas. This is the cube. you know, all the macro headwinds that we love to And we're gonna be unpacking all of that with one of our alumni. It's good to be here after a couple years. It's a bit of a blur after Covid. Cuz I am. It's just good to be doing the good old things. I know you guys, Palo Alto Networks recently acquired cyber security. And the reason for that is the modern software supply chain, not the physical supply chain, IDC security. Yeah, so look, if you look at our history lease over the last four years, And the cloud in and of itself, because, you know, shared responsibility doesn't do that. And that's why, you know, we've always taken a platform approach of our biggest partners and you know, we've integrated with, with a lot of their services. this is a board level initiative? the board is asking very simple question, what are you doing to secure that? So what are you seeing in the, And one of the primary reason is that when you know the I mean, not every cyber firm has You know, I know. I mean, and it was, and and you know, the large customers were continuing to And over time we have added XDR with the first one to introduce You talked about the run rate and I was reading a And that's the great thing about AWS where it doesn't have to be wall garden open I think different, I mean, yeah, you got guard duty and you got some other stuff there. So you know, And at least today they're not like directly, you know, in your space. So my favorite thing is that, you know, moving fast and going digital is not a monopoly of just a tech So the other thing too, I mean, I'll just give you some data. Absolutely. So you've got that tailwind going for you. and ask the customers to deploy it. Yeah. So give us a little, show us a little leg if you would. Hey, look, I mean, a lot of exciting new things coming. You're gonna take over the the the Times Square Nasdaq. But I'm gonna go with our mission cyber We look forward to seeing you in a couple weeks back here in Vegas. Can't have enough of Vegas. but we're gonna be able to see you on the cubes coverage, which you could catch up.

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Haiyan Song & Dan Woods, F5 | AWS re:Invent 2022


 

>> Hello friends and welcome back to Fabulous Las Vegas, Nevada. We are here at AWS re:Invent in the heat of day three. Very exciting time. My name is Savannah Peterson, joined with John Furrier here on theCUBE. John, what's your, what's your big hot take from the day? Just from today. >> So right now the velocity of content is continuing to flow on theCUBE. Thank you, everyone, for watching. The security conversations. Also, the cost tuning of the cloud kind of vibe is going on. You're hearing that with the looming recession, but if you look at the show it's the bulk of the keynote time spent talking is on data and security together. So Security, Security Lake, Amazon, they continue to talk about security. This next segment's going to be awesome. We have a multi-, eight-time CUBE alumni coming back and great conversation about security. I'm looking forward to this. >> Alumni VIP, I know, it's so great. Actually, both of these guests have been on theCUBE before so please welcome Dan and Haiyan. Thank you both for being here from F5. How's the show going? You're both smiling and we're midway through day three. Good? >> It's so exciting to be here with you all and it's a great show. >> Awesome. Dan, you having a good time too? >> It's wearing me out. I'm having a great time. (laughter) >> It's okay to be honest. It's okay to be honest. It's wearing out our vocal cords for sure up here, but it is definitely a great time. Haiyan, can you tell me a little bit about F5 just in case the audience isn't familiar? >> Sure, so F5 we specialize in application delivery and security. So our mission is to deliver secure and optimize any applications, any APIs, anywhere. >> I can imagine you have a few customers in the house. >> Absolutely. >> Yeah, that's awesome. So in terms of a problem that, well an annoyance that we've all had, bots. We all want the anti-bots. You have a unique solution to this. How are you helping AWS customers with bots? Let's send it to you. >> Well we, we collect client side signals from all devices. We might study how it does floating point math or how it renders emojis. We analyze those signals and we can make a real time determination if the traffic is from a bot or not. And if it's from a bot, we could take mitigating action. And if it's not, we just forward it on to origin. So client side signals are really important. And then the second aspect of bot protection I think is understanding that bot's retool. They become more sophisticated. >> Savannah: They learn. >> They learn. >> They unfortunately learn as well. >> Exactly, yeah. So you have to have a second stage what we call retrospective analysis where you're looking over all the historical transactions, looking for anything that may have been missed by a realtime defense and then updating that stage one that real time defense to deal with the newly discovered threat. >> Let's take a step back for a second. I want to just set the table in the context for the bot conversation. Bots, automation, that's, people know like spam bots but Amazon has seen the bot networks develop. Can you scope the magnitude and the size of the problem of bots? What is the problem? And give a size of what this magnitude of this is. >> Sure, one thing that's important to realize is not all bots are bad. Okay? Some bots are good and you want to identify the automation from those bots and allow listed so you don't interfere with what they're doing. >> I can imagine that's actually tricky. >> It is, it is. Absolutely. Yeah. >> Savannah: Nuanced. >> Yeah, but the bad bots, these are the ones that are attempting credential stuffing attacks, right? They're trying username password pairs against login forms. And because of consumer habits to reuse usernames and passwords, they end up taking over a lot of accounts. But those are the bookends. There are all sorts of types of bots in between those two bookends. Some are just nuisance, like limited time offer bots. You saw some of this in the news recently with Ticketmaster. >> That's a spicy story. >> Yeah, it really is. And it's the bots that is causing that problem. They use automation to buy all these concert tickets or sneakers or you know, any limited time offer project. And then they resell those on the secondary market. And we've done analysis on some of these groups and they're making millions of dollars. It isn't something they're making like 1200 bucks on. >> I know Amazon doesn't like to talk about this but the cloud for its double edged sword that it is for all the greatness of the agility spinning up resources bots have been taking advantage of that same capability to hide, change, morph. You've seen the matrix when the bots attacked the ship. They come out of nowhere. But Amazon actually has seen the bot problem for a long time, has been working on it. Talk about that kind of evolution of how this problem's being solved. What's Amazon doing about, how do you guys help out? >> Yeah, well we have this CloudFront connector that allows all Amazon CloudFront customers to be able to leverage this technology very, very quickly. So what historically was available only to like, you know the Fortune 500 at most of the global 2000 is now available to all AWS customers who are using CloudFront just by really you can explain how do they turn it on in CloudFront? >> Yeah. So I mean CloudFront technologies like that is so essential to delivering the digital experience. So what we do is we do a integration natively. And so if your CloudFront customers and you can just use our bot defense solution by turning on, you know, that traffic. So go through our API inspection, go through our bot inspection and you can benefit from all the other efficiencies that we acquired through serving the highest and the top institutions in the world. >> So just to get this clarification, this is a super important point. You said it's native to the service. I don't have to bolt it on? Is it part of the customer experience? >> Yeah, we basically built the integration. So if you're already a CloudFront customer and you have the ability to turn on our bot solutions without having to do the integration yourself. >> Flick a switch and it's on. >> Haiyan: Totally. >> Pretty much. >> Haiyan: Yeah. >> That's how I want to get rid of all the spam in my life. We've talked a lot about the easy button. I would also like the anti-spam button if we're >> Haiyan: 100% >> Well we were talking before you came on camera that there's a potentially a solution you can sit charge. There are techniques. >> Yeah. Yeah. We were talking about the spam emails and I thought they just charge, you know 10th of a penny for every sent email. It wouldn't affect me very much. >> What's the, are people on that? You guys are on this but I mean this is never going to stop. We're going to see the underbelly of the web, the dark web continue to do it. People are harvesting past with the dark web using bots that go in test challenge credentials. I mean, it's just happening. It's never going to stop. What's, is it going to be that cat and mouse game? Are we going to see solutions? What's the, when are we going to get some >> Well it's certainly not a cat and mouse game for F5 customers because we win that battle every time. But for enterprises who are still battling the bots as a DIY project, then yes, it's just going to be a cat and mouse. They're continuing to block by IP, you know, by rate limiting. >> Right, which is so early 2000's. >> Exactly. >> If we're being honest. >> Exactly. And the attackers, by the way, the attackers are now coming from hundreds of thousands or even millions of IP addresses and some IPs are using one time. >> Yeah, I mean it seems like such an easy problem to circumnavigate. And still be able to get in. >> What are I, I, let's stick here for a second. What are some of the other trends that you're seeing in how people are defending if they're not using you or just in general? >> Yeah, maybe I'll add to to that. You know, when we think about the bot problem we also sort of zoom out and say, Hey, bot is only one part of the problem when you think about the entire digital experience the customer experiencing, right? So at F5 we actually took a more holistic sort of way to say, well it's about protecting the apps and applications and the APIs that's powering all of those. And we're thinking not only the applications APIs we're thinking the infrastructure that those API workloads are running. So one of the things we're sharing since we acquired Threat Stack, we have been busy doing integrations with our distributed cloud services and we're excited. In a couple weeks you will hear announcement of the integrated solution for our application infrastructure protection. So that's just another thing. >> On that Threat Stack, does that help with that data story too? Because it's a compliance aspect as well. >> Yeah, it helps with the telemetries, collecting more telemetries, the data story but is also think about applications and APIs. You can only be as secure as the infrastructure you're running on it, right? So the infrastructure protection is a key part of application security. And the other dimension is not only we can help with the credentials, staffing and, and things but it's actually thinking about the customer's top line. Because at the end of the day when all this inventory are being siphoned out the customer won't be happy. So how do we make sure their loyal customers have the right experience so that can improve their top line and not just sort of preventing the bots. So there's a lot of mission that we're on. >> Yeah, that surprise and delight in addition to that protection. >> 100% >> If I could talk about the evolution of an engagement with F5. We first go online, deploy the client side signals I described and take care of all the bad bots. Okay. Mitigate them. Allow list all the good bots, now you're just left with human traffic. We have other client side signals that'll identify the bad humans among the good humans and you could deal with them. And then we have additional client side signals that allow us to do silent continuous authentication of your good customers extending their sessions so they don't have to endure the friction of logging in over and over and over. >> Explain that last one again because I think that was, that's, I didn't catch that. >> Yeah. So right now we require a customer to enter in their username and password before we believe it's them. But we had a customer who a lot of their customers were struggling to log in. So we did analysis and we realized that our client side signals, you know of all those that are struggling to log in, we're confident like 40% of 'em are known good customers based on some of these signals. Like they're doing floating point math the way they always have. They're rendering emojis the way they always have all these clients that signals are the same. So why force that customer to log in again? >> Oh yeah. And that's such a frustrating user experience. >> So true. >> I actually had that thought earlier today. How many time, how much of my life am I going to spend typing my email address? Just that in itself. Then I could crawl back under the covers but >> With the biometric Mac, I forget my passwords. >> Or how about solving CAPTCHA's? How fun is that? >> How many pictures have a bus? >> I got one wrong the other day because I had to pick all the street signs. I got it wrong and I called a Russian human click farm and figured out why was I getting it wrong? And they said >> I love that you went down this rabbit hole deeply. >> You know why that's not a street sign. That's a road sign, they told me. >> That's the secret backdoor. >> Oh well yeah. >> Talk about your background because you have fascinating background coming from law enforcement and you're in this kind of role. >> He could probably tell us about our background. >> They expunge those records. I'm only kidding. >> 25, 30 years in working in local, state and federal law enforcement and intelligence among those an FBI agent and a CIA cyber operations officer. And most people are drawn to that because it's interesting >> Three letter agencies can get an eyebrow raise. >> But I'll be honest, my early, early in my career I was a beat cop and that changed my life. That really did, that taught me the importance of an education, taught me the criminal mindset. So yeah, people are drawn to the FBI and CIA background, but I really value the >> So you had a good observation eye for kind of what, how this all builds out. >> It all kind of adds up, you know, constantly fighting the bad guys, whether they're humans, bots, a security threat from a foreign nation. >> Well learning their mindset and learning what motivates them, what their objectives are. It is really important. >> Reading the signals >> You don't mind slipping into the mind of a criminal. It's a union rule. >> Right? It actually is. >> You got to put your foot and your hands in and walk through their shoes as they say. >> That's right. >> The bot networks though, I want to get into, is not it sounds like it's off the cup but they're highly organized networks. >> Dan: They are. >> Talk about the aspect of the franchises or these bots behind them, how they're financed, how they use the money that they make or ransomware, how they collect, what's the enterprise look like? >> Unfortunately, a lot of the nodes on a botnet are now just innocent victim computers using their home computers. They can subscribe to a service and agree to let their their CPU be used while they're not using it in exchange for a free VPN service, say. So now bad actors not, aren't just coming from you know, you know, rogue cloud providers who accept Bitcoin as payment, they're actually coming from residential IPs, which is making it even more difficult for the security teams to identify. It's one thing when it's coming from- >> It's spooky. I'm just sitting here kind of creeped out too. It's these unknown hosts, right? It's like being a carrier. >> You have good traffic coming from it during the day. >> Right, it appears normal. >> And then malicious traffic coming from it. >> Nefarious. >> My last question is your relationship with Amazon. I'll see security center piece of this re:Invent. It's always been day zero as they say but really it's the security data lake. A lot of gaps are being filled in the products. You kind of see that kind of filling out. Talk about the relationship with F5 and AWS. How you guys are working together, what's the status? >> We've been long-term partners and the latest release the connector for CloudFront is just one of the joint work that we did together and try to, I think, to Dan's point, how do we make those technology that was built for the very sophisticated big institutions to be available for all the CloudFront customers? So that's really what's exciting. And we also leverage a lot of the technology. You talked about the data and our entire solution are very data driven, as you know, is automation. If you don't use data, you don't use analytics, you don't use AI, it's hard to really sort of win that war. So a lot of our stuff, it's very data driven >> And the benefit to customers is what? Access? >> The customer's access, the customer's top line. We talked about, you know, like how we're really bringing better experiences at the end of the day. F5's mission is try to bring a better digital world to life. >> And it's also collaborative. We've had a lot of different stories here on on the set about companies collaborating. You're obviously collaborating and I also love that we're increasing access, not just narrowing this focus for the larger companies at scale already, but making sure that these companies starting out, a lot of the founders probably milling around on the floor right now can prevent this and ensure that user experience for their customers. throughout the course of their product development. I think it's awesome. So we have a new tradition here on theCUBE at re:Invent, and since you're alumni, I feel like you're maybe going to be a little bit better at this than some of the rookies. Not that rookies can't be great, but you're veterans. So I feel strong about this. We are looking for your 30-second Instagram reel hot take. Think of it like your sizzle of thought leadership from the show this year. So eventually eight more visits from now we can compile them into a great little highlight reel of all of your sound bites over the evolution of time. Who wants to give us their hot take first? >> Dan? >> Yeah, sure. >> Savannah: You've been elected, I mean you are an agent. A former special agent >> I guess I want everybody to know the bot problem is much worse than they think it is. We go in line and we see 98, 99% of all login traffic is from malicious bots. And so it is not a DIY project. >> 98 to 99%? That means only 1% of traffic is actually legitimate? >> That's right. >> Holy moly. >> I just want to make sure that everybody heard you say that. >> That's right. And it's very common. Didn't happen once or twice. It's happened a lot of times. And when it's not 99 it's 60 or it's 58, it's high. >> And that's costing a lot too. >> Yes, it is. And it's not just in fraud, but think about charges that >> Savannah: I think of cloud service providers >> Cost associated with transactions, you know, fraud tools >> Savannah: All of it. >> Yes. Sims, all those things. There's a lot of costs associated with that much automation. So the client side signals and multi-stage defense is what you need to deal with it. It's not a DIY project. >> Bots are not DIY. How would you like to add to that? >> It's so hard to add to that but I would say cybersecurity is a team sport and is a very data driven solution and we really need to sort of team up together and share intelligence, share, you know, all the things we know so we can be better at this. It's not a DIY project. We need to work together. >> Fantastic, Dan, Haiyan, so great to have you both back on theCUBE. We look forward to seeing you again for our next segment and I hope that the two of you have really beautiful rest of your show. Thank you all for tuning into a fantastic afternoon of coverage here from AWS re:Invent. We are live from Las Vegas, Nevada and don't worry we have more programming coming up for you later today with John Furrier. I'm Savannah Peterson. This is theCUBE, the leader in high tech coverage.

Published Date : Dec 1 2022

SUMMARY :

in the heat of day three. So right now the velocity of content How's the show going? It's so exciting to Dan, you It's wearing me out. just in case the audience isn't familiar? So our mission is to deliver secure few customers in the house. How are you helping AWS determination if the traffic that real time defense to deal with in the context for the bot conversation. and you want to identify the automation It is, it is. Yeah, but the bad bots, And it's the bots that for all the greatness of the the Fortune 500 at most of the and the top institutions in the world. Is it part of the customer experience? built the integration. We've talked a lot about the easy button. solution you can sit charge. and I thought they just charge, you know the dark web continue to do it. are still battling the bots And the attackers, by the way, And still be able to get in. What are some of the other So one of the things we're sharing does that help with that data story too? and not just sort of preventing the bots. to that protection. care of all the bad bots. Explain that last one again the way they always have. And that's such a my life am I going to spend With the biometric Mac, all the street signs. I love that you went down That's a road sign, they told me. because you have fascinating He could probably tell They expunge those records. And most people are drawn to can get an eyebrow raise. taught me the importance So you had a good observation eye fighting the bad guys, and learning what motivates into the mind of a criminal. It actually is. You got to put your is not it sounds like it's off the cup for the security teams to identify. kind of creeped out too. coming from it during the day. And then malicious but really it's the security data lake. lot of the technology. at the end of the day. a lot of the founders elected, I mean you are an agent. to know the bot problem everybody heard you say that. It's happened a lot of times. And it's not just in fraud, So the client side signals How would you like to add to that? all the things we know so I hope that the two of you have

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Kevin Farley, MariaDB | AWS re:Invent 2022 - Global Startup Program


 

>>Well, hello everybody at John Wallace here on the Cube, and glad to have you along here for day two of our coverage here at AWS Reinvent 22. We're up in the global startup program, which is part of AWS's Startup Showcase, and I've got Kevin Farley with me. He is the director of Strategic Alliances with Maria Day db. And Kevin, good to see you this morning. Good to see you, John. Thanks for joining us. Thank >>You. >>Appreciate it. Yeah. First off, tell us about Maria db. Sure. Obviously data's your thing. Yep. But to share that with some folks at home who might not be familiar with your offering. >>Yeah. So Maria DB's been around as a corporate entity for 10 plus years, and we have a massive customer base. You know, there's a billion downloads from Docker Hub, 75% of the Fortune 500. We have an enormous sea of really happy users. But what we realize is that all of these users are really thinking about what do we, what does it mean to transform it? What does cloud modernization mean? And how do we build a strategy on something we really love to drive it into the cloud and take it to the future. So what we launched about two years ago, two and a half years ago, is Skye. It's our database as a service. It leverages all the best elements, what we provide on the enterprise platform. It marries to the AWS cloud, and it really provides the best of both worlds for our >>Customers. So in your thought then, what, what problem is that solving? >>I think what you see in the overall database market is that many people have been using what we would call legacy technology. There's been lots of sort of stratification and mixes of different database solutions. All of them come with some promise, and all of 'em come with a lot of compromise. So I think what the market is really looking for is something that can take what they know and love, can bring it to the cloud and can survive the port drive the performance and scale. That completely changes the landscape, especially as you think about what modern data needs look like, right? What people did 10 years ago with the exponential scale of data no longer works. And what they need is something that not only can really deliver against their core business values and their core business deliverables, but gets 'em to the future. How do we drive something new? How do we innovate? How do we change the game? And I think what we built with AWS really delivers what we call cloud scale. It's taking something that is the best technology, and I as a V can build, marrying it to, you know, Kubernetes layer, marrying it to global availability, thinking about having true global high availability across all of your environments and really delivering that to customers through an integrated partnership. >>Could we see this coming? I mean, because you know data, right? I mean, yeah, we, we, everybody talked about the tsunami of growth, you know, >>Back 10 >>Sure. 11 years ago. But, but maybe the headlights didn't go far enough or, or, but, but you could see that there was going to be crunch time. >>There's no doubt. And I think that this has been a, there's, there's been these sort of pocket solutions, right? So if you think at the entire no sequel world, right? People said, oh, I need scale, I can get it, but what do I have to give up asset compliance? So I have to change the way I think about what data is and how I, I can govern it. So there's been these things that deliver on half the promise, but there's never been something that comes together and really drives what we deliver through CIQ is something called expand. So distributed SQL really tied to the SQL Query language, having that asset data. So having everything you need without the compromise built on the cloud allows you to scale out and allows you to think about, I can actually do exponential layers of, of data, data modeling, data querying, complete read, write, driving that forward. And I think it gives us a whole nother dynamic that we can deliver on in a way that hasn't been before. And I think that's kind of the holy grail of what people are looking for is how am I building modern applications and how do I have a database in the cloud that's really gonna support >>It? You know, you talk about distributed, you know, sequel and, and I mean, there's a little mystery behind it, isn't there? Or at least maybe not mystery. There's a little, I guess, confusion or, or just misunderstanding. I mean, I, how, nail that down a little bit. I >>Would say the best way to say it, honestly, this is the great thing, is it people believe it's too good to be true. And I think what we see over and over >>Again, you know, what they say about that. >>But this is the great part is, you know, you know, we've just had two taste studies recently with aws, with HIT labs and Certified power, both on expand, both proof in the pudding. They did the POCs, they're like, oh my God, this works. If you watch the keynote yesterday, you know, Adam had a slide that was, you know, as big as the entire room and it highlighted Samsung and they said, you know, we're doing 80,000 requests per second. So the, you know, the story there is that AWS is able as, as an entity with their scale and their breadth to handle that kind of workload. But guess what that is? That's MariaDB expand underneath there driving all of that utilization. So it's already there, it's already married, it's already in the cloud, and now we're taking it to a completely different level with a fully managed database solution. Right? >>How impressive is that? Right? I mean, you would think that somebody out there who, I mean that that volume, that kind of capacity is, is mind blowing. >>I mean, to your kind of previous point, it's like one of those things, do I see what's coming and it's here, right? You know, it's, is it actually ever gonna be possible? And now we're showing that it really is on a daily basis for some of the biggest brands in the world. We're also seeing companies moving off not only transitioning from, you know, MariaDB or myse, but all of the big licensed, you know, conversions as well. So you think about Oracle DBS Bank is one of our biggest customers, one of the largest Oracle conversions in the world onto MariaDB. And now thinking about what is the promise of connecting that to the cloud? How do you take things that you're currently doing, OnPrem delivering a hybrid model that also then starts to say, Hey, here's my path to cloud modernization. Skye gives me that bridge. And then you take it one layer farther and you think about multi-cloud, right? That's one of the things that's critical that ISVs can really only deliver in a meaningful way, is how can we have a solution for a customer that we can take to any availability zone. We can have performance, proximity, cost, proximity. We're always able to have that total data dexterity across any environment we need and we can build on that for the future. >>So if, if we're talking about cloud database and there's so many good things going forward here. You're talking about easy use and scalability and all that. But as with ever have you talked about this, there's some push and there's some pull. Yeah. So, so what's the, what's the other side that's still, you know, you that you think has to be >>Addressed? And I think that's a great question. So there's, we see that there's poll, right? We've seen these deals, this pipeline growth, this, there's great adoption. But what I think we're still not at the point of massive hockey stick adoption is that customers still don't fully understand the capabilities distributed SQL and the power they can actually deliver. So the more we drive case studies, the more we drive POCs, the more we prove the model, I think you're gonna see just a massive adoption scale. And I also think customers are tired of doing lots of different things in lots of different pockets. So neither one of the key elements of Sky SQL is we can do both transactional and analytical data out of the same database driven by the same proxy. So what, instead of having DBAs and developers try to figure out, okay, I'm gonna pull from this database here. >>Yeah. That there, it's, it's this big spaghetti wire concept that is super expensive and super time intensive. So the ability to write modern applications and pull data from both pockets and really be able to have that as a seamless entity and deliver that to customers is massive. I mean, another part of the keynote yesterday was a new deliverable, like kind of no etl. Adam talked about Aurora and Redshift and the massive complexity of what used to exist for getting data back and forth. You also have to pay for two different databases. It's super expensive. So I think the idea that you can take the real focus of AWS and US is customer value. How do you deliver that next thing that changes the game? Always utilizes AWS delivers on that promise, but then takes a net new technology that really starts to think about how do we bring things together? How do we make it more simple? How do we make it more powerful? And how do we deliver more customer value as we go forward? >>But you know, if, if I'm, I'm still an on-prim guy, just pretend I'm not saying I am. Just pretend I just for the sake of the discussion here, it's like I just can't let it go. Yeah. Right. I, I still, you know, there's control, there's the known versus the unknown. The uncertain. Yeah. So twist my arm just a little bit more and get me over the hum. >>Well, first of all, you don't have to, right? And there's gonna be some industries and some verticals that will always have elements of their business that will be OnPrem. Guess what? We make the best based in the world. It can be MariaDB, but there's those that then say, these, these elements of our business are gonna be far more effective moving to the cloud. So we give you Skye, there's a natural symbiotic bridge between everything we do and how we deliver it. Where you can be hybrid and it's great. You can adopt the cloud as your business needs grow. And you can have multi-cloud. This is that, that idea that you can, can have your cake and eat it too, right? You can literally have all these elements of your business met without these big pressure to say, you gotta throw that away. You gotta move to this. It's really, how do you kind of gracefully adopt the cloud in a way that makes sense for your business? Where are you trying to drive your business? Is it time to value, right? Is it governance? Is it is there's different elements of what matters the most to individual businesses. You know, we wanna address those and we can address >>Those. So you're saying you don't have to dive >>In, you don't have to dive >>In. You, you can, you can go ankle deep, knee deep, whatever you wanna >>Do. Absolutely. And you know, some of the largest MariaDB users still have massive, massive on-prem implementations. And that's okay. But there's elements that are starting to fall behind. There's cost savings, there's things that they need to do in the cloud that they can't do. OnPrem. And that's where expand Skye really says, okay, here is your platform. Grow as you want to, migrate as you want to. And we're there every step along the way. We, we also provide a whole Sky DBA team. Some guys just say, I wanna get outta the database world at all. This is, this is expensive, it's costly and it's difficult to be an expert. So you can bring in our DBA team and they'll man and run, they'll, they'll run your entire environment. They'll optimize it, you know, they'll troubleshoot it, they'll bug fix, they'll do everything for you. So you can just say, I just wanna focus on building phenomenal applications for my customers. And the database game as we knew it is not something that I know I want to invest in anymore. Right. I wanna make that transition >>That makes that really, yeah. You know, I mean really attractive to a lot of people because you are, you talk about a lot of headache there. Yeah. So let's talk about AWS before Sure. I let you go just about that relationship. Okay. You've talked about the platform that it provides you and, and obviously the benefits, but just talk about how you've worked with AWS over the years Yep. And, and how you see that relationship allowing you to expand your services, no pun intended. >>For sure. So, I mean, I would start with the way we even contemplated architecture. You know, we worked with the satisfactory team. We made sure that the things that we built were optimized in their environment. You know, I think it was a lot of collaboration on how does this combined entity really make the most value for our customers? How does it make the most sense for our developers as we build it out? Then we work in the, in the global startup team. So the strategic element of who we are, not all startups are created equal, right? We have, right, we have 75% of the Fortune 100, we've got over a billion downloads. So, you know, we come in with promise. And the reason this partnership is so valuable and the reason there's so much investment going forward is cuz what really, what do the cloud guys care about? >>The very, very most, they want all of these mission critical, big workloads that are on prem to land in their cloud. What do we have a massive, massive TAM sitting out there, these customers that could go to aws. So we both see, like if we can deliver incredible value to that customer base, these big workloads will end up in aws. They'll use other AWS services. And as we scale and grow, you know, we have that platform that's already built for it. So I think that when you go back to like the tenants, the core principles of aws, the one that always stands out, the one that we always kind of lean back on is, are we delivering customer value? Is this the best thing for the customer? Because we do have some competition just like many other, other partners do, right? So there is Aurora and there is rds and there is times when that's a great service for a customer. But when people are really thinking about where do I need my database to go? Where do I really need to be set for the future growth? Where am I gonna get the kind of ROI I need going forward? That's where you can go, Hey, sky sql, expand distributed sql. This is the best game in town. It's built on aws and collectively, you know, we're gonna present that to a customer. I'm >>Sold. Done. >>I love it. Right? >>Maria db, check 'em out, they're on the show floor. Great traffic. I know at at the, at the booth. They're here at AWS Reinvent. So check 'em out. Maria db. Thanks >>Kevin. Hey, thanks John. Appreciate your >>Time. Appreciate Great. That was great. Right back with more, you're watching the cube, the leader in high tech coverage.

Published Date : Nov 30 2022

SUMMARY :

Well, hello everybody at John Wallace here on the Cube, and glad to have you along here for day two of But to share that with some folks at home who might not be familiar with your offering. drive it into the cloud and take it to the future. So in your thought then, what, what problem is that solving? I think what you see in the overall database market is that many people have or, but, but you could see that there was going to be crunch time. the compromise built on the cloud allows you to scale out and allows you to think about, You know, you talk about distributed, you know, sequel and, and I And I think what we see over and over But this is the great part is, you know, you know, we've just had two taste studies recently with aws, I mean, you would think that somebody out there who, And then you take it one layer farther and you think about multi-cloud, But as with ever have you talked about this, there's some push and there's some So neither one of the key elements of Sky SQL is we can do both transactional and analytical So I think the idea that you can take the real focus of AWS and But you know, if, if I'm, I'm still an on-prim guy, just pretend I'm not saying I am. So we give you Skye, there's a natural symbiotic bridge between everything So you're saying you don't have to dive And the database game as we knew it is not something that I know I want to invest in anymore. You know, I mean really attractive to a lot of people because you are, you talk about a lot of headache We made sure that the things that we built were optimized And as we scale and grow, you know, we have that platform that's already built for it. I love it. at the booth. Right back with more, you're watching the cube, the leader in

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Breaking Analysis: Snowflake caught in the storm clouds


 

>> From the CUBE Studios in Palo Alto in Boston, bringing you data driven insights from the Cube and ETR. This is Breaking Analysis with Dave Vellante. >> A better than expected earnings report in late August got people excited about Snowflake again, but the negative sentiment in the market is weighed heavily on virtually all growth tech stocks and Snowflake is no exception. As we've stressed many times the company's management is on a long term mission to dramatically simplify the way organizations use data. Snowflake is tapping into a multi hundred billion dollar total available market and continues to grow at a rapid pace. In our view, Snowflake is embarking on its third major wave of innovation data apps, while its first and second waves are still bearing significant fruit. Now for short term traders focused on the next 90 or 180 days, that probably doesn't matter. But those taking a longer view are asking, "Should we still be optimistic about the future of this high flyer or is it just another over hyped tech play?" Hello and welcome to this week's Wiki Bond Cube Insights powered by ETR. Snowflake's Quarter just ended. And in this breaking analysis we take a look at the most recent survey data from ETR to see what clues and nuggets we can extract to predict the near term future in the long term outlook for Snowflake which is going to announce its earnings at the end of this month. Okay, so you know the story. If you've been investor in Snowflake this year, it's been painful. We said at IPO, "If you really want to own this stock on day one, just hold your nose and buy it." But like most IPOs we said there will be likely a better entry point in the future, and not surprisingly that's been the case. Snowflake IPOed a price of 120, which you couldn't touch on day one unless you got into a friends and family Delio. And if you did, you're still up 5% or so. So congratulations. But at one point last year you were up well over 200%. That's been the nature of this volatile stock, and I certainly can't help you with the timing of the market. But longer term Snowflake is targeting 10 billion in revenue for fiscal year 2028. A big number. Is it achievable? Is it big enough? Tell you what, let's come back to that. Now shorter term, our expert trader and breaking analysis contributor Chip Simonton said he got out of the stock a while ago after having taken a shot at what turned out to be a bear market rally. He pointed out that the stock had been bouncing around the 150 level for the last few months and broke that to the downside last Friday. So he'd expect 150 is where the stock is going to find resistance on the way back up, but there's no sign of support right now. He said maybe at 120, which was the July low and of course the IPO price that we just talked about. Now, perhaps earnings will be a catalyst, when Snowflake announces on November 30th, but until the mentality toward growth tech changes, nothing's likely to change dramatically according to Simonton. So now that we have that out of the way, let's take a look at the spending data for Snowflake in the ETR survey. Here's a chart that shows the time series breakdown of snowflake's net score going back to the October, 2021 survey. Now at that time, Snowflake's net score stood at a robust 77%. And remember, net score is a measure of spending velocity. It's a proprietary network, and ETR derives it from a quarterly survey of IT buyers and asks the respondents, "Are you adopting the platform new? Are you spending 6% or more? Is you're spending flat? Is you're spending down 6% or worse? Or are you leaving the platform decommissioning?" You subtract the percent of customers that are spending less or churning from those that are spending more and adopting or adopting and you get a net score. And that's expressed as a percentage of customers responding. In this chart we show Snowflake's in out of the total survey which ranges... The total survey ranges between 1,200 and 1,400 each quarter. And the very last column... Oh sorry, very last row, we show the number of Snowflake respondents that are coming in the survey from the Fortune 500 and the Global 2000. Those are two very important Snowflake constituencies. Now what this data tells us is that Snowflake exited 2021 with very strong momentum in a net score of 82%, which is off the charts and it was actually accelerating from the previous survey. Now by April that sentiment had flipped and Snowflake came down to earth with a 68% net score. Still highly elevated relative to its peers, but meaningfully down. Why was that? Because we saw a drop in new ads and an increase in flat spend. Then into the July and most recent October surveys, you saw a significant drop in the percentage of customers that were spending more. Now, notably, the percentage of customers who are contemplating adding the platform is actually staying pretty strong, but it is off a bit this past survey. And combined with a slight uptick in planned churn, net score is now down to 60%. That uptick from 0% and 1% and then 3%, it's still small, but that net score at 60% is still 20 percentage points higher than our highly elevated benchmark of 40% as you recall from listening to earlier breaking analysis. That 40% range is we consider a milestone. Anything above that is actually quite strong. But again, Snowflake is down and coming back to churn, while 3% churn is very low, in previous quarters we've seen Snowflake 0% or 1% decommissions. Now the last thing to note in this chart is the meaningful uptick in survey respondents that are citing, they're using the Snowflake platform. That's up to 212 in the survey. So look, it's hard to imagine that Snowflake doesn't feel the softening in the market like everyone else. Snowflake is guiding for around 60% growth in product revenue against the tough compare from a year ago with a 2% operating margin. So like every company, the reaction of the street is going to come down to how accurate or conservative the guide is from their CFO. Now, earlier this year, Snowflake acquired a company called Streamlit for around $800 million. Streamlit is an open source Python library and it makes it easier to build data apps with machine learning, obviously a huge trend. And like Snowflake, generally its focus is on simplifying the complex, in this case making data science easier to integrate into data apps that business people can use. So we were excited this summer in the July ETR survey to see that they added some nice data and pick on Streamlit, which we're showing here in comparison to Snowflake's core business on the left hand side. That's the data warehousing, the Streamlit pieces on the right hand side. And we show again net score over time from the previous survey for Snowflake's core database and data warehouse offering again on the left as compared to a Streamlit on the right. Snowflake's core product had 194 responses in the October, 22 survey, Streamlit had an end of 73, which is up from 52 in the July survey. So significant uptick of people responding that they're doing business in adopting Streamlit. That was pretty impressive to us. And it's hard to see, but the net scores stayed pretty constant for Streamlit at 51%. It was 52% I think in the previous quarter, well over that magic 40% mark. But when you blend it with Snowflake, it does sort of bring things down a little bit. Now there are two key points here. One is that the acquisition seems to have gained exposure right out of the gate as evidenced by the large number of responses. And two, the spending momentum. Again while it's lower than Snowflake overall, and when you blend it with Snowflake it does pull it down, it's very healthy and steady. Now let's do a little pure comparison with some of our favorite names in this space. This chart shows net score or spending velocity in the Y-axis, an overlap or presence, pervasiveness if you will, in the data set on the X-axis. That red dotted line again is that 40% highly elevated net score that we like to talk about. And that table inserted informs us as to how the companies are plotted, where the dots set up, the net score, the ins. And we're comparing a number of database players, although just a caution, Oracle includes all of Oracle including its apps. But we just put it in there for reference because it is the leader in database. Right off the bat, Snowflake jumps out with a net score of 64%. The 60% from the earlier chart, again included Streamlit. So you can see its core database, data warehouse business actually is higher than the total company average that we showed you before 'cause the Streamlit is blended in. So when you separate it out, Streamlit is right on top of data bricks. Isn't that ironic? Only Snowflake and Databricks in this selection of names are above the 40% level. You see Mongo and Couchbase, they know they're solid and Teradata cloud actually showing pretty well compared to some of the earlier survey results. Now let's isolate on the database data platform sector and see how that shapes up. And for this analysis, same XY dimensions, we've added the big giants, AWS and Microsoft and Google. And notice that those three plus Snowflake are just at or above the 40% line. Snowflake continues to lead by a significant margin in spending momentum and it keeps creeping to the right. That's that end that we talked about earlier. Now here's an interesting tidbit. Snowflake is often asked, and I've asked them myself many times, "How are you faring relative to AWS, Microsoft and Google, these big whales with Redshift and Synapse and Big Query?" And Snowflake has been telling folks that 80% of its business comes from AWS. And when Microsoft heard that, they said, "Whoa, wait a minute, Snowflake, let's partner up." 'Cause Microsoft is smart, and they understand that the market is enormous. And if they could do better with Snowflake, one, they may steal some business from AWS. And two, even if Snowflake is winning against some of the Microsoft database products, if it wins on Azure, Microsoft is going to sell more compute and more storage, more AI tools, more other stuff to these customers. Now AWS is really aggressive from a partnering standpoint with Snowflake. They're openly negotiating, not openly, but they're negotiating better prices. They're realizing that when it comes to data, the cheaper that you make the offering, the more people are going to consume. At scale economies and operating leverage are really powerful things at volume that kick in. Now Microsoft, they're coming along, they obviously get it, but Google is seemingly resistant to that type of go to market partnership. Rather than lean into Snowflake as a great partner Google's field force is kind of fighting fashion. Google itself at Cloud next heavily messaged what they call the open data cloud, which is a direct rip off of Snowflake. So what can we say about Google? They continue to be kind of behind the curve when it comes to go to market. Now just a brief aside on the competitive posture. I've seen Slootman, Frank Slootman, CEO of Snowflake in action with his prior companies and how he depositioned the competition. At Data Domain, he eviscerated a company called Avamar with their, what he called their expensive and slow post process architecture. I think he actually called it garbage, if I recall at one conference I heard him speak at. And that sort of destroyed BMC when he was at ServiceNow, kind of positioning them as the equivalent of the department of motor vehicles. And so it's interesting to hear how Snowflake openly talks about the data platforms of AWS, Microsoft, Google, and data bricks. I'll give you this sort of short bumper sticker. Redshift is just an on-prem database that AWS morphed to the cloud, which by the way is kind of true. They actually did a brilliant job of it, but it's basically a fact. Microsoft Excel, a collection of legacy databases, which also kind of morphed to run in the cloud. And even Big Query, which is considered cloud native by many if not most, is being positioned by Snowflake as originally an on-prem database to support Google's ad business, maybe. And data bricks is for those people smart enough to get it to Berkeley that love complexity. And now Snowflake doesn't, they don't mention Berkeley as far as I know. That's my addition. But you get the point. And the interesting thing about Databricks and Snowflake is a while ago in the cube I said that there was a new workload type emerging around data where you have AWS cloud, Snowflake obviously for the cloud database and Databricks data for the data science and EML, you bring those things together and there's this new workload emerging that's going to be very powerful in the future. And it's interesting to see now the aspirations of all three of these platforms are colliding. That's quite a dynamic, especially when you see both Snowflake and Databricks putting venture money and getting their hooks into the loyalties of the same companies like DBT labs and Calibra. Anyway, Snowflake's posture is that we are the pioneer in cloud native data warehouse, data sharing and now data apps. And our platform is designed for business people that want simplicity. The other guys, yes, they're formidable, but we Snowflake have an architectural lead and of course we run in multiple clouds. So it's pretty strong positioning or depositioning, you have to admit. Now I'm not sure I agree with the big query knockoffs completely. I think that's a bit of a stretch, but snowflake, as we see in the ETR survey data is winning. So in thinking about the longer term future, let's talk about what's different with Snowflake, where it's headed and what the opportunities are for the company. Snowflake put itself on the map by focusing on simplifying data analytics. What's interesting about that is the company's founders are as you probably know from Oracle. And rather than focusing on transactional data, which is Oracle's sweet spot, the stuff they worked on when they were at Oracle, the founder said, "We're going to go somewhere else. We're going to attack the data warehousing problem and the data analytics problem." And they completely re-imagined the database and how it could be applied to solve those challenges and reimagine what was possible if you had virtually unlimited compute and storage capacity. And of course Snowflake became famous for separating the compute from storage and being able to completely shut down compute so you didn't have to pay for it when you're not using it. And the ability to have multiple clusters hit the same data without making endless copies and a consumption/cloud pricing model. And then of course everyone on the planet realized, "Wow, that's a pretty good idea." Every venture capitalist in Silicon Valley has been funding companies to copy that move. And that today has pretty much become mainstream in table stakes. But I would argue that Snowflake not only had the lead, but when you look at how others are approaching this problem, it's not necessarily as clean and as elegant. Some of the startups, the early startups I think get it and maybe had an advantage of starting later, which can be a disadvantage too. But AWS is a good example of what I'm saying here. Is its version of separating compute from storage was an afterthought and it's good, it's... Given what they had it was actually quite clever and customers like it, but it's more of a, "Okay, we're going to tier to storage to lower cost, we're going to sort of dial down the compute not completely, we're not going to shut it off, we're going to minimize the compute required." It's really not true as separation is like for instance Snowflake has. But having said that, we're talking about competitors with lots of resources and cohort offerings. And so I don't want to make this necessarily all about the product, but all things being equal architecture matters, okay? So that's the cloud S-curve, the first one we're showing. Snowflake's still on that S-curve, and in and of itself it's got legs, but it's not what's going to power the company to 10 billion. The next S-curve we denote is the multi-cloud in the middle. And now while 80% of Snowflake's revenue is AWS, Microsoft is ramping up and Google, well, we'll see. But the interesting part of that curve is data sharing, and this idea of data clean rooms. I mean it really should be called the data sharing curve, but I have my reasons for calling it multi-cloud. And this is all about network effects and data gravity, and you're seeing this play out today, especially in industries like financial services and healthcare and government that are highly regulated verticals where folks are super paranoid about compliance. There not going to share data if they're going to get sued for it, if they're going to be in the front page of the Wall Street Journal for some kind of privacy breach. And what Snowflake has done is said, "Put all the data in our cloud." Now, of course now that triggers a lot of people because it's a walled garden, okay? It is. That's the trade off. It's not the Wild West, it's not Windows, it's Mac, it's more controlled. But the idea is that as different parts of the organization or even partners begin to share data that they need, it's got to be governed, it's got to be secure, it's got to be compliant, it's got to be trusted. So Snowflake introduced the idea of, they call these things stable edges. I think that's the term that they use. And they track a metric around stable edges. And so a stable edge, or think of it as a persistent edge is an ongoing relationship between two parties that last for some period of time, more than a month. It's not just a one shot deal, one a done type of, "Oh guys shared it for a day, done." It sent you an FTP, it's done. No, it's got to have trajectory over time. Four weeks or six weeks or some period of time that's meaningful. And that metric is growing. Now I think sort of a different metric that they track. I think around 20% of Snowflake customers are actively sharing data today and then they track the number of those edge relationships that exist. So that's something that's unique. Because again, most data sharing is all about making copies of data. That's great for storage companies, it's bad for auditors, and it's bad for compliance officers. And that trend is just starting out, that middle S-curve, it's going to kind of hit the base of that steep part of the S-curve and it's going to have legs through this decade we think. And then finally the third wave that we show here is what we call super cloud. That's why I called it multi-cloud before, so it could invoke super cloud. The idea that you've built a PAS layer that is purpose built for a specific objective, and in this case it's building data apps that are cloud native, shareable and governed. And is a long-term trend that's going to take some time to develop. I mean, application development platforms can take five to 10 years to mature and gain significant adoption, but this one's unique. This is a critical play for Snowflake. If it's going to compete with the big cloud players, it has to have an app development framework like Snowpark. It has to accommodate new data types like transactional data. That's why it announced this thing called UniStore last June, Snowflake a summit. And the pattern that's forming here is Snowflake is building layer upon layer with its architecture at the core. It's not currently anyway, it's not going out and saying, "All right, we're going to buy a company that's got to another billion dollars in revenue and that's how we're going to get to 10 billion." So it's not buying its way into new markets through revenue. It's actually buying smaller companies that can complement Snowflake and that it can turn into revenue for growth that fit in to the data cloud. Now as to the 10 billion by fiscal year 28, is that achievable? That's the question. Yeah, I think so. Would the momentum resources go to market product and management prowess that Snowflake has? Yes, it's definitely achievable. And one could argue to $10 billion is too conservative. Indeed, Snowflake CFO, Mike Scarpelli will fully admit his forecaster built on existing offerings. He's not including revenue as I understand it from all the new stuff that's in the pipeline because he doesn't know what it's going to look like. He doesn't know what the adoption is going to look like. He doesn't have data on that adoption, not just yet anyway. And now of course things can change quite dramatically. It's possible that is forecast for existing businesses don't materialize or competition picks them off or a company like Databricks actually is able in the longer term replicate the functionality of Snowflake with open source technologies, which would be a very competitive source of innovation. But in our view, there's plenty of room for growth, the market is enormous and the real key is, can and will Snowflake deliver on the promises of simplifying data? Of course we've heard this before from data warehouse, the data mars and data legs and master data management and ETLs and data movers and data copiers and Hadoop and a raft of technologies that have not lived up to expectations. And we've also, by the way, seen some tremendous successes in the software business with the likes of ServiceNow and Salesforce. So will Snowflake be the next great software name and hit that 10 billion magic mark? I think so. Let's reconnect in 2028 and see. Okay, we'll leave it there today. I want to thank Chip Simonton for his input to today's episode. Thanks to Alex Myerson who's on production and manages the podcast. Ken Schiffman as well. Kristin Martin and Cheryl Knight help get the word out on social media and in our newsletters. And Rob Hove is our Editor in Chief over at Silicon Angle. He does some great editing for us. Check it out for all the news. Remember all these episodes are available as podcasts. Wherever you listen, just search Breaking Analysis podcast. I publish each week on wikibon.com and siliconangle.com. Or you can email me to get in touch David.vallante@siliconangle.com. DM me @dvellante or comment on our LinkedIn post. And please do check out etr.ai, they've got the best survey data in the enterprise tech business. This is Dave Vellante for the CUBE Insights, powered by ETR. Thanks for watching, thanks for listening and we'll see you next time on breaking analysis. (upbeat music)

Published Date : Nov 10 2022

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Breaking Analysis: Survey Says! Takeaways from the latest CIO spending data


 

>> From theCUBE Studios in Palo Alto and Boston, bringing you data driven insights from theCUBE and ETR. This is breaking analysis with Dave Vellante. >> The technology spending outlook is not pretty and very much unpredictable right now. The negative sentiment is of course being driven by the macroeconomic factors in earnings forecasts that have been coming down all year in an environment of rising interest rates. And what's worse, is many people think earnings estimates are still too high. But it's understandable why there's so much uncertainty. I mean, technology is still booming, digital transformations are happening in earnest, leading companies have momentum and they got cash runways. And moreover, the CEOs of these leading companies are still really optimistic. But strong guidance in an environment of uncertainty is somewhat risky. Hello and welcome to this week's Wikibon CUBE Insights Powered by ETR. In this breaking analysis, we share takeaways from ETR'S latest spending survey, which was released to their private clients on October 21st. Today, we're going to review the macro spending data. We're going to share where CIOs think their cloud spend is headed. We're going to look at the actions that organizations are taking to manage uncertainty and then review some of the technology companies that have the most positive and negative outlooks in the ETR data set. Let's first look at the sample makeup from the latest ETR survey. ETR captured more than 1300 respondents in this latest survey. Its highest figure for the year and the quality and seniority of respondents just keeps going up each time we dig into the data. We've got large contributions as you can see here from sea level executives in a broad industry focus. Now the survey is still North America centric with 20% of the respondents coming from overseas and there is a bias toward larger organizations. And nonetheless, we're still talking well over 400 respondents coming from SMBs. Now ETR for those of you who don't know, conducts a quarterly spending intention survey and they also do periodic drilldowns. So just by the way of review, let's take a look at the expectations in the latest drilldown survey for IT spending. Before we look at the broader technology spending intentions survey data, followers of this program know that we reported on this a couple of weeks ago, spending expectations that peaked last December at 8.3% are now down to 5.5% with a slight uptick expected for next year as shown here. Now one CIO in the ETR community said these figures could be understated because of inflation. Now that's an interesting comment. Real GDP in the US is forecast to be around 1.5% in 2022. So these figures are significantly ahead of that. Nominal GDP is forecast to be significantly higher than what is shown in that slide. It was over 9% in June for example. And one would interpret that survey respondents are talking about real dollars which reflects inflationary factors in IT spend. So you might say, well if nominal GDP is in the high single digits this means that IT spending is below GDP which is usually not the case. But the flip side of that is technology tends to be deflationary because prices come down over time on a per unit basis, so this would be a normal and even positive trend. But it's mixed right now with prices on hard to find hardware, they're holding more firms. Software, you know, software tends to be driven by lock in and competition and switching costs. So you have those countervailing factors. Services can be inflationary, especially now as wages rise but certain sectors like laptops and semis and NAND are seeing less demand and maybe even some oversupply. So the way to look at this data is on a relative basis. In other words, IT buyers are reporting 280 basis point drop in spending sentiment from the end of last year. Now, something that we haven't shared from the latest drilldown survey which we will now is how IT bar buyers are thinking about cloud adoption. This chart shows responses from 419 IT execs from that drilldown and depicts the percentage of workloads their organizations have in the cloud today and what the expectation is through years from now. And you can see it's 27% today and it's nearly 50% in three years. Now the nuance is if you look at the question, that ETRS, it's they asked about IaaS and PaaS, which to some could include on-prem. Now, let me come back to that. In particular, financial services, IT, telco and retail and services industry cited expectations for the future for three years out that we're well above the average of the mean adoption levels. Regardless of how you interpret this data there's most certainly plenty of public cloud in the numbers. And whether you believe cloud is an operating environment or a place out there in the cloud, there's plenty of room for workloads to move into a cloud model well beyond mid this decade. So you know, as ho hum as we've been toward recent as-a-service models announced from the likes of HPE with GreenLake and Dell with APEX, the timing of those offerings may be pretty good actually. Now let's expand on some of the data that we showed a couple weeks ago. This chart shows responses from 282 execs on actions their organizations are taking over the next three months. And the Deltas are quite traumatic from the early part of this charter than the left hand side. The brown line is hiring freezes, the black line is freezing IT projects, and the green line is hiring increases and that red line is layoffs. And we put a box around the sort of general area of the isolation economy timeframe. And you can see the wild swings on this chart. By mid last summer, people were kickstarting things and more hiring was going on and the black line shows IT project freezes, you know, came way down. And now, or on the way back up as our hiring freezes. So we're seeing these wild swings in organizational actions and strategies which underscores the lack of predictability. As with supply chains around the world, this is likely due to the fact that organizations, pre pandemic they were optimized for efficiency, not a lot of waste rather than business resilience. Meaning, you know, there's again not a lot of fluff in the system or if there was it got flushed out during the pandemic. And so the need for productivity and automation is becoming increasingly important, especially as actions that solely rely on headcount changes are very, very difficult to manage. Now, let's dig into some of the vendor commentary and take a look at some of the names that have momentum and some of the others possibly facing headwinds. Here's a list of companies that stand out in the ETR survey. Snowflake, once again leads the pack with a positive spending outlook. HashiCorp, CrowdStrike, Databricks, Freshworks and ServiceNow, they round out the top six. Microsoft, they seem to always be in the mix, as do a number of other security and related companies including CyberArk, Zscaler, CloudFlare, Elastic, Datadog, Fortinet, Tenable and to a certain extent Akamai, you can kind of put them sort of in that group. You know, CDN, they got to worry about security. Everybody worries about security, but especially the CDNs. Now the other software names that are highlighted here include Workday and Salesforce. On the negative side, you can see Dynatrace saw some negatives in the latest survey especially around its analytics business. Security is generally holding up better than other sectors but it's still seeing greater levels of pressure than it had previously. So lower spend. And defections relative to its observability peers, that's really for Dynatrace. Now the other one that was somewhat surprising is IBM. You see the IBM was sort of in that negative realm here but IBM reported an outstanding quarter this past week with double digit revenue growth, strong momentum in software, consulting, mainframes and other infrastructure like storage. It's benefiting from the Kyndryl restructuring and it's on track IBM to deliver 10 billion in free cash flow this year. Red Hat is performing exceedingly well and growing in the very high teens. And so look, IBM is in the midst of a major transformation and it seems like a company that is really focused now with hybrid cloud being powered by Red Hat and consulting and a decade plus of AI investments finally paying off. Now the other big thing we'll add is, IBM was once an outstanding acquire of companies and it seems to be really getting its act together on the M&A front. Yes, Red Hat was a big pill to swallow but IBM has done a number of smaller acquisitions, I think seven this year. Like for example, Turbonomic, which is starting to pay off. Arvind Krishna has the company focused once again. And he and Jim J. Kavanaugh, IBM CFO, seem to be very confident on the guidance that they're giving in their business. So that's a real positive in our view for the industry. Okay, the last thing we'd like to do is take 12 of the companies from the previous chart and plot them in context. Now these companies don't necessarily compete with each other, some do. But they are standouts in the ETR survey and in the market. What we're showing here is a view that we like to often show, it's net score or spending velocity on the vertical axis. And it's a measure, that's a measure of the net percentage of customers that are spending more on a particular platform. So ETR asks, are you spending more or less? They subtract less from the mores. I mean I'm simplifying, but that's what net score is. Now in the horizontal axis, that is a measure of overlap which is which measures presence or pervasiveness in the dataset. So bigger the better. We've inserted a table that informs how the dots in the companies are positioned. These companies are all in the green in terms of net score. And that right most column in the table insert is indicative of their presence in the dataset, the end. So higher, again, is better for both columns. Two other notes, the red dotted line there you see at 40%. Anything over that indicates an highly elevated spending momentum for a given platform. And we purposefully took Microsoft out of the mix in this chart because it skews the data due to its large size. Everybody else would cluster on the left and Microsoft would be all alone in the right. So we take them out. Now as we noted earlier, Snowflake once again leads with a net score of 64%, well above the 40% line. Having said that, while adoption rates for Snowflake remains strong the company's spending velocity in the survey has come down to Earth. And many more customers are shifting from where they were last year and the year before in growth mode i.e. spending more year to year with Snowflake to now shifting more toward flat spending. So a plus or minus 5%. So that puts pressure on Snowflake's net score, just based on the math as to how ETR calculates, its proprietary net score methodology. So Snowflake is by no means insulated completely to the macro factors. And this was seen especially in the data in the Fortune 500 cut of the survey for Snowflake. We didn't show that here, just giving you anecdotal commentary from the survey which is backed up by data. So, it showed steeper declines in the Fortune 500 momentum. But overall, Snowflake, very impressive. Now what's more, note the position of Streamlit relative to Databricks. Streamlit is an open source python framework for developing data driven, data science oriented apps. And it's ironic that it's net score and shared in is almost identical to those of data bricks, as the aspirations of Snowflake and Databricks are beginning to collide. Now, however, the Databricks net score has held up very well over the past year and is in the 92nd percentile of its machine learning and AI peers. And while it's seeing some softness, like Snowflake in the Fortune 500, Databricks has steadily moved to the right on the X axis over the last several surveys even though it was unable to get to the public markets and do an IPO during the lockdown tech bubble. Let's come back to the chart. ServiceNow is impressive because it's well above the 40% mark and it has 437 shared in on this cut, the largest of any company that we chose to plot here. The only real negative on ServiceNow is, more large customers are keeping spending levels flat. That's putting a little bit pressure on its net score, but that's just conservatives. It's kind of like Snowflakes, you know, same thing but in a larger scale. But it's defections, the ServiceNow as in Snowflake as well. It's defections remain very, very low, really low churn below 2% for ServiceNow, in fact, within the dataset. Now it's interesting to also see Freshworks hit the list. You can see them as one of the few ITSM vendors that has momentum and can potentially take on ServiceNow. Workday, on this chart, it's the other big app player that's above the 40% line and we're only showing Workday HCM, FYI, in this graphic. It's Workday Financials, that offering, is below the 40% line just for reference. Now let's talk about CrowdStrike. We attended Falcon last month, CrowdStrike's user conference and we're very impressed with the product visio, the company's execution, it's growing partnerships. And you can see in this graphic, the ETR survey data confirms the company's stellar performance with a net score at 50%, well above the 40% mark. And importantly, more than 300 mentions. That's second only to ServiceNow, amongst the 12 companies that we've chosen to highlight here. Only Microsoft, which is not shown here, has a higher net score in the security space than CrowdStrike. And when it comes to presence, CrowdStrike now has caught up to Splunk in terms of pervasion in the survey. Now CyberArk and Zscaler are the other two security firms that are right at that 40% red dotted line. CyberArk for names with over a hundred citations in the security sector, is only behind Microsoft and CrowdStrike. Zscaler for its part in the survey is seeing strong momentum in the Fortune 500, unlike what we said for Snowflake. And its pervasion on the X-axis has been steadily increasing. Again, not that Snowflake and CrowdStrike compete with each other but they're too prominent names and it's just interesting to compare peers and business models. Cloudflare, Elastic and Datadog are slightly below the 40% mark but they made the sort of top 12 that we showed to highlight here and they continue to have positive sentiment in the survey. So, what are the big takeaways from this latest survey, this really quick snapshot that we've taken. As you know, over the next several weeks we're going to dig into it more and more. As we've previously reported, the tide is going out and it's taking virtually all the tech ships with it. But in many ways the current market is a story of heightened expectations coming down to Earth, miscalculations about the economic patterns and the swings and imperfect visibility. Leading Barclays analyst, Ramo Limchao ask the question to guide or not to guide in a recent research note he wrote. His point being, should companies guide or should they be more cautious? Many companies, if not most companies, are actually giving guidance. Indeed, when companies like Oracle and IBM are emphatic about their near term outlook and their visibility, it gives one confidence. On the other hand, reasonable people are asking, will the red hot valuations that we saw over the last two years from the likes of Snowflake, CrowdStrike, MongoDB, Okta, Zscaler, and others. Will they return? Or are we in for a long, drawn out, sideways exercise before we see sustained momentum? And to that uncertainty, we add elections and public policy. It's very hard to predict right now. I'm sorry to be like a two-handed lawyer, you know. On the one hand, on the other hand. But that's just the way it is. Let's just say for our part, we think that once it's clear that interest rates are on their way back down and we'll stabilize it under 4% and we have clarity on the direction of inflation, wages, unemployment and geopolitics, the wild swings and sentiment will subside. But when that happens is anyone's guess. If I had to peg, I'd say 18 months, which puts us at least into the spring of 2024. What's your prediction? You know, it's almost that time of year. Let's hear it. Please keep in touch and let us know what you think. Okay, that's it for now. Many thanks to Alex Myerson. He is on production and he manages the podcast for us. Ken Schiffman as well is our newest addition to the Boston Studio. Kristin Martin and Cheryl Knight, they help get the word out on social media and in our newsletters. And Rob Hoff is our EIC, editor-in-chief over at SiliconANGLE. He does some wonderful editing for us. Thank you all. Remember all these episodes, they are available as podcasts. Wherever you listen, just search breaking analysis podcast. I publish each week on wikibon.com and siliconangle.com. Or you can email me at david.vellante@siliconangle.com or DM me @dvellante. Or feel free to comment on our LinkedIn posts. And please do check out etr.ai. They've got the best survey data in the enterprise tech business. If you haven't checked that out, you should. It'll give you an advantage. This is Dave Vellante for theCUBE Insights Powered by ETR. Thanks for watching. Be well and we'll see you next time on Breaking Analysis. (soft upbeat music)

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Druva Why Ransomware Isn't Your Only Problem


 

>> The past 2 1/2 years have seen a dramatic change in the security posture of virtually all organizations. By accelerating the digital business mandate, the isolation economy catalyzed a move toward cloud computing to support remote workers. This we know. This had several ripple effects on CSO and CIO strategies that were highly visible at the Board of Directors' level. Now, the first major change was to recognize that the perimeter had suddenly been vaporized. Protection, as a result, moved away from things like perimeter-based firewalls toward more distributed endpoints, cloud security, and modern identity management. The second major change was a heightened awareness of the realities of ransomware. Ransomware as a service, for example, emerged as a major threat where virtually anyone with access to critical data and criminal intentions could monetize corporate security exposures. The third major change was a much more acute understanding of how data protection needed to become a fundamental component of cybersecurity strategies, and more specifically, CIOs quickly realized that their business resilience strategies were too narrowly DR-focused, that their DR approach was not cost efficient and needed to be modernized, and that new approaches to operational resilience were needed to reflect the architectural and business realities of this new environment. Hello, and welcome to "Why Ransomware isn't Your Only Problem," a service of theCUBE made possible by Druva, and in collaboration with IDC. I'm your host, Dave Vellante, and today, we're presenting a three-part program. We'll start with the data. IDC recently conducted a global survey of 500 business technology practitioners across 20 industries to understand the degree to which organizations are aware of and prepared for the threats they face in today's new world. IDC Research Vice President Phil Goodwin is here to share the highlights of the study and to summarize the findings from a recent research report on the topic. After that, we're going to hear from Curtis Preston, who's the Chief Technical Evangelist at Druva. I've known Curtis for decades. He's one of the world's foremost experts on backup and recovery, specifically, and data protection, generally. Curtis will help us understand how the survey data presented by IDC aligns with the real world findings from the field from his point of view. And he'll discuss why so many organizations have failed to successfully recover from an attack without major pains and big costs, and how to avoid such operational disruptions and disasters. And then finally, we'll hear from the technical experts at Druva, Stephen Manley and Anjan Srinivas. Stephen is a 10-time CUBE alum and Chief Technology Officer at Druva, and Anjan is Vice President and General Manager of Product Management at the company. And these individuals will specifically address how Druva is closing the gaps presented in the IDC survey through their product innovation. But right now I'm going to toss it to Lisa Martin, another one of the hosts for today's program. Lisa, over to you. (upbeat music) >> Bill Goodwin joins me next, the VP of Research at IDC. We're going to be breaking down what's going on in the threat landscape. Phil, welcome to the program. It's great to have you back on theCUBE. >> Hey, Lisa, it's great to be here with you. >> So talk to me about the state of the global IT landscape as we see cyberattacks massively increasing, the threat landscape changing so much. What is IDC seeing? >> You know, you really hit the top topic that we find from IT organizations as well as business organizations. And really, it's that digital resilience, that ransomware that has everybody's attention, and it has the attention, not just of the IT people, but of the business people alike, because it really does have profound effects across the organization. The other thing that we're seeing, Lisa, is really a move towards cloud. And I think part of that is driven by the economics of cloud, which fundamentally changed the way that we can approach disaster recovery, but also has accelerated during the pandemic for all the reasons that people have talked about in terms of work from home and so on. And then really the third thing is the economic uncertainty, and this is relatively new for 2022, but within IDC we've been doing a lot of research around what are those impacts going to be? And what we find people doing is they want greater flexibility, they want more cost certainty, and they really want to be able to leverage those cloud economics to have the scale up or scale down on demand nature of cloud. So those are, in a nutshell, kind of the three things that people are looking at. >> You mentioned ransomware. It's a topic we've been talking about a lot. It's a household word these days. It's now, Phil, no longer if we're going to get attacked, it's when, it's how often, it's the severity. Talk about ransomware as a priority all the way up the stack to the C-suite, and what are they trying to do to become resilient against it? >> Well, what some of the research that we did is we found that about 77% of organizations have digital resilience as a top priority within their organization. And so what you're seeing is organizations trying to leverage things to become more resilient, more digitally resilient, and to be able to really hone in on those kinds of issues that are keeping them awake at night, quite honestly. If you think about digital resilience, it really is foundational to the organization, whether it's through digital transformation or whether it's simply data availability, whatever it might happen to be. Digital resilience is really a large umbrella term that we use to describe that function that is aimed at avoiding data loss, assuring data availability, and helping the organization to extract value from their data. >> And digital resilience, data resilience, as every company these days has to be a data company to be competitive. Digital resilience, data resilience, are you using those terms interchangeably or is data resilience defined as something a little bit different? >> Well, sometimes yeah, we do get caught using them when one is the other. But data resilience is really a part of digital resilience, if you think about the data itself in the context of IT computing. So it really is a subset of that, but it is foundational to IT resilience. You can't have IT resilience without data resilience. So that's where we're coming from on it. >> Inextricably linked, and it's becoming a corporate initiative, but there's some factors that can complicate digital resilience, data resilience for organizations. What are some of those complications that organizations need to be aware of? >> Well, one of the biggest is what you mentioned at the top of the segment, and that is the area of ransomware. The research that we found is about 46% of organizations have been hit within the last three years. You know, it's kind of interesting how it's changed over the years. Originally, being hit by ransomware had a real stigma attached to it. Organizations didn't want to admit it, and they really avoided confronting that. Nowadays, so many people have been hit by it that that stigma has gone. And so really it is becoming more of a community kind of effort as people try to defend against these ransomers. The other thing about it is it's really a lot like Whac-A-Mole, you know. They attack us in one area and we defend against it so they attack us in another area, and we defend against it. And in fact, I had an individual come up to me at a show not long ago and said, "You know, one of these days we're going to get pretty well defended against ransomware and it's going to go away." And I responded I don't think so because we're constantly introducing new systems, new software, and introducing new vulnerabilities. And the fact is ransomware is so profitable, the bad guys aren't going to just fade into the night without giving it a a lot of fight. So I really think that ransomware is one of those things that is here for the long term and something that we have to address and have to get proactive about. >> You mentioned some stats there, and recently IDC and Druva did a white paper together that really revealed some quite shocking results. Talk to me about some of the things. Let's talk a little bit about the demographics of the survey and then talk about what was the biggest finding there, especially where it's concerning ransomware? >> Yeah, this was a worldwide study. It was sponsored by Druva and conducted by IDC as an independent study. And what we did, we surveyed 500, it was a little over 500 different individuals across the globe in North America, select countries in Western Europe, as well as several in Asia Pacific. And we did it across industries there were 20 different industries represented, they're all evenly represented. We had surveys that included IT practitioners, primarily CIOs, CTOs, VP of infrastructure, you know, managers of data centers, things like that. And the biggest finding that we had in this, Lisa, was really finding that there is a huge disconnect, I believe, between how people think they are ready and what the actual results are when they get attacked. Some of the statistics that we learned from this, Lisa, include 83% of organizations believe, or told us that they have a playbook that they have for ransomware. I think 93% said that they have a high degree, or a high or very high degree of confidence in their recovery tools and are fully automated. And yet, when you look at the actual results, you know, I told you a moment ago, 46% have been attacked successfully. I can also tell you that in separate research, fewer than 1/3 of organizations were able to fully recover their data without paying the ransom, and some 2/3 actually had to pay the ransom. And even when they did, they didn't necessarily achieve their full recovery. You know, the bad guys aren't necessarily to be trusted, and so the software that they provide sometimes is fully recovered, sometimes it's not. So you look at that and you go, wow. On the one hand, people think they're really, really prepared, and on the other hand, the results are absolutely horrible. You know, 2/3 of people having to pay the ransom. So you start to ask yourself, well, what's going on there? And I believe that a lot of it comes down to, kind of reminds me of the old quote from Mike Tyson. "Everybody has a plan until they get punched in the mouth." And I think that's kind of what happens with ransomware. You think you know what you're doing. You think you're ready, based on the information you have. And these people are smart people, and they're professionals, but oftentimes, you don't know what you don't know. And like I said, the bad guys are always dreaming up new ways to attack us. And so, I think, for that reason, a lot of these have been successful. So that was kind of the key finding to me and kind of the aha moment really in this whole thing, Lisa. >> That's a massive disconnect with the vast majority saying, "We have a cyber recovery playbook," yet nearly 1/2 being the victims of ransomware in the last three years, and then 1/2 of them experiencing data loss. What is it then that organizations in this situation across any industry can do to truly enable cyber resilience, data resilience? As we said, this is a matter of this is going to happen, just a matter of when and how often. >> It is a matter, yeah, as you said, it's not if, when, or how often, it's really how badly. So I think what organizations are really doing now is starting to turn more to cloud-based services, you know, finding professionals who know what they're doing, who have that breadth of experience and who have seen the kinds of necessary steps that it takes to do a recovery. And the fact of the matter is a disaster recovery and a cyber recovery are really not the same thing. And so organizations need to be able to plan the kinds of recovery associated with cyber recovery in terms of forensics, in terms of scanning, in terms of analysis, and so forth. So they're turning to professionals in the cloud much more, in order to get that breadth of experience, and to take advantage of cloud-based services that are out there. >> Talk to me about some of the key advantages of cloud-based services for data resilience versus traditional legacy on-prem equipment. What are some of the advantages? Why is IDC seeing this big shift to cloud where data resilience is concerned? >> Well, the first and foremost is the economics of it. You know, you can have on-demand resources. In the old days, when we had disaster recoveries where we had two different data centers and a failover and so forth, you know, you had double the infrastructure. If you're financial services, it might even be triple the infrastructure. It was very complicated, very difficult. By going to the cloud, organizations can subscribe to disaster recovery as a service. And increasingly what we see is a new market of cyber recovery as a service. So being able to leverage those resources, to be able to have the forensic analysis available to them, to be able to have the other resources available that are on demand, and to have that plan in place to have those resources in place. I think what happens in a number of situations, Lisa, is that organizations think they're ready, but then all of a sudden they get hit, and all of a sudden they have to engage with outside consultants, or they have to bring in other experts, and that extends the time to recover that they have and it also complicates it. So if they have those resources in place, then they can simply turn them on, engage them, and get that recovery going as quickly as possible. >> So what do you think the big issue here is? Is it that these IPT practitioners, over 500 that you surveyed across 20 industries, this a global survey, do they they not know what they don't know? What's the overlying issue here? >> Yeah, I think that's right. You don't know what you don't know, and until you get into a specific attack, you know, there are so many different ways that organizations can be attacked. And, in fact, from this research that we found is that, in many cases, data exfiltration exceeds data corruption by about 50%. But when you think about that, the issue is, once I have your data, what are you going to do? I mean, there's no amount of recovery that is going to help. So organizations are either faced with paying the ransom to keep the data from perhaps being used on the dark web, or whatever, or simply saying no, and taking their chances. So best practice things like encryption, immutability, things like that that organizations can put into place. Certainly air gaps, having a solid backup foundation to where data is, you have a high recovery, high probability of recovery, things like that. Those are the kinds of things that organizations have to put into place, really as a baseline to assure that they can recover as fast as possible and not lose data in the event of a ransomware attack. >> Given some of the disconnect that you articulated, the stats that show so many think we are prepared, we've got a playbook, yet so many are being attacked, the vulnerabilities as the landscape, threat landscape, just gets more and more amorphous. What do you recommend organizations do? You talked to the IT practitioners, but does this go all the way up to the board level in terms of, hey guys, across every industry, we are vulnerable, this is going to happen. We've got to make sure that we are truly resilient and proactive? >> Yes, and in fact, what we found from this research is in more than 1/2 of cases, the CEO is directly involved in the recovery. So this is very much a C-suite issue. And if you look at the consequences of ransomware, it's not just the ransom, it's the lost productivity, it's the loss of revenue. It's the loss of customer faith and goodwill, and organizations that have been attacked have suffered those consequences, and many of them are permanent. So people at the board level, whether it's the CEO, the CFO, the CIO, the CSO, you know, whoever it is, they're extremely concerned about these. And I can tell you, they are fully engaged in addressing those issues within their organization. >> So all the way at the top, and critically important, business critical for any industry. I imagine some industries may be a little bit more vulnerable than others, financial services, healthcare, education. We've just seen a big attack in Los Angeles County. But in terms of establishing data resilience, you mentioned ransomware isn't going anywhere, it's a big business, it's very profitable. But what is IDC's prediction where ransomware is concerned? Do you think that organizations, if they truly adopt cloud and SaaS-based technologies, can they get to a place where the C-suite doesn't have to be involved to the point where they really actually have a functioning playbook? >> I don't know if we'll ever get to the point where the C-suite is not involved. It's probably very important to have that level of executive sponsorship. But what we are seeing is, in fact, we predict that by 2025, 55% of organizations will have shifted to a cloud-centric strategy for their data resilience. And the reason we say that is, you know, workloads on premises aren't going away. So that's the core. We have an increasing number of workloads in the cloud and at the edge, and that's really where the growth is. So being able to take that cloud-centric model and take advantage of cloud resources like immutable storage, being able to move data from region to region inexpensively and easily, and to be able to take that cloud-centric perspective and apply it on premises as well as in the cloud and at the edge is really where we believe that organizations are shifting their focus. >> Got it, we're just cracking the surface here, Phil. I wish we had more time, but I had a chance to read the Druva-sponsored IDC white paper. Fascinating finds. I encourage all of you to download that, take a read. You're going to learn some very interesting statistics and recommendations for how you can really truly deploy data resilience in your organization. Phil, it's been a pleasure to have you on the program. Thank you for joining me. >> No problem. Thank you, Lisa. >> In a moment, John Furrier will be here with his next guest. For right now, I'm Lisa Martin, and you are watching theCUBE, the leader in live tech coverage. >> We live in a world of infinite data. Sprawling, dispersed, valuable, but also vulnerable. So how do organizations achieve data resiliency when faced with ever expanding workloads, increasing security threats, and intensified regulations? Unfortunately, the answer often boils down to what flavor of complexity do you like best? The common patchwork approaches are expensive, convoluted, and difficult to manage. There's multiple software and hardware vendors to worry about, different deployments for workloads running on-premises or in the cloud. And an inconsistent security framework resulting in enterprises maintaining four to five copies of the same data, increasing costs and risk, building to an incoherent mess of complications. Now, imagine a world free from these complexities. Welcome to the the Druva Data Resiliency Cloud, where full data protection and beautiful simplicity converge. No hardware, no upgrades, no management, just total data resilience. With just a few clicks, you can get started integrating all of your data resiliency workflows in minutes. Through a true cloud experience built on Amazon Web Services, the Druva platform automates and manages critical daily tasks, giving you time to focus on your business. In other words, get simplicity, scalability, and security instantly. With the Druva Data Resiliency Cloud, your data isn't just backed up, it's ready to be used 24/7 to meet compliance needs and to extract critical insights. You can archive data for long-term retention, be protected against device failure and natural disasters, and recover from ransomware lightning fast. Druva is trusted with billions of backups annually by thousands of enterprises, including more than 60 of the Fortune 500, costing up to 50% less than the convoluted hardware, software, and appliance solutions. As data grows and becomes more critical to your business advantage, a data resiliency plan is vital, but it shouldn't be complicated. Druva makes it simple. (upbeat music) (mouse clicks) >> Welcome back, everyone, to theCUBE and the Druva special presentation of "Why Ransomware isn't Your Only Problem." I'm John Furrier, host of theCUBE. We're here with W Curtis Preston, Curtis Preston, as he's known in the industry, Chief Technical Evangelist at Druva. Curtis, great to see you. We're here at "Why Ransomware isn't Your Only Problem." Great to see you, thanks for coming on. >> Happy to be here. >> So we always see each other at events now events are back. So it's great to have you here for this special presentation. The white paper from IDC really talks about this in detail. I'd like to get your thoughts, and I'd like you to reflect on the analysis that we've been covering here in this survey data, how it lines up with the real world that you're seeing out there. >> Yeah, I think it's, the survey results really, I'd like to say, I'd like to say that they surprised me, but unfortunately, they didn't. The data protection world has been this way for a while where there's this difference in belief, or difference between the belief and the reality. And what we see is that there are a number of organizations that have been hit, successfully hit by ransomware, paid the ransom and/or lost data, and yet the same people that were surveyed, they had high degrees of confidence in their backup system. And, you know, I could probably go on for an hour as to the various reasons why that would be the case, but I think that this long running problem that as long as I've been associated with backups, which, you know, has been a while, it's that problem of, you know, nobody wants to be the backup person. And people often just, they don't want to have anything to do with the backup system, and so it sort of exists in this vacuum. And so then management is like, "Oh, the backup system's great," because the backup person often, you know, might say that it's great because maybe it's their job to say so. But the reality has always been very, very different. >> It's funny, you know. "We're good, boss, we got this covered." >> Yeah, it's all good, it's all good. >> And the fingers crossed, right? So again, this is the reality, and as it becomes backup and recovery, which we've talked about many times on theCUBE, certainly we have with you before, but now with ransomware, also, the other thing is people get ransomware hit multiple times. So it's not only like they get hit once, so, you know, this is a constant chasing the tail on some ends, but there are some tools out there, You guys have a solution, and so let's get into that. You know, you have had hands-on backup experience. What are the points that surprise you the most about what's going on in this world and the realities of how people should be going forward? What's your take? >> Well, I would say that the one part in the survey that surprised me the most was people that had a huge, you know, there was a huge percentage of people that said that they had, you know, a ransomware response, you know, and readiness program. And you look at that, and how could you be, you know, that high a percentage of people be comfortable with their ransomware readiness program, which includes a number of things, right? There's the cyberattack aspect of responding to a ransomware attack, and then there's the recovery aspect. And so you believe that your company was ready for that, and then you go, and I think it was 67% of the people in the survey paid the ransom, which as a person who, you know, has spent my entire career trying to help people successfully recover their data, that number, I think, just hurt me the most is that because, you talked about re-infections. The surest way to guarantee that you get re-attacked and reinfected is to pay the ransom. This goes back all the way to ransom since the beginning of time, right? Everyone knows if you pay the blackmail, all you're telling people is that you pay blackmail. >> You're in business, you're a good customer >> Yeah, yeah, exactly. >> for ransomware. >> Yeah, so the fact that, you know, 60, what, 2/3 of the people that were attacked by ransomware paid the ransom. That one statistic just hurt my heart. >> Yeah, and I think this is the reality. I mean, we go back, and even the psychology of the practitioners was, you know, it's super important to get backup and recovery, and that's been around for a long time, but now that's an attack vector, okay? And there's dollars involved, like I said, I'm joking, but there's recurring revenue for the bad guys if they know you're paying up and if you're stupid enough not to change your tooling. So again, it works both ways. So I got to ask you, why do you think so many owners are unable to successfully respond after an attack? Is it because, they know it's coming, I mean, they're not that dumb. I mean, they have to know it's coming. Why aren't they responding successfully to this? >> I think it's a litany of things, starting with that aspect that I mentioned before, that nobody wants to have anything to do with the backup system, right? So nobody wants to be the one to raise their hand because if you're the one that raises their hand, "You know, that's a good idea, Curtis, why don't you look into that?" Nobody wants to be- >> Where's that guy now? He doesn't work here anymore. Yeah, I hear where you coming from. >> Exactly. >> It's psychology (indistinct) >> Yeah, so there's that. But then the second is that because of that, no one's looking at the fact that backups are the attack vector. They become the attack vector. And so because they're the attack vector, they have to be protected as much, if not more than the rest of the environment. The rest of the environment can live off of Active Directory and, you know, and things like Okta, so that you can have SSO and things like that. The backup environment has to be segregated in a very special way. Backups have to be stored completely separate from your environment. The login and authentication and authorization system needs to be completely separate from your typical environment. Why? Because if that production environment is compromised, now knowing that the attacks or that the backup systems are a significant portion of the attack vector, then if the production system is compromised, then the backup system is compromised. So you've got to segregate all of that. And I just don't think that people are thinking about that. You know, and they're using the same backup techniques that they've used for many, many years. >> So what you're saying is that the attack vectors and the attackers are getting smarter. They're saying, "Hey, we'll just take out the backup first so they can't backup. So we got the ransomware." It makes sense. >> Yeah, exactly. The largest ransomware group out there, the Conti ransomware group, they are specifically targeting specific backup vendors. They know how to recognize the backup servers. They know how to recognize where the backups are stored, and they are exfiltrating the backups first, and then deleting them, and then letting you know you have ransom. >> Okay, so you guys have a lot of customers. They all kind of have the same problem. What's the patterns that you're seeing? How are they evolving? What are some of the things that they're implementing? What is the best practice? >> Well, again, you've got to fully segregate that data, and everything about how that data is stored and everything about how that data's created and accessed, there are ways to do that with other, you know, with other commercial products. You can take a standard product and put a number of layers of defense on top of it, or you can switch to the way Druva does things, which is a SaaS offering that stores your data completely in the cloud in our account, right? So your account could be completely compromised. That has nothing to do with our account. It's a completely different authentication and authorization system. You've got multiple layers of defense between your computing environment and where we store your backups. So basically, what you get by default with the way Druva stores your backups is the best you can get after doing many, many layers of defense on the other side and having to do all that work. With us, you just log in and you get all of that. >> I guess, how do you break the laws of physics? I guess that's the question here. >> Well, because that's the other thing is that by storing the data in the cloud, and I've said this a few times, you get to break the laws of physics, and the only way to do that is time travel. (both laughing) So yes, so Druva has time travel. And this is a Curtisism, by the way, I don't think this is our official position, but the idea is that the only way to restore data as fast as possible is to restore it before you actually need it, and that's kind of what I mean by time travel, in that you, basically, you configure your DR, your disaster recovery environment in Druva one time, and then we are pre-restoring your data as often as you tell us to do, to bring your DR environment up to the, you know, the current environment as quickly as we can so that in a disaster recovery scenario, which is part of your ransomware response, right? Again, there are many different parts, but when you get to actually restoring the data, you should be able to just push a button and go. The data should already be restored. And that's the way that you break the laws of physics is you break the laws of time. >> (laughs) Well, all right, everyone wants to know the next question, and this is a real big question is, are you from the future? >> (laughs) Yeah. Very much the future. >> What's it like in the future, backup, recovery? How does it restore? Is it air gapping everything? >> Yeah, well, it's a world where people don't have to worry about their backups. I like to use the phrase get out of the backup business, just get into the restore business. You know, I'm a grandfather now, and I love having a granddaughter, and I often make the joke that if I'd have known how great grandkids were, I would've skipped straight to them, right? Not possible. Just like this. Recoveries are great. Backups are really hard. So in the future, if you use a SaaS data protection system and data resiliency system, you can just do recoveries and not have to worry about backups. >> Yeah, and what's great about your background is you've got a lot of historical perspective. You've seen that, the waves of innovation. Now it really is about the recovery and real time. So a lot of good stuff going on. And got to think automated, things got to be rocking and rolling. >> Absolutely. Yeah. I do remember, again, having worked so hard with many clients over the years, back then, we worked so hard just to get the backup done. There was very little time to work on the recovery. And I really, I kid you not, that our customers don't have to do all of those things that all of our competitors have to do to, you know, to break, to try to break the laws of physics, I've been fighting the laws of physics my entire career, to get the backup done in the first place, then to secure all the data, and to air gap it and make sure that a ransomware attack isn't going to attack it. Our customers get to get straight to a fully automated disaster recovery environment that they get to test as often as possible and they get to do a full test by simply pressing a single button. And you know, I wish everybody had that ability. >> Yeah, I mean, security's a big part of it. Data's in the middle of it all. This is now mainstream, front lines, great stuff. Curtis, great to have you on, bring that perspective, and thanks for the insight. Really appreciate it. >> Always happy to talk about my favorite subject. >> All right, we'll be back in a moment. We'll have Stephen Manley, the CTO, and Anjan Srinivas, the GM and VP of Product Management will join me. You're watching theCUBE, the leader in high tech enterprise coverage. >> Ransomware is top of mind for everyone. Attacks are becoming more frequent and more sophisticated. It's a problem you can't solve alone anymore. Ransomware is built to exploit weaknesses in your backup solution, destroying data, and your last line of defense. With many vendors, it can take a lot of effort and configuration to ensure your backup environment is secure. Criminals also know that it's easy to fall behind on best practices like vulnerability scans, patches, and updates. In fact, 42% of vulnerabilities are exploited after a patch has been released. After an attack, recovery can be a long and manual process that still may not restore clean or complete data. The good news is that you can keep your data safe and recover faster with the Druva Data Resiliency Cloud on your side. The Druva platform functions completely in the cloud with no hardware, software, operating system, or complex configurations, which means there are none of the weaknesses that ransomware commonly uses to attack backups. Our software as a service model delivers 24/7/365 fully managed security operations for your backup environment. We handle all the vulnerability scans, patches, and upgrades for you. Druva also makes zero trust security easy with built-in multifactor authentication, single sign-on, and role-based access controls. In the event of an attack, Druva helps you stop the spread of ransomware and quickly understand what went wrong with built-in access insights and anomaly detection. Then you can use industry first tools and services to automate the recovery of clean, unencrypted data from the entire timeframe of the attack. Cyberattacks are a major threat, but you can make protection and recovery easy with Druva. (electronic music) (upbeat music) (mouse clicks) >> Welcome back, everyone, to theCUBE's special presentation with Druva on "Why Ransomware isn't Your Only Problem." I'm John Furrier, host of theCUBE. Our next guests are Stephen Manley, Chief Technology Officer of Druva, and Anjan Srinivas, who is the General Manager and Vice President of Product Management at Druva. Gentlemen, you got the keys to the kingdom, the technology, ransomware, data resilience. This is the topic. The IDC white paper that you guys put together with IDC really kind of nails it out. I want to get into it right away. Welcome to this segment. I really appreciate it. Thanks for coming on. >> Great to be here, John. >> So what's your thoughts on the survey's conclusion? Obviously, the resilience is huge. Ransomware continues to thunder away at businesses and causes a lot of problems, disruption. I mean, it's endless ransomware problems. What's your thoughts on the conclusion? >> So I'll say the thing that pops out to me is, on the one hand, everybody who sees the survey and reads it is going to say, "Well, that's obvious." Of course, ransomware continues to be a problem. Cyber resilience is an issue that's plaguing everybody. But I think when you dig deeper and there's a lot of subtleties to look into, but one of the things that I hear on a daily basis from the customers is, it's because the problem keeps evolving. It's not as if the threat was a static thing to just be solved and you're done. Because the threat keeps evolving, it remains top of mind for everybody because it's so hard to keep up with what's happening in terms of the attacks. >> And I think the other important thing to note, John, is that people are grappling with this ransomware attack all of a sudden where they were still grappling with a lot of legacy in their own environment. So they were not prepared for the advanced techniques that these ransomware attackers were bringing to market. It's almost like these ransomware attackers had a huge leg up in terms of technology that they had in their favor while keeping the lights on was keeping IT away from all the tooling that they needed to do. A lot of people are even still wondering, when that happens next time, what do I even do? So clearly not very surprising. Clearly, I think it's here to stay, and I think as long as people don't retool for a modern era of data management, this is going to to stay this way. >> Yeah, I hear this all the time in our CUBE conversations with practitioners. It's kind of like the security pro, give me more tools, I'll buy anything that comes in the market, I'm desperate. There's definitely attention, but it doesn't seem like people are satisfied with the tooling that they have. Can you guys share kind of your insights into what's going on in the product side? Because, you know, people claim that they have tools at crime points of recovery opportunities, but they can't get there. So it seems to be that there's a confidence problem here in the market. How do you guys see that? 'cause I think this is where the rubber meets the road with ransomware 'cause it is a moving train, it's always changing, but it doesn't seem there's confidence. Can you guys talk about that? What's your reaction? >> Yeah, let me jump in first, and Stephen can add to it. What happens is, I think this is a panic buying and they have accumulated this tooling now just because somebody said they could solve your problem, but they haven't had a chance to take a real look from a ground up perspective to see where are the bottlenecks? Where are the vulnerabilities? And which tooling set needs to lie where? Where does the logic need to reside? And what, in Druva, we are watching people do and people do it successfully, is that as they have adopted Druva technology, which is ground up built for the cloud, and really built in a way which is, you know, driven at a data insight level where we have people even monitoring our service for anomalies and activities that are suspicious. We know where we need to play a role in really kind of mitigating this ransomware, and then there's a whole plethora of ecosystem players that kind of combine to really finish the story, so to say, right? So I think this has been a panic buying situation. This is like, "Get me any help you can give me." And I think as this settles down and people really understand that longer term as they really build out a true defense mechanism, they need to think really ground up. They will start to really see the value of technologies like Druva, and try to identify the right set of ecosystem to really bring together to solve it meaningfully. >> Yes, Stephen? >> I was going to say, I mean, one of the the really interesting things in the survey for me, and for a moment, a little more than a moment, it made me think was that the large number of respondents who said, "I've got a really efficient, well-run back environment," who, then, on basically the next question said, "And I have no confidence that I can recover from a ransomware attack." And you scratch your head and you think, "Well, if your backup environment is so good, why do you have such low confidence?" And I think that's the moment when we dug deeper and we realized, if you've got a traditional architecture, and let's face it, the disk-based architecture's been around for almost two decades now, in terms of disk-based backup, you can have that tuned to the hilt. That can be running as efficiently as you want it, but it was built before the ransomware attacks, before all these cyber issues, you know, really start hitting companies. And so I have this really well-run traditional backup environment that is not at all built for these modern threat vectors. And so that's really why customers are saying, "I'm doing the best I can," but as Anjan pointed out, the architecture, the tooling isn't there to support what problems I need to solve today. >> Yeah, great point. >> And so, yeah. >> Well, that's a great point. Before we get into the customer side I want to get to in second, you know, I interviewed Jaspreet, the founder and CEO many years ago, even before the pandemic, and you mentioned modern. You guys have always had the cloud with Druva. This is huge. Now that you're past the pandemic, what is that modern cloud edge that you guys have? 'Cause that's a great point. A lot of stuff was built kind of backup and recovery bolted on, not really kind of designed into the current state of the infrastructure and the cloud native application modern environment we're seeing right now. It's a huge issue. >> I think, to me there's three things that come up over and over and over again as we talk to people in terms of, you know, being built in cloud, being cloud native, why is it an advantage? The first one is security and ransomware. And we can go deeper, but the most obvious one that always comes up is every single backup you do with Druva is air gapped, offsite, managed under a separate administrative domain so that you're not retrofitting any sort of air gap network and buying another appliance or setting up your own cloud environment to manage this. Every backup is ransomware protected, guaranteed. The second advantage is the scalability. And you know, this certainly plays into account as your business grows, or, in some cases, as you shrink or repurpose workloads, you're only paying for what you use. But it also plays a big role, again, when you start thinking of ransomware recoveries because we can scale your recovery in cloud, on premises as much or as little as you want. And then I think the third one is we're seeing, basically, things evolving, new workloads, data sprawl, new threat vectors. And one of the nice parts of being a SaaS service in the cloud is we're able to roll out new functionality every two weeks and there's no upgrade cycle, there's no waiting. The customer doesn't have to say, "Wow, I needed six months in the lab before I upgrade it and it's an 18-month, 24-month cycle before the functionality releases. You're getting it every two weeks, and it's backed by Druva to make sure it works. >> Anjan, you know, you got the product side, you know, it's a challenging job 'cause you have so many customers asking for things, probably on the roadmap, you probably can go an hour for that one, but I want to get your thoughts on what you're hearing and seeing from customers. We just reviewed the IDC with Phil. How are you guys responding to your customer's needs? Because it seems that it's highly accelerated, probably on the feature requests, but also structurally as ransomware continues to evolve. What are you hearing? What's the key customer need? How are you guys responding? >> Yeah, actually, I have two things that I hear very clearly when I talk to customers. One, I think, after listening to their security problems and their vulnerability challenges, because we see customers and help customers who are getting challenged by ransomware on a weekly basis. And what I find that this problem is not just a technology problem, it's an operating model problem. So in order to really secure themselves, they need a security operating model and a lot of them haven't figured out that security operating model in totality. Now where we come in, as Druva, is that we are providing them the cloud operating model and a data protection operating model, combined with a data insights operating model which all fit into their overall security operating model that they are really owning and they need to manage and operate, because this is not just about a piece of technology. On top of that, I think our customers are getting challenged by all the same challenges of not just spending time on keeping the lights on, but innovating faster with less. And that has been this age old problem, do more with less. But in this whole, they're like trying to innovate in the middle of the war, so to say. The war is happening, they're getting attacked, but there's also net new shadow IT challenges that's forcing them to make sure that they can manage all the new applications that are getting developed in the cloud. There is thousands of SaaS applications that they're consuming, not knowing which data is critical to their success and which ones to protect and govern and secure. So all of these things are coming at them at 100 miles per hour, while they're just trying to live one day at a time. And unless they really develop this overall security operating model, helped by cloud native technologies like Druva that really providing them a true cloud native model of really giving like a touchless and an invisible protection infrastructure. Not just beyond backups, beyond just the data protection that we all know of into this mindset of kind of being able to look at where each of those functionalities need to lie. That's where I think they're grappling with. Now Druva is clearly helping them with keep up to pace with the public cloud innovations that they need to do and how to protect data. We just launched our EC2 offering to protect EC2 virtual machines back in AWS, and we are going to be continuing to evolve that to further the many services that public cloud software 'cause our customers are really kind of consuming them at breakneck speed. >> So new workloads, new security capabilities. Love that. Good call out there. Stephen, there's still the issue of the disruption side of it. You guys have a guarantee. There's a cost of ownership as you get more tools. Can you talk about that angle of it? You got new workloads, you got the new security needs, what's the disruption impact? 'Cause you want to avoid that. How much is it going to cost you? And you guys have this guarantee, can you explain that? >> Yeah, absolutely. So Druva launched our $10 million data resiliency guarantee. And for us, there were really two key parts to this. The first obviously is $10 million means that, you know, again, we're willing to put our money where our mouth is, and that's a big deal, right? That we're willing to back this with the guarantee. But then the second part, and this is the part that I think reflects that sort of model that Anjan was talking about. We sort of look at this and we say the goal of Druva is to do the job of protecting and securing your data for you so that you, as a customer, don't have to do it anymore. And so the guarantee actually protects you against multiple types of risks, all with SLAs. So everything from your data's going to be recoverable in the case of a ransomware attack. Okay, that's good. Of course, for it to be recoverable, we're also guaranteeing your backup success rate. We're also guaranteeing the availability of the service. We're guaranteeing that the data that we're storing for you can't be compromised or leaked externally, and we're guaranteeing the long-term durability of the data so that if you backup with us today and you need to recover 30 years from now, that data's going to be recovered. So we wanted to really attack the end-to-end risks that affect our customers. Cybersecurity is a big deal, but it is not the only problem out there, and the only way for this to work is to have a service that can provide you SLAs across all of the risks, because that means, as a SaaS vendor, we're doing the job for you so you're buying results as opposed to technology. >> That's great. Great point. Ransomware isn't the only problem. That's the title of this presentation, but it's a big one. (laughs) People are concerned about it, so great stuff. In the last five minutes, guys, if you don't mind, I'd love to have you share what's on the horizon for Druva? You mentioned the new workloads, Anjan. You mentioned this new security. You're going to shift left. DevOps is now the developer model. They're running IT. Get data and security teams now stepping in and trying to be as high velocity as possible for the developers and enterprises. What's on the horizon for Druva? What trends is the company watching, and how are you guys putting that together to stay ahead in the marketplace and the competition? >> Yeah, I think, listening to our customers, what we realize is they need help with the public cloud, number one. I think that's a big wave of consumption. People are consolidating their data centers, moving to the public cloud. They need help in expanding data protection, which becomes the basis of a lot of the security operating model that I talked about. They need that first, from Druva, before they can start to get into much more advanced level of insights and analytics around that data to protect themselves and secure themselves and do interesting things with that data. So we are expanding our coverage on multiple fronts there. The second key thing is to really bring together a very insightful presentation layer, which, I think, is very unique to Druva because only we can look at multiple tenants, multiple customers because we are a SaaS vendor, and look at insights and give them best practices and guidances and analytics that nobody else can give. There's no silo anymore because we are able to take a good big vision view and now help our customers with insights that otherwise that information map is completely missing. So we are able to guide them down a path where they can optimize which workloads need what kind of protection, and then how to secure them. So that is the second level of insights and analytics that we are building. And there's a whole plethora of security offerings that we are going to build, all the way from a feature level where we have things like (audio distorts) that's already available to our customers today to prevent any anomalous behavior and attacks that would delete their backups and then they still have a way to recover from it, but also things to curate and get back to that point in time where it is safe to recover and help them with a sandbox which they can recover confidently knowing it's not going to jeopardize them again and reinfect the whole environment again. So there's a whole bunch of things coming, but the key themes are public cloud, data insights, and security, and that's where my focus is, to go and get those features delivered, and Stephen can add a few more things around services that Stephen is looking to build and launch. >> Sure, so, yeah, so John, I think one of the other areas that we see just an enormous groundswell of interest. So public cloud is important, but there are more and more organizations that are running hundreds, if not thousands of SaaS applications, and a lot of those SaaS applications have data. So there's the obvious things, like Microsoft 365, Google Workspace, but we're also seeing a lot of interest in protecting Salesforce because, if you think about it, if someone you know deletes some really important records in Salesforce, that's actually kind of the record of your business. And so, we're looking at more and more SaaS application protection, and really getting deep in that application awareness. It's not just about backup and recovery when you look at something like a Salesforce, or something like Microsoft 365. You do want to look into sandboxing, you want to look into long-term archival, because this is the new record of the business. What used to be in your on-premises databases, that all lives in cloud and SaaS applications now. So that's a really big area of investment for us. The second one, just to echo what Anjan said is, one of the great things of being a SaaS provider is I have metadata that spans across thousands of customers and tens of billions of backups a year. I'm tracking all sorts of interesting information that is going to enable us to do things like make backups more autonomous so that customers, again, I want to do the job for them. We'll do all the tuning, we'll do all the management for them to be able to better detect ransomware attacks, better respond to ransomware attacks, because we're seeing across the globe. And then, of course, being able to give them more insight into what's happening in their data environment so they can get a better security posture before any attack happens. Because, let's face it, if you can set your data up more cleanly, you're going to be a lot less worried and a lot less exposed when that attack happens. So we want to be able to, again, cover those SaaS applications in addition to the public cloud, and then we want to be able to use our metadata and use our analytics and use this massive pipeline we've got to deliver value to our customers. Not just charts and graphs, but actual services that enable them to focus their attention on other parts of the business. >> That's great stuff. >> And remember, John, I think all this while keeping things really easy to consume, consumer grade UI, APIs, and then really the power of SaaS as a service, simplicity to kind of continue on, amongst kind of keeping these complex technologies together. >> Anjan, that's a great callout. I was going to mention ease of use and self-service. Big part of the developer and IT experience. Expected. It's the table stakes. Love the analytic angle, I think that brings the scale to the table, and faster time to value to get to learn best practices. But at the end of the day, automation, cross-cloud protection and security to protect and recover. This is huge, and this is a big part of not only just protecting against ransomware and other things, but really being fast and being agile. So really appreciate the insights. Thanks for sharing on this segment, really under the hood and really kind of the value of the product. Thanks for coming on, appreciate it. >> Thank you very much. >> Okay, there it is. You have the experts talk about under the hood, the product, the value, the future of what's going on with Druva, and the future of cloud native protecting and recovering. This is what it's all about. It's not just ransomware they have to worry about. In a moment, Dave Vellante will give you some closing thoughts on the subject here. You're watching theCUBE, the leader in high tech enterprise coverage. >> As organizations migrate their business processes to multi-cloud environments, they still face numerous threats and risks of data loss. With a growing number of cloud platforms and fragmented applications, it leads to an increase in data silos, sprawl, and management complexity. As workloads become more diverse, it's challenging to effectively manage data growth, infrastructure, and resource costs across multiple cloud deployments. Using numerous backup vendor solutions for multiple cloud platforms can lead to management complexity. More importantly, the lack of centralized visibility and control can leave you exposed to security vulnerabilities, including ransomware that can cripple your business. The Druva Data Resiliency Cloud is the only 100% SaaS data resiliency platform that provides centralized, secure, air gapped, and immutable backup and recovery. With Druva, your data is safe with multiple layers of protection and is ready for fast recovery from cyberattacks, data corruption, or accidental data loss. Through a simple, easy to manage platform, you can seamlessly protect fragmented, diverse data at scale, across public clouds, and your business critical SaaS applications. Druva is the only 100% SaaS vendor that can manage, govern, and protect data across multiple clouds and business critical SaaS applications. It supports not just backup and recovery, but also data resiliency across high value use cases, such as e-discovery, sensitive data governance, ransomware, and security. No other vendor can match Druva for customer experience, infinite scale, storage optimization, data immutability, and ransomware protection. The Druva Data Resiliency Cloud, your data, always safe, always ready. Visit druva.com today to schedule a free demo. (upbeat music) >> One of the big takeaways from today's program is that in the scramble to keep business flowing over the past 2+ years, a lot of good technology practices have been put into place, but there's much more work to be done, specifically, because the frequency of attacks is on the rise and the severity of lost, stolen, or inaccessible data is so much higher today, business resilience must be designed into architectures and solutions from the start. It cannot be an afterthought. Well, actually it can be, but you won't be happy with the results. Now, part of the answer is finding the right partners, of course, but it also means taking a system's view of your business, understanding the vulnerabilities and deploying solutions that can balance cost efficiency with appropriately high levels of protection, flexibility, and speed slash accuracy of recovery. Here we hope you found today's program useful and informative. Remember, this session is available on demand in both its full format and the individual guest segments. All you got to do is go to thecube.net, and you'll see all the content, or you can go to druva.com. There are tons of resources available, including analyst reports, customer stories. There's this cool TCO calculator. You can find out what pricing looks like and lots more. Thanks for watching "Why Ransomware isn't Your Only Problem," made possible by Druva, in collaboration with IDC and presented by theCUBE, your leader in enterprise and emerging tech coverage. (upbeat music)

Published Date : Oct 13 2022

SUMMARY :

and prepared for the threats they face It's great to have you back on theCUBE. to be here with you. of the global IT landscape and it has the attention, all the way up the stack to the C-suite, and helping the organization has to be a data company in the context of IT computing. that organizations need to be aware of? and that is the area of ransomware. the demographics of the survey and kind of the aha moment of this is going to happen, and to take advantage of the key advantages and that extends the time to recover and not lose data in the that you articulated, the CIO, the CSO, you know, whoever it is, So all the way at the top, And the reason we say that is, you know, to have you on the program. Thank you, Lisa. and you are watching theCUBE, and to extract critical insights. and the Druva special presentation So it's great to have you here because the backup person often, you know, It's funny, you know. and the realities of how is that you pay blackmail. Yeah, so the fact that, you know, 60, and even the psychology Yeah, I hear where you coming from. or that the backup systems is that the attack vectors and then letting you know you have ransom. They all kind of have the same problem. is the best you can get I guess that's the question here. And that's the way that you Very much the future. So in the future, if you use Now it really is about the and they get to do a full test and thanks for the insight. Always happy to talk and Anjan Srinivas, the GM and VP none of the weaknesses This is the topic. and causes a lot of problems, disruption. and reads it is going to that they needed to do. that comes in the market, I'm desperate. Where does the logic need to reside? and let's face it, the disk-based and the cloud native of being a SaaS service in the cloud is We just reviewed the IDC with Phil. and they need to manage and operate, of the disruption side of it. And so the guarantee actually protects you I'd love to have you share So that is the second level of insights actually kind of the record really easy to consume, the scale to the table, and the future of cloud native Druva is the only 100% SaaS vendor is that in the scramble

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Eric Herzog, Infinidat | CUBEConversation


 

>>Hey everyone, welcome to this cube conversation. I'm your host Lisa Martin, and I have the pleasure of welcoming back our most prolific guest on the cube in its history, the CMO of Fin Ad, Eric Herzog. Eric, it's great to see you. Welcome back, >>Lisa. It's great to be here. Love being on the cube. I think this might be number 55 or 56. Been doing 'em a long time with the Cube. You guys are great. >>You, you have, and we always recognize you lately with the Hawaiian shirts. It's your brand that's, that's the Eric Hizo brand. We love it. But I like the pin, the infin nut pin on brand. Thank you. >>Yeah. Oh, gotta be on brand. >>Exactly. So talk about the current IT landscape. So much change we've seen in the last couple of years. Specifically, what are some of the big challenges that you are talking with enterprise customers and cloud service providers? About what, what are some of those major things on their minds? >>So there's a couple things. First of all is obviously with the Rocky economy and even before covid, just for storage in particular, CIOs hate storage. I've been doing this now since 1986. I have never, ever, ever met a CIO at any company I've bid with. And I've been with four of the biggest storage companies on this planet. Never met a cio. Used to be a storage guy. So they know they need it, but boy, they really don't like it. So the storage admins have to manage more and more storage. Exabytes, exabytes, it just ballooning for what a storage admin has to do. Then you then have the covid and is it recession? No. Is it a growth? And then clearly what's happened in the last year with what's going on in Europe and the, is it a recession, the inflation. So they're always looking to, how do we cut money on storage yet still get what we need for our applications, workloads, and use cases. So that's definitely the biggest, the first topic. >>So never met a CIO that was a storage admin or as a fan, but as you point out, they need it. And we've seen needs changing in customer landscapes, especially as the threat landscape has changed so dramatically the last couple of years. Ransomware, you've said it before, I say it too. It's no longer if it's when it's how often. It's the frequency. We've gotta be able to recover. Backups are being targeted. Talk to me about some of, in that landscape, some of the evolutions of customer challenges and maybe those CIOs going, We've gotta make sure that our, our storage data is protected. >>So it's starting to change. However, historically with the cio and then when they started hiring CISOs or security directors, whatever they had, depending on the company size, it was very much about protecting the edge. Okay, if you will, the moat and the wall of the castle. Then it was the network in between. So keep the streets inside the castle clean. Then it was tracking down the bad guy. So if they did get over, the issue is, if I remember correctly, the sheriff of Nottingham never really caught Robinhood. So the problem is the dwell time where the ransomware malware's hidden on storage could be as much as 200 days. So I think they're starting to realize at the security level now, forget, forget the guys on the storage side, the security guys, the cso, the CIO, are starting to realize that if you're gonna have a comprehensive cybersecurity strategy, must include storage. And that is new >>That, well, that's promising then. That's new. I mean obviously promising given the, the challenges and the circumstances. So then from a storage perspective, customers that are in this multi-cloud hybrid cloud environment, you talked about the the edge cloud on-prem. What are some of the key things from a storage perspective that customers have to achieve these days to be secure as data volumes continue to grow and spread? >>So what we've done is implement on both primary storage and secondary storage and technology called infin safe. So Infin Safe has the four legs of the storage cyber security stool. So first of all is creating an air gap. In this case, a logical air gap can be local or remote. We create an immutable snapshot, which means it can't be changed, it can't be altered, so you can't change it. We have a fenced forensic environment to check out the storage because you don't wanna recover. Again, malware and rans square can is hidden. So you could be making amenable snapshots of actually malware, ransomware, and never know you're doing it right. So you have to check it out. Then you need to do a rapid recovery. The most important thing if you have an attack is how fast can you be up and going with recovery? So we have actually instituted now a number of cyber storage security guarantees. >>We will guarantee the SLAs on a, the snapshot is absolutely immutable. So they know that what they're getting is what they were supposed to be getting. And then also we are guaranteeing recovery times on primary storage. We're guaranteeing recovery of under one minute. We'll make the snapshot available under one minute and on secondary storage under 20 minutes. So those are things you gotta look for from a security perspective. And then the other thing you gotta practice, in my world, ransomware, malware, cyber tech is basically a disaster. So yes, you got the hurricane, yes, you got the flood, yes, you got the earthquake. Yes, you got the fire in the building. Yes you got whatever it may be. But if you don't practice malware, ransomware, recoveries and protection, then it might as well be a hurricane or earthquake. It will take your data, >>It will take your data on the numbers of customers that pay ransom is pretty high, isn't it? And and not necessarily able to recover their data. So it's a huge risk. >>So if you think about it, the government documented that last year, roughly $6 trillion was spent either protecting against ransomware and malware or paying ransomware attacks. And there's been several famous ones. There was one in Korea, 72 million ransom. It was one of the Korea's largest companies. So, and those are only the ones that make the news. Most of 'em don't make the news. Right. >>So talk to me then, speaking and making the news. Nobody wants to do that. We, we know every industry is vulnerable to this. Some of the ones that might be more vulnerable, healthcare, government, public sector education. I think the Los Angeles Unified School district was just hit as well in September. They >>Were >>What, talk to me about how infin out is helping customers really dial down the risk when the threat actors are becoming more and more sophisticated? >>Well, there's a couple things. First of all, our infin safe software comes free on our main product. So we have a product called infin Guard for Secondary Storage and it comes for free on that. And then our primary storage product's called the Infin Box. It also comes for free. So they don't have to use it, but we embed it. And then we have reference architectures that we give them our ses, our solutions architects and our technical advisors all up to speed on why they should do it, how they should do it. We have a number of customers doing it. You know, we're heavily concentrated the global Fortune 2000, for example, we publicly announced that 26% of the Fortune 50 use our technology, even though we're a small company. So we go to extra lengths to a B, educated on our own front, our own teams, and then B, make sure they portray that to the end users and our channel partners. But the end users don't pay a dime for the software that does what I just described, it's free, it's included when you get you're Infin box or you're ingar, it's included at no charge. >>That's pretty differentiating from a competitive standpoint. I might, I would guess >>It is. And also the guarantee. So for example, on primary storage, okay, whether you'd put your Oracle or put your SAP or I Mongo or your sequel or your highly transactional workloads, right? Your business finance workload, all your business critical stuff. We are the first and only storage company that offers a primary guarantee on cyber storage resilience. And we offer two of them on primary storage. No other vendor offers a guarantee, which we do on primary storage. Whether you the first and right now as of here we are sitting in the middle of October. We are still the only vendor that offers anything on primary storage from a guaranteed SLA on primary storage for cyber storage resilience. >>Let's talk about those guarantees. Walk me through what you just announced. There's been a a very, a lot of productivity at Infin DAT in 2022. A lot of things that you've announced but on crack some of the things you're announcing. Sure. Talk to me specifically about those guarantees and what's in it for me as a customer. It sounds pretty obvious, but I'd love to hear it from you. >>Okay, so we've done really three different types of guarantees. The first one is we have a hundred percent availability guarantee on our primary storage. And we've actually had that for the last, since 2019. So it's a hundred percent availability. We're guaranteed no downtime, a hundred percent availability, which for our customer base being heavily concentrated, the global Fortune 2000 large government enterprises, big universities and even smaller companies, we do a lot of business with CSPs and MSPs. In fact, at the Flash Memory Summit are Infin Box ssa All Flash was named the best product for hyperscaler deployment. Hyperscaler basically means cloud servers provider. So they need a hundred percent availability. So we have a guarantee on that. Second guarantee we have is a performance guarantee. We'll do an analysis, we look at all their workloads and then we will guarantee in writing what the performance should be based on which, which of our products they want to buy are Infin Box or Infin Box ssa, which is all flash. >>Then we have the third one is all about cyber resilience. So we have two on our Infin box, our Infin box SSA for primary storage, which is a one the immutability of the snapshot and immediately means you can't erase the data. Right? Camp tamper with it. Second one is on the recovery time, which is under a minute. We just announced in the middle of October that we are doing a similar cyber storage resilience guarantee on our ARD secondary product, which is designed for backup recovery, et cetera. We will also offer the immutably snapshot guarantee and also one on the recoverability of that data in under 20 minutes. In fact, we just did a demo at our live launch earlier this week and we demoed 20 petabytes of Veeam backup data recovered in 12 minutes. 12 >>Minutes 2012. >>20 petabytes In >>12 bytes in 12 minutes. Yes. That's massive. That's massively differentiating. But that's essential for customers cuz you know, in terms of backups and protecting the data, it's all about recovery >>A and once they've had the attack, it's how fast you get back online, right? That that's what happens if they've, if they can't stop the attack, can't stop the threat and it happens. They need to get that back as fast as they can. So we have the speed of recovery on primary stores, the first in the industry and we have speed on the backup software and we'll do the same thing for a backup data set recovery as well. Talk >>To me about the, the what's in it for me, For the cloud service providers, they're obviously the ones that you work with are competing with the hyperscalers. How does the guarantees and the differentiators that Fin out is bringing to market? How do you help those cloud SPS dial up their competitiveness against the big cheeses? >>Well, what we do is we provide that underlying infrastructure. We, first of all, we only sell things that are petabyte in scale. That's like always sell. So for example, on our in fitter guard product, the raw capacity is over four petabytes. And the effective capacity, cuz you do data reduction is over 85 petabytes on our newest announced product, on our primary storage product, we now can do up to 17 petabytes of effective capacity in a single rack. So the value to the service rider is they can save on what slots? Power and floor. A greener data center. Yeah, right. Which by the way is not just about environmentals, but guess what? It also translate into operational expense. >>Exactly. CapEx office, >>With a lot of these very large systems that we offer, you can consolidate multiple products from our competitors. So for example, with one of the competitors, we had a deal that we did last quarter 18 competitive arrays into one of ours. So talk about saving, not just on all of the operational expense, including operational manpower, but actually dramatically on the CapEx. In fact, one of our Fortune 500 customers in the telco space over the last five years have told us on CapEx alone, we've saved them $104 million on CapEx by consolidating smaller technology into our larger systems. And one of the key things we do is everything is automated. So we call it autonomous automation use AI based technology. So once you install it, we've got several public references who said, I haven't touched this thing in three or four years. It automatically configures itself. It automatically adjusts to changes in performance and new apps. When I put in point a new app at it automatically. So in the old days the storage admin would optimize performance for a new application. We don't do that, we automatically do it and autonomously the admin doesn't even click a button. We just sense there's new applications and we automate ourselves and configure ourselves without the admin having to do anything. So that's about saving operational expense as well as operational manpower. >>Absolutely. I was, one of the things that was ringing in my ear was workforce productivity and obviously those storage admins being able to to focus on more strategic projects. Can't believe the CIOs aren't coming around yet. But you said there's, there's a change, there's a wave coming. But if we think about the the, the what's in it for me as a customer, the positive business outcomes that I'm hearing, lower tco, your greener it, which is key. So many customers that we talk to are so focused on sustainability and becoming greener, especially with an on-prem footprint, workforce productivity. Talk about some of the other key business outcomes that you're helping customers achieve and how it helps them to be more competitive. >>Sure. So we've got a, a couple different things. First of all, storage can't go down. When the storage goes down, everyone gets blamed. Mission. When an app goes down, no one really thinks about it. It's always the storage guy's fault. So you want to be a hundred percent available. And that's today's businesses, and I'd actually argue it's been this way for 20 years are 24 by seven by 365. So that's one thing that we deliver. Second thing is performance. So we have public references talk about their SAP workload that used to take two hours, now takes 20 minutes, okay? We have another customer that was doing SAP queries. They improved their performance three times, Not 3%, not 3%, three times. So 300% better performance just by using our storages. They didn't touch the sap, they didn't touch the servers. All they do is to put our storage in there. >>So performance relates basically to applications, workloads and use cases and productivity beyond it. So think the productivity of supply chain guys, logistics guys, the shipping guys, the finance guys, right? All these applications that run today's enterprises. So we can automate all that. And then clearly the cyber threat. Yeah, that is a huge issue. And every CIO is concerned about the cyber threat. And in fact, it was interesting, Fortune magazine did a survey of CEOs, and this was last May, the number one concern, 66% in that may survey was cyber security number one concern. So this is not just a CIO thing, this is a CEO thing and a board level >>Thing. I was gonna say it's at at the board level that the cyber security threats are so real, they're so common. No one wants to be the next headline, like the colonial pipeline, right? Or the school districts or whatnot. And everybody is at risk. So then what you're enabling with what you've just announced, the all the guarantees on the SLAs, the massively fast recovery times, which is critical in cyber recovery. Obviously resilience is is key there. Modern data protection it sounds like to me. How do you define that and and what are customers looking for with respect to modern cyber resilience versus data protection? >>Yeah, so we've got normal data protection because we work with all the backup vendors. Our in ARD is what's known as a purpose built backup appliance. So that allows you to back at a much faster rate. And we work all the big back backup vendors, IBM spectrum Protect, we work with veritas vem com vault, oracle arm, anybody who does backup. So that's more about the regular side, the traditional backup. But the other part of modern data protection is infusing that with the cyber resilience. Cuz cyber resilience is a new thing. Yes, from a storage guy perspective, it hasn't been around a long time. Many of our competitors have almost nothing. One or two of our competitors have a pretty robust, but they don't guarantee it the way we guarantee it. So they're pretty good at it. But the fact that we're willing to put our money where our mouth is, we think says we price stand above and then most of the other guys in the storage industry are just starting to get on the bandwagon of having cyber resilience. >>So that changes what you do from data protection, what would call modern data protection is a combination of traditional backup recovery, et cetera. Now with this influence and this infusion of cybersecurity cyber resilience into a storage environment. And then of course we've also happened to add it on primary storage as well. So whether it's primary storage or backup and archive storage, we make sure you have that right cyber resilience to make it, if you will, modern data protection and diff different from what it, you know, the old backup of your grandfather, father, son backup in tape or however you used to do it. We're well beyond that now we adding this cyber resilience aspect. Well, >>From a cyber resilience perspective, ransomware, malware, cyber attacks are, that's a disaster, right? But traditional disaster recovery tools aren't really built to be able to pull back that data as quickly as it sounds like in Trinidad is able to facilitate. >>Yeah. So one of the things we do is in our reference architectures and written documentation as well as when we do the training, we'd sell the customers you need to practice, if you practice when there's a fire, a flood, a hurricane, an earthquake or whatever is the natural disaster you're practicing that you need to practice malware and ran somewhere. And because our recovery is so rapid and the case of our ingar, our fenced environment to do the testing is actually embedded in it. Several of our competitors, if you want the fenced environment, you have to buy a second product with us. It's all embedded in the one item. So A, that makes it more effective from a CapEx and opex perspective, but it also makes it easier. So we recommend that they do the practice recoveries monthly. Now whether they do it or not separate issue, but at least that's what we're recommending and say, you should be doing this on a monthly basis just like you would practice a disaster, like a hurricane or fire or a flood or an earthquake. Need to be practicing. And I think people are starting to hear it, but they don't still think more about, you know, the flood. Yeah. Or about >>The H, the hurricane. >>Yeah. That's what they think about. They not yet thinking about cybersecurity as really a disaster model. And it is. >>Absolutely. It is. Is is the theme of cyber resilience, as you said, this is a new concept, A lot of folks are talking about it, applying it differently. Is that gonna help dial up those folks just really being much more prepared for that type of cyber disaster? >>Well, we've made it so it's automated. Once you set up the immutable snapshots, it just does its thing. You don't set it and forget it. We create the logical air back. Once you do it, same thing. Set it and forget it. The fence forensic environment, easy to deploy. You do have to just configure it once and then obviously the recovery is almost instantaneous. It's under a minute guaranteed on primary storage and under 20 minutes, like I told you when we did our launch this week, we did 20 petabytes of Veeam backup data in 12 minutes. So that's pretty incredible. That's a lot of data to have recovered in 12 minutes. So the more automated we make it, which is what our real forte is, is this autonomous automation and automating as much as possible and make it easy to configure when you do have to configure. That's what differentiates what we do from our perspective. But overall in the storage industry, it's the recognition finally by the CISOs and the CIOs that, wait a second, maybe storage might be an essential part of my corporate cybersecurity strategy. Yes. Which it has not been historically, >>But you're seeing that change. Yes. >>We're starting to see that change. >>Excellent. So talk to me a little bit before we wrap here about the go to market one. Can folks get their hands on the updates to in kindergar and Finn and Safe and Penta box? >>So all these are available right now. They're available now either through our teams or through our, our channel partners globally. We do about 80% of our business globally through the channel. So whether you talk to us or talk to our channel partners, we're there to help. And again, we put our money where your mouth is with those guarantees, make sure we stand behind our products. >>That's awesome. Eric, thank you so much for joining me on the program. Congratulations on the launch. The the year of productivity just continues for infinit out is basically what I'm hearing. But you're really going in the extra mile for customers to help them ensure that the inevitable cyber attacks, that they, that they're complete storage environment on prem will be protected and more importantly, recoverable Very quickly. We appreciate your insights and your input. >>Great. Absolutely love being on the cube. Thank you very much for having us. Of >>Course. It's great to have you back. We appreciate it. For Eric Herzog, I'm Lisa Martin. You're watching this cube conversation live from Palo Alto.

Published Date : Oct 12 2022

SUMMARY :

and I have the pleasure of welcoming back our most prolific guest on the cube in Love being on the cube. But I like the pin, the infin nut pin on brand. So talk about the current IT landscape. So the storage admins have to manage more and more So never met a CIO that was a storage admin or as a fan, but as you point out, they need it. So the problem is the dwell time where the ransomware malware's hidden on storage could be as much as 200 days. So then from a storage perspective, customers that are in this multi-cloud hybrid cloud environment, So Infin Safe has the four legs of the storage cyber security stool. So yes, you got the hurricane, yes, you got the flood, yes, you got the earthquake. And and not necessarily able to recover their data. So if you think about it, the government documented that last year, So talk to me then, speaking and making the news. So we have a product called infin Guard for Secondary Storage and it comes for free I might, I would guess We are the first and only storage company that offers a primary guarantee on cyber on crack some of the things you're announcing. So we have a guarantee on that. in the middle of October that we are doing a similar cyber cuz you know, in terms of backups and protecting the data, it's all about recovery of recovery on primary stores, the first in the industry and we have speed on the backup software How does the guarantees and the differentiators that Fin And the effective capacity, cuz you do data reduction Exactly. So in the old days the storage admin would optimize performance for a new application. So many customers that we talk to are so focused on sustainability So that's one thing that we deliver. So performance relates basically to applications, workloads and use cases and productivity beyond it. So then what you're enabling with what you've just announced, So that's more about the regular side, the traditional backup. So that changes what you do from data protection, what would call modern data protection is a combination of traditional built to be able to pull back that data as quickly as it sounds like in Trinidad is able to facilitate. And because our recovery is so rapid and the case And it is. Is is the theme of cyber resilience, as you said, So the more automated we make it, which is what our real forte is, But you're seeing that change. So talk to me a little bit before we wrap here about the go to market one. So whether you talk to us or talk to our channel partners, we're there to help. Congratulations on the launch. Absolutely love being on the cube. It's great to have you back.

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Druva Why Ransomware Isn't Your Only Problem Full Episode V3


 

>>The past two and a half years have seen a dramatic change in the security posture of virtually all organizations. By accelerating the digital business mandate, the isolation economy catalyzed a move toward cloud computing to support remote workers. This, we know this had several ripple effects on CISO and CIO strategies that were highly visible at the board of directors level. Now, the first major change was to recognize that the perimeter had suddenly been vaporized protection. As a result moved away from things like perimeter based firewalls toward more distributed endpoints, cloud security, and modern identity management. The second major change was a heightened awareness of the realities of ransomware. Ransomware as a service, for example, emerges a major threat where virtually anyone with access to critical data and criminal intentions could monetize corporate security exposures. The third major change was a much more acute understanding of how data protection needed to become a fundamental component of cybersecurity strategies. >>And more specifically, CIOs quickly realized that their business resilient strategies were too narrowly DR focused that their DR approach was not cost efficient and needed to be modernized. And that new approaches to operational resilience were needed to reflect the architectural and business realities of this new environment. Hello, and welcome to Why Ransomware isn't your Only Problem, a service of the Cube made possible by dva. And in collaboration with idc. I'm your host, Dave Ante, and today we're present a three part program. We'll start with the data. IDC recently conducted a global survey of 500 business technology practitioners across 20 industries to understand the degree to which organizations are aware of and prepared for the threats they face. In today's new world, IDC Research Vice President Phil Goodwin is here to share the highlights of the study and summarize the findings from a recent research report on the topic. >>After that, we're gonna hear from Curtis Preston, who's the Chief Technical Evangelist at Druva. I've known Curtis for decades. He's one of the world's foremost experts on backup and recovery, specifically in data protection. Generally. Curtis will help us understand how the survey data presented by IDC aligns with the real world findings from the field, from his point of view. And he'll discuss why so many organizations have failed to successfully recover from an attack without major pains and big costs, and how to avoid such operational disruptions and disasters. And then finally, we'll hear from the technical experts at dva, Steven Manly and Anja Serenas. Steven is a 10 time cubo and Chief technology officer at dva. And Anjan is vice president and general manager of product management at the company. And these individuals will specifically address how DVA is closing the gaps presented in the IDC survey through their product innovation. Or right now I'm gonna toss it to Lisa Martin, another one of the hosts for today's program. Lisa, over to you. >>Bill Goodwin joins me next, the VP of research at idc. We're gonna be breaking down what's going on in the threat landscape. Phil, welcome to the program. It's great to have you back on the cube. >>Hey, Lisa, it's great to be here with you. >>So talk to me about the state of the global IT landscape as we see cyber attacks massively increasing, the threat landscape changing so much, what is IDC seeing? >>You know, you, you really hit the, the top topic that we find from IT organizations as well as business organizations. And really it's that digital resilience that that ransomware that has everybody's attention, and it has the attention not just of the IT people, but of the business people alike, because it really does have profound effects across the organization. The other thing that we're seeing, Lisa, is really a move towards cloud. And I think part of that is driven by the economics of cloud, which fundamentally changed the way that we can approach disaster recovery, but also is accelerated during the pandemic for all the reasons that people have talked about in terms of work from home and so on. And then really the third thing is the economic uncertainty. And this is relatively new for 2022, but within idc we've been doing a lot of research around what are those impacts going to be. And what we find people doing is they want greater flexibility, they want more cost certainty, and they really want to be able to leverage those cloud economics to be, have the scale, upper scale, down on demand nature of cloud. So those are in a nutshell, kind of the three things that people are looking at. >>You mentioned ransomware, it's a topic we've been talking about a lot. It's a household word these days. It's now Phil, no longer if we're gonna get attacked. It's when it's how often it's the severity. Talk about ransomware as a priority all the way up the stack to the C-suite. And what are they trying to do to become resilient against it? >>Well, what, what some of the research that we did is we found that about 77% of organizations have digital resilience as a, as a top priority within their organization. And so what you're seeing is organizations trying to leverage things to become more, more resilient, more digitally resilient, and to be able to really hone in on those kinds of issues that are keeping keeping them awake at night. Quite honestly, if you think about digital resilience, it really is foundational to the organization, whether it's through digital transformation or whether it's simply data availability, whatever it might happen to be. Digital resilience is really a, a large umbrella term that we use to describe that function that is aimed at avoiding data loss, assuring data availability, and helping the organization to extract value from their data >>And digital resilience, data resilience as every company these days has to be a data company to be competitive, digital resilience, data resilience. Are you using those terms interchangeably or data resilience to find as something a little bit different? >>Well, sometimes yeah, that we do get caught using them when, when one is the other. But data resilience is really a part of digital resilience, if you think about the data itself and the context of of IT computing. So it really is a subset of that, but it is foundational to IT resilience. You, you really, you can't have it resilience about data resilience. So that, that's where we're coming from on it >>Inextricably linked and it's becoming a corporate initiative, but there's some factors that can complicate digital resilience, data resilience for organizations. What are some of those complications that organizations need to be aware of? >>Well, one of the biggest is what, what you mentioned at the, at the top of the segment. And, and that is the, the area of ransomware, the research that we found is about 46% of organizations have been hit within the last three years. You know, it's kind of interesting how it's changed over the years. Originally being hit by ransomware had a real stigma attached to it. Organizations didn't want to admit it, and they really avoided confronting that. Nowadays, so many people have been hit by it, that that stigma has gone. And so really it is becoming more of a community kind of effort as people try to, to defend against these ransoms. The other thing about it is it's really a lot like whackamole. You know, they attack us in one area and and, and we defend against it. They, so they attack us in another area and we defend against it. >>And in fact, I had a, an individual come up to me at a show not long ago and said, You know, one of these days we're gonna get pretty well defended against ransomware and it's gonna go away. And I responded, I don't think so because we're constantly introducing new systems, new software, and introducing new vulnerabilities. And the fact is ransomware is so profitable, the bad guys aren't gonna just fade into the night without giving it a a lot of fight. So I really think that ransomware is one of those things that here is here for the long term and something that we, we have to address and have to get proactive about. >>You mentioned some stats there and, and recently IDC and DVA did a white paper together that really revealed some quite shocking results. Talk to me about some of the things. Let, let's talk a little bit about the demographics of the survey and then talk about what was the biggest finding there, especially where it's concern concerning ransomware. >>Yeah, this, this was a worldwide study. It was sponsored by DVA and conducted by IDC as an independent study. And what we did, we surveyed 500 is a little over 500 different individuals across the globe in North America select countries in in western Europe, as well as several in, in Asia Pacific. And we did it across industries with our 20 different industries represented. They're all evenly represented. We had surveys that included IT practitioners, primarily CIOs, CTOs, VP of of infrastructure, you know, managers of data centers, things like that. And the, and the biggest finding that we had in this, Lisa, was really finding that there is a huge disconnect, I believe, between how people think they are ready and what the actual results are when they, when they get attacked. Some of the, some of the statistics that we learned from this, Lisa, include 83% of organizations believe or tell, told us that they have a, a playbook that, that they have for ransomware. >>I think 93% said that they have a high degree or a high or very high degree of confidence in their recovery tools and, and are fully automated. And yet when you look at the actual results, you know, I told you a moment ago, 46% have been attacked successfully. I can also tell you that in separate research, fewer than a third of organizations were able to fully recover their data without paying the ransom. And some two thirds actually had to pay the ransom. And even when they did, they didn't necessarily achieve their full recovery. You know, the bad guys aren't, aren't necessarily to be trusted. And, and so the software that they provide sometimes is, is fully recovered. Sometimes it's not. So you look at that and you go, Wow. On, on the one hand, people think they're really, really prepared, and on the other hand, the results are, are absolutely horrible. >>You know, two thirds of people having, having to pay their ransom. So you start to ask yourself, well, well, what is, what's going on there? And I believe that a lot of it comes down to, kind of reminds me of the old quote from Mike Tyson. Everybody has a plan until they get punched in the mouth. And I think that's kind of what happens with ransomware. You, you think you know what you're, you're doing, you think you're ready based on the information you have. And these people are smart people and, and they're professionals, but oftentimes you don't know what you don't know. And like I say, the bad guys are always dreaming up new ways to attack us. And so I think for that reason, a lot of these have been successful. So that was kind of the key finding to me in kind of the aha moment really in this whole thing. Lisa, >>That's a massive disconnect with the vast majority saying we have a cyber recovery playbook, yet nearly half being the victims of ransomware in the last three years, and then half of them experiencing data loss. What is it then that organizations in this situation across any industry can do to truly enable cyber resilience data resilience as it's, as we said, this is a matter of this is gonna happen just a matter of when and how often >>It it is a matter, Yeah, as you said, it's not if when or, or how often. It's really how badly. So I think what organizations are really do doing now is starting to turn more to cloud-based services. You know, finding professionals who know what they're doing, who have that breadth of experience and who have seen the kinds of, of necessary steps that it takes to do a recovery. And the fact of the matter is a disaster recovery and a cyber recovery are really not the same thing. And so organizations need to be able to, to plan the kinds of recovery associated with cyber recovery in terms of forensics, in terms of, of scanning, in terms of analysis and so forth. So they're, they're turning to professionals in the cloud much more in order to get that breadth of experience and, and to take advantage of cloud based services that are out there. >>Talk to me about some of the key advantages of cloud-based services for data resilience versus traditional legacy on-prem equipment. What are some of the advantages? Why are is IDC seeing this big shift to cloud where, where data resilience is concerned? >>Well, the first and foremost is the economics of it. You know, you can, you can have on demand resources. And in the old days when we had disaster recoveries where there we had two different data centers and a failover and so forth, you know, you had double the infrastructure. If your financial services, it might even be triple, the infrastructure is very complicated, very difficult by going to the cloud. Organizations can subscribe to disaster recovery as a service. It increasingly what we see is a new market of cyber recovery as a service. So being able to leverage those resources to be able to have the forensic analysis available to them, to be able to have the other resources available that are on demand, and to have that plan in place to have those resources in place. I think what happens in a number of situations, Lisa, is that that organizations think they're ready, but then all of a sudden they get hit and all of a sudden they have to engage with outside consultants or they have to bring in other experts and that, and that extends the time to recover that they have and it also complicates it. >>So if they have those resources in place, then they can simply turn them on, engage them, and get that recover going as quickly as possible. >>So what do you think the big issue here is, is it that these, these I p T practitioners over 500 that you surveyed across 20 industries is a global survey? Do they not know what they don't know? What's the the overlying issue here? >>Yeah, I think that's right. It's, you don't know what you don't know and until you get into a specific attack, you know, there, there are so many different ways that, that organizations can be attacked. And in fact, from this research that we found is that in many cases, data exfiltration exceeds data corruption by about 50%. And when you think about that, the, the issue is, once I have your data, what are you gonna do? I mean, there's no amount of recovery that is gonna help. So organizations are either faced with paying the ransom to keep the data from perhaps being used on the dark web or whatever, or simply saying no and, and taking their chances. So best practice things like encryption, immutability, you know, things like that that organizations can put into place. Certainly air gaps. Having a, a solid backup foundation to, to where data is you have a high recovery, high probability of recovery, things like that. Those are the kinds of things that organizations have to put into place really is a baseline to assure that they can recover as fast as possible and not lose data in the event of a ransomware attack. >>Given some of the, the, the disconnect that you articulated, the, the stats that show so many think we are prepared, we've got a playbook, yet so many are being, are being attacked. The vulnerabilities and the, and the, as the, the landscape threat landscape just gets more and more amorphous. Why, what do you recommend organizations? Do you talk to the IT practitioners, but does this go all the way up to the board level in terms of, hey guys, across every industry, we are vulnerable, this is gonna happen, we've gotta make sure that we are truly resilient and proactive? >>Yes, and in fact, what we found from this research is in more than half of cases, the CEO is directly involved in the recovery. So this is very much a C-suite issue. And if you look at the, the, the consequences of ransom where it's not just the ransom, it's the loss productivity, it's, it's the loss of, of revenue. It's, it's the loss of, of customer faith and, and, and goodwill and organizations that have been attacked have, have suffered those consequences. And, and many of them are permanent. So people at the board level where it's, whether it's the ceo, the cfo, the cio, the c cso, you know, whoever it is, they're extremely concerned about these. And I can tell you they are fully engaged in addressing these issues within their organization. >>So all the way at the top critically important, business critical for any industry. I imagine some industries may be a little bit more vulnerable than others, financial services, healthcare, education, we've just seen big attack in Los Angeles County. But in terms of establishing data resilience, you mentioned ransomware isn't going anywhere, It's a big business business, it's very profitable. But what is IDCs prediction where ransomware is concerned? Do you think that organizations, if they truly adopt cloud and status based technologies, can they get to a place where the C-suite doesn't have to be involved to the point where they're, they really actually have i i functioning playbook? >>I i, I don't know if we'll ever get to the point where the CCC C suite is not involved. It's probably very important to have that, that level of executive sponsorship. But, but what we are seeing is, in fact, we predicted by 20 25, 50 5% of organizations we'll have shifted to a cloud centric strategy for their data resilience. And the reason we say that is, you know, workloads on premises aren't going away. So that's the core. We have an increasing number of workloads in the cloud and, and at the edge, and that's really where the growth is. So being able to take that cloud centric model and take advantage of, of cloud resources like immutable storage, being able to move data from region to region inexpensively and easily and, and to be able to take that cloud centric perspective and apply it on premises as well as in the cloud and at the edge is really where we believe that organizations are shifting their focus. >>Got it. We're just cracking the surface here. Phil, I wish we had more time, but I had a chance to read the Juba sponsored IDC White paper. Fascinating finds. I encourage all of you to download that, Take a read, you're gonna learn some very interesting statistics and recommendations for how you can really truly deploy data resilience in your organization. Phil, it's been a pleasure to have you on the program. Thank you for joining >>Me. No problem. Thank you, Lisa. >>In a moment, John Furrier will be here with his next guest. For right now, I'm Lisa Martin and you are watching the Cube, the leader in live tech coverage. >>We live in a world of infinite data, sprawling, dispersed valuable, but also vulnerable. So how do organizations achieve data resiliency when faced with ever expanding workloads, increasing security threats and intensified regulations? Unfortunately, the answer often boils down to what flavor of complexity do you like best? The common patchwork approaches are expensive, convoluted, and difficult to manage. There's multiple software and hardware vendors to worry about different deployments for workloads running on premises or in the cloud. And an inconsistent security framework resulting in enterprises maintaining four of five copies of the same data, increasing costs and risk building to an incoherent mess of complications. Now imagine a world free from these complexities. Welcome to the dr. A data resiliency cloud where full data protection and beautiful simplicity converge. No hardware, no upgrades, no management, just total data resili. With just a few clicks, you can get started integrating all of your data resiliency workflows in minutes. >>Through a true cloud experience built on Amazon web services, the DR A platform automates and manages critical daily tasks giving you time to focus on your business. In other words, get simplicity, scalability, and security instantly with the dr A data resiliency cloud, your data isn't just backed up, it's ready to be used 24 7 to meet compliance needs and to extract critical insights. You can archive data for long term retention, be protected against device failure and natural disasters, and recover from ransomware lightning fast. DVA is trusted with billions of backups annually by thousands of enterprises, including more than 60 of the Fortune 500 costing up to 50% less in the convoluted hardware, software, and appliance solutions. As data grows and becomes more critical to your business advantage, a data resiliency plan is vital, but it shouldn't be complicated. Dr. A makes it simple. >>Welcome back everyone to the cube and the drew of a special presentation of why ransomware isn't your only problem. I'm John Furrier, host of the Cube. We're here with w Curtis Preston. Curtis Preston, he known in the industry Chief Technical Evangelist at Druva. Curtis, great to see you. We're here at why ransomware isn't your only problem. Great to see you. Thanks for coming on. >>Happy to be here. >>So we always see each other events now events are back. So it's great to have you here for this special presentation. The white paper from IDC really talks about this in detail. I to get your thoughts and I'd like you to reflect on the analysis that we've been covering here and the survey data, how it lines up with the real world that you're seeing out there. >>Yeah, I think it's the, the survey results really, I'd like to say, I'd like to say that they surprised me, but unfortunately they didn't. The, the, the, the data protection world has been this way for a while where there's this, this difference in belief or difference between the belief and the reality. And what we see is that there are a number of organizations that have been hit successfully, hit by ransomware, paid the ransom and, and, and or lost data. And yet the same people that were surveyed, they had to high degrees of confidence in their backup system. And I, you know, I, I could, I could probably go on for an hour as to the various reasons why that would be the case, but I, I think that this long running problem that as long as I've been associated with backups, which you know, has been a while, it's that problem of, you know, nobody wants to be the backup person. And, and people often just, they, they, they don't wanna have anything to do with the backup system. And so it sort of exists in this vacuum. And so then management is like, oh, the backup system's great, because the backup person often, you know, might say that it's great because maybe it's their job to say so. But the reality has always been very, very different. >>It's funny, you know, we're good boss, we got this covered. Good, >>It's all good, it's all good, >>You know, and the fingers crossed, right? So again, this is the reality and, and, and as it becomes backup and recovery, which we've talked about many times on the cube, certainly we have with you before, but now with ransomware also, the other thing is people get ransomware hit multiple times. So it's not, not only like they get hit once, so, you know, this is a constant chasing the tail on some ends, but there are some tools out there, You guys have a solution. And so let's get into that. You know, you have had hands on backup experience. What are the points that surprised you the most about what's going on in this world and the realities of how people should be going forward? What's your take? >>Well, I would say that the, the, the one part in the survey that surprised me the most was people that had a huge, you know, that there, there was a huge percentage of people that said that they had a, a, a, you know, a a a ransomware response, you know, in readiness program. And you look at that and you, how could you be, you know, that high percentage of people be comfortable with their ransomware readiness program and a, you know, which includes a number of things, right? There's the cyber attack aspect of responding to a ransomware attack, and then there's the recovery aspect. And so your, you believe that your company was ready for that, and then you go, and I, I think it was 67% of the people in the survey paid the ransom, which as, as a person who, you know, has spent my entire career trying to help people successfully recover their data, that number I think just hurt me the most is that because you, you talked about re infections, the surest way to guarantee that you get rein attacked and reinfected is to pay the ransom. This goes back all the way ransom since the beginning of time, right? Everyone knows if you pay the blackmail, all you're telling people is that you pay blackmail and >>You're in business, you're a good customer arr for ransomware. >>Yeah. So the, the fact that, you know, 60 what two thirds of the people that were attacked by ransomware paid the ransom. That one statistic just, just hurt my heart. >>Yeah. And I think this is the reality. I mean, we go back and even the psychology of the practitioners was, you know, it's super important to get back in recovery and that's been around for a long time, but now that's an attack vector, okay? And there's dollars involved, like I said, the arr joking, but there's recurring revenue for the, for the bad guys if they know you're paying up and if you're stupid enough not to change, you're tooling, right? So, so again, it works both ways. So I gotta ask you, why do you think so many are unable to successfully respond after an attack? Is it because they know it's coming? I mean, I mean, they're not that dumb. I mean, they have to know it's coming. Why aren't they responding and successfully to this? >>I I think it's a, it's a litany of thing starting with the, that aspect that I mentioned before, that nobody wants to have anything to do with the backup system, right? So nobody wants to be the one to raise their hand because if, if you're the one that raises their hand, you know what, that's a good idea, Curtis, why don't you look into that? Right. Nobody, nobody wants to be, Where's >>That guy now? He doesn't work here anymore. Yeah, but I I I hear where you come from exactly. Psychology. >>Yeah. So there, there's that. But then the second is that because of that, no one's looking at the fact that backups are the attack vector. They, they, they become the attack vector. And so because they're the attack vector, they have to be protected as much, if not more than the rest of the environment. The rest of the environment can live off of active directory and, you know, and things like Okta, so that you can have SSO and things like that. The backup environment has to be segregated in a very special way. Backups have to be stored completely separate for from your environment. The login and authentication and authorization system needs to be completely separate from your typical environment. Why? Because if you, if that production environment is compromised now knowing that the attacks or that the backup systems are a significant portion of the attack vector, then you've, if, if the production system is compromised, then the backup system is compromised. So you've got to segregate all of that. And I, and I just don't think that people are thinking about that. Yeah. You know, and they're using the same backup techniques that they've used for many, many years. >>So what you're saying is that the attack vectors and the attackers are getting smarter. They're saying, Hey, we'll just take out the backup first so they can backup. So we got the ransomware it >>Makes Yeah, exactly. The the largest ransomware group out there, the KTI ransomware group, they are specifically targeting specific backup vendors. They know how to recognize the backup servers. They know how to recognize where the backups are stored, and they are exfiltrating the backups first and then deleting them and then letting you know you have ransom. >>Okay, so you guys have a lot of customers, they all kind of have the same this problem. What's the patterns that you're seeing? How are they evolving? What are some of the things that they're implementing? What is the best practice? >>Well, again, you, you've got to fully segregate that data. There are, and, and everything about how that data is stored and everything about how that data's created and accessed. There are ways to do that with other, you know, with other commercial products, you can take a, a, a standard product and put a number of layers of defense on top of it, or you can switch to the, the way Druva does things, which is a SAS offering that stores your data completely in the cloud in our account, right? So your account could be completely compromised. That has nothing to do with our account. And the, the, it's a completely different authentication and authorization system. You've got multiple layers of defense between your computing environment and where we store your backups. So basically what you get by default with the, the way juva stores your backups is the best you can get after doing many, many layers of defense on the other side and having to do all that work with us. You just log in and you get all of that. >>I guess how do, how do you break the laws of physics? I guess that's the question here. >>Well, when, because that's the other thing is that by storing the data in the cloud, we, we do, and I've said this a few times, that you get to break the laws of physics and the, the only way to do that is to, is time travel and what, that's what it, so yeah, so Druva has time travel. What, and this is a criticism by the way. I don't think this is our official position, but Yeah. But the, the idea is that the only way to restore data as fast as possible is to restore it before you actually need it. And that's what kind of what I mean by time travel in that you basically, you configure your dr your disaster recovery environment in, in DVA one time. And then we are pre restoring your data as often as you tell us to do, to bring your DR environment up to the, you know, the, the current environment as quickly as we can so that in a disaster recovery scenario, which is part of your ransomware response, right? Again, there are many different parts, but when you get to actually restoring the data, you should be able to just push a button and go the, the data should already be restored. And that's the, i that's the way that you break the laws of physics is you break the laws of time. >>Well, I, everyone wants to know the next question, and this is the real big question, is, are you from the future? >>Yeah. Very much the future. >>What's it like in the future? Backup recovery as a restore, Is it air gaping? Everything? >>Yeah. It, it, it, Well it's a world where people don't have to worry about their backups. I I like to use the phrase, get outta the backup business. Just get into the ReSTOR business. I I, you know, I'm, I'm a grandfather now and I, and I love having a granddaughter and I often make the joke that if I don't, if I'd have known how great grandkids were, I would've skipped straight to them, right? Not possible. Just like this. Recoveries are great. Backups are really hard. So in the future, if you use a SAS data protection system and data resiliency system, you can just do recoveries and not have to worry about >>Backups. Yeah. And what's great about your background is you've got a lot of historical perspective. You've seen that been in the ways of innovation now it's really is about the recovery and real time. So a lot of good stuff going on. And God think automated thingss gotta be rocking and rolling. >>Absolutely. Yeah. I do remember, again, having worked so hard with many clients over the years, back then, we worked so hard just to get the backup done. There was very little time to work on the recovery. And I really, I kid you not that our customers don't have to do all of those things that all of our competitors have to do to, you know, to, to break, to try to break the laws of physics. I've been fighting the laws of physics my entire career to get the backup done in the first place. Then to secure all the data, right to air gap it and make sure that a ransomware attack isn't going to attack it. Our customers get to get straight to a fully automated disaster recovery environment that they get to test as often as possible and they get to do a full test by simply pressing a single button. And you know, I, I wish that, I wish everybody had that ability. >>Yeah, I mean, security's a big part of it. Data's in the middle of it all. This is now mainstream front lines. Great stuff Chris, great to have you on, bring that perspective and thanks for the insight. Really >>Appreciate it. Always happy to talk about my favorite subject. >>All right, we'll be back in a moment. We'll have Steven Manley, the cto and on John Shva, the GM and VP of Product Manage will join me. You're watching the cube, the leader in high tech enterprise coverage. >>Ransomware is top of mind for everyone. Attacks are becoming more frequent and more sophisticated. It's a problem you can't solve alone anymore. Ransomware is built to exploit weaknesses in your backup solution, destroying data and your last line of defense. With many vendors, it can take a lot of effort and configuration to ensure your backup environment is secure. Criminals also know that it's easy to fall behind on best practices like vulnerability, scans, patches and updates. In fact, 42% of vulnerabilities are exploited after a patch has been released after an attack. Recovery can be a long and manual process that still may not restore clean or complete data. The good news is that you can keep your data safe and recover faster with the DR A data resiliency cloud on your side. The DR A platform functions completely in the cloud with no hardware, software, operating system, or complex configurations, which means there are none of the weaknesses that ransomware commonly uses to attack backups. >>Our software as a service model delivers 24 7 365 fully managed security operations for your backup environment. We handle all the vulnerability scans, patches and upgrades for you. DVA also makes zero trust security easy with builtin multifactor authentication, single sign-on and role-based access controls in the event of an attack. Druva helps you stop the spread of ransomware and quickly understand what went wrong. With builtin access insights and anomaly detection, then you can use industry first tools and services to automate the recovery of clean unencrypted data from the entire timeframe of the attack. Cyber attacks are a major threat, but you can make protection and recovery easy with dva. >>Welcome back everyone to the Cubes special presentation with DVA on why ransomware isn't your only problem. I'm John er, host of the Cube. Our next guest are Steven Manley, Chief Technology Officer of dva and I, John Trini VAs, who is the general manager and vice president of product management and Druva. Gentleman, you got the keys to the kingdom, the technology, ransomware, data resilience. This is the topic, the IDC white paper that you guys put together with IDC really kind of nails it out. I want to get into it right away. Welcome to this segment. I really appreciate it. Thanks for coming on. >>Great to be here John. >>So what's your thoughts on the survey's conclusion? I've obviously the resilience is huge. Ransomware is continues to thunder away at businesses and causes a lot of problems. Disruption, I mean just it's endless ransomware problems. What's your thoughts on the con conclusion? >>So I'll say the, the thing that pops out to me is, is on the one hand, everybody who sees the survey, who reads, it's gonna say, well that's obvious. Of course ransomware continues to be a problem. Cyber resilience is an issue that's plaguing everybody. But, but I think when you dig deeper and there and there's a lot of subtleties to look into, but, but one of the things that, that I hear on a daily basis from the customers is it's because the problem keeps evolving. It, it's not as if the threat was a static thing to just be solved and you're done because the threat keeps evolving. It remains top of mind for everybody because it's so hard to keep up with with what's happening in terms of the attacks. >>And I think the other important thing to note, John, is that people are grappling with this ransomware attack all of a sudden where they were still grappling with a lot of legacy in their own environment. So they were not prepared for the advanced techniques that these ransomware attackers were bringing to market. It's almost like these ransomware attackers had a huge leg up in terms of technology that they had in their favor while keeping the lights on was keeping it away from all the tooling that needed to do. A lot of people are even still wondering when that happens next time, what do I even do? So clearly not very surprising. Clearly I think it's here to stay and I think as long as people don't retool for a modern era of data management, this is going to stay this >>Way. Yeah, I mean I hear this whole time and our cube conversations with practitioners, you know there, it's kind of like the security pro give me more tools, I'll buy anything that comes in the market. I'm desperate. There's definitely attention but it doesn't seem like people are satisfied with the tooling that they have. Can you guys share kind of your insights into what's going on in the product side? Because you know, people claim that they have tools at fine points of, of recovery opportunities but they can't get there. So it seems to be that there's a confidence problem here in the market. What, how do you guys see that? Cuz I think this is where the rubber meets the road with ransomware cuz it's, it is a moving train, it's always changing but it doesn't seem as confidence. Can you guys talk about that? What's your reaction? >>Yeah, let me jump in first and Steven can add to it. What happens is I think this is a panic buying and they have accumulated this tooling now just because somebody said could solve your problem, but they haven't had a chance to take a re-look from a ground up perspective to see where are the bottlenecks, where are the vulnerabilities and which tooling set needs to lie? Where, where does the logic need to recite and what in Drew we are watching people do and people do it successfully, is that as they have adopted through our technology, which is ground up built for the cloud and really built in a way which is, you know, driven at a data insight level where we have people even monitoring our service for anomalies and activities that are suspicious. We know where we need to play a role in really kind of mitigating this ransomware. >>And then there's a whole plethora of ecosystem players that kind of combine to really really finish the story so to say, right? So I think this has been a panic buying situation. This is like, get me any help you can give me. And I think as this settles down and people really understand that longer term as they really build out a true defense mechanism, they need to think really ground up. They will start to really see the value of technologies like Druva and tried to identify the right set of ecosystem to really bring together to solve it meaningfully. >>Steven, >>I was gonna say, I mean one, one of the, one of the really interesting things in the survey for me and, and, and for a moment, little more than a moment, it made me think was that the large number of respondents who said I've got a really efficient well run backup environment, who then on basically the next question said, and I have no confidence that I can recover from a ransomware attack. And you scratch your head and you think, well if your backup environment is so good, why do you have such low confidence? And, and, and I think that's the moment when we, we dug deeper and we realized, you know, if you've got a traditional architecture and let's face the dis base architecture's been around for almost two decades now in terms of dis based backup, you can have that tune to the help that can be running as efficiently, efficiently as you want it, but it was built before the ransomware attacks before, before all these cyber issues, you know, really start hitting companies. And so I have this really well run traditional backup environment that is not at all built for these modern threat vectors. And so that's really why customers are saying I'm doing the best I can, but as Angen pointed out, the architecture, the tooling isn't there to support what, what problems I need to solve today. Yeah, >>Great point. And so yeah, well that's a great point. Before we get into the customer side, I wanna get to in second, you know, I interviewed Jare, the the founder CEO many years ago, even before the pandemic. You mentioned modern, you guys have always had the cloud, which r this is huge. Now that you're past the pandemic, what is that modern cloud edge you guys have? Cuz that's a great point. A lot of stuff was built kind of Beckham recovery bolted on, not really kind of designed into the, the current state of the infrastructure and the cloud native application modern environment we're seeing. Right? Now's a huge issue >>I think. I think it's, it's to me there's, there's three things that come up over and over and over again as, as we talk to people in terms of, you know, being built in cloud, being cloud native, why is an advantage? The first one is, is security and ransomware. And, and, and we can go deeper, but the most obvious one that always comes up is every single backup you do with DVA is air gap offsite managed under a separate administrative domain so that you're not retrofitting any sort of air gap network and buying another appliance or setting up your own cloud environment to manage this. Every backup is ransomware protected, guaranteed. I think the second advantage is the scalability. And you know this, this certainly plays into account as your, your business grows or in some cases as you shrink or repurpose workloads, you're only paying for what you use. >>But it also plays a a big role again when you start thinking of ransomware recoveries because we can scale your recovery in cloud on premises as much or as little as you want. And then I think the third one is we're seeing a basically things evolving new workloads, data sprawl, new threat vectors. And one of the nice parts of being a SA service in the cloud is you're able to roll out new functionality every two weeks and there's no upgrade cycle, there's no waiting, you know, the customer doesn't have to say, Wow, I need it six months in the lab before I upgrade it and it's an 18 month, 24 month cycle before the functionality releases. You're getting it every two weeks and it's backed by Druva to make sure it works. >>That says on John, you know, you got the, the product side, you know, it's challenging job cuz you have so many customers asking for things probably on the roadmap you probably go hour for that one. But I wanna get your thoughts on what you're hearing and seeing from customers. You know, we just reviewed the IDC with Phil. How are you guys responding to your customer's needs? Because it seems that it's highly accelerated on the, probably on the feature request, but also structurally as as ransomware continues to evolve. What are you hearing, what's the key customer need? How are you guys responding? >>Yeah, actually I have two things that I hear very clearly when I talk to customers. One, I think after listening to their security problems and their vulnerability challenges because we see customers and help customers who are getting challenge by ransomware on a weekly basis. And what I find that this problem is not just a technology problem, it's an operating model problem. So in order to really secure themselves, they need a security operating model and a lot of them haven't figured out that security operating model in totality. Now where we come in as rua is that we are providing them the cloud operating model and a data protection operating model combined with a data insights operating model which all fit into their overall security operating model that they are really owning and they need to manage and operate because this is just not about a piece of technology. >>On top of that, I think our customers are getting challenged by all the same challenges of not just spending time on keeping the lights on but innovating faster with faster, with less. And that has been this age old problem, do more with less. But in this, in this whole, they're like trying to innovate in the middle of the war so to say, right, the war is happening, they're getting attacked, but there's also net new shadow IT challenges that's forcing them to make sure that they can manage all the new applications that are getting developed in the cloud. There is thousands of SaaS applications that they're consuming not knowing which data is critical to their success and which ones to protect and govern and secure. So all of these things are coming at them at a hundred miles per hour while they're just, you know, trying to live one day at a time. >>And unless they really develop this overall security operating model helped by cloud native technologies like Druva that really providing them a true cloud native model of really giving like a touchless and an invisible protection infrastructure. Not just beyond backups, beyond just the data protection that we all know of into this kind of this mindset of kind of being able to look at where each of those functionalities need to lie. That's where I think they're grappling with now. Drew is clearly helping them with keep up to pace with the public cloud innovations that they need to do and how to protect data. We just launched our EC two offering to protect EC two virtual machines back in aws and we are gonna be continuing to evolve that to further many services that public cloud software cuz our customers are really kind of consuming them at breakneck speed. >>So the new workloads, the new security capabilities. Love that. Good, good call out there. Steven, this still the issue of the disruption side of it, you guys have a guarantee there's a cost of ownership as you get more tools. Can you talk about that angle of it? Because this is, you got new workloads, you got the new security needs, what's the disruption impact? Cause you know, you won't avoid that. How much is it gonna cost you? And you guys have this guarantee, can you explain that? >>Yeah, absolutely. So, so Dr launched our 10 million data resiliency guarantee. And, and for us, you know, there were, there were really two key parts to this. The first obviously is 10 million means that, you know, again we're, we're we're willing to put our money where our mouth is and, and that's a big deal, right? That that, that we're willing to back this with the guarantee. But then the second part, and, and, and this is the part that I think reflects that, that sort of model that Angen was talking about, we, we sort of look at this and we say the goal of DVA is to do the job of protecting and securing your data for you so that you as a customer don't have to do it anymore. And so the guarantee actually protects you against multiple types of risks all with SLAs. So everything from, you know, your data's gonna be recoverable in the case of a ransomware attack. >>Okay, that's good. Of course for it to be recoverable, we're also guaranteeing, you know, your backup, your backup success rate. We're also guaranteeing the availability of the service. You know, we're, we're guaranteeing that the data that we're storing for you can't be compromised or leaked externally and you know, we're guaranteeing the long term durability of the data so that if you back up with us today and you need to recover 30 years from now, that data's gonna be recovered. So we wanted to really attack the end to end, you know, risks that, that, that affect our customers. Cybersecurity is a big deal, but it is not the only problem out there and the only way for this to work is to have a service that can provide you SLAs across all of the risks because that means, again, as a SAS vendor, we're doing the job for you so you're buying results as opposed to technology. >>That's great. Great point. Ransomware isn't the only problem that's the title of this presentation, but is a big one. People concerned about it. So great stuff. In the last five minutes guys, if you don't mind, I'd love to have you share what's on the horizon for dva. You mentioned the new workloads on John, you mentioned this new security hearing shift left DevOps is now the developer model, they're running it get data and security teams now stepping in and trying to be as vo high velocity as possible for the developers and enterprises. What's on the horizon, Ava? What trends is the company watching and how are you guys putting that together to stay ahead in the marketplace and the competition? >>Yeah, I think listening to our customers, what we realize is they need help with the public cloud. Number one. I think that's a big wave of consumption. People are consolidating their data centers, moving to the public cloud. They need help in expanding data protection, which becomes the basis of a lot of the security operating model that I talked about. They need that first from before they can start to get into much more advanced level of insights and analytics on that data to protect themselves and secure themselves and do interesting things with that data. So we are expanding our coverage on multiple fronts there. The second key thing is to really bring together a very insightful presentation layer, which I think is very unique to thwa because only we can look at multiple tenants, multiple customers because we are a SAS vendor and look at insights and give them best practices and guidances and analytics that nobody else can give. >>There's no silo anymore because we are able to take a good big vision view and now help our customers with insights that otherwise that information map is completely missing. So we are able to guide them down a path where they can optimize which workloads need, what kind of protection, and then how to secure them. So that is the second level of insights and analytics that we are building. And there's a whole plethora of security offerings that we are gonna build all the way from a feature level where we have things like recycle bin that's already available to our customers today to prevent any anomalous behavior and attacks that would delete their backups and then they still have a way to recover from it, but also things to curate and get back to that point in time where it is safe to recover and help them with a sandbox which they can recover confidently knowing it's not going to jeopardize them again and reinfect the whole environment again. So there's a whole bunch of things coming, but the key themes are public cloud, data insights and security and that's where my focus is to go and get those features delivered and Steven can add a few more things around services that Steven is looking to build in launch. >>Sure. So, so yeah, so, so John, I think one of the other areas that we see just an enormous groundswell of interest. So, so public cloud is important, but there are more and more organizations that are running hundreds if not thousands of SaaS applications and a lot of those SaaS applications have data. So there's the obvious things like Microsoft 365 Google workspace, but we're also seeing a lot of interest in protecting Salesforce because if you think about it, you know, if you, if if someone you know deletes some really important records in Salesforce, that's, that's actually actually kind of the record of your business. And so, you know, we're looking at more and more SaaS application protection and, and really getting deep in that application awareness. It's not just about backup and recovery. When you look at something like, like a sales force or something like Microsoft 365, you do wanna look into sandboxing, you wanna, you wanna look into long term archival because again, this is the new record of the business, what used to be in your on premises databases that all lives in cloud and SaaS applications now. >>So that's a really big area of investment for us. The second one, just to echo what, what engine said is, you know, one of the great things of being a SaaS provider is I have metadata that spans across thousands of customers and tens of billions of backups a year. And I'm tracking all sorts of interesting information that is going to enable us to do things like make backups more autonomous so that customers, again, I want to do the job for them, will do all the tuning, we'll do all the management for them to be able to better detect ransomware attacks, better respond to ransomware attacks because we're seeing across the globe. And then of course being able to give them more insight into what's happening in their data environment so they can get a better security posture before any attack happens. Because let's face it, if you can set your, your data up more cleanly, you're gonna be a lot less worried and a lot less exposed from that attack happens. So we want to be able to again, cover those SaaS applications in addition to the public cloud. And then we want to be able to use our metadata and use our analytics and use this massive pipeline. We've got to deliver value to our customers, not just charts and graphs, but actual services that enable them to focus their attention on other parts of the business. >>That's great stuff. Run John. >>And remember John, I think all this while keeping things really easy to consume consumer grade UI APIs and the, the really, the power of SaaS as a service simplicity to kind of continue on amongst kind of keeping these complex technologies together. >>Aj, that's a great call out. I was gonna mention ease of use is and self-service, big part of the developer and IT experience expected, it's the table stakes, love the analytic angle. I think that brings the scale to the table and faster time to value to get to learn best practices. But the end of the day automation, cross cloud protection and security to protect and recover. This is huge and this is big part of not only just protecting against ransomware and other things, but really being fast and being agile. So really appreciate the insights. Thanks for sharing on this segment, really under the hood and really kind of the value of of the product. Thanks for coming on. Appreciate it. >>Thank you very much. >>Okay, there it is. You got the experts talking about under the hood, the product, the value, the future of what's going on with Druva and the future of cloud native protecting and recovering. This is what it's all about. It's not just ransomware they have to worry about. In a moment, Dave Ante will give you some closing thoughts on the subject here you're watching the cube, the leader in high tech enterprise coverage. >>As organizations migrate their business processes to multi-cloud environments, they still face numerous threats and risks of data loss. With a growing number of cloud platforms and fragmented applications, it leads to an increase in data silos, sprawl, and management complexity. As workloads become more diverse, it's challenging to effectively manage data growth infrastructure, and resource costs across multiple cloud deployments. Using numerous backup vendor solutions for multiple cloud platforms can lead to management complexity. More importantly, the lack of centralized visibility and control can leave you exposed to security vulnerabilities, including ransomware that can cripple your business. The dr. A Data Resiliency Cloud is the only 100% SAS data resiliency platform that provides centralized, secure air gapped and immutable backup and recovery. With dva, your data is safe with multiple layers of protection and is ready for fast recovery from cyber attack, data corruption, or accidental data loss. Through a simple, easy to manage platform, you can seamlessly protect fragmented, diverse data at scale, across public clouds and your business critical SaaS applications. Druva is the only 100% SAS fender that can manage, govern, and protect data across multiple clouds and business critical SAS applications. It supports not just backup and recovery, but also data resiliency across high value use cases such as e-discovery, sensitive data governance, ransomware, and security. No other vendor can match Druva for customer experience, infinite scale storage optimization, data immutability and ransomware protection. The DVA data resiliency cloud your data always safe, always ready. Visit druva.com today to schedule a free demo. >>One of the big takeaways from today's program is that in the scramble to keep business flowing over the past two plus years, a lot of good technology practices have been put into place, but there's much more work to be done specifically because the frequency of attacks is on the rise and the severity of lost, stolen, or inaccessible data is so much higher. Today, business resilience must be designed into architectures and solutions from the start. It cannot be an afterthought. Well, actually it can be, but you won't be happy with the results. Now, part of the answer is finding the right partners, of course, but it also means taking a systems' view of your business, understanding the vulnerabilities and deploying solutions that can balance cost efficiency with appropriately high levels of protection, flexibility, and speed slash accuracy of recovery. You know, we hope you found today's program useful and informative. Remember, this session is available on demand in both its full format and the individual guest segments. All you gotta do is go to the cube.net and you'll see all the content, or you can go to druva.com. There are tons of resources available, including analyst reports, customer stories. There's this cool TCO calculator. You can find out what pricing looks like and lots more. Thanks for watching why Ransomware isn't your only problem Made possible by dva, a collaboration with IDC and presented by the Cube, your leader in enterprise and emerging tech coverage.

Published Date : Oct 6 2022

SUMMARY :

Now, the first major change was to recognize that the perimeter had suddenly And that new approaches to operational resilience were general manager of product management at the company. It's great to have you back on the cube. of the IT people, but of the business people alike, because it really does have a priority all the way up the stack to the C-suite. and helping the organization to extract value from their data to be a data company to be competitive, digital resilience, data resilience. But data resilience is really a part of digital resilience, if you think about the data itself What are some of those complications that organizations need to be aware of? Well, one of the biggest is what, what you mentioned at the, at the top of the segment. And the fact Let, let's talk a little bit about the demographics of the survey and then talk about what was CTOs, VP of of infrastructure, you know, managers of data centers, the bad guys aren't, aren't necessarily to be trusted. And these people are smart people and, and they're professionals, but oftentimes you don't know what you don't know. in this situation across any industry can do to truly enable And the fact of the matter is a disaster recovery What are some of the advantages? And in the old days when we had disaster recoveries where So if they have those resources in place, then they can simply turn them on, Those are the kinds of things that organizations have to put into place really what do you recommend organizations? the c cso, you know, whoever it is, they're extremely concerned about these. So all the way at the top critically important, business critical for any industry. And the reason we say that is, you know, Phil, it's been a pleasure to have you on the program. Thank you, Lisa. I'm Lisa Martin and you are watching the Cube, the leader in live tech coverage. the answer often boils down to what flavor of complexity do you like best? the DR A platform automates and manages critical daily tasks giving you time I'm John Furrier, host of the Cube. So it's great to have you here for this special presentation. because the backup person often, you know, might say that it's great because maybe It's funny, you know, we're good boss, we got this covered. not only like they get hit once, so, you know, this is a constant chasing the tail on some the ransom, which as, as a person who, you know, the people that were attacked by ransomware paid the ransom. for the bad guys if they know you're paying up and if you're stupid enough not to change, I I think it's a, it's a litany of thing starting with the, that aspect that I mentioned before, Yeah, but I I I hear where you come from exactly. so that you can have SSO and things like that. So what you're saying is that the attack vectors and the attackers are getting smarter. the backups first and then deleting them and then letting you know you Okay, so you guys have a lot of customers, they all kind of have the same this problem. after doing many, many layers of defense on the other side and having to do all that work with I guess how do, how do you break the laws of physics? And that's the, i that's the way that you break the laws So in the future, if you use a SAS data protection system seen that been in the ways of innovation now it's really is about the recovery and real time. all of our competitors have to do to, you know, to, to break, to try to break the laws Great stuff Chris, great to have you on, bring that perspective and thanks for the insight. Always happy to talk about my favorite subject. the GM and VP of Product Manage will join me. The good news is that you can keep your data safe and recover faster with in the event of an attack. the IDC white paper that you guys put together with IDC really kind Ransomware is continues to thunder away at businesses and causes a lot of So I'll say the, the thing that pops out to me is, is on the one hand, And I think the other important thing to note, John, is that people are grappling So it seems to be that there's a confidence problem you know, driven at a data insight level where we have people even monitoring our service finish the story so to say, right? And you scratch your head and you think, well if your backup environment I wanna get to in second, you know, I interviewed Jare, the the founder CEO many years ago, but the most obvious one that always comes up is every single backup you do with DVA And one of the nice parts of being a SA service in the cloud is How are you guys responding to your customer's needs? overall security operating model that they are really owning and they need to manage and operate And that has been this age old problem, do more with less. of this mindset of kind of being able to look at where each of those functionalities need to lie. And you guys have this guarantee, And so the guarantee actually protects you against multiple types of risks all with SLAs. this to work is to have a service that can provide you SLAs across all of the risks because You mentioned the new workloads on John, you mentioned this new security hearing shift left DevOps is now the and analytics on that data to protect themselves and secure themselves and do interesting things with So that is the second level of insights and And so, you know, what engine said is, you know, one of the great things of being a SaaS provider is I have metadata That's great stuff. a service simplicity to kind of continue on amongst kind of keeping these complex But the end of the day automation, cross cloud protection and security to protect and It's not just ransomware they have to worry about. and control can leave you exposed to security vulnerabilities, including ransomware that frequency of attacks is on the rise and the severity of

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Jon Sahs, Charles Mulrooney, John Frey, & Terry Richardson | Better Together with SHI


 

foreign [Music] Lisa Martin of the cube here hpe and AMD better together with Shi is the name of our segment and I'm here with four guests please welcome Charlie mulrooney Global pre-sales engineering manager at SHI John saw is also of shi joins us Global pre-sales Technical consultant and back with me are Terry Richardson North American Channel Chief and Dr John Fry Chief technologist of sustainable transformation at hpe welcome gang great to have you here all here Thank you Lisa thank you good to be here all right Charlie let's go ahead and start with you keeping the Earth sustainable and minimizing carbon emissions greenhouse gases is a huge priority for businesses right everywhere globally can you talk truly about what Shi is seeing in the marketplace with respect to sustainable I.T sure so starting about a year and a half two years ago we really noticed that our customers certainly our largest Enterprise customers were putting into their annual reports their Chairman's letters their SEC filings that they had sustainability initiatives ranging from achieving carbon neutral uh or carbon zero goals starting with 20 50 dates and then since then we've seen 20 40 and 2030 targets to achieve net neutrality and rfps rfis that we're Fielding certainly all now contain elements of that so this is certainly top of mind for our largest customers our Fortune 250 and Fortune 500 customers for sure where we're seeing an onslaught of requests for this we get into many conversations with the folks that are leading these efforts to understand you know here's what we have today what can we do better what can we do different to help make it an impact on those goals so making an impact top of Mind pretty much for everyone as you mentioned John Sal's let's bring you into the conversation now when you're in customer conversations what are some of the things that you talk about with respect to shi's approach to sustainability sustainable I.T are you seeing more folks that are implementing things tactically versus strategically what's going on in the customer space well so Charlie touched on something really important that you know the the wake-up moment for us was receiving you know proposal requests or customer meeting requests that were around sustainability and it was really around two years ago I suppose for the first time and those requests started coming from european-based companies because they had a bit of a head start uh over the U.S based global companies even um and what we found was that sustainability was already well down the road and that they were doing very interesting things to uh use renewable energy for data centers uh utilized they were already considering sustainability for new technologies as a high priority versus just performance costs and other factors that you typically had at the top so as we started working with them uh I guess that beginning was more tactical because we really had to find a way to respond uh we were starting to be asked about our own efforts and in regards to sustainability we have our headquarters in Somerset and our second Headquarters in Austin Texas um those are the gold certified we've been installing solar panels producing waste across the company recycling efforts and so forth charging stations for electric vehicles all that sort of thing to make our company more sustainable in in uh in our offices and in our headquarters um but it's a lot more than that and what we found was that we wanted to look to our vast number of supply of customers and partners we have over 30 000 partners that would work with globally and tens of thousands of customers and we wanted to find best practices and Technologies and services that we could uh talk about with these customers and apply and help integrate together as a as a really large Global uh reseller and integrator we can have a play there and bring these things together from multiple uh partners that we work with to help solve customer problems and so over time it's become more strategic and we've been uh as a company building the uh the the the forward efforts through organizing a true formal sustainability team and growing that um and then also reporting for CDP echovatus and so forth and it's really that all has been coming about in the last couple of years and we take it very seriously it sounds like it also sounds like from the customer's perspective they're shifting from that tactical maybe early initial approach to being more strategic to really enabling sustainable I.T across their organization and I imagine from a business driver's perspective John saws and Charlie are you hearing customers you talked about it being part of rfps but also where are customers in terms of we need to have a sustainable I.T strategy so that we can attract and retain the right investors we can attract and retain customers Charlie John what are your thoughts on that yeah that's top of mind with uh with all the folks that we're talking to uh I would say there's probably a three-way tie for the importance of uh attracting and retaining investors as you said plus customers customers are shopping their customers are shopping for who has aligned their ESG priorities in sustainable priorities uh with their own and who is going to help them with their own reporting of you know spoke to and ultimately scope three reporting from greenhouse gas emissions and then the attracting and retaining Talent uh it's another element now of when you're bringing on a new talent to your organization they have a choice and they're thinking with their decision to accept a role or not within your organization of what your strategies are and do they align so we're seeing those almost interchangeable in terms of priorities with with the customers we're talking to it was a little surprising because we thought initially this is really focused on investors attracting the investors but it really has become quite a bit more than that and it's been actually very interesting to see the development of that prioritization more comprehensive across the organization let's bring Dr John Fry into the conversation and Terry your neck so stay tuned Dr Frey can you talk about hpe and Shia partnering together what are some of the key aspects of the relationship that help one another support and enable each other's aggressive goals where sustainability is concerned yeah it's a great question and one of the things about the sustainability domain in solving these climate challenges that we all have is we've got to come together and partner to solve them no one company's going to solve them by themselves and for our Collective customers the same way from an hpe perspective we bring the expertise on our products we bring in a sustainable I.T point of view where we've written many white papers on the topic and even workbooks that help companies Implement a sustainable I.T program but our direct sales forces can't reach all of our customers and in many cases we don't have the local knowledge that our business partners like Shi bring to the table so they extend the reach they bring their own expertise their portfolio that they offer to the customer is wider than just Enterprise Products so by working together we can do a better job of helping the customer meet their own needs give them the right Technology Solutions and enhance that customer experience it's because they get more value from us collectively it really is better together which is a very appropriate name for our segment here Terry let's bring you into the conversation talk to us about AMD how is it helping customers to create that sustainable I.T strategy and what are some of the differentiators that what AMD is doing that that are able to be delivered through Partners like Shi well Lisa you use the word enabling um just a short while ago and fundamentally AMD enables hpe and partners like Shi to bring differentiated solutions to customers so in the data center space We Begin our journey in 2017 with some fundamental Design Elements for our processor technology that we're really keenly focused on improving performance but also efficiency so now the the most common measure that we see for the types of customers that Charlie and John were talking about was really that measure of performance per watt and you'll continue to see AMD enable um customers to to try to find ways to to do more in a sustainable way within the constraints that they may be facing whether it's availability of power data center space or just needing to meet overall sustainability goals so we have skills and expertise and tools that we make available to hpe and to Shi to help them have even stronger differentiated conversations with customers sounds like to me Terry that it's that AMD can be even more of an more than an enabler but really an accelerator of what customers are able to do from a strategic perspective on sustainability you're right about that and and we actually have tools greenhouse gas TCO tools that can be leveraged to really quantify the impact of some of the the new technology decisions that customers are making to allow them to achieve their goals so we're really proud of the work that we're doing in partnership with companies like hpe and Shi Better Together as we've said at the beginning and just a minute ago Charlie let's bring you back in talk to us a little bit about what Shi is doing to leverage sustainable I.T and enable your customers to meet their sustainability goals and their initiatives so for quite a while we've had uh some offerings to help customers especially in the end user compute side a lot of customers were interested in I've got assets for you know let's say a large sales force that had been carrying tablets or laptops and you know those need to be refreshed what do I do with those how do I responsibly retire or recycle those and we've been offering solutions for that for quite some time it's within the last year or two when we started offering for them guarantees and Assurance assurances of how they can if that equipment is reusable by somebody else how can we issue them you know credits for uh carving credits for reuse of that equipment somewhere else so it's not necessarily going to be E-Waste it's uh something that can be recycled and reused we have other programs with helping extend the life of of some systems where they look at boy I have an awful lot of data on these machines where historically they might want to just retire those because the the sensitivity of the data needed to be handled very specifically we can help them properly remove the sensitive data and still allow reuse of that equipment so we've been able to accomplish some Creative Solutions specifically around end user compute in the past but we are looking to new ways now to to really help extend that into Data Center infrastructure and Beyond to really help with what are the needs what are the the best ways to help our customers handle the things that are challenging them [Music] that's a great point that you bring up Charlie and the security kind of popped into my head here John saw his question for you when you're in customer conversations and you're talking about or maybe they're talking about help us with waste reduction with recycling where are you having those customer conversations I know sustainability is a board level it's a c-level discussion but where are you having those conversations within the customer organization well so it's a it's a combination of um organizations within the customer these are these Global organizations typically when we're talking about asset like cycle management asset recovery how do you do that in a sustainable Green Way and securely the customers we're dealing with I mean security is top sustainability is right up there too obviously but uh um Charlie touched on a lot of those things and these are Global rollouts tens of thousands of employees typically to to have mobile devices laptops and phones and so forth um and they often are looking for a true managed service around the world that takes into consideration things like the most efficient way to ship products to to the employees and how do you do that in a sustainable way you need to think about that does it all go to a central location um or to each individual's home during the pandemic that made a lot of sense to do it that way I think the reason I wanted to touch on those things is that well for for example one European pharmaceutical that the states and their reports that they are already in scope one in scope two they're fully uh Net Zero at this point and and they say but that only solves three percent of our overall sustainability goals uh 97 is scope three it's travel it's shipping it's it's uh it's all the all these things that are out of their direct control a lot of times but they're coming to us now as a as a supplier and ask and and we're filling out forms and rfps and so forth uh to show that we can be a sustainable supplier in their supply chain because that's their next big goal so sustainable supply chain absolutely Dr John Fry and Terry I want to kind of get your perspectives Charlie talked about from a customer requirements perspective customers coming through RFP saying hey we've got to work with vendors who have clear sustainability initiatives that are well underway hpe and AMD hearing the same thing Dr Fry will start with you and then Terry sure absolutely we receive about 2500 customer questionnaires just on sustainability every year and that's come up from a few hundred so yeah absolutely accelerating then the conversations turn deeper can you help us quantify our carbon emissions and power consumption then the conversation has recently gone even further to when can hpe offer Net Zero or carbon neutral Technology Solutions to the customer so that they don't have to account for those Solutions in their own carbon footprint so the questions are getting more sophisticated the need for the data and the accuracy of the data is climbing and as we see potential regulatory disclosure requirements around carbon emissions I think this trend is just going to continue up yeah and we see the same thing uh we get asked more and more from our customers and partners around our own corporate sustainability goals but the surveying that the survey work that we've done with customers has led us to you know understand that you know approximately 75 percent of customers are going to make sustainability goals a key component of their rfis in 2023 which is right around the corner and you know 60 of those same customers really expect to have business level kpis uh in the new year that are really related to sustainability so this is not just a a kind of a buzzword topic this is this is kind of business imperatives that you know the company the companies like hpe and AMD and the partners like Shi that really stand behind it and really are proactive in getting out in front of customers to help are really going to be ahead of the game that's a great point that you make Terry there that this isn't we're not talking about a buzzword here we're talking about a business imperative for businesses of probably all sizes across all Industries and Dr Farr you mentioned regulations and something that we just noticed is that the SEC recently said it's proposing some rules where companies must disclose greenhouse gas emissions um if they were if that were to to come into play I'm going to come back to Charlie and John saws how would Shi and frankly at hpe and AMD be able to help companies comply if that type of Regulation were to be implemented Charlie yeah so we are in the process right now of building out a service to help customers specifically with that with the reporting we know reporting is a challenge uh the scope 2 reporting is a challenge and scope three that I guess people thought was going to be a ways out now all of a sudden hey if you have made a public statement that you're going to make an impact on your scope three uh targets and you have to report on them so that that has become really important very quickly uh as word about this requirement is rumbling around uh there's concern so we are actually working right now on something it's a little too early to fully disclose but stay tuned because we have something coming that's interesting definitely peaked my ears are are parked here Charlie well stay tuned for that Dr Brian Terry can you talk about together with Shi hpe and AMD enabling customers to manage access to the data obviously which is critical and it's doing nothing but growing and proliferating key folks need access to it we talked a little bit about security but how are from a Better Together perspective Dr Fry will start with you how are you really helping organizations on that sustainability journey to ensure that data can be accessible to those who need it when they need it and these days what is real-time requirements yeah it's an increasing challenge in fact we have changed the HP Story the way we talk about hpe's value proposition to talk about data first modernization so how often do you collect data where do you store it how do you avoid moving it how do you make sure if you're going to collect data you get insights from that data that change your business or add business value and then how long do you retain that data afterward and all of that factors into sustainable I.T because when I talk to technology Executives what they tell me again and again is there's this presumption within their user community that storage is free and so when when they have needs for collecting data for example if if once an hour would do okay but the system would collect it once a minute the default the user asks for of course is once a minute and then are you getting insights from that data or are we moving it that becomes more important when you're moving data back and forth between the public cloud or the edge because there is quite a network penalty for moving that equipment across your network there's huge power and carbon implications of doing that so it's really making a better decision about what do we collect why do we collect it what we're going to do with it when we collect and how we store it and for years customers have really talked about you know modernization and the need to modernize their data center you know I fundamentally believe that sustainability is really that Catalyst to really Drive true modernization and as they think forward um you know when we work with with hpe you know they offer a variety of purpose-built servers that can play a role in you know specific customer workloads from the larger supercomputers down to kind of general purpose servers and when we work with Partners like Shi not only can they deliver the full Suite of um offerings for on-premise deployments they're also very well positioned to leverage the public Cloud infrastructure for those workloads that really belong there and that certainly can help customers kind of achieve an end-to-end sustainability goal that's a great point that that it needs to be strategic but it also needs to be an end-to-end goal we're just about out of time but I wanted to give John saws the last word here take us out John what are some of the things Charlie kind of teased some of the things that are coming out that piqued my interest but what are some of the things that you're excited about as hpe AMD and Shi really help customers achieve their sustainability initiatives sure um a couple of comments here um so Charlie yeah you touched on some upcoming capabilities uh that uh Shi will have around the area of monitoring and management see this is difficult for all customers to be able to report in this formal way this is a train coming at everybody very quickly and um they're not ready most customers aren't ready and if we can help um as as a reseller integrator assessments to be able to understand what they're currently running compared to different scenarios of where they could go to in a future state that seems valuable if we can help in that way that's those are things that we're looking into specifically uh you know greenhouse gas emissions relevant assessments and and um and what in the comments uh of Terry and John around the power per watt and um the vast um uh portfolio of technologies that they that they had to address various workloads is uh is fantastic we'd be able to help point to Technologies like that and move customers in that direction I think as a as an integrator and a technical advisor to customers I saw an article on BBC this morning that I I think if we think about how we're working with our customers and we can help them maybe think differently about how they're using their technology to solve problems um the BBC article mentioned this was ethereum a cryptocurrency and they have a big project called merge and today was a go live date and BBC US news outlets have been reporting on it they basically changed the model from a model called The Power of work which takes a a lot of compute and graphic GPU power and so forth around the world and it's now called a power of stake which means that the people that validate that their actions in this environment are correct they have to put up a stake of their own cryptocurrency and if they're wrong it's taken from them this new model reduces the emissions of their um uh environment by 99 plus percent the June emissions from ethereum were it was 120 uh terawatts per per year terawatt hours per year and they reduced it um actually that's the equivalent of what the Netherlands needed for energy so the comparable to a medium-sized country so if you can think differently about how to solve problems it may be on-prem it may be extremely it may be that may be the public cloud in some cases or other you know interesting Innovative Technologies that the AMD hpe other partners that we can bring in along along with them as well we can solve problems differently there is a lot going on the opportunities that you all talked about to really make such a huge societal impact and impact to our planet are exciting we thank you so much for talking together about how hpe AMD and sha are really working in partnership in Synergy to help your customers across every organization really become much more focused much more collaborative about sustainable I.T guys we so appreciate your time and thank you for your insights Thank you Lisa thank you my pleasure for my guests I'm Lisa Martin in a moment Dan Molina is going to join me he's the co-president and chief technology officer of nth generation you're watching the cube the leader in high tech Enterprise coverage [Music]

Published Date : Sep 15 2022

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Alan Jacobson, Alteryx | Democratizing Analytics Across the Enterprise


 

>>Hey, everyone. Welcome back to accelerating analytics, maturity. I'm your host. Lisa Martin, Alan Jacobson joins me next. The chief data and analytics officer at Altrix Ellen. It's great to have you on the program. >>Thanks Lisa. >>So Ellen, as we know, everyone knows that being data driven is very important. It's a household term these days, but 93% of organizations are not utilizing the analytics skills of their employees, which is creating a widening analytics gap. What's your advice, your recommendations for organizations who are just starting out with analytics >>And you're spot on many organizations really aren't leveraging the, the full capability of their knowledge workers. And really the first step is probably assessing where you are on the journey, whether that's you personally, or your organization as a whole, we just launched an assessment tool on our website that we built with the international Institute of analytics, that in a very short period of time, in about 15 minutes, you can go on and answer some questions and understand where you sit versus your peer set versus competitors and kind of where you are on the journey. >>So when people talk about data analytics, they often think, ah, this is for data science experts like people like you. So why should people in the lines of business like the finance folks, the marketing folks, why should they learn analytics? >>So domain experts are really in the best position. They, they know where the gold is buried in their companies. They know where the inefficiencies are, and it is so much easier and faster to teach a domain expert a bit about how to automate a process or how to use analytics than it is to take a data scientist and try to teach them to have the knowledge of a 20 year accounting professional or a, or a logistics expert of your company. It much harder to do that. And really, if you think about it, the world has changed dramatically in a very short period of time. If, if you were a marketing professional 30 years ago, you likely didn't need to know anything about the internet, but today, do you know what you would call that marketing professional? If they didn't know anything about the internet, probably unemployed or retired. And so knowledge workers are having to learn more and more skills to really keep up with their professions. And analytics is really no exception. Pretty much in every profession, people are needing to learn analytics, to stay current and, and be capable for their companies. And companies need people who can do that. >>Absolutely. It seems like it's table stakes. These days, let's look at different industries. Now, are there differences in how you see analytics in automation being employed in different industries? I know Altrix is being used across a lot of different types of organizations from government to retail. I also see you're now with some of the leading sports teams, any differences in industries. >>Yeah. There's an incredible actually commonality between domains industry to industry. So if you look at what an HR professional is doing, maybe attrition analysis, it's probably quite similar, whether they're in oil and gas or in a high tech software company. And so really the similarities are, are much larger than you might think. And even on the, on, on the, on the sports front, we see many of the analytics that sports teams perform are very similar. So McLaren is one of the great partners that we work with and they use TRICS across many areas of their business from finance to production, extreme sports, logistics, wind tunnel engineering, the marketing team analyzes social media data, all using Altrics. And if I take as an example, the finance team, the finance team is trying to optimize the budget to make sure that they can hit the very stringent targets that F1 sports has. And I don't see a ton of difference between the optimization that they're doing to hit their budget numbers and what I see fortune 500 finance departments doing to optimize their budget. And so really the, the commonality is very high. Even across industries. >>I bet every F fortune 500 or even every company would love to be compared to the same department within McLaren F1, just to know that wow, what they're doing is so in incre incredibly important as is what we are doing. Absolutely. So talk about lessons learned, what lessons can business leaders take from those organizations like McLaren, who are the most analytically mature >>Probably first and foremost, is that the ROI with analytics and automation is incredibly high. Companies are having a ton of success. It's becoming an existential threat to some degree, if, if your company isn't going on this journey and your competition is it, it can be a, a huge problem. IDC just did a recent study about how companies are unlocking the ROI using analytics. And the data was really clear organizations that have a higher percentage of their workforce using analytics are enjoying a much higher return from their analytic investment. And so it's not about hiring two double PhD statisticians from Oxford. It really is how widely you can bring your workforce on this journey. Can they all get 10% more capable? And that's having incredible results at businesses all over the world. An another key finding that they had is that the majority of them said that when they had many folks using analytics, they were going on the journey faster than companies they didn't. And so picking technologies, that'll help everyone do this and, and do this fast and do it easily. Having an approachable piece of software that everyone can use is really a key, >>So faster able to move faster, higher ROI. I also imagine analytics across the organization is a big competitive advantage for organizations in any industry. >>Absolutely the IDC or not. The IDC, the international Institute of analytics showed huge correlation between companies that were more analytically mature versus ones that were not. They showed correlation to growth of the company. They showed correlation to revenue and they showed correlation to shareholder values. So across really all of the, the, the key measures of business, the more analytically mature companies simply outperformed their competition. >>And that's key these days is to be able to outperform your competition. You know, one of the things that we hear so often, Alan, is people talking about democratizing data and analytics. You talked about the line of business workers, but I gotta ask you, is it really that easy for the line of business workers who aren't trained in data science, to be able to jump in, look at data, uncover and extract business insights to make decisions. >>So in, in many ways, it really is that easy. I have a 14 and 16 year old kid. Both of them have learned Altrics they're, Altrics certified. And, and it was quite easy. It took 'em about 20 hours and they were, they, they were off to the races, but there can be some hard parts. The hard parts have more to do with change management. I mean, if you're an accountant, that's been doing the best accounting work in your company for the last 20 years. And all you happen to know is a spreadsheet for those 20 years. Are you ready to learn some new skills? And, and I would suggest you probably need to, if you want, keep up with your profession. The, the big four accounting firms have trained over a hundred thousand people in Altrix just one firm has trained over a hundred thousand. >>You, you can't be an accountant or an auditor at some of these places with, without knowing Altrix. And so the hard part, really in the end, isn't the technology and learning analytics and data science. The harder part is this change management change is hard. I should probably eat better and exercise more, but it's, it's hard to always do that. And so companies are finding that that's the hard part. They need to help people go on the journey, help people with the change management to, to help them become the digitally enabled accountant of the future. The, the logistics professional that is E enabled that that's the challenge. >>That's a huge challenge. Cultural, cultural shift is a challenge. As you said, change management. How, how do you advise customers? If you might be talking with someone who might be early in their analytics journey, but really need to get up to speed and mature to be competitive, how do you guide them or give them recommendations on being able to facilitate that change management? >>Yeah, that's a great question. So, so people entering into the workforce today, many of them are starting to have these skills Altrics is used in over 800 universities around the globe to teach finance and to teach marketing and to teach logistics. And so some of this is happening naturally as new workers are entering the workforce, but for all of those who are already in the workforce have already started their careers, learning in place becomes really important. And so we work with companies to put on programmatic approaches to help their workers do this. And so it's, again, not simply putting a box of tools in the corner and saying free, take one. We put on hackathons and analytic days, and it can, it can be great fun. We, we have a great time with, with many of the customers that we work with helping them, you know, do this, helping them go on the journey and the ROI, as I said, you know, is fantastic. And not only does it sometimes affect the bottom line, it can really make societal changes. We've seen companies have breakthroughs that really make great impact to society as a whole. >>Isn't that so fantastic to see the, the difference that that can make. It sounds like you're, you guys are doing a great job of democratizing access to alter X to everybody. We talked about the line of business folks and the incredible importance of enabling them and the, the ROI, the speed, the competitive advantage. Can you share some specific examples that you think of Alter's customers that really show data breakthroughs by the lines of business using the technology? >>Yeah, absolutely. So, so many to choose from I'll I'll, I'll give you two examples. Quickly. One is armor express. They manufacture life saving equipment, defensive equipments, like armor plated vests, and they were needing to optimize their supply chain, like many companies through the pandemic. We, we see how important the supply chain is. And so adjusting supply to, to match demand is, is really vital. And so they've used all tricks to model some of their supply and demand signals and built a predictive model to optimize the supply chain. And it certainly helped out from a, a dollar standpoint, they cut over a half a million dollars of inventory in the first year, but more importantly, by matching that demand and supply signal, you're able to better meet customer customer demand. And so when people have orders and are, are looking to pick up a vest, they don't wanna wait. >>And, and it becomes really important to, to get that right. Another great example is British telecom. They're, they're a company that services the public sector. They have very strict reporting regulations that they have to meet and they had, and, and this is crazy to think about over 140 legacy spreadsheet models that they had to run to comply with these regulatory processes and, and report, and obviously running 140 legacy models that had to be done in a certain order and linked incredibly challenging. It took them over four weeks, each time that they had to go through that process. And so to, to save time and have more efficiency in doing that, they trained 50 employees over just a two week period to start using Altrix and, and, and learn Altrix. And they implemented an all new reporting process that saw a 75% reduction in the number of man hours. >>It took to run in a 60% runtime performance. And so, again, a huge improvement. I can imagine it probably had better quality as well, because now that it was automated, you don't have people copying and past data into a spreadsheet. And that was just one project that this group of, of folks were able to accomplish that had huge ROI, but now those people are moving on and automating other processes and performing analytics in, in other areas, you can imagine the impact by the end of the year that they will have on their business, you know, potentially millions upon millions of dollars. This is what we see again. And again, company after company government agency, after government agency is how analytics are really transforming the way work is being done. >>That was the word that came to mind when you were describing the all three customer examples, the transformation, this is transformative. The ability to leverage alters to, to truly democratize data and analytics, give access to the lines of business is transformative for every organization. And, and also the business outcomes. You mentioned, those are substantial metrics based business outcomes. So the ROI and leveraging a technology like alri seems to be right there, sitting in front of you. >>That's right. And, and to be honest, it's not only important for these businesses. It's important for, for the knowledge workers themselves. I mean, we, we hear it from people that they discover Alrich, they automate a process. They finally get to get home for dinner with their families, which is fantastic, but, but it leads to new career paths. And so, you know, knowledge workers that have these added skills have so much larger opportunity. And I think it's great when the needs of businesses to become more analytics and analytic and automate processes actually matches the needs of the employees. And, you know, they too wanna learn these skills and become more advanced in their capabilities, >>Huge value there for the business, for the employees themselves to expand their skillset, to, to really open up so many opportunities for not only the business to meet the demands of the demanding customer, but the employees to be able to really have that breadth and depth in their field of service. Great opportunities there. Alan, is there anywhere that you wanna point the audience to go, to learn more about how they can get started? >>Yeah. So one of the things that we're really excited about is how fast and easy it is to learn these tools. So any of the listeners who wanna experience Altrix, they can go to the website, there's a free download on the website. You can take our analytic maturity assessment, as we talked about at the beginning and, and see where you are on the journey and just reach out. You know, we'd love to work with you and your organization to see how we can help you accelerate your journey on, on analytics and automation, >>Alan, it was a pleasure talking to you about democratizing data and analytics, the power in it for organizations across every industry. We appreciate your insights and your time. >>Thank you so much >>In a moment, Paula Hanson, who is the president and chief revenue officer of ultras and Jackie Vander lay graying. Who's the global head of tax technology at eBay will join me. You're watching the cube, the leader in high tech enterprise coverage.

Published Date : Sep 13 2022

SUMMARY :

It's great to have you on the program. the analytics skills of their employees, which is creating a widening analytics gap. And really the first step is probably assessing finance folks, the marketing folks, why should they learn analytics? about the internet, but today, do you know what you would call that marketing professional? government to retail. And so really the similarities are, are much larger than you might think. to the same department within McLaren F1, just to know that wow, what they're doing is so And the data was really I also imagine analytics across the organization is a big competitive advantage for They showed correlation to revenue and they showed correlation to shareholder values. And that's key these days is to be able to outperform your competition. And all you happen to know is a spreadsheet for those 20 years. And so companies are finding that that's the hard part. their analytics journey, but really need to get up to speed and mature to be competitive, the globe to teach finance and to teach marketing and to teach logistics. job of democratizing access to alter X to everybody. So, so many to choose from I'll I'll, I'll give you two examples. models that they had to run to comply with these regulatory processes and, the end of the year that they will have on their business, you know, potentially millions upon millions So the ROI and leveraging a technology like alri seems to be right there, And so, you know, knowledge workers that have these added skills have so much larger opportunity. of the demanding customer, but the employees to be able to really have that breadth and depth in So any of the listeners who wanna experience Altrix, Alan, it was a pleasure talking to you about democratizing data and analytics, the power in it for Who's the global head of tax technology at eBay will

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Alteryx Democratizing Analytics Across the Enterprise Full Episode V1b


 

>> It's no surprise that 73% of organizations indicate analytics spend will outpace other software investments in the next 12 to 18 months. After all as we know, data is changing the world and the world is changing with it. But is everyone's spending resulting in the same ROI? This is Lisa Martin. Welcome to "theCUBE"'s presentation of democratizing analytics across the enterprise, made possible by Alteryx. An Alteryx commissioned IDC info brief entitled, "Four Ways to Unlock Transformative Business Outcomes from Analytics Investments" found that 93% of organizations are not utilizing the analytics skills of their employees, which is creating a widening analytics gap. On this special "CUBE" presentation, Jason Klein, product marketing director of Alteryx, will join me to share key findings from the new Alteryx commissioned IDC brief and uncover how enterprises can derive more value from their data. In our second segment, we'll hear from Alan Jacobson, chief data and analytics officer at Alteryx. He's going to discuss how organizations across all industries can accelerate their analytic maturity to drive transformational business outcomes. And then in our final segment, Paula Hansen, who is the president and chief revenue officer of Alteryx, and Jacqui Van der Leij Greyling, who is the global head of tax technology at eBay, they'll join me. They're going to share how Alteryx is helping the global eCommerce company innovate with analytics. Let's get the show started. (upbeat music) Jason Klein joins me next, product marketing director at Alteryx. Jason, welcome to the program. >> Hello, nice to be here. >> Excited to talk with you. What can you tell me about the new Alteryx IDC research, which spoke with about 1500 leaders, what nuggets were in there? >> Well, as the business landscape changes over the next 12 to 18 months, we're going to see that analytics is going to be a key component to navigating this change. 73% of the orgs indicated that analytics spend will outpace other software investments. But just putting more money towards technology, it isn't going to solve everything. And this is why everyone's spending is resulting in different ROIs. And one of the reasons for this gap is because 93% of organizations, they're still not fully using the analytics skills of their employees, and this widening analytics gap, it's threatening operational progress by wasting workers' time, harming business productivity and introducing costly errors. So in this research, we developed a framework of enterprise analytics proficiency that helps organizations reap greater benefits from their investments. And we based this framework on the behaviors of organizations that saw big improvements across financial, customer, and employee metrics, and we're able to focus on the behaviors driving higher ROI. >> So the info brief also revealed that nearly all organizations are planning to increase their analytics spend. And it looks like from the info brief that nearly three quarters plan on spending more on analytics than any other software. And can you unpack, what's driving this demand, this need for analytics across organizations? >> Sure, well first there's more data than ever before, the data's changing the world, and the world is changing data. Enterprises across the world, they're accelerating digital transformation to capitalize on new opportunities, to grow revenue, to increase margins and to improve customer experiences. And analytics along with automation and AI is what's making digital transformation possible. They're providing the fuel to new digitally enabled lines of business. >> One of the things that the study also showed was that not all analytics spending is resulting in the same ROI. What are some of the discrepancies that the info brief uncovered with respect to the changes in ROI that organizations are achieving? >> Our research with IDC revealed significant roadblocks across people, processes, and technologies. They're preventing companies from reaping greater benefits from their investments. So for example, on the people side, only one out of five organizations reported a commensurate investment in upskilling for analytics and data literacy as compared to the technology itself. And next, while data is everywhere, most organizations, 63% from our survey, are still not using the full breadth of data types available. Yet data's never been this prolific, it's going to continue to grow, and orgs should be using it to their advantage. And lastly organizations, they need to provide the right analytics tools to help everyone unlock the power of data. >> So they- >> They instead rely on outdated spreadsheet technology. In our survey, nine out of 10 respondents said less than half of their knowledge workers are active users of analytics software beyond spreadsheets. But true analytic transformation can't happen for an organization in a few select pockets or silos. We believe everyone regardless of skill level should be able to participate in the data and analytics process and be driving value. >> Should we retake that, since I started talking over Jason accidentally? >> Yep, absolutely we can do so. We'll just go, yep, we'll go back to Lisa's question. Let's just, let's do the, retake the question and the answer, that'll be able to. >> It'll be not all analytics spending results in the same ROI, what are some of the discrepancies? >> Yes, Lisa, so we'll go from your ISO, just so we get that clean question and answer. >> Okay. >> Thank you for that. On your ISO, we're still speeding, Lisa, so give it a beat in your head and then on you. >> Yet not all analytics spending is resulting in the same ROI. So what are some of the discrepancies that the info brief uncovered with respect to ROI? >> Well, our research with IDC revealed significant roadblocks across people, processes, and technologies, all preventing companies from reaping greater benefits from their investments. So on the people side, for example, only one out of five organizations reported a commensurate investment in upskilling for analytics and data literacy as compared to the technology itself. And next, while data is everywhere, most organizations, 63% in our survey, are still not using the full breadth of data types available. Data has never been this prolific. It's going to continue to grow and orgs should be using it to their advantage. And lastly, organizations, they need to provide the right analytic tools to help everyone unlock the power of data, yet instead they're relying on outdated spreadsheet technology. Nine of 10 survey respondents said that less than half of their knowledge workers are active users of analytics software. True analytics transformation can't happen for an organization in a few select pockets or silos. We believe everyone regardless of skill level should be able to participate in the data and analytics process and drive value. >> So if I look at this holistically, then what would you say organizations need to do to make sure that they're really deriving value from their investments in analytics? >> Yeah, sure. So overall, the enterprises that derive more value from their data and analytics and achieve more ROI, they invested more aggressively in the four dimensions of enterprise analytics proficiency. So they've invested in the comprehensiveness of analytics across all data sources and data types, meaning they're applying analytics to everything. They've invested in the flexibility of analytics across deployment scenarios and departments, meaning they're putting analytics everywhere. They've invested in the ubiquity of analytics and insights for every skill level, meaning they're making analytics for everyone. And they've invested in the usability of analytics software, meaning they're prioritizing easy technology to accelerate analytics democratization. >> So very strategic investments. Did the survey uncover any specific areas where most companies are falling short, like any black holes that organizations need to be aware of at the outset? >> It did, it did. So organizations, they need to build a data-centric culture. And this begins with people. But what the survey told us is that the people aspect of analytics is the most heavily skewed towards low proficiency. In order to maximize ROI, organizations need to make sure everyone in the organization has access to the data and analytics technology they need. And then the organizations also have to align their investments with upskilling in data literacy to enjoy that higher ROI. Companies who did so experience higher ROI than companies who underinvested in analytics literacy. So among the high ROI achievers, 78% have a good or great alignment between analytics investment and workforce upskilling compared to only 64% among those without positive ROI. And as more orgs adopt cloud data warehouses or cloud data lakes, in order to manage the massively increasing workloads- Can I start that one over. >> Sure. >> Can I redo this one? >> Yeah. >> Of course, stand by. >> Tongue tied. >> Yep, no worries. >> One second. >> If we could do the same, Lisa, just have a clean break, we'll go your question. >> Yep, yeah. >> On you Lisa. Just give that a count and whenever you're ready. Here, I'm going to give us a little break. On you Lisa. >> So are there any specific areas that the survey uncovered where most companies are falling short? Like any black holes organizations need to be aware of from the outset? >> It did. You need to build a data-centric culture and this begins with people, but we found that the people aspect of analytics is most heavily skewed towards low proficiency. In order to maximize ROI organizations need to make sure everyone has access to the data and analytics technology they need. Organizations that align their analytics investments with upskilling enjoy higher ROI than orgs that are less aligned. For example, among the high ROI achievers in our survey, 78% had good or great alignment between analytics investments and workforce upskilling, compared to only 64% among those without positive ROI. And as more enterprises adopt cloud data warehouses or cloud data lakes to manage increasingly massive data sets, analytics needs to exist everywhere, especially for those cloud environments. And what we found is organizations that use more data types and more data sources generate higher ROI from their analytics investments. Among those with improved customer metrics, 90% were good or great at utilizing all data sources, compared to only 67% among the ROI laggards. >> So interesting that you mentioned people, I'm glad that you mentioned people. Data scientists, everybody talks about data scientists. They're in high demand, we know that, but there aren't enough to meet the needs of all enterprises. So given that discrepancy, how can organizations fill the gap and really maximize the investments that they're making in analytics? >> Right, so analytics democratization, it's no longer optional, but it doesn't have to be complex. So we at Alteryx, we're democratizing analytics by empowering every organization to upskill every worker into a data worker. And the data from this survey shows this is the optimal approach. Organizations with a higher percentage of knowledge workers who are actively using analytics software enjoy higher returns from their analytics investment than orgs still stuck on spreadsheets. Among those with improved financial metrics, AKA the high ROI achievers, nearly 70% say that at least a quarter of their knowledge workers are using analytics software other than spreadsheets compared to only 56% in the low ROI group. Also among the high ROI performers, 63% said data and analytic workers collaborate well or extremely well compared to only 51% in the low ROI group. The data from the survey shows that supporting more business domains with analytics and providing cross-functional analytics correlates with higher ROI. So to maximize ROI, orgs should be transitioning workers from spreadsheets to analytics software. They should be letting them collaborate effectively and letting them do so cross-functionally. >> Yeah, that cross-functional collaboration is essential for anyone in any organization and in any discipline. Another key thing that jumped out from the survey was around shadow IT. The business side is using more data science tools than the IT side. And it's expected to spend more on analytics than other IT. What risks does this present to the overall organization, if IT and the lines of business guys and gals aren't really aligned? >> Well, there needs to be better collaboration and alignment between IT and the line of business. The data from the survey, however, shows that business managers, they're expected to spend more on analytics and use more analytics tools than IT is aware of. And this isn't because the lines of business have recognized the value of analytics and plan to invest accordingly, but a lack of alignment between IT and business. This will negatively impact governance, which ultimately impedes democratization and hence ROI. >> So Jason, where can organizations that are maybe at the outset of their analytics journey, or maybe they're in environments where there's multiple analytics tools across shadow IT, where can they go to Alteryx to learn more about how they can really simplify, streamline, and dial up the value on their investment? >> Well, they can learn more on our website. I also encourage them to explore the Alteryx community, which has lots of best practices, not just in terms of how you do the analytics, but how you stand up in Alteryx environment, but also to take a look at your analytics stack and prioritize technologies that can snap to and enhance your organization's governance posture. It doesn't have to change it, but it should be able to align to and enhance it. >> And of course, as you mentioned, it's about people, process, and technologies. Jason, thank you so much for joining me today, unpacking the IDC info brief and the great nuggets in there. Lots that organizations can learn and really become empowered to maximize their analytics investments. We appreciate your time. >> Thank you, it's been a pleasure. >> In a moment, Alan Jacobson, who's the chief data and analytics officer at Alteryx is going to join me. He's going to be here to talk about how organizations across all industries can accelerate their analytic maturity to drive transformational business outcomes. You're watching "theCUBE", the leader in tech enterprise coverage. >> Somehow many have come to believe that data analytics is for the few, for the scientists, the PhDs, the MBAs. Well, it is for them, but that's not all. You don't have to have an advanced degree to do amazing things with data. You don't even have to be a numbers person. You can be just about anything. A titan of industry or a future titan of industry. You could be working to change the world, your neighborhood, or the course of your business. You can be saving lives or just looking to save a little time. The power of data analytics shouldn't be limited to certain job titles or industries or organizations because when more people are doing more things with data, more incredible things happen. Analytics makes us smarter and faster and better at what we do. It's practically a superpower. That's why we believe analytics is for everyone, and everything, and should be everywhere. That's why we believe in analytics for all. (upbeat music) >> Hey, everyone. Welcome back to "Accelerating Analytics Maturity". I'm your host, Lisa Martin. Alan Jacobson joins me next. The chief of data and analytics officer at Alteryx. Alan, it's great to have you on the program. >> Thanks, Lisa. >> So Alan, as we know, everyone knows that being data driven is very important. It's a household term these days, but 93% of organizations are not utilizing the analytics skills of their employees, which is creating a widening analytics gap. What's your advice, your recommendations for organizations who are just starting out with analytics? >> You're spot on, many organizations really aren't leveraging the full capability of their knowledge workers. And really the first step is probably assessing where you are on the journey, whether that's you personally, or your organization as a whole. We just launched an assessment tool on our website that we built with the International Institute of Analytics, that in a very short period of time, in about 15 minutes, you can go on and answer some questions and understand where you sit versus your peer set versus competitors and kind of where you are on the journey. >> So when people talk about data analytics, they often think, ah, this is for data science experts like people like you. So why should people in the lines of business like the finance folks, the marketing folks, why should they learn analytics? >> So domain experts are really in the best position. They know where the gold is buried in their companies. They know where the inefficiencies are. And it is so much easier and faster to teach a domain expert a bit about how to automate a process or how to use analytics than it is to take a data scientist and try to teach them to have the knowledge of a 20 year accounting professional or a logistics expert of your company. Much harder to do that. And really, if you think about it, the world has changed dramatically in a very short period of time. If you were a marketing professional 30 years ago, you likely didn't need to know anything about the internet, but today, do you know what you would call that marketing professional if they didn't know anything about the internet, probably unemployed or retired. And so knowledge workers are having to learn more and more skills to really keep up with their professions. And analytics is really no exception. Pretty much in every profession, people are needing to learn analytics to stay current and be capable for their companies. And companies need people who can do that. >> Absolutely, it seems like it's table stakes these days. Let's look at different industries now. Are there differences in how you see analytics in automation being employed in different industries? I know Alteryx is being used across a lot of different types of organizations from government to retail. I also see you're now with some of the leading sports teams. Any differences in industries? >> Yeah, there's an incredible actually commonality between the domains industry to industry. So if you look at what an HR professional is doing, maybe attrition analysis, it's probably quite similar, whether they're in oil and gas or in a high tech software company. And so really the similarities are much larger than you might think. And even on the sports front, we see many of the analytics that sports teams perform are very similar. So McLaren is one of the great partners that we work with and they use Alteryx across many areas of their business from finance to production, extreme sports, logistics, wind tunnel engineering, the marketing team analyzes social media data, all using Alteryx, and if I take as an example, the finance team, the finance team is trying to optimize the budget to make sure that they can hit the very stringent targets that F1 Sports has, and I don't see a ton of difference between the optimization that they're doing to hit their budget numbers and what I see Fortune 500 finance departments doing to optimize their budget, and so really the commonality is very high, even across industries. >> I bet every Fortune 500 or even every company would love to be compared to the same department within McLaren F1. Just to know that wow, what they're doing is so incredibly important as is what we're doing. >> So talk- >> Absolutely. >> About lessons learned, what lessons can business leaders take from those organizations like McLaren, who are the most analytically mature? >> Probably first and foremost, is that the ROI with analytics and automation is incredibly high. Companies are having a ton of success. It's becoming an existential threat to some degree, if your company isn't going on this journey and your competition is, it can be a huge problem. IDC just did a recent study about how companies are unlocking the ROI using analytics. And the data was really clear, organizations that have a higher percentage of their workforce using analytics are enjoying a much higher return from their analytic investment, and so it's not about hiring two double PhD statisticians from Oxford. It really is how widely you can bring your workforce on this journey, can they all get 10% more capable? And that's having incredible results at businesses all over the world. An another key finding that they had is that the majority of them said that when they had many folks using analytics, they were going on the journey faster than companies that didn't. And so picking technologies that'll help everyone do this and do this fast and do it easily. Having an approachable piece of software that everyone can use is really a key. >> So faster, able to move faster, higher ROI. I also imagine analytics across the organization is a big competitive advantage for organizations in any industry. >> Absolutely the IDC, or not the IDC, the International Institute of Analytics showed huge correlation between companies that were more analytically mature versus ones that were not. They showed correlation to growth of the company, they showed correlation to revenue and they showed correlation to shareholder values. So across really all of the key measures of business, the more analytically mature companies simply outperformed their competition. >> And that's key these days, is to be able to outperform your competition. You know, one of the things that we hear so often, Alan, is people talking about democratizing data and analytics. You talked about the line of business workers, but I got to ask you, is it really that easy for the line of business workers who aren't trained in data science to be able to jump in, look at data, uncover and extract business insights to make decisions? >> So in many ways, it really is that easy. I have a 14 and 16 year old kid. Both of them have learned Alteryx, they're Alteryx certified and it was quite easy. It took 'em about 20 hours and they were off to the races, but there can be some hard parts. The hard parts have more to do with change management. I mean, if you're an accountant that's been doing the best accounting work in your company for the last 20 years, and all you happen to know is a spreadsheet for those 20 years, are you ready to learn some new skills? And I would suggest you probably need to, if you want to keep up with your profession. The big four accounting firms have trained over a hundred thousand people in Alteryx. Just one firm has trained over a hundred thousand. You can't be an accountant or an auditor at some of these places without knowing Alteryx. And so the hard part, really in the end, isn't the technology and learning analytics and data science, the harder part is this change management, change is hard. I should probably eat better and exercise more, but it's hard to always do that. And so companies are finding that that's the hard part. They need to help people go on the journey, help people with the change management to help them become the digitally enabled accountant of the future, the logistics professional that is E enabled, that's the challenge. >> That's a huge challenge. Cultural shift is a challenge, as you said, change management. How do you advise customers if you might be talking with someone who might be early in their analytics journey, but really need to get up to speed and mature to be competitive, how do you guide them or give them recommendations on being able to facilitate that change management? >> Yeah, that's a great question. So people entering into the workforce today, many of them are starting to have these skills. Alteryx is used in over 800 universities around the globe to teach finance and to teach marketing and to teach logistics. And so some of this is happening naturally as new workers are entering the workforce, but for all of those who are already in the workforce, have already started their careers, learning in place becomes really important. And so we work with companies to put on programmatic approaches to help their workers do this. And so it's, again, not simply putting a box of tools in the corner and saying free, take one. We put on hackathons and analytic days, and it can be great fun. We have a great time with many of the customers that we work with, helping them do this, helping them go on the journey, and the ROI, as I said, is fantastic. And not only does it sometimes affect the bottom line, it can really make societal changes. We've seen companies have breakthroughs that have really made great impact to society as a whole. >> Isn't that so fantastic, to see the difference that that can make. It sounds like you guys are doing a great job of democratizing access to Alteryx to everybody. We talked about the line of business folks and the incredible importance of enabling them and the ROI, the speed, the competitive advantage. Can you share some specific examples that you think of Alteryx customers that really show data breakthroughs by the lines of business using the technology? >> Yeah, absolutely, so many to choose from. I'll give you two examples quickly. One is Armor Express. They manufacture life saving equipment, defensive equipments, like armor plated vests, and they were needing to optimize their supply chain, like many companies through the pandemic. We see how important the supply chain is. And so adjusting supply to match demand is really vital. And so they've used Alteryx to model some of their supply and demand signals and built a predictive model to optimize the supply chain. And it certainly helped out from a dollar standpoint. They cut over a half a million dollars of inventory in the first year, but more importantly, by matching that demand and supply signal, you're able to better meet customer demand. And so when people have orders and are looking to pick up a vest, they don't want to wait. And it becomes really important to get that right. Another great example is British Telecom. They're a company that services the public sector. They have very strict reporting regulations that they have to meet and they had, and this is crazy to think about, over 140 legacy spreadsheet models that they had to run to comply with these regulatory processes and report, and obviously running 140 legacy models that had to be done in a certain order and length, incredibly challenging. It took them over four weeks each time that they had to go through that process. And so to save time and have more efficiency in doing that, they trained 50 employees over just a two week period to start using Alteryx and learn Alteryx. And they implemented an all new reporting process that saw a 75% reduction in the number of man hours it took to run in a 60% run time performance. And so, again, a huge improvement. I can imagine it probably had better quality as well, because now that it was automated, you don't have people copying and pasting data into a spreadsheet. And that was just one project that this group of folks were able to accomplish that had huge ROI, but now those people are moving on and automating other processes and performing analytics in other areas. So you can imagine the impact by the end of the year that they will have on their business, potentially millions upon millions of dollars. And this is what we see again and again, company after company, government agency after government agency, is how analytics are really transforming the way work is being done. >> That was the word that came to mind when you were describing the all three customer examples, transformation, this is transformative. The ability to leverage Alteryx, to truly democratize data and analytics, give access to the lines of business is transformative for every organization. And also the business outcome you mentioned, those are substantial metrics based business outcomes. So the ROI in leveraging a technology like Alteryx seems to be right there, sitting in front of you. >> That's right, and to be honest, it's not only important for these businesses. It's important for the knowledge workers themselves. I mean, we hear it from people that they discover Alteryx, they automate a process, they finally get to get home for dinner with their families, which is fantastic, but it leads to new career paths. And so knowledge workers that have these added skills have so much larger opportunity. And I think it's great when the needs of businesses to become more analytic and automate processes actually matches the needs of the employees, and they too want to learn these skills and become more advanced in their capabilities. >> Huge value there for the business, for the employees themselves to expand their skillset, to really open up so many opportunities for not only the business to meet the demands of the demanding customer, but the employees to be able to really have that breadth and depth in their field of service. Great opportunities there, Alan. Is there anywhere that you want to point the audience to go to learn more about how they can get started? >> Yeah, so one of the things that we're really excited about is how fast and easy it is to learn these tools. So any of the listeners who want to experience Alteryx, they can go to the website, there's a free download on the website. You can take our analytic maturity assessment, as we talked about at the beginning, and see where you are on the journey and just reach out. We'd love to work with you and your organization to see how we can help you accelerate your journey on analytics and automation. >> Alan, it was a pleasure talking to you about democratizing data and analytics, the power in it for organizations across every industry. We appreciate your insights and your time. >> Thank you so much. >> In a moment, Paula Hansen, who is the president and chief revenue officer of Alteryx, and Jacqui Van der Leij Greyling, who's the global head of tax technology at eBay, will join me. You're watching "theCUBE", the leader in high tech enterprise coverage. >> 1200 hours of wind tunnel testing, 30 million race simulations, 2.4 second pit stops. >> Make that 2.3. >> Sector times out the wazoo. >> Way too much of this. >> Velocities, pressures, temperatures, 80,000 components generating 11.8 billion data points and one analytics platform to make sense of it all. When McLaren needs to turn complex data into winning insights, they turn to Alteryx. Alteryx, analytics automation. (upbeat music) >> Hey, everyone, welcome back to the program. Lisa Martin here, I've got two guests joining me. Please welcome back to "theCUBE" Paula Hansen, the chief revenue officer and president at Alteryx, and Jacqui Van der Leij Greyling joins us as well, the global head of tax technology at eBay. They're going to share with you how Alteryx is helping eBay innovate with analytics. Ladies, welcome, it's great to have you both on the program. >> Thank you, Lisa, it's great to be here. >> Yeah, Paula, we're going to start with you. In this program, we've heard from Jason Klein, we've heard from Alan Jacobson. They talked about the need to democratize analytics across any organization to really drive innovation. With analytics, as they talked about, at the forefront of software investments, how's Alteryx helping its customers to develop roadmaps for success with analytics? >> Well, thank you, Lisa. It absolutely is about our customers' success. And we partner really closely with our customers to develop a holistic approach to their analytics success. And it starts of course with our innovative technology and platform, but ultimately we help our customers to create a culture of data literacy and analytics from the top of the organization, starting with the C-suite. And we partner with our customers to build their roadmaps for scaling that culture of analytics, through things like enablement programs, skills assessments, hackathons, setting up centers of excellence to help their organization scale and drive governance of this analytics capability across the enterprise. So at the end of the day, it's really about helping our customers to move up their analytics maturity curve with proven technologies and best practices, so they can make better business decisions and compete in their respective industries. >> Excellent, sounds like a very strategic program, we're going to unpack that. Jacqui, let's bring you into the conversation. Speaking of analytics maturity, one of the things that we talked about in this event is the IDC report that showed that 93% of organizations are not utilizing the analytics skills of their employees, but then there's eBay. How Jacqui did eBay become one of the 7% of organizations who's really maturing and how are you using analytics across the organization at eBay? >> So I think the main thing for us is when we started out was is that, our, especially in finance, they became spreadsheet professionals instead of the things that we really want our employees to add value to. And we realized we had to address that. And we also knew we couldn't wait for all our data to be centralized until we actually start using the data or start automating and being more effective. So ultimately we really started very, very actively embedding analytics in our people and our data and our processes. >> Starting with people is really critical. Jacqui, continuing with you, what were some of the roadblocks to analytics adoption that you faced and how did you overcome them? >> So I think eBay is a very data driven company. We have a lot of data. I think we are 27 years around this year, so we have the data, but it is everywhere. And how do you use that data? How do you use it efficiently? How do you get to the data? And I believe that that is definitely one of our biggest roadblocks when we started out and just finding those data sources and finding ways to connect to them to move forward. The other thing is that people were experiencing a lot of frustration. I mentioned before about the spreadsheet professionals. And there was no, we were not independent. You couldn't move forward, you would've put it on somebody else's roadmap to get the data and to get the information if you want it. So really finding something that everybody could access analytics or access data. And finally we have to realize is that this is uncharted territory. This is not exactly something that everybody is used to working with every day. So how do you find something that is easy, and that is not so daunting on somebody who's brand new to the field? And I would call those out as your major roadblocks, because you always have, not always, but most of the times you have support from the top, and in our case we have, but at the end of the day, it's our people that need to actually really embrace it, and making that accessible for them, I would say is definitely not per se, a roadblock, but basically a block you want to be able to move. >> It's really all about putting people first. Question for both of you, and Paula we'll start with you, and then Jacqui we'll go to you. I think the message in this program that the audience is watching with us is very clear. Analytics is for everyone, should be for everyone. Let's talk now about how both of your organizations are empowering people, those in the organization that may not have technical expertise to be able to leverage data, so that they can actually be data driven. Paula. >> Yes, well, we leverage our platform across all of our business functions here at Alteryx. And just like Jacqui explained, at eBay finance is probably one of the best examples of how we leverage our own platform to improve our business performance. So just like Jacqui mentioned, we have this huge amount of data flowing through our enterprise and the opportunity to leverage that into insights and analytics is really endless. So our CFO Kevin Rubin has been a key sponsor for using our own technology. We use Alteryx for forecasting all of our key performance metrics, for business planning, across our audit function, to help with compliance and regulatory requirements, tax, and even to close our books at the end of each quarter. So it's really going to remain across our business. And at the end of the day, it comes to how do you train users? How do you engage users to lean into this analytic opportunity to discover use cases? And so one of the other things that we've seen many companies do is to gamify that process, to build a game that brings users into the experience for training and to work with each other, to problem solve and along the way, maybe earn badges depending on the capabilities and trainings that they take. And just have a little healthy competition as an employee base around who can become more sophisticated in their analytic capability. So I think there's a lot of different ways to do it. And as Jacqui mentioned, it's really about ensuring that people feel comfortable, that they feel supported, that they have access to the training that they need, and ultimately that they are given both the skills and the confidence to be able to be a part of this great opportunity of analytics. >> That confidence is key. Jacqui, talk about some of the ways that you're empowering folks without that technical expertise to really be data driven. >> Yeah, I think it means to what Paula has said in terms of getting people excited about it, but it's also understanding that this is a journey and everybody is at a different place in their journey. You have folks that's already really advanced who has done this every day. And then you have really some folks that this is brand new or maybe somewhere in between. And it's about how you get everybody in their different phases to get to the initial destination. I say initial, because I believe a journey is never really complete. What we have done is that we decided to invest, and built a proof of concept, and we got our CFO to sponsor a hackathon. We opened it up to everybody in finance in the middle of the pandemic. So everybody was on Zoom and we told people, listen, we're going to teach you this tool, it's super easy, and let's just see what you can do. We ended up having 70 entries. We had only three weeks. So and these are people that do not have a background. They are not engineers, they're not data scientists. And we ended up with a 25,000 hour savings at the end of that hackathon from the 70 entries with people that have never, ever done anything like this before. And there you have the result. And then it just went from there. People had a proof of concept. They knew that it worked and they overcame the initial barrier of change. And that's where we are seeing things really, really picking up now. >> That's fantastic. And the business outcome that you mentioned there, the business impact is massive, helping folks get that confidence to be able to overcome sometimes the cultural barriers is key here. I think another thing that this program has really highlighted is there is a clear demand for data literacy in the job market, regardless of organization. Can each of you share more about how you're empowering the next generation of data workers? Paula, we'll start with you. >> Absolutely, and Jacqui says it so well, which is that it really is a journey that organizations are on and we as people in society are on in terms of upskilling our capabilities. So one of the things that we're doing here at Alteryx to help address this skillset gap on a global level is through a program that we call SparkED, which is essentially a no-cost analytics education program that we take to universities and colleges globally to help build the next generation of data workers. When we talk to our customers like eBay and many others, they say that it's difficult to find the skills that they want when they're hiring people into the job market. And so this program's really developed just to do just that, to close that gap and to work hand in hand with students and educators to improve data literacy for the next generation. So we're just getting started with SparkED. We started last May, but we currently have over 850 educational institutions globally engaged across 47 countries, and we're going to continue to invest here because there's so much opportunity for people, for society and for enterprises, when we close the gap and empower more people with the necessary analytics skills to solve all the problems that data can help solve. >> So SparkED has made a really big impact in such a short time period. It's going to be fun to watch the progress of that. Jacqui, let's go over to you now. Talk about some of the things that eBay is doing to empower the next generation of data workers. >> So we basically wanted to make sure that we kept that momentum from the hackathon, that we don't lose that excitement. So we just launched the program called eBay Masterminds. And what it basically is, is it's an inclusive innovation in each other, where we firmly believe that innovation is for upskilling for all analytics roles. So it doesn't matter your background, doesn't matter which function you are in, come and participate in in this where we really focus on innovation, introducing new technologies and upskilling our people. We are, apart from that, we also said, well, we shouldn't just keep it to inside eBay. We have to share this innovation with the community. So we are actually working on developing an analytics high school program, which we hope to pilot by the end of this year, where we will actually have high schoolers come in and teach them data essentials, the soft skills around analytics, but also how to use Alteryx. And we're working with, actually, we're working with SparkED and they're helping us develop that program. And we really hope that at, say, by the end of the year, we have a pilot and then also next year, we want to roll it out in multiple locations in multiple countries and really, really focus on that whole concept of analytics for all. >> Analytics for all, sounds like Alteryx and eBay have a great synergistic relationship there that is jointly aimed at especially going down the stuff and getting people when they're younger interested, and understanding how they can be empowered with data across any industry. Paula, let's go back to you, you were recently on "theCUBE"'s Supercloud event just a couple of weeks ago. And you talked about the challenges the companies are facing as they're navigating what is by default a multi-cloud world. How does the Alteryx Analytics Cloud platform enable CIOs to democratize analytics across their organization? >> Yes, business leaders and CIOs across all industries are realizing that there just aren't enough data scientists in the world to be able to make sense of the massive amounts of data that are flowing through organizations. Last I checked, there was 2 million data scientists in the world, so that's woefully underrepresented in terms of the opportunity for people to be a part of the analytics solution. So what we're seeing now with CIOs, with business leaders is that they're integrating data analysis and the skillset of data analysis into virtually every job function, and that is what we think of when we think of analytics for all. And so our mission with Alteryx Analytics Cloud is to empower all of those people in every job function, regardless of their skillset, as Jacqui pointed out from people that are just getting started all the way to the most sophisticated of technical users. Every worker across that spectrum can have a meaningful role in the opportunity to unlock the potential of the data for their company and their organizations. So that's our goal with Alteryx Analytics Cloud, and it operates in a multi cloud world and really helps across all sizes of data sets to blend, cleanse, shape, analyze, and report out so that we can break down data silos across the enterprise and help drive real business outcomes as a result of unlocking the potential of data. >> As well as really lessening that skill gap. As you were saying, there's only 2 million data scientists. You don't need to be a data scientist, that's the beauty of what Alteryx is enabling and eBay is a great example of that. Jacqui, let's go ahead and wrap things with you. You talked a great deal about the analytics maturity that you have fostered at eBay. It obviously has the right culture to adapt to that. Can you talk a little bit and take us out here in terms of where Alteryx fits in as that analytics maturity journey continues and what are some of the things that you are most excited about as analytics truly gets democratized across eBay? >> When we're starting up and getting excited about things when it comes to analytics, I can go on all day, but I'll keep it short and sweet for you. I do think we are on the top of the pool of data scientists. And I really feel that that is your next step, for us anyways, is that how do we get folks to not see data scientists as this big thing, like a rocket scientist, it's something completely different. And it's something that is in everybody in a certain extent. So again, partnering with Alteryx who just released the AI ML solution, allowing folks to not have a data scientist program, but actually build models and be able to solve problems that way. So we have engaged with Alteryx and we purchased the licenses, quite a few. And right now through our Masterminds program, we're actually running a four month program for all skill levels, teaching them AI ML and machine learning and how they can build their own models. We are really excited about that. We have over 50 participants without a background from all over the organization. We have members from our customer services. We have even some of our engineers are actually participating in the program. We just kicked it off. And I really believe that that is our next step. I want to give you a quick example of the beauty of this is where we actually just allow people to go out and think about ideas and come up with things. And one of the people in our team who doesn't have a data scientist background at all, was able to develop a solution where there is a checkout feedback functionality on the eBay side where sellers or buyers can verbatim add information. And she built a model to be able to determine what relates to tax specific, what is the type of problem, and even predict how that problem can be solved before we as a human even step in, and now instead of us or somebody going to verbatim and try to figure out what's going on there, we can focus on fixing the error versus actually just reading through things and not adding any value, and it's a beautiful tool and I was very impressed when I saw the demo and definitely developing that sort of thing. >> That sounds fantastic. And I think just the one word that keeps coming to mind, and we've said this a number of times in the program today is empowerment. What you're actually really doing to truly empower people across the organization with varying degrees of skill level, going down to the high school level, really exciting. We'll have to stay tuned to see what some of the great things are that come from this continued partnership. Ladies, I want to thank you so much for joining me on the program today and talking about how Alteryx and eBay are really partnering together to democratize analytics and to facilitate its maturity. It's been great talking to you. >> Thank you, Lisa. >> Thank you so much. (cheerful electronic music) >> As you heard over the course of our program, organizations where more people are using analytics who have deeper capabilities in each of the four Es, that's everyone, everything, everywhere, and easy analytics, those organizations achieve more ROI from their respective investments in analytics and automation than those who don't. We also heard a great story from eBay, great example of an enterprise that is truly democratizing analytics across its organization. It's enabling and empowering line of business users to use analytics, not only focused on key aspects of their job, but develop new skills rather than doing the same repetitive tasks. We want to thank you so much for watching the program today. Remember you can find all of the content on thecube.net. You can find all of the news from today on siliconangle.com and of course alteryx.com. We also want to thank Alteryx for making this program possible and for sponsoring "theCUBE". For all of my guests, I'm Lisa Martin. We want to thank you for watching and bye for now. (upbeat music)

Published Date : Sep 10 2022

SUMMARY :

in the next 12 to 18 months. Excited to talk with you. over the next 12 to 18 months, And it looks like from the info brief and the world is changing data. that the info brief uncovered with respect So for example, on the people side, in the data and analytics and the answer, that'll be able to. just so we get that clean Thank you for that. that the info brief uncovered as compared to the technology itself. So overall, the enterprises to be aware of at the outset? is that the people aspect of analytics If we could do the same, Lisa, Here, I'm going to give us a little break. to the data and analytics and really maximize the investments And the data from this survey shows this And it's expected to spend more and plan to invest accordingly, that can snap to and the great nuggets in there. Alteryx is going to join me. that data analytics is for the few, Alan, it's great to that being data driven is very important. And really the first step the lines of business and more skills to really keep of the leading sports teams. between the domains industry to industry. to be compared to the same is that the majority of them said So faster, able to So across really all of the is to be able to outperform that is E enabled, that's the challenge. and mature to be competitive, around the globe to teach finance and the ROI, the speed, that they had to run to comply And also the business of the employees, and they of the demanding customer, to see how we can help you the power in it for organizations and Jacqui Van der Leij 1200 hours of wind tunnel testing, to make sense of it all. back to the program. going to start with you. So at the end of the day, one of the 7% of organizations to be centralized until we of the roadblocks to analytics adoption and to get the information if you want it. that the audience is watching and the confidence to be able to be a part to really be data driven. in their different phases to And the business outcome and to work hand in hand Jacqui, let's go over to you now. We have to share this Paula, let's go back to in the opportunity to unlock and eBay is a great example of that. and be able to solve problems that way. that keeps coming to mind, Thank you so much. in each of the four Es,

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Breaking Analysis: We Have the Data…What Private Tech Companies Don’t Tell you About Their Business


 

>> From The Cube Studios in Palo Alto and Boston, bringing you data driven insights from The Cube at ETR. This is "Breaking Analysis" with Dave Vellante. >> The reverse momentum in tech stocks caused by rising interest rates, less attractive discounted cash flow models, and more tepid forward guidance, can be easily measured by public market valuations. And while there's lots of discussion about the impact on private companies and cash runway and 409A valuations, measuring the performance of non-public companies isn't as easy. IPOs have dried up and public statements by private companies, of course, they accentuate the good and they kind of hide the bad. Real data, unless you're an insider, is hard to find. Hello and welcome to this week's "Wikibon Cube Insights" powered by ETR. In this "Breaking Analysis", we unlock some of the secrets that non-public, emerging tech companies may or may not be sharing. And we do this by introducing you to a capability from ETR that we've not exposed you to over the past couple of years, it's called the Emerging Technologies Survey, and it is packed with sentiment data and performance data based on surveys of more than a thousand CIOs and IT buyers covering more than 400 companies. And we've invited back our colleague, Erik Bradley of ETR to help explain the survey and the data that we're going to cover today. Erik, this survey is something that I've not personally spent much time on, but I'm blown away at the data. It's really unique and detailed. First of all, welcome. Good to see you again. >> Great to see you too, Dave, and I'm really happy to be talking about the ETS or the Emerging Technology Survey. Even our own clients of constituents probably don't spend as much time in here as they should. >> Yeah, because there's so much in the mainstream, but let's pull up a slide to bring out the survey composition. Tell us about the study. How often do you run it? What's the background and the methodology? >> Yeah, you were just spot on the way you were talking about the private tech companies out there. So what we did is we decided to take all the vendors that we track that are not yet public and move 'em over to the ETS. And there isn't a lot of information out there. If you're not in Silicon (indistinct), you're not going to get this stuff. So PitchBook and Tech Crunch are two out there that gives some data on these guys. But what we really wanted to do was go out to our community. We have 6,000, ITDMs in our community. We wanted to ask them, "Are you aware of these companies? And if so, are you allocating any resources to them? Are you planning to evaluate them," and really just kind of figure out what we can do. So this particular survey, as you can see, 1000 plus responses, over 450 vendors that we track. And essentially what we're trying to do here is talk about your evaluation and awareness of these companies and also your utilization. And also if you're not utilizing 'em, then we can also figure out your sales conversion or churn. So this is interesting, not only for the ITDMs themselves to figure out what their peers are evaluating and what they should put in POCs against the big guys when contracts come up. But it's also really interesting for the tech vendors themselves to see how they're performing. >> And you can see 2/3 of the respondents are director level of above. You got 28% is C-suite. There is of course a North America bias, 70, 75% is North America. But these smaller companies, you know, that's when they start doing business. So, okay. We're going to do a couple of things here today. First, we're going to give you the big picture across the sectors that ETR covers within the ETS survey. And then we're going to look at the high and low sentiment for the larger private companies. And then we're going to do the same for the smaller private companies, the ones that don't have as much mindshare. And then I'm going to put those two groups together and we're going to look at two dimensions, actually three dimensions, which companies are being evaluated the most. Second, companies are getting the most usage and adoption of their offerings. And then third, which companies are seeing the highest churn rates, which of course is a silent killer of companies. And then finally, we're going to look at the sentiment and mindshare for two key areas that we like to cover often here on "Breaking Analysis", security and data. And data comprises database, including data warehousing, and then big data analytics is the second part of data. And then machine learning and AI is the third section within data that we're going to look at. Now, one other thing before we get into it, ETR very often will include open source offerings in the mix, even though they're not companies like TensorFlow or Kubernetes, for example. And we'll call that out during this discussion. The reason this is done is for context, because everyone is using open source. It is the heart of innovation and many business models are super glued to an open source offering, like take MariaDB, for example. There's the foundation and then there's with the open source code and then there, of course, the company that sells services around the offering. Okay, so let's first look at the highest and lowest sentiment among these private firms, the ones that have the highest mindshare. So they're naturally going to be somewhat larger. And we do this on two dimensions, sentiment on the vertical axis and mindshare on the horizontal axis and note the open source tool, see Kubernetes, Postgres, Kafka, TensorFlow, Jenkins, Grafana, et cetera. So Erik, please explain what we're looking at here, how it's derived and what the data tells us. >> Certainly, so there is a lot here, so we're going to break it down first of all by explaining just what mindshare and net sentiment is. You explain the axis. We have so many evaluation metrics, but we need to aggregate them into one so that way we can rank against each other. Net sentiment is really the aggregation of all the positive and subtracting out the negative. So the net sentiment is a very quick way of looking at where these companies stand versus their peers in their sectors and sub sectors. Mindshare is basically the awareness of them, which is good for very early stage companies. And you'll see some names on here that are obviously been around for a very long time. And they're clearly be the bigger on the axis on the outside. Kubernetes, for instance, as you mentioned, is open source. This de facto standard for all container orchestration, and it should be that far up into the right, because that's what everyone's using. In fact, the open source leaders are so prevalent in the emerging technology survey that we break them out later in our analysis, 'cause it's really not fair to include them and compare them to the actual companies that are providing the support and the security around that open source technology. But no survey, no analysis, no research would be complete without including these open source tech. So what we're looking at here, if I can just get away from the open source names, we see other things like Databricks and OneTrust . They're repeating as top net sentiment performers here. And then also the design vendors. People don't spend a lot of time on 'em, but Miro and Figma. This is their third survey in a row where they're just dominating that sentiment overall. And Adobe should probably take note of that because they're really coming after them. But Databricks, we all know probably would've been a public company by now if the market hadn't turned, but you can see just how dominant they are in a survey of nothing but private companies. And we'll see that again when we talk about the database later. >> And I'll just add, so you see automation anywhere on there, the big UiPath competitor company that was not able to get to the public markets. They've been trying. Snyk, Peter McKay's company, they've raised a bunch of money, big security player. They're doing some really interesting things in developer security, helping developers secure the data flow, H2O.ai, Dataiku AI company. We saw them at the Snowflake Summit. Redis Labs, Netskope and security. So a lot of names that we know that ultimately we think are probably going to be hitting the public market. Okay, here's the same view for private companies with less mindshare, Erik. Take us through this one. >> On the previous slide too real quickly, I wanted to pull that security scorecard and we'll get back into it. But this is a newcomer, that I couldn't believe how strong their data was, but we'll bring that up in a second. Now, when we go to the ones of lower mindshare, it's interesting to talk about open source, right? Kubernetes was all the way on the top right. Everyone uses containers. Here we see Istio up there. Not everyone is using service mesh as much. And that's why Istio is in the smaller breakout. But still when you talk about net sentiment, it's about the leader, it's the highest one there is. So really interesting to point out. Then we see other names like Collibra in the data side really performing well. And again, as always security, very well represented here. We have Aqua, Wiz, Armis, which is a standout in this survey this time around. They do IoT security. I hadn't even heard of them until I started digging into the data here. And I couldn't believe how well they were doing. And then of course you have AnyScale, which is doing a second best in this and the best name in the survey Hugging Face, which is a machine learning AI tool. Also doing really well on a net sentiment, but they're not as far along on that access of mindshare just yet. So these are again, emerging companies that might not be as well represented in the enterprise as they will be in a couple of years. >> Hugging Face sounds like something you do with your two year old. Like you said, you see high performers, AnyScale do machine learning and you mentioned them. They came out of Berkeley. Collibra Governance, InfluxData is on there. InfluxDB's a time series database. And yeah, of course, Alex, if you bring that back up, you get a big group of red dots, right? That's the bad zone, I guess, which Sisense does vis, Yellowbrick Data is a NPP database. How should we interpret the red dots, Erik? I mean, is it necessarily a bad thing? Could it be misinterpreted? What's your take on that? >> Sure, well, let me just explain the definition of it first from a data science perspective, right? We're a data company first. So the gray dots that you're seeing that aren't named, that's the mean that's the average. So in order for you to be on this chart, you have to be at least one standard deviation above or below that average. So that gray is where we're saying, "Hey, this is where the lump of average comes in. This is where everyone normally stands." So you either have to be an outperformer or an underperformer to even show up in this analysis. So by definition, yes, the red dots are bad. You're at least one standard deviation below the average of your peers. It's not where you want to be. And if you're on the lower left, not only are you not performing well from a utilization or an actual usage rate, but people don't even know who you are. So that's a problem, obviously. And the VCs and the PEs out there that are backing these companies, they're the ones who mostly are interested in this data. >> Yeah. Oh, that's great explanation. Thank you for that. No, nice benchmarking there and yeah, you don't want to be in the red. All right, let's get into the next segment here. Here going to look at evaluation rates, adoption and the all important churn. First new evaluations. Let's bring up that slide. And Erik, take us through this. >> So essentially I just want to explain what evaluation means is that people will cite that they either plan to evaluate the company or they're currently evaluating. So that means we're aware of 'em and we are choosing to do a POC of them. And then we'll see later how that turns into utilization, which is what a company wants to see, awareness, evaluation, and then actually utilizing them. That's sort of the life cycle for these emerging companies. So what we're seeing here, again, with very high evaluation rates. H2O, we mentioned. SecurityScorecard jumped up again. Chargebee, Snyk, Salt Security, Armis. A lot of security names are up here, Aqua, Netskope, which God has been around forever. I still can't believe it's in an Emerging Technology Survey But so many of these names fall in data and security again, which is why we decided to pick those out Dave. And on the lower side, Vena, Acton, those unfortunately took the dubious award of the lowest evaluations in our survey, but I prefer to focus on the positive. So SecurityScorecard, again, real standout in this one, they're in a security assessment space, basically. They'll come in and assess for you how your security hygiene is. And it's an area of a real interest right now amongst our ITDM community. >> Yeah, I mean, I think those, and then Arctic Wolf is up there too. They're doing managed services. You had mentioned Netskope. Yeah, okay. All right, let's look at now adoption. These are the companies whose offerings are being used the most and are above that standard deviation in the green. Take us through this, Erik. >> Sure, yet again, what we're looking at is, okay, we went from awareness, we went to evaluation. Now it's about utilization, which means a survey respondent's going to state "Yes, we evaluated and we plan to utilize it" or "It's already in our enterprise and we're actually allocating further resources to it." Not surprising, again, a lot of open source, the reason why, it's free. So it's really easy to grow your utilization on something that's free. But as you and I both know, as Red Hat proved, there's a lot of money to be made once the open source is adopted, right? You need the governance, you need the security, you need the support wrapped around it. So here we're seeing Kubernetes, Postgres, Apache Kafka, Jenkins, Grafana. These are all open source based names. But if we're looking at names that are non open source, we're going to see Databricks, Automation Anywhere, Rubrik all have the highest mindshare. So these are the names, not surprisingly, all names that probably should have been public by now. Everyone's expecting an IPO imminently. These are the names that have the highest mindshare. If we talk about the highest utilization rates, again, Miro and Figma pop up, and I know they're not household names, but they are just dominant in this survey. These are applications that are meant for design software and, again, they're going after an Autodesk or a CAD or Adobe type of thing. It is just dominant how high the utilization rates are here, which again is something Adobe should be paying attention to. And then you'll see a little bit lower, but also interesting, we see Collibra again, we see Hugging Face again. And these are names that are obviously in the data governance, ML, AI side. So we're seeing a ton of data, a ton of security and Rubrik was interesting in this one, too, high utilization and high mindshare. We know how pervasive they are in the enterprise already. >> Erik, Alex, keep that up for a second, if you would. So yeah, you mentioned Rubrik. Cohesity's not on there. They're sort of the big one. We're going to talk about them in a moment. Puppet is interesting to me because you remember the early days of that sort of space, you had Puppet and Chef and then you had Ansible. Red Hat bought Ansible and then Ansible really took off. So it's interesting to see Puppet on there as well. Okay. So now let's look at the churn because this one is where you don't want to be. It's, of course, all red 'cause churn is bad. Take us through this, Erik. >> Yeah, definitely don't want to be here and I don't love to dwell on the negative. So we won't spend as much time. But to your point, there's one thing I want to point out that think it's important. So you see Rubrik in the same spot, but Rubrik has so many citations in our survey that it actually would make sense that they're both being high utilization and churn just because they're so well represented. They have such a high overall representation in our survey. And the reason I call that out is Cohesity. Cohesity has an extremely high churn rate here about 17% and unlike Rubrik, they were not on the utilization side. So Rubrik is seeing both, Cohesity is not. It's not being utilized, but it's seeing a high churn. So that's the way you can look at this data and say, "Hm." Same thing with Puppet. You noticed that it was on the other slide. It's also on this one. So basically what it means is a lot of people are giving Puppet a shot, but it's starting to churn, which means it's not as sticky as we would like. One that was surprising on here for me was Tanium. It's kind of jumbled in there. It's hard to see in the middle, but Tanium, I was very surprised to see as high of a churn because what I do hear from our end user community is that people that use it, like it. It really kind of spreads into not only vulnerability management, but also that endpoint detection and response side. So I was surprised by that one, mostly to see Tanium in here. Mural, again, was another one of those application design softwares that's seeing a very high churn as well. >> So you're saying if you're in both... Alex, bring that back up if you would. So if you're in both like MariaDB is for example, I think, yeah, they're in both. They're both green in the previous one and red here, that's not as bad. You mentioned Rubrik is going to be in both. Cohesity is a bit of a concern. Cohesity just brought on Sanjay Poonen. So this could be a go to market issue, right? I mean, 'cause Cohesity has got a great product and they got really happy customers. So they're just maybe having to figure out, okay, what's the right ideal customer profile and Sanjay Poonen, I guarantee, is going to have that company cranking. I mean they had been doing very well on the surveys and had fallen off of a bit. The other interesting things wondering the previous survey I saw Cvent, which is an event platform. My only reason I pay attention to that is 'cause we actually have an event platform. We don't sell it separately. We bundle it as part of our offerings. And you see Hopin on here. Hopin raised a billion dollars during the pandemic. And we were like, "Wow, that's going to blow up." And so you see Hopin on the churn and you didn't see 'em in the previous chart, but that's sort of interesting. Like you said, let's not kind of dwell on the negative, but you really don't. You know, churn is a real big concern. Okay, now we're going to drill down into two sectors, security and data. Where data comprises three areas, database and data warehousing, machine learning and AI and big data analytics. So first let's take a look at the security sector. Now this is interesting because not only is it a sector drill down, but also gives an indicator of how much money the firm has raised, which is the size of that bubble. And to tell us if a company is punching above its weight and efficiently using its venture capital. Erik, take us through this slide. Explain the dots, the size of the dots. Set this up please. >> Yeah. So again, the axis is still the same, net sentiment and mindshare, but what we've done this time is we've taken publicly available information on how much capital company is raised and that'll be the size of the circle you see around the name. And then whether it's green or red is basically saying relative to the amount of money they've raised, how are they doing in our data? So when you see a Netskope, which has been around forever, raised a lot of money, that's why you're going to see them more leading towards red, 'cause it's just been around forever and kind of would expect it. Versus a name like SecurityScorecard, which is only raised a little bit of money and it's actually performing just as well, if not better than a name, like a Netskope. OneTrust doing absolutely incredible right now. BeyondTrust. We've seen the issues with Okta, right. So those are two names that play in that space that obviously are probably getting some looks about what's going on right now. Wiz, we've all heard about right? So raised a ton of money. It's doing well on net sentiment, but the mindshare isn't as well as you'd want, which is why you're going to see a little bit of that red versus a name like Aqua, which is doing container and application security. And hasn't raised as much money, but is really neck and neck with a name like Wiz. So that is why on a relative basis, you'll see that more green. As we all know, information security is never going away. But as we'll get to later in the program, Dave, I'm not sure in this current market environment, if people are as willing to do POCs and switch away from their security provider, right. There's a little bit of tepidness out there, a little trepidation. So right now we're seeing overall a slight pause, a slight cooling in overall evaluations on the security side versus historical levels a year ago. >> Now let's stay on here for a second. So a couple things I want to point out. So it's interesting. Now Snyk has raised over, I think $800 million but you can see them, they're high on the vertical and the horizontal, but now compare that to Lacework. It's hard to see, but they're kind of buried in the middle there. That's the biggest dot in this whole thing. I think I'm interpreting this correctly. They've raised over a billion dollars. It's a Mike Speiser company. He was the founding investor in Snowflake. So people watch that very closely, but that's an example of where they're not punching above their weight. They recently had a layoff and they got to fine tune things, but I'm still confident they they're going to do well. 'Cause they're approaching security as a data problem, which is probably people having trouble getting their arms around that. And then again, I see Arctic Wolf. They're not red, they're not green, but they've raised fair amount of money, but it's showing up to the right and decent level there. And a couple of the other ones that you mentioned, Netskope. Yeah, they've raised a lot of money, but they're actually performing where you want. What you don't want is where Lacework is, right. They've got some work to do to really take advantage of the money that they raised last November and prior to that. >> Yeah, if you're seeing that more neutral color, like you're calling out with an Arctic Wolf, like that means relative to their peers, this is where they should be. It's when you're seeing that red on a Lacework where we all know, wow, you raised a ton of money and your mindshare isn't where it should be. Your net sentiment is not where it should be comparatively. And then you see these great standouts, like Salt Security and SecurityScorecard and Abnormal. You know they haven't raised that much money yet, but their net sentiment's higher and their mindshare's doing well. So those basically in a nutshell, if you're a PE or a VC and you see a small green circle, then you're doing well, then it means you made a good investment. >> Some of these guys, I don't know, but you see these small green circles. Those are the ones you want to start digging into and maybe help them catch a wave. Okay, let's get into the data discussion. And again, three areas, database slash data warehousing, big data analytics and ML AI. First, we're going to look at the database sector. So Alex, thank you for bringing that up. Alright, take us through this, Erik. Actually, let me just say Postgres SQL. I got to ask you about this. It shows some funding, but that actually could be a mix of EDB, the company that commercializes Postgres and Postgres the open source database, which is a transaction system and kind of an open source Oracle. You see MariaDB is a database, but open source database. But the companies they've raised over $200 million and they filed an S-4. So Erik looks like this might be a little bit of mashup of companies and open source products. Help us understand this. >> Yeah, it's tough when you start dealing with the open source side and I'll be honest with you, there is a little bit of a mashup here. There are certain names here that are a hundred percent for profit companies. And then there are others that are obviously open source based like Redis is open source, but Redis Labs is the one trying to monetize the support around it. So you're a hundred percent accurate on this slide. I think one of the things here that's important to note though, is just how important open source is to data. If you're going to be going to any of these areas, it's going to be open source based to begin with. And Neo4j is one I want to call out here. It's not one everyone's familiar with, but it's basically geographical charting database, which is a name that we're seeing on a net sentiment side actually really, really high. When you think about it's the third overall net sentiment for a niche database play. It's not as big on the mindshare 'cause it's use cases aren't as often, but third biggest play on net sentiment. I found really interesting on this slide. >> And again, so MariaDB, as I said, they filed an S-4 I think $50 million in revenue, that might even be ARR. So they're not huge, but they're getting there. And by the way, MariaDB, if you don't know, was the company that was formed the day that Oracle bought Sun in which they got MySQL and MariaDB has done a really good job of replacing a lot of MySQL instances. Oracle has responded with MySQL HeatWave, which was kind of the Oracle version of MySQL. So there's some interesting battles going on there. If you think about the LAMP stack, the M in the LAMP stack was MySQL. And so now it's all MariaDB replacing that MySQL for a large part. And then you see again, the red, you know, you got to have some concerns about there. Aerospike's been around for a long time. SingleStore changed their name a couple years ago, last year. Yellowbrick Data, Fire Bolt was kind of going after Snowflake for a while, but yeah, you want to get out of that red zone. So they got some work to do. >> And Dave, real quick for the people that aren't aware, I just want to let them know that we can cut this data with the public company data as well. So we can cross over this with that because some of these names are competing with the larger public company names as well. So we can go ahead and cross reference like a MariaDB with a Mongo, for instance, or of something of that nature. So it's not in this slide, but at another point we can certainly explain on a relative basis how these private names are doing compared to the other ones as well. >> All right, let's take a quick look at analytics. Alex, bring that up if you would. Go ahead, Erik. >> Yeah, I mean, essentially here, I can't see it on my screen, my apologies. I just kind of went to blank on that. So gimme one second to catch up. >> So I could set it up while you're doing that. You got Grafana up and to the right. I mean, this is huge right. >> Got it thank you. I lost my screen there for a second. Yep. Again, open source name Grafana, absolutely up and to the right. But as we know, Grafana Labs is actually picking up a lot of speed based on Grafana, of course. And I think we might actually hear some noise from them coming this year. The names that are actually a little bit more disappointing than I want to call out are names like ThoughtSpot. It's been around forever. Their mindshare of course is second best here but based on the amount of time they've been around and the amount of money they've raised, it's not actually outperforming the way it should be. We're seeing Moogsoft obviously make some waves. That's very high net sentiment for that company. It's, you know, what, third, fourth position overall in this entire area, Another name like Fivetran, Matillion is doing well. Fivetran, even though it's got a high net sentiment, again, it's raised so much money that we would've expected a little bit more at this point. I know you know this space extremely well, but basically what we're looking at here and to the bottom left, you're going to see some names with a lot of red, large circles that really just aren't performing that well. InfluxData, however, second highest net sentiment. And it's really pretty early on in this stage and the feedback we're getting on this name is the use cases are great, the efficacy's great. And I think it's one to watch out for. >> InfluxData, time series database. The other interesting things I just noticed here, you got Tamer on here, which is that little small green. Those are the ones we were saying before, look for those guys. They might be some of the interesting companies out there and then observe Jeremy Burton's company. They do observability on top of Snowflake, not green, but kind of in that gray. So that's kind of cool. Monte Carlo is another one, they're sort of slightly green. They are doing some really interesting things in data and data mesh. So yeah, okay. So I can spend all day on this stuff, Erik, phenomenal data. I got to get back and really dig in. Let's end with machine learning and AI. Now this chart it's similar in its dimensions, of course, except for the money raised. We're not showing that size of the bubble, but AI is so hot. We wanted to cover that here, Erik, explain this please. Why TensorFlow is highlighted and walk us through this chart. >> Yeah, it's funny yet again, right? Another open source name, TensorFlow being up there. And I just want to explain, we do break out machine learning, AI is its own sector. A lot of this of course really is intertwined with the data side, but it is on its own area. And one of the things I think that's most important here to break out is Databricks. We started to cover Databricks in machine learning, AI. That company has grown into much, much more than that. So I do want to state to you Dave, and also the audience out there that moving forward, we're going to be moving Databricks out of only the MA/AI into other sectors. So we can kind of value them against their peers a little bit better. But in this instance, you could just see how dominant they are in this area. And one thing that's not here, but I do want to point out is that we have the ability to break this down by industry vertical, organization size. And when I break this down into Fortune 500 and Fortune 1000, both Databricks and Tensorflow are even better than you see here. So it's quite interesting to see that the names that are succeeding are also succeeding with the largest organizations in the world. And as we know, large organizations means large budgets. So this is one area that I just thought was really interesting to point out that as we break it down, the data by vertical, these two names still are the outstanding players. >> I just also want to call it H2O.ai. They're getting a lot of buzz in the marketplace and I'm seeing them a lot more. Anaconda, another one. Dataiku consistently popping up. DataRobot is also interesting because all the kerfuffle that's going on there. The Cube guy, Cube alum, Chris Lynch stepped down as executive chairman. All this stuff came out about how the executives were taking money off the table and didn't allow the employees to participate in that money raising deal. So that's pissed a lot of people off. And so they're now going through some kind of uncomfortable things, which is unfortunate because DataRobot, I noticed, we haven't covered them that much in "Breaking Analysis", but I've noticed them oftentimes, Erik, in the surveys doing really well. So you would think that company has a lot of potential. But yeah, it's an important space that we're going to continue to watch. Let me ask you Erik, can you contextualize this from a time series standpoint? I mean, how is this changed over time? >> Yeah, again, not show here, but in the data. I'm sorry, go ahead. >> No, I'm sorry. What I meant, I should have interjected. In other words, you would think in a downturn that these emerging companies would be less interesting to buyers 'cause they're more risky. What have you seen? >> Yeah, and it was interesting before we went live, you and I were having this conversation about "Is the downturn stopping people from evaluating these private companies or not," right. In a larger sense, that's really what we're doing here. How are these private companies doing when it comes down to the actual practitioners? The people with the budget, the people with the decision making. And so what I did is, we have historical data as you know, I went back to the Emerging Technology Survey we did in November of 21, right at the crest right before the market started to really fall and everything kind of started to fall apart there. And what I noticed is on the security side, very much so, we're seeing less evaluations than we were in November 21. So I broke it down. On cloud security, net sentiment went from 21% to 16% from November '21. That's a pretty big drop. And again, that sentiment is our one aggregate metric for overall positivity, meaning utilization and actual evaluation of the name. Again in database, we saw it drop a little bit from 19% to 13%. However, in analytics we actually saw it stay steady. So it's pretty interesting that yes, cloud security and security in general is always going to be important. But right now we're seeing less overall net sentiment in that space. But within analytics, we're seeing steady with growing mindshare. And also to your point earlier in machine learning, AI, we're seeing steady net sentiment and mindshare has grown a whopping 25% to 30%. So despite the downturn, we're seeing more awareness of these companies in analytics and machine learning and a steady, actual utilization of them. I can't say the same in security and database. They're actually shrinking a little bit since the end of last year. >> You know it's interesting, we were on a round table, Erik does these round tables with CISOs and CIOs, and I remember one time you had asked the question, "How do you think about some of these emerging tech companies?" And one of the executives said, "I always include somebody in the bottom left of the Gartner Magic Quadrant in my RFPs. I think he said, "That's how I found," I don't know, it was Zscaler or something like that years before anybody ever knew of them "Because they're going to help me get to the next level." So it's interesting to see Erik in these sectors, how they're holding up in many cases. >> Yeah. It's a very important part for the actual IT practitioners themselves. There's always contracts coming up and you always have to worry about your next round of negotiations. And that's one of the roles these guys play. You have to do a POC when contracts come up, but it's also their job to stay on top of the new technology. You can't fall behind. Like everyone's a software company. Now everyone's a tech company, no matter what you're doing. So these guys have to stay in on top of it. And that's what this ETS can do. You can go in here and look and say, "All right, I'm going to evaluate their technology," and it could be twofold. It might be that you're ready to upgrade your technology and they're actually pushing the envelope or it simply might be I'm using them as a negotiation ploy. So when I go back to the big guy who I have full intentions of writing that contract to, at least I have some negotiation leverage. >> Erik, we got to leave it there. I could spend all day. I'm going to definitely dig into this on my own time. Thank you for introducing this, really appreciate your time today. >> I always enjoy it, Dave and I hope everyone out there has a great holiday weekend. Enjoy the rest of the summer. And, you know, I love to talk data. So anytime you want, just point the camera on me and I'll start talking data. >> You got it. I also want to thank the team at ETR, not only Erik, but Darren Bramen who's a data scientist, really helped prepare this data, the entire team over at ETR. I cannot tell you how much additional data there is. We are just scratching the surface in this "Breaking Analysis". So great job guys. I want to thank Alex Myerson. Who's on production and he manages the podcast. Ken Shifman as well, who's just coming back from VMware Explore. Kristen Martin and Cheryl Knight help get the word out on social media and in our newsletters. And Rob Hof is our editor in chief over at SiliconANGLE. Does some great editing for us. Thank you. All of you guys. Remember these episodes, they're all available as podcast, wherever you listen. All you got to do is just search "Breaking Analysis" podcast. I publish each week on wikibon.com and siliconangle.com. Or you can email me to get in touch david.vellante@siliconangle.com. You can DM me at dvellante or comment on my LinkedIn posts and please do check out etr.ai for the best survey data in the enterprise tech business. This is Dave Vellante for Erik Bradley and The Cube Insights powered by ETR. Thanks for watching. Be well. And we'll see you next time on "Breaking Analysis". (upbeat music)

Published Date : Sep 7 2022

SUMMARY :

bringing you data driven it's called the Emerging Great to see you too, Dave, so much in the mainstream, not only for the ITDMs themselves It is the heart of innovation So the net sentiment is a very So a lot of names that we And then of course you have AnyScale, That's the bad zone, I guess, So the gray dots that you're rates, adoption and the all And on the lower side, Vena, Acton, in the green. are in the enterprise already. So now let's look at the churn So that's the way you can look of dwell on the negative, So again, the axis is still the same, And a couple of the other And then you see these great standouts, Those are the ones you want to but Redis Labs is the one And by the way, MariaDB, So it's not in this slide, Alex, bring that up if you would. So gimme one second to catch up. So I could set it up but based on the amount of time Those are the ones we were saying before, And one of the things I think didn't allow the employees to here, but in the data. What have you seen? the market started to really And one of the executives said, And that's one of the Thank you for introducing this, just point the camera on me We are just scratching the surface

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Said Ouissal, Zededa | VMware Explore 2022


 

>>Hey, everyone. Welcome back to San Francisco. Lisa Martin and John furrier live on the floor at VMware Explorer, 2022. This is our third day of wall to wall coverage on the cube. But you know that cuz you've been here the whole time. We're pleased to welcome up. First timer to the cubes we saw is here. The CEO and founder of ZDA. Saed welcome to the program. >>Thank you for having me >>Talk to me a little bit about what ZDA does in edge. >>Sure. So ZDA is a company purely focused in edge computing. I started a company about five years ago, go after edge. So what we do is we help customers with orchestrating their edge, helping them to deploy secure monitor application services and devices at the edge. >>What's the business model for you guys. We get that out there. So the targeting the edge, which is everything from telco to whatever. Yeah. What's the business model. Yeah. >>Maybe before we go there, let's talk about edge itself. Cuz edge is complex. There's a lot of companies. I call 'em lens company nowadays, if you're not a cloud company, you're probably an edge company at this point. So we are focusing something called the distributed edge. So distributed edge. When you start putting tiny servers in environments like factory floors, solar farms, wind farms, even inside machines or well sites, et cetera. And a question that people always ask me, like why, why would you want to put, you know, servers there on servers supposed to be in a data center in the cloud? And the answer to the question actually is data gravity. So traditionally wherever the data gets created is where your applications live. But as we're connecting more and more devices to the edge of the network, we basically customers now are required to push the applications to the edge cause they can't go all the data to the cloud. So basically that's where we focus on people call it the far edge as well. You know, that's the term we've heard in the past as well. And what we do in our business model is provide customers a, a software as a service solution where they can basically deploy and monitor these applications at these highly distributed environments. >>Data, gravity comes up a lot and I want you to take a minute to explain the definition as it is today. And people have used that term, you know, with big data, going back to 2010 leads when we covering the Hadoop wave, which ended up becoming, you know, data, data, bricks, and snowflake now, but, but a lots changed, but what does it mean to be data gravity? It means that staying local, it's just what specifically describe and, and define what data gravity is. >>Yeah. So for me, data gravity is where you need to process the data, right? It's where the data usually gets created. So if you think about a web app, where does the data get created? Where people click on buttons, they, they interface with it. They, they upload content to it, et cetera. So that's where the data gravity therefore is therefore that's where you do your analytics. That's where you do your visualization processing, machine learning and all of those pieces. So it's really where that data gets created is where the data gravity in my view says, >>What are some of the challenges that data and opportunities that data gravity presents to customers? >>Well, obviously I think every enterprise in this day is trying to take data and make it a competitive advantage, right? Like faster decisions, better decisions, outcompete your competition by, you know, being first with a product or being first with a product with the future, et cetera. So, so I think, you know, if you're not a data driven enterprise by now, then I think the future may be a little bit bleak. >>Okay. So you're targeting the market distributed edge business model, SAS technology, secret sauce. What's that piece. >>Yeah. So that's, that's what the interesting part comes in. I think, you know, if you kind of look at the data center in the cloud, we've had these virtualization and orchestration stacks create, I mean, we're here in VMware Explorer. And as an example, what we basically, what we saw is that the edge is so unique and so different than what we've seen in the data center, in the cloud that we needed to build a complete brand new purpose-built illustration and virtualization solution. So that's really what we, we set off to do. So there's two components that we do. One end is we built a purpose-built edge operating system for the edge and we actually open sourced it. And the reason we opensource it, we said, Hey, you know, edge is so diverse. You know, depending on the environment you're running in a machine or in a vehicle or in a well site, you have different hardware, different networks, different applications you need to enable. >>And we will never be able to support all of them ourselves. As a matter of fact, we actually think there's a need for standardization at the edge. We need to kind of cut through all these silos that have been created traditionally from the embedded way of thinking. So we created basically an open source project in the Linux foundation in LFS, which is a sister organization through the CNCF it's called project Eve. And the idea is to create the Android of the edge, basically what Android became for mobile computing, an a common operating system. So you build one app. You can run in any phone in the world that runs Android, build an architecture. You build one app. You can run in any Eve powered node in the world, >>So distributed edge and you get the tech here, get the secret sauce. We'll get more into that in a second, but I wanna just tie one kick quick point and get your clarification on edge is becoming much more about the physical side too. I mean, absolutely. So when you talk about Android, you're making the reference of a phone. I get that's metaphor to what you're doing at the edge, wind farms, factories, alarms, light bulbs, buildings. I mean, that's what you're talking about, right? Yes. We're getting down to that very, >>Very physical, dark distributed locations. >>We're gonna come back to the CISO CSO. We're gonna come back to the CISO versus CSO question because is the CISO or CIO or who runs that anyway? So that's true. What's the important thing that's happening because that sounds like old OT world, like yes. Operating technology, not it information technology, is it a complete reset of those worlds or is it a collision? >>It's a great question. So what we're seeing is first of all, there is already compute in these environments, industrial PCs of existed well beyond, you know, an industrial automation has been done for many, many decades. The point is that that stuff has been done. Collect data has been collected, but never connected, right? So with edge computing, we're connecting now this data from an industrial machine and industrial process to the cloud, right? And one of the problems is it's data that comes of that industrial process too much to upload to the cloud. So I gotta analyze, analyze it locally. So one of the, the things we saw early on in edge is there's a lot of brownfield. Most of our customers today actually have applications running on windows and they would love to make in Linux and containers and Kubernetes, but it took them 20, 30 years to build those apps. And they basically are the money makers of the enterprise. So they are in a, in a transitionary phase and they need something that can take them from the brown to the Greenfield. So to your point, you gotta support all of these types of unique brownfield applications. >>So you're, you're saying I don't really care if this is a customer, how you get the data, you wanna start new start fresh. That's cool. But if you wanna take your old data, you'll >>Take that. Yeah. You don't wanna rebuild the whole machine. You're >>Just, they can life cycle it out on their own timetable. Yeah. >>So we had to learn, first of all, how do we take and lift and shift windows based industrial application and make it run at the edge on, on our architecture. Right? And then the second step is how do we then Sen off that data that this application is generating and do we fuse it with cloud native capability? Like, >>So your cloud, so your staff is your open source that you're giving to the Linux foundation as part of that Eve project that's available to everybody. So they can, they can look at the code, which is great by the way. Yeah. So people wanna do that. Yeah. Your self source, I'm assuming, is your hardened version with support? >>Well, we took what we took, what the open source companies did, opensource companies traditionally have sold, you know, basically a support model around the open source. We actually saw another problem. Customers has like, okay, now I have this node running and I can, you know, do this data analytics, but what if I have 15 or 20,000 of these node? And they're all around the world in remote locations on satellite links or wireless connectivity, how do I orchestrate them? So we actually build an orchestration service for these nodes running this open source >>Software. So that's a key secret sauce right there. >>That is the business model that taking open store and a lot. >>And you're taking your own code that you have. Okay. Got it. Cool. And then the customer's customer piece is, is key. So that's the final piece, I guess who's using it. >>Yeah. Well, and, >>And, and one of the business outcomes that they're achieving. Oh >>Yeah. Well, so maybe start with that first. I mean, we are deployed in customers in all and gas, for instance, helping them with the transition to renewable energy, right? So basically we, we have customers for instance, that deploy us in the, how they drill Wells is one use case and doing that better, faster, and cheaper and, and less environmental impacting. But we also have customers that use us in wind farms. We have, and solar farms, like we, one of the leading solar energy companies in the world is using us to bring down the cost of power by predicting failures ahead of time, for >>Instance. And when you're working with customers to create the optimal solution at the distributed edge, who are you working with in, within an organization? Yeah. >>It's usually a mix of OT and it people. Okay. So the OT people typically they're >>Arm wrestling, well, or they're getting along, actually, >>I think they're getting along very well. Okay, good. But they also agree that they have to have swim lanes. The it folks, obviously their job is to make sure, you know, everything is secure. Everything is according to the compliance it's, it's, you know, the, the best TCO on the infrastructure, those type of things, the OT guy, they, they, or girl, they care about the application. They care about the services. They care about the support new business. So how can you create a model that too can coexist? And if you do that, they get along really well. >>You know, we had an event called Supercloud and@theurlsupercloud.world, if you're watching check it out, it's our version of what we think multicloud will merge into including edge cuz edge is just another node in the, in the, in the network. As far as we're concerned, hybrid is the steady state. That's distributed computing on premise, private cloud, public cloud. We know what that looks like. People love that things are happening. Edge is like a whole nother new area. That's blossoming and with disruption, yeah. There's a lot of existing market and incumbents that need to be disrupted. And there's also a new capabilities that are coming that we don't yet see. So we're seeing it with the super cloud idea that these new kinds of clouds are emerging. Like there could be an edge cloud. Yeah. Why isn't there a security cloud, whereas the financial services cloud, whereas the insurance cloud, whereas the, so these become super clouds where the CapEx could be done by the Amazon, whatnot you've been following them is edge cloud. Can you make that a cloud? Is that what you guys are trying to do? And if so, what does that look like? Cause we we're adding a new track to our super cloud site. I mentioned on edge specifically, we're trying to figure out you and if you share your opinion, it'd be great. Can the E can edge clouds exist and be run by companies? Yeah. Or is that what you guys are trying to do? >>I, I, I mean, I think first of all, there is no edge without cloud, right? So when I meet any customer who says, Hey, we're gonna do edge without cloud. Then I'm like, you're probably not gonna do edge computing. Right. And, and the way we built the company and the way we think about it, it's about extending the cloud experience all the way into these embedded distributed environments. That's really, I think what customers are looking for, cuz customers love the simplicity of the cloud. They love the ease of use agility, all of that greatness. And they're like, Hey, I want that. But not in a, you know, in an Amazon or Azure data center. I want that in my factories. I want that in my wealth sites, in my vehicles. And that's really what I think the future >>Is gonna. And how long have you guys been around? What's the, what's the history of the company because you might actually be that cloud. Yeah. And are you on AWS or Azure? You're building your own. What's the, >>Yeah. Yeah. So >>Take it through the, the architecture because yeah, yeah, sure. You're a modern startup. I mean you gotta, and the edges you're going after you gotta be geared up. Yeah. To win that. Yeah. >>So, so the company's about five years old. So we, when we started focusing on edge, people didn't necessarily talk as much about edge. We kind of identified the it's like, you know, how do you find a black hole in, in the universe? Cuz you can't see it, but you sort of look around that's why you in it. And so we were like looking at it, like there's something gonna happen here at the edge of the network, because everybody's saying we're connecting these vice upload the data to the cloud's never gonna work. My background is networking. I worked at companies like Juniper and Ericsson ran several products there. So I know how the internet networks have built. And it was very Evan to me. It's not gonna be possible. My co-founders come from open source companies like pivotal and Cloudera. My auto co-founder was a, an engineer at sun Microsystems built the first network stack in the solar is operating system. So a lot of experience that kind of came together to build this. >>Yeah. Cloudera is a big day. That's where the cube started by the way. Yeah. >>Yeah. So, so we, we, we have, I think a good view on the stack, the cloud stack and therefore a good view of what the ed stack needs to look like. And then I think, you know, to answer your other question, our orchestration service runs in the cloud. We have, we actually are multi-cloud company. So we offer customers choice where they want to orchestrate the node from the nodes themself, never sit in a data center. They always highly embedded. We have customers are putting machines or inside these factory lines, et cetera. Are >>You running your SAS on Amazon web services or which >>Cloud we're running it on several clouds, including Amazon, all of, pretty much the cloud. So some customers say, Hey, I'd prefer to be on the Amazon set. And others customers say, I wanna be on Azure set. >>And you leverage their CapEx on that side. Yes. On behalf of yeah. >>Yeah. We, yes. Yes. But the majority of the customer data and, and all the data that the nodes process, the customer send it to their clouds. They don't send it to us. We don't get a copy of the camera feed analytics or the machine data. We actually decouple those though. So basically the, the team production data go straight to the customer's cloud and that's why they love us. >>And they choose that they can control their own desktop. >>Yeah. So we separate the management plane from the data plane at the edge. Yeah. >>That's a good call >>Actually. Yeah. That was another very important part of the architecture early on. Cause customers don't want us to see their, you know, highly confidential production data and we don't wanna have it either. So >>We had a great chat with Chris Wolf who works with kit culvert about control plane, data, plane. So that seems to be the trend data, plane customers want full yeah. Management of that. Yeah. Control plane. Maybe give multiple >>Versions. Yeah. Yeah. So our cloud consumption what the data we stories about the apps, their behavior, the networking, the security, all of that. That's what we store in our cloud. And then customers can access that and monitor. But the actual machine that I go somewhere else >>Here we are at VMware. Explore. Talk a little bit about the VMware relationship. You just had some big news the other day. >>Yeah. So two days ago we actually made a big announcement with VMware. So we signed an OEM agreement with VMware. So we're part now of VMware's edge compute stack. So VMware customers, as they start using the recently announced edge compute stack 2.0, that was announced here. Basically it's powered by Edda technology. So it's a really exciting partnership as part of this, we actually building integrations with the VMware organization products. So that's basically now extending to more, you know, other groups inside VMware. >>So what's the value in it for VMware customers. >>Yeah. So I think the, the, the benefit of, of VMware customers, I think cus VMware customers want that multi-cloud multi edge orchestration experience. So they wanna be able to deploy workloads in the cloud. They wanna deploy the workloads in the data center. And of course also at the edge. So by us integrating in that vision customers now can have that unified experience from cloud to edge and anywhere in between. >>What's the big vision that you see happening at the edge. I mean, a lot of the VMware customers here, they're classic it that have evolved into ops now, dev ops. Now you've got second data ops coming. The edge is gonna right around the corner for them. They're dealing with it now, probably just kicking the tires, towing the water kind of thing. Where do you see the vision going? Cuz now, no matter what happens with VMware, the Broadcom, this wave is still here. You got AWS, got Azure, got Google cloud, you got Oracle, Alibaba internationally. And the cloud native surges here. How do you see that disrupting the existing edge? Because let's face it the O some of those OT players, a little bit old and antiquated, a little bit outdated. I mean, I was talking to a telco person. They, they puked the word open source. I mean, these people are so dogmatic on, on their architecture. Yeah. They're gonna get disrupted. It's a matter of time. Yeah. Where's the new guard come in. How do you see the configuration changing in the landscape? Because some people will cross over to the right side of the street here. Yeah. Some won't yeah. Open circle. Dominate cloud native will be key. Yeah. >>Well, I mean, I think, again, let's, let's take an example of a vertical that's heavily disrupted now as the automotive market, right? The, so look at Tesla and look at all these companies, they built, they built software first cars, right? Software, first delivery of capabilities and everything else. And the, and the incumbents. They have only two options, right? Either they try to respond by adopting open source cloud, native technologies. Like the, these new entrants have done and really, you know, compete with them at that level, or they can become commodity. Right. So, and I think that's the customers we're seeing the smart customers go like, we need to compete with these guys. We need to figure out how to take this technology in. And they need partners like us and partners like VMware for them. >>Do you see customers becoming cloud super cloud players? If they continue to keep leveraging the CapEx of the clouds and focus all their operational capital on top line revenue, generating activities. >>Yeah. I, so I think the CapEx model of the cloud is a great benefit of the cloud, but I think that is not, what's the longer term future of the cloud. I think the op the cloud operating model is the future. Like the agility, the ability imagine embedded software that, you know, you do an over the year update to fix a bug, but it's very hard to make a, an embedded device smarter over time. And then imagine if you can run cloud native software, you can roll out every two weeks new features and make that thing smarter, intelligent, and continue to help you in your business. That I think is what cloud did ultimately. And I think that is what really these customers are gonna need at their edge. >>Well, we talked about the value within it for customers with the VMware partnership, but what are some of your expectations? Obviously, this is a pretty powerful partnership for you guys. Yeah. What are some of the things that you're expecting that this is gonna drive? Yeah, >>So we, we, we have always operated at the more OT layer, distributed organizations in retail, energy, industrial automotive. Those are the verticals we, so we've developed. I think a lot of experience there, what, what we're seeing as we talk to those customers is they obviously have it organizations and the it organizations, Hey, that's great. You're looking at its computing, but how do we tie this into the existing investments we made with VMware? And how do we kind of take that also to this new environment? And I think that's the expectation I have is that I think we will be able to, to talk to the it folks and say, Hey, you can actually talk to the OT person. And both of you will speak the same language. You probably will both standardize on the same architecture and you'll be together deploying and enabling this new agility at the edge. >>What are some of the next things coming up for ZDA and the team? >>Well, so we've had a really amazing few quarters. We just close a series B round. So we've raised the companies raised over 55 million so far, we're growing very rapidly. We opened up no new international offices. I would say the, the early customers that we started deploying, wait a while back, they're now going into mass scale deployment. So we have now deployments underway in, you know, the 10 to hundred thousands of nodes at certain customers and in amazing environments. And so, so for us, it's continuing to prove the product in more and more verticals. Our, our product is really built for the largest of the largest. So, you know, for the size of the company, we are, we have a high concentration of fortune 500 global 500 customers, and some of them even invested in our rounds recently. So we we've been really, you know, honored with that support. Well, congratulations. Good stuff, edges popping. All right. Thank you. >>Thank you so much for joining us, talking about what you're doing in distributed edge. What's in it for customers, the VMware partnership, and by the way, congratulations on >>That too. Thank you. Thank you so much. Nice to meet you. Thank >>You. All right. Nice to meet you as well for our guest and John furrier. I'm Lisa Martin. You're watching the cube live from VMware Explorer, 22, John and I will be right back with our next guest.

Published Date : Sep 1 2022

SUMMARY :

But you know that cuz you've been here the whole time. So what we do is we help customers with orchestrating What's the business model for you guys. And the answer to the question actually And people have used that term, you know, with big data, going back to 2010 leads when we covering the Hadoop So that's where the data gravity therefore is therefore that's where you do your analytics. so I think, you know, if you're not a data driven enterprise by now, then I think the future may be a little bit bleak. What's that piece. And the reason we opensource it, And the idea is to create the Android of the edge, basically what Android became for mobile computing, So when you talk about Android, you're making the reference of a phone. So that's true. So one of the, the things we saw early But if you wanna take your old data, you'll You're Just, they can life cycle it out on their own timetable. So we had to learn, first of all, how do we take and lift and shift windows based industrial application So they can, they can look at the code, which is great by the way. So we actually build an orchestration service for these nodes running this open source So that's a key secret sauce right there. So that's the final piece, I guess who's using it. And, and one of the business outcomes that they're achieving. I mean, we are deployed in customers in all and gas, edge, who are you working with in, within an organization? So the OT people typically they're So how can you create a model that too can coexist? Or is that what you guys are trying to do? And, and the way we built the company and And are you on AWS or Azure? I mean you gotta, and the edges you're going after you gotta be We kind of identified the it's like, you know, how do you find a black hole in, That's where the cube started by the way. And then I think, you know, to answer your other question, So some customers say, And you leverage their CapEx on that side. the team production data go straight to the customer's cloud and that's why they love us. you know, highly confidential production data and we don't wanna have it either. So that seems to be the trend data, plane customers want full yeah. But the actual machine that I go somewhere else You just had some big news the other day. So that's basically now extending to more, you know, other groups inside VMware. And of course also at the edge. What's the big vision that you see happening at the edge. Like the, these new entrants have done and really, you know, compete with them at that level, Do you see customers becoming cloud super cloud players? that thing smarter, intelligent, and continue to help you in your business. What are some of the things that you're expecting that this is gonna drive? And I think that's the expectation I have is that I think we will be able to, to talk to the it folks and say, So we we've been really, you know, honored with that support. Thank you so much for joining us, talking about what you're doing in distributed edge. Thank you so much. Nice to meet you as well for our guest and John furrier.

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Howie Xu, Zscaler | Supercloud22


 

(upbeat music) >> Welcome back to Supercloud 22. I'm John Furrier, your host of "The Cube." We're here for a live performance in studio bringing all the thought leaders around this concept of Supercloud, which is a consortium of the smartest people in the industry, the the Cloudaratti some say, or just people in the field building out next generation Cloud technologies for businesses, for the industry, you know, software meets infrastructure at scale and platforms. All great stuff. We have an expert here, Cube alumni and friend of ours, Howie Xu, VP of machine learning and AI at Zscaler, hugely successful company, platform, whatever you want to call it. They're definitely super clouding in their own. Howie, great to see you. Thanks for spending time with us to unpack and grock the direction of the industry that we see. We call it Supercloud. >> Hey, John, great to be back. I'm expecting a nice very educational and interesting conversation here again. >> Yeah, well, you know, one of the things I love talking with you about is you're deep on the technology side, as well as you got the historian view like we do. We've seen the movies before, we've seen the patterns, and now we're seeing structural change that has happened, that's cloud. Thank you very much, AWS. And as your GCP and others. Now we're seeing structural change happening in real time and we want to talk about it as it's happening. This is the purpose of this event. And that is that Cloud is one. Okay, great Cloud operations, on premises and Edge are emerging. Software is open source. It's the perfect storm for innovation and new things are emerging. You're seeing companies like Snowflake, and Databricks, and Zscaler all building great products. But now it's not one thing anymore. It's a lot of things going on. So what is your take on Supercloud? How do you see this evolving? What is some of the structural change that's happening in your mind? >> Yeah, so when you first reached out a few weeks ago about this event, I was like, "Hey, what is Supercloud." I know you tweeted a little bit here and there, but I never really, you know, double clicked, right. So I actually listened to some of your episodes you know, the previous conversations. You know, I would say the way you define Supercloud is it's not just the multi-cloud. The multi-Cloud is probably one aspect of it, right. You know, it's actually more beyond that, right. You know, a little bit, you know, towards past, a little bit more towards the flexibility, and then, you know, including, and also you want to include the on-prem, the edge, not just the Big 3 cloud, right. So there is a lot of the, let's say hybrid, more inclusive, right. So, the way I look at it is it's now very different from my imagination of where the Cloud would be, should be 10, 12 years ago. Because, you know, at that time it was, you know, on-prem dominant and then we say, hey, let's go cloud. I never for a second thought, you know, we would've ditch the on-prem completely, right. You know, on-prem has its own value. It's own kind of characteristics we wanted to keep, right. But the way we went for the last 10 years is, hey, Cloud, Cloud everywhere. We embrace Cloud. You know, the way I look at architecture is always very much like a pendulum, right? We swung from decentralized in the mainframe days, you know back in the days, to more distributed, right, PC, kind of a architecture, you know, servers in your own data center. And then to the now, the Cloud, the Big 3 Cloud in particular, right. I think in the next 10, 15, 20 years, it will swing back to more decentralized, more distributed architecture again. Every time you have a swing, because there is some fundamental reason behind that, we all knew the reason behind the current swing to the Cloud. It's because hey, the on-prem data center was too complex, right. You know, too expensive, right. You know, it would've take at least the six months to get any business application going, right. So compared to Cloud, a swipe a credit card, frictionless, you know, pay as you go, it's so great. But I think we are going to see more and more reason for people to say, "Hey, I need a architecture the other way around because of the decentralized the use case," right. Web3 is one example. Even though Web3 is still, you know, emerging right, very, very early days. But that could be one reason, right? You mentioned the Zscaler is kind of a Supercloud of its own, right? We always embrace public Cloud, but a lot of the workloads is actually on our own, you know, within our own data center. We take advantage of the elasticity of the public Cloud, right. But we also get a value, get a performance of our private Cloud. So I want to say a company like Zscaler taking advantage of the Supercloud already, but there will be more and more use cases taking advantage. >> And the use cases are key. Let me just go back and share something we had on the panel earlier in the day, the Cloudaratti Panel. Back in 2008, a bunch of us were getting together and we kind of were riffing, oh yeah, the future's going to be web services and Clouds will talk to each other, workloads can work across this (indistinct) abstraction layer, APIs is going to be talking to each other. A little bit early but we tried to think about it in terms of the preferred architecture. Okay, way too early. Yeah. AWS was just getting going, really kind of pumping on all cylinders there, getting that trajectory up. But it was use case driven. The nirvana never happened. I mean, we were talking Supercloud back then with the Cloudaratti group and we were thinking, okay, hey this is cool. But it was just an evolutionary thing. So I want to get your reaction. Today, the use cases are different. It's not just developers deploying on public Cloud to get all those greatness and goodness of the Cloud, to your point about Zscaler and others, there's on premises use cases and edge use cases emerging. 5g is right there. That's going to explode. So, the use cases now are all Cloud based. Again, this is an input into what we're seeing around Supercloud. How do you see that? What's your reaction to that? And how do you see that evolving so that the methodologies and all the taxonomies are in place for the right solution? >> Right, I mean, you know, some of the use cases are already here, you know, have been here for the last few years. And again, I mentioned a Zscaler, right. The reason that a Zscaler needs the on-prem version of it is because it's impossible to route all the traffic to the Big 3 Cloud, because they're still far away. Sometimes you need the presence much closer to you in order for you to get the level of the performance latency you want, right. So that's why Zscaler has, you know, so many data center of our own instead of leveraging the public Cloud, you know, for most part. However, public Cloud is still super important for Zscaler. I can tell you a story, right. You know, two years ago, you know, at the beginning of the pandemics, everyone started working from home suddenly, right. You are talking about Fortune 500 companies with 200,000 employees, suddenly having 200,000 employees working from home. Their VPN architecture is not going to support that kind of the workload, right? Even Zscaler's own architecture or the presence is not enough. So overnight we just, having so many new workloads, to support this work from home, the zero trust network for our customers, literally overnight. So it wouldn't have happened without public Cloud. So we took advantage of the public Cloud. Yet at the same time, for many, many use cases that Zscaler is paying attention to in terms of the zero trust architecture, the latency, the latency guarantee aspect, the cost is so important. So we kind of take it advantage of both. >> Yeah, definitely. >> Today you may say, hey, you know, Zscaler is one of the, not a majority of the companies in terms of the Cloud adoption or public Cloud adoption, right. But I can say that, yeah, that's because it's more infrastructure, security infrastructure. It's a little bit different for some of the communication applications, right. Why not just support everything on the public Cloud? That's doable today. However, moving forward next to 5, 10, 15 years, we expect to see Web3 kind of the use cases to grow more and more. In those kind of decentralized use cases, I can totally see that we, you know, the on-prim presence is very important. >> Yeah. One of the things we're seeing with Supercloud that we're kind of seeing clarity on is that there's a lot of seamless execution around, less friction around areas that require a PhD or hard work. And you're seeing specialty Superclouds, apps, identity data security. You're also seeing vertical clouds, Goldman Sachs doing financial applications. I'm sure there'll be some insurance. People in these verse. Building on top of the CapEx on one Cloud really fast and moving to others. So that's clearly a trend. The interesting thing I want to get your thoughts on, Howie, on an architectural basis is in Cloud, public Cloud generally, SaaS depends on IAS. So there's an interplay between SaaS and the infrastructures of service and pass as well. But SaaS and IAS, they solve a lot of the problems. You mentioned latency. How do you see the interplay of these Superclouds that utilize the SaaS IS relationship to solve technical problems? So in architecturally, that's been a tight integration on these Clouds, but now as you get more complexity with Supercloud, how do you see SaaS applications changing? >> Yeah, I view the Supercloud is actually reduced the complexity. The reason I'm saying that is, think about it in the world where you have predominantly public Cloud kind of the architecture, right? 10 years ago, AWS has probably 20 services. Now they probably have, you know, more than 1,000 services. Same thing with Azure, same thing with GCP. I mean, who can make sense out of it, right. You know, if you just consume the eyes or the Big 3 Cloud service as is. You know, you need a PhD these days to make sense all of them. So the way I think about Supercloud or where, you know it is going, is it has to provide more simplicity, a better way for people to make sense out of it, right. Cause if I'm an architecture and I have to think, hey, this is a public Cloud, this is a multi-Cloud, and by the way, certain things need to be run on the on-prem. And how do I deal with the uniform nature of it? My mind would blow up. So I need a higher level abstraction. That higher level abstraction will hide the complexity of the where it is, which vendor. It will only tell me the service level, right. You know, we always say, you know, the Cloud is like electricity. I only wanted to know is that like 110 volt or 220, 240, whatever that is. I don't really want to know more than that, right. So I want to say a key requirement for the Supercloud is it's reduced the complexity, higher level abstraction. It has to be like that. >> And operational consistencies at the bottom. Howie, we have one minute left. I want to get your thoughts. I'd like you to share what you're working on that you're excited about. It doesn't have to be with Zscaler. As you see the Supercloud trend emerging, this is the next generation Cloud, Cloud 2.0, whatever we want to call it, it's happening. It's changing. It's getting better. What are you excited about? What do you see as really key inflection point variables in this big wave? >> Yeah. One of the things I really like, what I heard from you in the past about Supercloud is a Supercloud is not just a one Cloud or one vendor. It's almost like every company should have its own Supercloud, right. You're talking about JP Morgan, Goldman Sachs of the world, that they need to have their own Supercloud. Zscaler and their security vendors, they may have their own Cloud. So I think every Fortune 500, Fortune 2,000 companies will have its own Supercloud. So I'm excited about that. So why that's important? We also say that, you know, in the next 10, 20 years, AI machine learning is going to help us a lot, right. So without Supercloud, it's very hard to do AI machine learning. 'Cause if you don't have a place that you know where the data is, and then it's pretty hard. And in the context of Supercloud, I totally foresee that the AI model will follow the data. If the data is in the cloud, it will go there. If the data is on-prem, it will go there. And then the Supercloud will hide the complexity of it. So if you ask me, my passion is leveraging AI machine learning to change the world, but Supercloud will make that easier, right. If you think about why Google, Facebook of the world, are able to leverage AI better than 99% of the rest of the world, because they figure out the Supercloud for themselves, right. And I think now it's the time for the rest of the Fortune 500, of Fortune 2,000 company to figure out its own Supercloud strategy. What is my Supercloud? I need to have my own Supercloud. Each company needs to have its own Supercloud. That's how I see it. >> Howie, always great to have you on. Thanks so much for spending the time and weighing in on this really important topic. We're going to be opening this up. It's not over. We're going to continue to watch the change as it unfolds and get an open community perspective. Thank you so much for being a great expert in our network and community. We really appreciate your time. >> Thank you for having me. >> Okay. Okay, that's it. We'll be up with more coverage here, Supercloud event, after this short break. I'm John Furrier, host of "The Cube." Thanks for watching. (upbeat music)

Published Date : Aug 7 2022

SUMMARY :

and grock the direction of Hey, John, great to be back. This is the purpose of this event. the current swing to the Cloud. and goodness of the Cloud, instead of leveraging the public Cloud, kind of the use cases and the infrastructures of You know, we always say, you know, consistencies at the bottom. of the rest of the world, Howie, always great to have you on. I'm John Furrier, host of "The Cube."

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Erik Bradley | AWS Summit New York 2022


 

>>Hello, everyone. Welcome to the cubes coverage here. New York city for AWS Amazon web services summit 2022. I'm John furrier, host of the cube with Dave ante. My co-host. We are breaking it down, getting an update on the ecosystem. As the GDP drops, inflations up gas prices up the enterprise continues to grow. We're seeing exceptional growth. We're here on the ground floor. Live at the Summit's packed house, 10,000 people. Eric Bradley's here. Chief STR at ETR, one of the premier enterprise research firms out there, partners with the cube and powers are breaking analysis that Dave does check that out as the hottest podcast in enterprise. Eric. Great to have you on the cube. Thanks for coming on. >>Thank you so much, John. I really appreciate the collaboration always. >>Yeah. Great stuff. Your data's amazing ETR folks watching check out ETR. They have a unique formula, very accurate. We love it. It's been moving the market. Congratulations. Let's talk about the market right now. This market is booming. Enterprise is the hottest thing, consumers kind of in the toilet. Okay. I said that all right, back out devices and, and, and consumer enterprise is still growing. And by the way, this first downturn, the history of the world where hyperscalers are on full pumping on all cylinders, which means they're still powering the revolution. >>Yeah, it's true. The hyperscalers were basically at this two sun system when Microsoft and an AWS first came around and everything was orbiting around it. And we're starting to see that sun cool off a little bit, but we're talking about a gradient here, right? When we say cool off, we're not talking to shutdown, it's still burning hot. That's for sure. And I can get it to some of the macro data in a minute, if that's all right. Or do you want me to go right? No, go go. Right. Yeah. So right now we just closed our most recent survey and that's macro and vendor specific. We had 1200 people talk to us on the macro side. And what we're seeing here is a cool down in spending. We originally had about 8.5% increase in budgets. That's cool down is 6.5 now, but I'll say with the doom and gloom and the headlines that we're seeing every day, 6.5% growth coming off of what we just did the last couple of years is still pretty fantastic as a backdrop. >>Okay. So you, you started to see John mentioned consumer. We saw that in Snowflake's earnings. For example, we, we certainly saw, you know, Walmart, other retailers, the FA Facebooks of the world where consumption was being dialed down, certain snowflake customers. Not necessarily, they didn't have mentioned any customers, but they were able to say, all right, we're gonna dial down, consumption this quarter, hold on until we saw some of that in snowflake results and other results. But at the same time, the rest of the industry is booming. But your data is showing softness within the fortune 500 for AWS, >>Not only AWS, but fortune 500 across the board. Okay. So going back to that larger macro data, the biggest drop in spending that we captured is fortune 500, which is surprising. But at the same time, these companies have a better purview into the economy. In general, they tend to see things further in advance. And we often remember they spend a lot of money, so they don't need to play catch up. They'll easily more easily be able to pump the brakes a little bit in the fortune 500. But to your point, when we get into the AWS data, the fortune 500 decrease seems to be hitting them a little bit more than it is Azure and GCP. I >>Mean, we're still talking about a huge business, right? >>I mean, they're catching up. I mean, Amazon has been transforming from owning the developer cloud startup cloud decade ago to really putting a dent on the enterprise as being number one cloud. And I still contest that they're number one by a long ways, but Azure kicking ass and catching up. Okay. You seeing people move to Azure, you got Charlie bell over there, Sean, by former Amazonians, Theresa Carlson, people are going over there, there there's lift over at Azure. >>There certainly is. >>Is there kinks in the arm or for AWS? There's >>A couple of kinks, but I think your point is really good. We need to take a second there. If you're talking about true pass or infrastructure is a service true cloud compute. I think AWS still is the powerhouse. And a lot of times the, the data gets a little muddied because Azure is really a hosted platform for applications. And you're not really sure where that line is drawn. And I think that's an important caveat to make, but based on the data, yes, we are seeing some kinks in the armor for AWS. Yes. Explain. So right now, a first of all caveat, 40% net score, which is our proprietary spending metric across the board. So we're not like raising any alarms here. It's still strong that said there are declines and there are declines pretty much across the board. The only spot we're not seeing a decline at all is in container, spend everything else is coming down specifically. We're seeing it come down in data analytics, data warehousing, and M I, which is a little bit of a concern because that, that rate of decline is not the same with Azure. >>Okay. So I gotta ask macro, I see the headwinds on the macro side, you pointed that out. Is there any insight into any underlying conditions that might be there on AWS or just a chronic kind of situational thing >>Right now? It seems situational. Other than that correlation between their big fortune 500, you know, audience and that being our biggest decline. The other aspect of the macro survey is we ask people, if you are planning to decline spend, how do you plan on doing it? And the number two answer is taking a look at our cloud spend and auditing it. So they're kind say, all right, you know, for the last 10 years it's been drunken, sail or spend, I >>Was gonna use that same line, you know, >>Cloud spend, just spend and we'll figure it out later, who cares? And then right now it's time to tighten the belts a little bit, >>But this is part of the allure of cloud at some point. Yeah. You, you could say, I'm gonna, I'm gonna dial it down. I'm gonna rein it in. So that's part of the reason why people go to the cloud. I want to, I wanna focus in on the data side of things and specifically the database. Let, just to give some context if, and correct me if I'm, I'm a little off here, but snowflake, which hot company, you know, on the planet, their net score was up around 80% consistently. It it's dropped down the last, you know, quarter, last survey to 60%. Yeah. So still highly, highly elevated, but that's relative to where Amazon is much larger, but you're saying they're coming down to the 40% level. Is that right? >>Yeah, they are. And I remember, you know, when I first started doing this 10 years ago, AWS at a 70%, you know, net score as well. So what's gonna happen over time is those adoptions are gonna get less and you're gonna see more flattening of spend, which ultimately is going to lower the score because we're looking for expansion rates. We wanna see adoption and increase. And when you see flattening a spend, it starts to contract a little bit. And you're right. Snowflake also was in the stratosphere that cooled off a little bit, but still, you know, very strong and AWS is coming down. I think the reason why it's so concerning is because a it's within the fortune 500 and their rate of decline is more than Azure right >>Now. Well, and, and one of the big trends you're seeing in database is this idea of converging function. In other words, bringing transaction and analytics right together at snowflake summit, they added the capability to handle transaction data, Mongo DB, which is largely mostly transactions added the capability in June to bring in analytic data. You see data bricks going from data engineering and data science now getting into snowflake space and analytics. So you're seeing that convergence Oracle is converging with my SQL heat wave and their core databases, couch base couch base is doing the same. Maria do virtually all these database companies are, are converging their platforms with the exception of AWS. AWS is still the right tool for the right job. So they've got Aurora, they've got RDS, they've got, you know, a dynamo DV, they've got red, they've got, you know, going on and on and on. And so the question everybody's asking is will that change? Will they start to sort of cross those swim lanes? We haven't seen it thus far. How is that affecting the data >>Performance? I mean, that's fantastic analysis. I think that's why we're seeing it because you have to be in the AWS ecosystem and they're really not playing nicely with others in the sandbox right now that now I will say, oh, Amazon's not playing nicely. Well, no, no. Simply to your point though, that there, the other ones are actually bringing in others at consolidating other different vendor types. And they're really not. You know, if you're in AWS, you need to stay within AWS. Now I will say their tools are fantastic. So if you do stay within AWS, they have a tool for every job they're advanced. And they're incredible. I think sometimes the complexity of their tools hurts them a little bit. Cause to your point earlier, AWS started as a developer-centric type of cloud. They have moved on to enterprise cloud and it's a little bit more business oriented, but their still roots are still DevOps friendly. And unless you're truly trained, AWS can be a little scary. >>So a common use case is I'm gonna be using Aurora for my transaction system and then I'm gonna ETL it into Redshift. Right. And, and I, now I have two data stores and I have two different sets of APIs and primitives two different teams of skills. And so that is probably causing some friction and complexity in the customer base that again, the question is, will they begin to expand some of those platforms to minimize some of that friction? >>Well, yeah, this is the question I wanted to ask on that point. So I've heard from people inside Amazon don't count out Redshift, we're making, we're catching up. I think that's my word, but they were kind of saying that right. Cuz Redshift is good, good database, but they're adding a lot more. So you got snowflake success. I think it's a little bit of a jealousy factor going on there within Redshift team, but then you got Azure synapse with the Synap product synapse. Yep. And then you got big query from Google big >>Query. Yep. >>What's the differentiation. What are you seeing for the data for the data warehouse or the data clouds that are out there for the customers? What's the data say, say to us? >>Yeah, unfortunately the data's showing that they're dropping a little bit whose day AWS is dropping a little bit now of their data products, Redshift and RDS are still the two highest of them, but they are starting to decline. Now I think one of the great data points that we have, we just closed the survey is we took a comparison of the legacy data. Now please forgive me for the word legacy. We're gonna anger a few people, but we Gotter data Oracle on-prem, we've got IBM. Some of those more legacy data warehouse type of names. When we look at our art survey takers that have them where their spend is going, that spends going to snowflake first, and then it's going to Google and then it's going to Microsoft Azure and, and AWS is actually declining in there. So when you talk about who's taking that legacy market share, it's not AWS right now. >>So legacy goes to legacy. So Microsoft, >>So, so let's work through in a little context because Redshift really was the first to take, you know, take the database to the cloud. And they did that by doing a one time license deal with par XL, which was an on-prem database. And then they re-engineered it, they did a fantastic job, but it was still engineered for on-prem. Then you along comes snowflake a couple years later and true cloud native, same thing with big query. Yep. True cloud native architecture. So they get a lot of props. Now what, what Amazon did, they took a page outta of the snowflake, for example, separating compute from storage. Now of course what's what, what Amazon did is actually not really completely separating like snowflake did they couldn't because of the architecture, they created a tearing system that you could dial down the compute. So little nuances like that. I understand. But at the end of the day, what we're seeing from snowflake is the gathering of an ecosystem in this true data cloud, bringing in different data types, they got to the public markets, data bricks was not able to get to the public markets. Yeah. And think is, is struggling >>And a 25 billion evaluation. >>Right. And so that's, that's gonna be dialed down, struggling somewhat from a go to market standpoint where snowflake has no troubles from a go to market. They are the masters at go to market. And so now they've got momentum. We talked to Frank sluman at the snowflake. He basically said, I'm not taking the foot off the gas, no way. Yeah. We, few of our large, you know, consumer customers dialed things down, but we're going balls to the >>Wall. Well, if you look at their show before you get in the numbers, you look at the two shows. Snowflake had their summit in person in Vegas. Data bricks has had their show in San Francisco. And if you compare the two shows, it's clear, who's winning snowflake is blew away from a, from a market standpoint. And we were at snowflake, but we weren't at data bricks, but there was really nothing online. I heard from sources that it was like less than 3000 people. So >>Snowflake was 1900 people in 2019, nearly 10,000. Yeah. In 2020, >>It's gonna be fun to sort of track that as a, as an odd caveat to say, okay, let's see what that growth is. Because in fairness, data, bricks, you know, a little bit younger, Snowflake's had a couple more years. So I'd be curious to see where they are. Their, their Lakehouse paradigm is interesting. >>Yeah. And I think it's >>And their product first company, yes. Their go to market might be a little bit weak from our analysis, but that, but they'll figure it out. >>CEO's pretty smart. But I think it's worth pointing out. It's like two different philosophies, right? It is. Snowflake is come into our data cloud. That's their proprietary environment. They're the, they think of the iPhone, right? End to end. We, we guarantee it's all gonna work. And we're in control. Snowflake is like, Hey, open source, no, bring in data bricks. I mean data bricks, open source, bring in this tool that too, now you are seeing snowflake capitulate a little bit. They announce, for instance, Apache iceberg support at their, at the snowflake summit. So they're tipping their cap to open source. But at the end of the day, they're gonna market and sell the fact that it's gonna run better in native snowflake. Whereas data bricks, they're coming at it from much more of an open source, a mantra. So that's gonna, you know, we'll see who look at, you had windows and you had apple, >>You got, they both want, you got Cal and you got Stanford. >>They both >>Consider, I don't think it's actually there yet. I, I find the more interesting dynamic right now is between AWS and snowflake. It's really a fun tit for tat, right? I mean, AWS has the S three and then, you know, snowflake comes right on top of it and announces R two, we're gonna do one letter, one number better than you. They just seem to have this really interesting dynamic. And I, and it is SLT and no one's betting against him. I mean, this guy's fantastic. So, and he hasn't used his war chest yet. He's still sitting on all that money that he raised to your point, that data bricks five, their timing just was a little off >>5 billion in >>Capital when Slootman hasn't used that money yet. So what's he gonna do? What can he do when he turns that on? He finds the right. >>They're making some acquisitions. They did the stream lit acquisitions stream. >>Fantastic >>Problem. With data bricks, their valuation is underwater. Yes. So they're recruiting and their MNAs. Yes. In the toilet, they cannot make the moves because they don't have the currency until they refactor the multiple, let the, this market settle. I I'm, I'm really nervous that they have to over factor the >>Valuation. Having said that to your point, Eric, the lake house architecture is definitely gaining traction. When you talk to practitioners, they're all saying, yeah, we're building data lakes, we're building lake houses. You know, it's a much, much smaller market than the enterprise data warehouse. But nonetheless, when you talk to practitioners that are actually doing things like self serve data, they're building data lakes and you know, snow. I mean, data bricks is right there. And as a clear leader in, in ML and AI and they're ahead of snowflake, right. >>And I was gonna say, that's the thing with data bricks. You know, you're getting that analytics at M I built into it. >>You know, what's ironic is I remember talking to Matt Carroll, who's CEO of auDA like four or five years ago. He came into the office in ma bro. And we were in temporary space and we were talking about how there's this new workload emerging, which combines AWS for cloud infrastructure, snowflake for the simple data warehouse and data bricks for the ML AI, and then all now all of a sudden you see data bricks yeah. And snowflake going at it. I think, you know, to your point about the competition between AWS and snowflake, here's what I think, I think the Redshift team is, you know, doesn't like snowflake, right. But I think the EC two team loves it. Loves it. Exactly. So, so I think snowflake is driving a lot of, >>Yeah. To John's point, there is plenty to go around. And I think I saw just the other day, I saw somebody say less than 40% of true global 2000 organizations believe that they're at real time data analytics right now. They're not really there yet. Yeah. Think about how much runway is left and how many tools you need to get to real time streaming use cases. It's complex. It's not easy. >>It's gonna be a product value market to me, snowflake in data bricks. They're not going away. Right. They're winning architectures. Yeah. In the cloud, what data bricks did would spark and took over the Haddo market. Yeah. To your point. Now that big data, market's got two players, in my opinion, snow flicking data, bricks converging. Well, Redshift is sitting there behind the curtain, their wild card. Yeah. They're wild card, Dave. >>Okay. I'm gonna give one more wild card, which is the edge. Sure. Okay. And that's something that when you talk about real time analytics and AI referencing at the edge, there aren't a lot of database companies in a position to do that. You know, Amazon trying to put outposts out there. I think it runs RDS. I don't think it runs any other database. Right. Snowflake really doesn't have a strong edge strategy when I'm talking the far edge, the tiny edge. >>I think, I think that's gonna be HPE or Dell's gonna own the outpost market. >>I think you're right. I'll come back to that. Couch base is an interesting company to watch with Capella Mongo. DB really doesn't have a far edge strategy at this point, but couch base does. And that's one to watch. They're doing some really interesting things there. And I think >>That, but they have to leapfrog bongo in my >>Opinion. Yeah. But there's a new architecture emerging at the edge and it's gonna take a number of years to develop, but it could eventually from an economic standpoint, seep back into the enterprise arm base, low end, take a look at what couch base is >>Doing. They hired an Amazon guard system. They have to leapfrog though. They need to, they can't incrementally who's they who >>Couch >>Base needs to needs to make a big move in >>Leap frog. Well, think they're trying to, that's what Capella is all about was not only, you know, their version of Atlas bringing to the cloud couch base, but it's also stretching it out to the edge and bringing converged database analytics >>Real quick on the numbers. Any data on CloudFlare, >>I was, I've been sitting here trying to get the word CloudFlare out my mouth the whole time you guys were talking, >>Is this another that's innovated in the ecosystem. So >>Platform, it was really simple for them early on, right? They're gonna get that edge network out there and they're gonna steal share from Akamai. Then they started doing exactly what Akamai did. We're gonna start rolling out some security. Their security is fantastic. Maybe some practitioners are saying a little bit too much, cuz they're not focused on one thing or another, but they are doing extremely well. And now they're out there in the cloud as well. You >>Got S3 compare. They got two, they got an S3 competitor. >>Exactly. So when I'm listening to you guys talk about, you know, a, a couch base I'm like, wow, those two would just be an absolute fantastic, you know, combination between the two of them. You mean >>CloudFlare >>Couch base. Yeah. >>I mean you got S3 alternative, right? You got a Mongo alternative basically in my >>Opinion. And you're going and you got the edge and you got the edge >>Network with security security, interesting dynamic. This brings up the super cloud date. I wanna talk about Supercloud because we're seeing a trend on we're reporting this since last year that basically people don't have to spend the CapEx to be cloud scale. And you're seeing Amazon enable that, but snowflake has become a super cloud. They're on AWS. Now they're on Azure. Why not tan expansion expand the market? Why not get that? And then it'll be on Google next, all these marketplaces. So the emergence of this super cloud, and then the ability to make that across a substrate across multiple clouds is a strategy we're seeing. What do you, what do you think? >>Well, honestly, I'm gonna be really Frank here. The, everything I know about the super cloud I know from this guy. So I've been following his lead on this and I'm looking forward to you guys doing that conference and that summit coming up from a data perspective. I think what you're saying is spot on though, cuz those are the areas we're seeing expansion in without a doubt. >>I think, you know, when you talk about things like super cloud and you talk about things like metaverse, there's, there's a, there, there look every 15 or 20 years or so this industry reinvents itself and a new disruption comes out and you've got the internet, you've got the cloud, you've got an AI and VR layer. You've got, you've got machine intelligence. You've got now gaming. There's a new matrix, emerging, super cloud. Metaverse there's something happening out there here. That's not just your, your father's SAS or is or pass. Well, >>No, it's also the spend too. Right? So if I'm a company like say capital one or Goldman Sachs, my it spend has traditionally been massive every year. Yes. It's basically like tons of CapEx comes the cloud. It's an operating expense. Wait a minute, Amazon has all the CapEx. So I'm not gonna dial down my budget. I want a competitive advantage. So next thing they know they have a super cloud by default because they just pivoted their, it spend into new capabilities that they then can sell to the market in FinTech makes total sense. >>Right? They're building out a digital platform >>That would, that was not possible. Pre-cloud >>No, it wasn't cause you weren't gonna go put all that money into CapEx expenditure to build that out. Not knowing whether or not the market was there, but the scalability, the ability to spend, reduce and be flexible with it really changes that paradigm entire. >>So we're looking at this market now thinking about, okay, it might be Greenfield in every vertical. It might have a power law where you have a head of the long tail. That's a player like a capital one, an insurance. It could be Liberty mutual or mass mutual that has so much it and capital that they're now gonna scale it into a super cloud >>And they have data >>And they have the data tools >>And the tools. And they're gonna bring that to their constituents. Yes, yes. And scale it using >>Cloud. So that means they can then service the entire vertical as a service provider. >>And the industry cloud is becoming bigger and bigger and bigger. I mean, that's really a way that people are delivering to market. So >>Remember in the early days of cloud, all the banks thought they could build their own cloud. Yeah. Yep. Well actually it's come full circle. They're like, we can actually build a cloud on top of the cloud. >>Right. And by the way, they can have a private cloud in their super cloud. Exactly. >>And you know, it's interesting cause we're talking about financial services insurance, all the people we know spend money in our macro survey. Do you know the, the sector that's spending the most right now? It's gonna shock you energy utilities. Oh yeah. I was gonna, the energy utilities industry right now is the one spending the most money I saw largely cuz they're playing ketchup. But also because they don't have these type of things for their consumers, they need the consumer app. They need to be able to do that delivery. They need to be able to do metrics. And they're the they're, they're the one spending right >>Now it's an arms race, but the, the vector shifts to value creation. So >>It's it just goes back to your post when it was a 2012, the trillion dollar baby. Yeah. It's a multi-trillion dollar baby that they, >>The world was going my chassis post on Forbes, headline trillion dollar baby 2012. You know, I should add it's happening. That's >>On the end. Yeah, exactly. >>Trillions of babies, Eric. Great to have you on the key. >>Thank you so much guys. >>Great to bring the data. Thanks for sharing. Check out ETR. If you're into the enterprise, want to know what's going on. They have a unique approach, very accurate in their survey data. They got a great market basket of, of, of, of, of data questions and people and community. Check it out. Thanks for coming on and sharing with. >>Thank you guys. Always enjoy. >>We'll be back with more coverage here in the cube in New York city live at summit 22. I'm John fur with Dave ante. We'll be right back.

Published Date : Jul 12 2022

SUMMARY :

Great to have you on the cube. I really appreciate the collaboration always. And by the way, And I can get it to some of the macro data in a minute, if that's all right. For example, we, we certainly saw, you know, Walmart, other retailers, So going back to that larger macro data, You seeing people move to Azure, you got Charlie bell over there, And I think that's an important caveat to make, Is there any insight into any underlying conditions that might be there on AWS And the number two answer the last, you know, quarter, last survey to 60%. And I remember, you know, when I first started doing this 10 years ago, AWS at a 70%, And so the question everybody's asking is will that change? I think that's why we're seeing it because you have to be in And so that is probably causing some friction and complexity in the customer base that again, And then you got big query from Google big Yep. What's the data say, say to us? So when you talk about who's taking that legacy market So legacy goes to legacy. But at the end of the day, what we're seeing from snowflake They are the masters at go to market. And if you compare the two shows, it's clear, who's winning snowflake is blew away Yeah. So I'd be curious to see where they are. And their product first company, yes. I mean data bricks, open source, bring in this tool that too, now you are seeing snowflake capitulate I mean, AWS has the S three and then, He finds the right. They did the stream lit acquisitions stream. I'm really nervous that they have to over factor the they're building data lakes and you know, snow. And I was gonna say, that's the thing with data bricks. I think, you know, to your point about the competition between AWS And I think I saw just the other day, In the cloud, what data bricks did would spark And that's something that when you talk about real time And I think but it could eventually from an economic standpoint, seep back into the enterprise arm base, They have to leapfrog though. Well, think they're trying to, that's what Capella is all about was not only, you know, Real quick on the numbers. So And now they're out there in the cloud as well. They got two, they got an S3 competitor. wow, those two would just be an absolute fantastic, you know, combination between the two of them. Yeah. And you're going and you got the edge and you got the edge So the emergence of this super So I've been following his lead on this and I'm looking forward to you guys doing that conference and that summit coming up from a I think, you know, when you talk about things like super cloud and you talk about things like metaverse, Wait a minute, Amazon has all the CapEx. No, it wasn't cause you weren't gonna go put all that money into CapEx expenditure to build that out. It might have a power law where you have a head of the long tail. And they're gonna bring that to their constituents. So that means they can then service the entire vertical as a service provider. And the industry cloud is becoming bigger and bigger and bigger. Remember in the early days of cloud, all the banks thought they could build their own cloud. And by the way, they can have a private cloud in their super cloud. And you know, it's interesting cause we're talking about financial services insurance, all the people we know spend money in So It's it just goes back to your post when it was a 2012, the trillion dollar baby. You know, I should add it's happening. On the end. Great to bring the data. Thank you guys. We'll be back with more coverage here in the cube in New York city live at summit 22.

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Kevin Farley, MariaDB | AWS Summit New York 2022


 

>>Good morning from New York city, Lisa Martin and John furrier with the cube. We are at AWS summit NYC. This is a series of summits this year, about 15 summit globally. And we're excited to be here, John, with about 10,000 folks. >>It's crowded. New York is packed big showing here at 80 of us summit. So it's super exciting, >>Super exciting. Just a little bit before the keynote. And we have our first guest, Kevin Farley joins us the director of strategic alliances at Maria DB. Kevin, welcome to >>The program. Thank you very much. Appreciate you guys having us. >>So all of us out from California to NYC. Yeah, lots of eyes. We got keynote with Warner Vogels coming up. We should be some good news, hopefully. Yep. But talk to us about Maria DB Skys cloud native version released a couple years ago. What's going on? >>Yeah, well, it's, you know, Skys SQL for us is really a be on the future. I think when we think about like the company's real mission is it's just creating a database for everyone. It's it's any cloud, any scale, um, any size of performance and really making sure that we're able to deliver on something that really kind of takes advantage of everything we've done in the market to date. If you think about it, there's not very many startups that have a billion downloads and 75% of the fortune 500 already using our service. So what we're really thinking about is how do we bridge that gap? How do we create a natural path for all of these customers? And if you think about not just Maria DB, but anyone else using the sequel query language, all the, my people, what I think most Andy jazzy TK, anyone says, you know, it's about 10% of the market currently is in the clouds. That's 90% of a total addressable market that hasn't done it yet. So creating cloud modernization for us, I think is just a huge opportunity. Do >>You guys have a great history with AWS? I want to just step back, you mentioned some stats on, on success. Can you scope the size and track record of Maria DB for us real quick and set the table? Because I think there's a bigger picture going on that we've been tracking for the past 13 years we address is the role of the database has always been one of those things where they didn't believe a one database fits all things, right. You guys have been part of that track record scope, the size and scale of Maria DB, the usage, the use cases and some of the successes. >>Yeah. I mean, like I said, some of the stats are already threw out there. So, you know, it is pervasive, I think is the best way to put it. I think what you look at what the database market really became is very siloed. Right? I think there was a lot of unique solutions that were built and delivered that had promise, but they also had compromise. And I think once you look at the landscape of a lot of fortune 500 companies, they have probably 10 to 15 different database solutions, right? And they're all doing unique things. They're difficult to manage. They're very costly. So what Marie DB is always kind of focused on is how do we continue to build more and more functionality into the database itself and allow that to be a single source of truth where application developers can seamlessly integrate applications. >>So then the theme of this event in New York city, which is scale dot, dot, dot, anything must align quite well with Maria and your >>Objectives. I mean, honestly, I think when I think of the problems that most database, um, companies, um, face customers, I should say it, it really comes down to performance and scale. Most of them like Maria DB, like you said, they it's like the car, you know, and love you've been driving it for years. You're an expert at it. It works great, but it doesn't have enough range. It doesn't go fast enough. It's hitting walls. That modern data requirements are just breaking. So scale for me is the favorite thing to talk about because what we launched as MariaDB expand, which is a plugable storage engine that is integrated into Skye, and it really gives you dynamic scale. So you can scale in, you can scale out, it's not costly compute to try to get for seasonality. So you can make your black Friday numbers. It's really about the dexterity to be able to come in and out as you need in a share, nothing architecture with full failover sale healing, high availability, married to the cloud for full cloud scale. And that's really the beauty of the AWS partnership. >>Can you elaborate a bit more on the partnership? How long have you guys been partners? Where is it now anything exciting coming out? >>Yeah, it it's, it's actually been a wonderful ride. They've really invested from the very beginning we went for the satisfactory. So they really brought a lot of resources to bear. And I think if you're looking at why it works, um, it's probably two things. I think the number one thing is that we share one of the core tenants and it's customer obsession in a, in a, in an environment where there is co-opetition right. You have to find paths for how do you get the best thing for the customer? And the second is pretty obvious, but if you look at any major cloud, their number one priority is getting large mission critical workloads into their cloud because the revenue is exponential on the backside. So what do we own? Large mission critical workloads. So if you marry that objective with AWS, the partnership is absolutely perfect for driving true revenue, growth scale, and, and revenue across, across both entities in the partner ecosystem. >>So Kevin talk about the, um, the hybrid strategy, cuz you're seeing cloud operations. Yep. Go hybrid. Amazon announced AWS announced outpost like four years ago. Right now edge is super hot. Yeah. So you're seeing like most of the enterprise is saying mm-hmm <affirmative> okay. Love cloud love the cloud database, but I got the on-prem hybrid cloud operations. Right. So it's not just proprietary operations. It's cloud ops. Yeah. How do you guys fit into that? What's the story. >>We, we actually it's. I mean, there's, there's all these new deliverables outposts, you know, come out with a promise. What we have is a reality right now, um, one of the largest, um, networking companies, which I can't mention yet publicly, um, we want a really big sky SQL deal, but what they had manufacturing plants, they needed to have on-prem deployments. So Maria DB naturally syncs with sky SQL. It's the same technology. It works in perfect harmony. So we really already deliver on the promise of hybrid, but of course there's a lot more we can grow in that area. And certainly thinking about app posts and other solutions, um, is definitely on the, the longer term roadmap of what could make sense for in our customer. What, >>What are some of the latest things that, that you guys are doing now that you weren't doing a few years ago that customers should know about the audience should know about? >>I mean, I think the game changer, we're always innovating. I mean, when you're the company that writes the code owns the code, you know, we can do hot fixes, we can do security patches, we can always do the things that give you real time access to what you need. But I think the game changer is what I mentioned a little bit earlier. And I think it's really the, the holy grail of the cloud. It's like, how can we take the, the SQL query language, which is well over 50% of the open source market. Right. And how do we convert that seamlessly into the cloud? How do we help you modernize on that journey? And expand gives you the ability to say, I can be the small, I can be a small startup. I got my C round. I don't wanna manage databases. I can use the exact same service as the largest fortune 100 company that has massive global scale and needs to be able to drive that across globe. Yeah. So I think that's the beauty is that it's really a democratization of the database, >>At least that, you know, we've been covering the big data space for 10 years. Remember all those different conversations had do those days and oh, they have big data and right. But then it's like too hard to set up. Then you had that kind of period where you saw a spark and data lakes emerge. Yeah. Then you, now it almost seems, seems like now more than ever, there's a data revolutions back. Right. It was almost like a lull in the, in, in the, in the market a little bit. Yeah. I'm gonna democratize data science right now. You got data. So now it just seems to be an explosion at that level. What's your analysis on that? Because you you've been in, in, in the weeds and in the, in the, in this market for 10 years. Yeah. And nothing really changed. It's just now it's more ready. Yeah. I think what's your observation. Why >>Is that? I think that's a really good question. And I love it cuz I mean, what the promise of things like could do and net new technologies sort of, it was always out there, but it required this whole net new lift and how do I do it? How do I manage it? How do I optimize it? The beauty of what we can do with Maria DB is that sky SQLs, which you already know and love. Right? And now we can Del you can deliver a data lake on S3, right? You can pull that data. And we also have the ability to do both analytical data and transactional data from the same database. So you can write applications that can pull column, store data up into, um, your application, but you can also have all of your asset transactions, which are absolutely required for all of your mission critical business. So I think that we're seeing more and more adoption. You've seen other companies start to talk about bringing the different elements in, but we're the only ones that really >>Do it and SQL standardizing that front end. Yeah. Even better than ever before. All the stuff under the covers is all being connected. >>That's the awesome part is right. Is you're literally doing what you already know how to do, but you blow it out on the back end, married to the cloud. And that I think is the real revolution of what makes usability real in the data space. And I think that's what was always the problem before >>When you're in partner conversations, you mentioned co-opetition. Yeah. <laugh> so I think when you're in partner conversations and customer conversations, there is a lot of the, the there's a lot of competition out there. Absolutely. Everyone's got their own key messages. What are the key differentiators that you're saying AWS Marie to be together better? And here's why, >>Yeah. I, I think that certainly you, you start with the global footprint of AWS, right? So what we rely on the most is having the ability to truly deal with global customers in availability zones, they're gonna optimize performance from them. But then when we look at what we do that really changes the game, it comes down to scale and performance. We actually just ran, um, a suspense test against cockroach that also does distributed sequel. Absolutely. You know, the results were off the chart. So we went public and said, we have an open challenge. Anyone that wants to try to beat, um, expand and Skye will we'll if you can, we'll put $25,000 towards charity. So we really are putting our money where our mouth is on that challenge. So we believe the performance cuz we've seen it and we know it's real, but then it's really always about data scale. Modern data requirements are breaking the mold of charting. They're breaking the mold of all these bandaids that people have put in these traditional services. And we give them future. We, we feature proof their investments, so they can say, Hey, I can start here. But if I end up being a startup that becomes Airbnb, I'm already built to blow it out on the back end. I can already use what I have. >>Speaking of startups, being the next Airbnb. If you look at behind us here, you can see, this is a really packed event in New York city events are back, but the ecosystem here is even flourishing. So Dave and I and Lisa were observing that we're still kind of in a growth mode, big time. So yeah, there's some market forces headwinds for the big unicorns, overfunded, you know, public companies, maybe the valuations are a little bit off, but there's still a surge of new innovations, new companies coming out of this. Um, and it's all around data and scale. It's all around new names. We've never heard of. Absolutely. What's your take on >>Reaction? Well, actually another awesome segues cuz in addition to the public clouds, I manage the ecosystem. And one of the things that we've really been focused on with Skys SQL is making it accessible API accessible. So if you're a company that has a huge Marine DB footprint change data capture might be the most important thing for you to say, we wanna do this, but we want you to stay in sync with our environments. Um, things like monitoring, things like BI, all of these are ecosystem plays and current partners that we have, um, that we really think about how do you holistically look at not only the database and what it can do, but how does it deliver value to different segments of your customer base or just your employee base that are using that stuff? So I think that's huge for us. >>Well, you know, one of the things that we talk often about is that every company, these days, regardless of industry, has to be a data company. Yep. You've gotta be able to access the data glean insights from an act on it quickly, whether it's manufacturing, retail, healthcare, are there any verticals in where Maria DB really excels? >>Um, so certainly we Excel in areas like financial services is huge DBS bank. Um, in APAC, one of our biggest customers, also one of the largest Oracle migrations, probably the, that we've ever done. A lot of people trying to get off Oracle, we make it seamless to get into Maria DB. Um, you can think about Samsung cloud and another, their entire consumer cloud is built on Maria DB, why it's integrated with expand right seasonality. So there's customers like that that really bring it home for us as far as ServiceNow tech sector. Right? So these are all different ones, but I think we're really strong in those >>Areas. So this brings up a good point. Dave and I a coined a term called super cloud at reinvent and Lisa and Dave were at multiple events we're together at events. And so a lot of people are getting behind this cuz it's multi-cloud sounds like something's broken. Yes. But so we call it super cloud because customers are building on top of ecosystems like Maria DB and others. Yeah. Not just AWS SOS does all the CapEx absolutely provide the value. So now people are having this new super cloud moment. We' saying we can get all the benefits of cloud scale mm-hmm <affirmative> without actually being a cloud. Right. So this is where the next gen layer comes. What's your reaction to, to super cloud. Do you think it's a thing? >>Well, I think it's a thing in the sense, from our perspective as an ISV, we're, we're laser focused on making sure that we support any cloud and we have a truly multicloud cloud platform. But the beauty of that as well is from a single UI, you're able to deploy databases in different clouds underneath that you're not looking at so you can have performance proximity, but you're still driving it through the same Skys UI. So for us it's, it's unequivocally true. Got it. And I think it's only ISVs like Maria DB that can deliver on that value because >>You're enabling, >>We're enabling it. Right. We partner, we build on top of everything. Right. So we can access everything underneath >>And they can then build on top of you. >>Sure, exactly. And that's exactly where it goes. Right? Yeah. So that, I think in that sense, the super cloud is actually already somewhat real. >>It's interesting. You look at the old, it spend, you take a big company. I won't say a name, but a leader in a, a vertical, they have such a big spend. Now they can leverage that spend in with the super cloud model. They then could become a service provider in the vertical. Absolutely capital one S doing it. Yeah. You're seeing, um, Goldman Sachs doing it. They have the power on the spend that they're leveraging in for their business and servicing their vertical and the smaller players. Do you see that trend? >>Well, I think that's the reality is that everyone is getting this place where if you're talking about sort of this broader super concept, you're talking about global scale, right? That's if in order to deliver a backbone that can service that model, you have to have the right data structure and the right database footprint to be able to scale. And I think that's what they all need to be able to do. And that's what we're really well positioned with Skys >>To enable companies, as we talked about a minute ago to truly become data companies. Yeah. And to be competitive and to scale on their own, where are your customer conversations? Are they at the C-suite level? Has that changed in the last couple of years? >>Uh, that's actually a really great way to state that question because I think you would've traditionally probably talked more to, um, the DBAs, right? They're the people that are having headaches. They're having problems. They're, they're trying to solve. We see a lot of developers now tons, right? They're thinking about, I have this, I have this new thing that I need to do to deliver this new application. And here's the requirements and the current model's broken. It doesn't optimize that it's a lot of work and it's hard to manage. So I think that we're in a great position to be able to take that to that next phase and deliver. And then of course, as you get deeper in with AWS, you're talking about, you know, CIO level, CISO level, they're they need to understand how do you fit into our larger paradigm. And many of these guys have, you know, hundreds of million dollar commits with AWS. So they think of their investment in the sense of the cloud stack. And we're part of that cloud stack, just like AWS services. So those conversations continue to happen certainly with our larger customers, cuz it truly is married. >>It is. And they continue to evolve. Kevin, thank you so much >>For joining. You're welcome. Great, >>John and me talking about what's going on with Maria >>D. Thank you, John. Thank you, Lisa. On behalf of Maria B, it was wonderful. Really >>Appreciate it. Fantastic as well for John furrier. I'm Lisa Martin. You're watching the cube live from New York city at AWS summit NYC, John and I we're back with our next guest in a minute.

Published Date : Jul 12 2022

SUMMARY :

And we're excited to be here, John, with about 10,000 folks. So it's super exciting, And we have our first guest, Kevin Farley joins us the director of strategic alliances Appreciate you guys having us. So all of us out from California to NYC. And if you think about not just Maria I want to just step back, you mentioned some stats on, And I think once you look at the landscape of a lot of fortune 500 companies, So scale for me is the favorite thing to talk about because what we launched as MariaDB expand, And I think if you're looking at why it works, How do you guys fit into that? I mean, there's, there's all these new deliverables outposts, you know, the code owns the code, you know, we can do hot fixes, we can do security patches, we can always do the things So now it just seems to be an explosion at And now we can Del you can deliver a data lake on S3, right? All the stuff under the covers is all being connected. And I think that's what was always the problem before What are the key differentiators that you're saying AWS So we believe the performance cuz we've seen it and we know it's real, but then it's really always about If you look at behind us here, you can see, data capture might be the most important thing for you to say, we wanna do this, but we want you to stay Well, you know, one of the things that we talk often about is that every company, these days, regardless of industry, you can think about Samsung cloud and another, their entire consumer cloud is built on Maria DB, Do you think it's a thing? And I think it's only ISVs like Maria DB that can deliver on that value because So we can access everything underneath So that, I think in that sense, the super cloud is actually already You look at the old, it spend, you take a big company. And I think that's what they all need to be able to do. And to be competitive and to scale on their own, where are your customer conversations? And then of course, as you get deeper in with AWS, you're talking about, And they continue to evolve. You're welcome. On behalf of Maria B, it was wonderful. New York city at AWS summit NYC, John and I we're back with our next guest in

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Justin Murrill, AMD & John Frey, HPE | HPE Discover 2022


 

>> Announcer: theCUBE presents HPE Discover 2022. Brought to you by HPE. >> Okay, we're back here at HPE Discover 2022, theCUBE's continuous coverage. This is day two, Dave Vellante with John Furrier. John Frey's here. He is the chief technologist for sustainable transformation at Hewlett Packard Enterprise and Justin Murrill who's the director of corporate responsibility for AMD. Guys, welcome to theCUBE. Good to see you. >> Thank you. >> Thank you. It's great to be here. >> So again, I remember the days where, you know, CIOs didn't really care about the power budget. They didn't pay the power budget. You had, you know, facilities over here, IT over here and they didn't talk to each other. That's changed. Why is there so much discussion around sustainable IT today? >> It's exciting to see how much it's up leveled, as you say. I think there are a couple different trends happening but mainly, you know, the IT teams and IT leaders that are making decisions are seeing to your point how their decisions are affecting enterprise level, greenhouse gas emission reduction goals. So that connection is becoming very clear. Everything from the server processor to beyond it, those decisions have a key role. And importantly we're seeing, you know, 60% of the Fortune 500 now have climate or energy efficiency related goals. So there's a perfect storm of sorts happening where more companies setting goals, IT decision makers looking particularly at the data center because as the computational heart of an organization, it has a wealth of opportunity from an energy and a mission savings perspective. >> I'm surprised it's only 60%. I mean, that number really shocked me. So it's got to be a 100% within the next couple of years here. I would think, I mean, it's not trivial, right? You've got responsibilities in terms of reporting and you can't just mail it in, right? >> Yeah, absolutely. So there's a lot more disclosure happening but the goal setting is really upleveling as well. >> And the metrics involved too. Can you just scope the scale and challenge of like getting the right metrics, not when you have the goals. Does that factor in, how do you see there? What's your commentary on that? >> Yeah, I think there's, the aperture is continuing to open as metrics go, so to speak. So from an operations perspective, companies are reporting on what's referred to as scope one and scope two. And scope two is the big one from electricity, right? And then scope three is everything else. That's the supply chain and the outside of that. So a lot of implications there as well from IT decision making. >> Is there a business case for sustainable IT? I mean, you're probably not going to lower the power budget, right? But is it just, hey, it's the right thing to do. We have to do it, it's good for the brand. It'll allow us to attract people or is there a a more of a rich business case? >> So there really is a business case even just within inside the data center walls, for example. There's inefficiencies that are inherent in many of these data centers. There's really low utilization levels as well. And by reducing over provisioning and increasing utilization, there's real money to be saved in terms of equipment costs, maintenance agreement costs, software licensing costs. So actually the power consumption and the environmental piece is an added benefit but it's not the main reason. So we actually had IDC do a survey for us last year and we asked IT executives, 500 senior IT executives, were you implementing sustainable IT programs and why? My guess initially was about 40% of them would say yes. Actually the number was 96% of them. And when we asked them why they fell into three categories. The digital leaders, those that are the early adopters moving the quickest. They said we do it to attract and retain institutional investors. They've been hearing from their boards. They've been hearing from their investor relations teams and investors are starting to ask and even in a couple cases board seats are becoming contentious based on the environmental perspective of the person being nominated. This digital mainstream, the folks in the middle about 80% of the total pie, they're doing it to attract and retain customers because customers are asking them about their sustainable IT programs. If they're a non-manufacturing customer, their data center consumption is probably the largest part of their company. It's also by the way usually the most expensive real estate the company owns. So customers are asking and customers are not only asking, do you have basic programs in place? But they're asking, what are your goals to Justin's point? The customers are starting to realize that carbon goals have been vaguely defined historically. So they're asking for specificity, they're asking for transparency and by the way the science-based target initiative recently released their requirements for net zero science-based targets. And that requires significant reduction to your point before you start considering renewable energy in that balance. The third reason those digital followers, that slowest group or folks that are in industries that move the slowest, they said they were doing this to attract and retain employees. Because they recognize the data scientists, the computer science, computer engineering students that they're trying to attract want to work at a company where they can see how what they do directly contributes to purpose. And they vote with their feet. If they come on and they can't make that connection pretty quickly or if they spend a lot of their time chasing down inefficiencies in a technology infrastructure, they're not going to stay there very long. >> I mean, the mission-driven organization is definitely an employee factor. People are interested in that. The work for company is responsible, doing the right thing but that business case is interesting because I think there's recognition now more than ever before. You think you're right on. It used to be kind of like mailed it in before. Okay, we're doing some stuff. Now it's like, we all have to do it. And it's a board issue. It's a financing issue. It might be a filing issue as you guys mentioned. So that's all great. So I got to ask how you guys specifically are working together, AMD and HPE. What are you guys doing to make it more efficient? And then I'll see with Cloud and Cloud scale, there's more servers being shipped now than ever before. And more devices at the edge. What are you guys doing together specifically? >> Yeah, we've been working together, AMD and HPE on advancing sustainability for many years. I've had the opportunity to working directly with John for many years and I've learned a lot from him and your team. It's fantastic to see all the developments here. I mean, so most recently the top 500 and the green 500 list of supercomputers came out. And at the top of that list is AMD HPE systems. And it shows kind of the pinnacle of what can be possible for other data centers looking to modernize and scale. So the number one system, the fastest system in the world and the most energy efficient system in the world, the Frontier supercomputer has AMD HPE technology in it. And it just passed the exit scale barrier. I mean, I'm still just blown away by this. A billion, billion calculations per second. It's just amazing. And the research is doing around clean energy, alternative energy sources, scientific research is really exciting. So there's that. The other system that really jumps out is the LUMI system, the number three system because it's a 100% powered by renewable energy. So not only that, it takes the heat and it channels it to a nearby town and covers 20% of that town's heating needs thereby avoiding 12,400 metric tons of carbon emissions. So this system is carbon negative, right? And you just go down the list. I mean, AMD is in the top eight out of 10 most green... >> Rewind that second. So you have the heat and the power shifting to a town? >> Yes, the LUMI supercomputer has the heat from the system to an nearby town. It's like a closed loop, the idea of circular economy but with energy. And it takes that waste and it makes it an input, a resource. >> But this is the kind of innovation that's going on, right? This is the scale, this is where scale and efficiency kind of come together. That's huge. Where's that going to go? What's your perspective on where that goes next because that's a blueprint that could be replicated. >> You bet. So I think we're going to continue to see overall power consumption go up at the system level. But performance per wat is climbing much more dramatically. So I think that's going to continue to scale. It's going to require a new cooling technology. So direct liquid cooling is becoming more and more in use and customers really interested in that. There's shifting from industry standard architectures to lower end high performance computer architectures to get direct liquid cooling, higher core processors and get the performance they want in a smaller footprint. And at the same time, they're really thinking about how do we operate the infrastructure as a system not as individual piece parts. And one of the things that Frontier and LUMI do so well is they were designed from the start as a system, not as piece parts making up the system. So I think that happens. The other thing that's really critical is no one company is going to solve these challenges ourself. So one of the things I love about our partnership with AMD is we look at each other's sustainability goals before we launch 'em. We say, well, how can we help? One of AMD's goals that I'll let Justin talk about came about because HPE at the time of separation laid a really aggressive product, energy efficiency goal out, said but we're not sure how we're going to make this. And AMD said we can help. So that collaboration, we critique each other's programs, we push each other, but we work together. I like to say partnership is leadership in this. >> Well, that's a nuance point. Before you get to that solution there Justin, this system's thinking is really important. You're seeing that now with Cloud. Some of the things that GreenLake and the systems are pointing out, this holistic systems' thinking is applied to partnerships, not just the company. >> Yep. >> This is a really nuanced point but we're seeing that more and more. >> Yeah, absolutely. In fact, Justin mentioned the heat reuse, same way with the national renewable energy lab. They actually did snow removal and building heating with the heat reuse. So if you're designing for example, a liquid cold system from the start, how do you make it a symbiotic relationship? There's more and more interest in co-locating data centers and greenhouses in colder environments for example. Because the principle of the circular economy is nothing is waste. So if you think it's waste or you think it's a byproduct, think about how can that be an input to something else. >> Right, so you might put a data center so you can use ambient cooling or in somewhere in the Columbia River so you can, you know, take advantage of, you know, renewable energy. What are some goals that you guys can share with us? >> So we've got some great momentum and a track record coming off of, going back to 2014, we set a 25 by 20 goal to improve the energy efficiency for our mobile processors and mobile devices, right? So laptops. And we were able to achieve a 31.7x in that timeframe. So which was twice the industry trend to that. And then moving on, we've doubled down on data center and we've set a new goal of a 30x increase in energy efficiency for our server processors and accelerators to really focused on HPC and AI training. So that's a 30x goal over 2020 to 2025 focused on these really important workloads 'cause they're fast growing. We heard yesterday 150 billion devices connected by 2025 generating a lot of data, right? So that's one of the reasons why we focused on that. 'Cause these are demanding workloads. And this represents a 2.5x increase over the historical trend, right? And fundamentally speaking, that's a 97% reduction in energy use per computation in five years. So we're very pleased. We announced an update recently. We're at 6.8x. We're on track for this goal and making great progress and showing how these, you know, solutions at a processor level and an accelerator level can be amplified, taken into HPE technology. >> Generally tech companies, you know, that compete want to rip each other's faces off. And is that the case in this space or do you guys collaborate with your competitors to share best practice? Is that beginning? Is it already there? >> There's much more collaboration in this space. This is one of the safe places I think where collaboration does occur more. >> Yeah. And we've all got to work together. A great example that was in the supply chain. When HPE first set our supply chain expectations for our suppliers around things like worker rights and environment and worker protection from a health and safety perspective. We initially had our code of conduct asked their suppliers to comply with it. Started auditing in event. And we quickly got into the factories and saw they were doing it for our workloads. But if you looked around the factory, they weren't doing in other places. And we took a step back and said, well, wait a minute. Why is that? And they said that vendor doesn't require it. So we took a step back and said let's get the industry together. We share a common supply chain. How do we have a common set of expectations and push them out to our supply chain? How to now do third party audits so the same supplier doesn't get audited by each of the major vendors and then share those audit results. And what we found was that really had a large lever effect of moving the electronic supply chain much more rapidly towards our expectations in all those areas. Well then other industries looked and said, well, wait a minute, if that worked for electronics, it'll probably work broader. And so now, the output of that is what's called the responsible business alliance across many industries taking that same approach. So that's a pre-competitive. We all have the same challenge. In many cases we share a common supply chain. So that's a great example of electronic companies coming together, design standards for things. There's a green grid group at the moment looking at liquid cooling connects. You know, we don't want every vendor to have a different connection point for liquid cooling for example. So how do we standardize that to make our customers have a easier time about looking at the technologies they want from any vendor and having common connection points. >> Right. Okay. So a lot of collaboration. Last question. How much of a difference do you think it can make? In other words, what percent of the blame pie goes to information technology? And I think regardless, you got to do your part. Will it make a dent? >> I think the sector has done a really good job of keeping that increase from going up while exponentially increasing performance. So it's been a really amazing industry effort. And moving forward, I think this is more important than ever, right? And with the slowdown of Moore's law we're seeing more gains that need to come from beyond process architecture to include packaging innovations, to power management, to just the architecture here. So the challenge of mitigating and minimizing energy growth is important. And we believe like with that 30x energy efficiency goal that it is doable but it does take a lot of collaboration and focus. >> That's a great point. I mean, if you didn't pay attention to this, IT could really become a big piece of the pie. Guys thanks so much for coming on theCUBE. Really appreciate. >> People are watching. They're paying attention at all levels. Congratulations. >> Absolutely. >> All right, Dave Vellante, John Furrier and our guests. Don't forget to go to SiliconANGLE.com for all the news. Our YouTube channel, actually go to CUBE.net. You'll get all these videos in our YouTube channel, youtube.com/SiliconANGLE. You can check out everything on demand. Keep it right there. We'll be right back. HPE Discover 2022 from Las Vegas. You're watching theCUBE. (soft music)

Published Date : Jun 29 2022

SUMMARY :

Brought to you by HPE. He is the chief technologist It's great to be here. So again, I remember the days where, Everything from the server So it's got to be a 100% but the goal setting is And the metrics involved too. and the outside of that. the right thing to do. and by the way the science-based So I got to ask how you guys specifically I've had the opportunity to So you have the heat and the has the heat from the system This is the scale, and get the performance they and the systems are pointing out, a really nuanced point but a liquid cold system from the start, or in somewhere in the So that's one of the reasons And is that the case in this space This is one of the safe places And so now, the output of that of the blame pie goes So the challenge of mitigating a big piece of the pie. People are watching. SiliconANGLE.com for all the news.

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Keith White, HPE | HPE Discover 2022


 

>> Announcer: theCube presents HPE Discover 2022, brought to you by HPE. >> Hey, everyone. Welcome back to Las Vegas. This is Lisa Martin with Dave Vellante live at HPE Discover '22. Dave, it's great to be here. This is the first Discover in three years and we're here with about 7,000 of our closest friends. >> Yeah. You know, I tweeted out this, I think I've been to 14 Discovers between the U.S. and Europe, and I've never seen a Discover with so much energy. People are not only psyched to get back together, that's for sure, but I think HPE's got a little spring in its step and it's feeling more confident than maybe some of the past Discovers that I've been to. >> I think so, too. I think there's definitely a spring in the step and we're going to be unpacking some of that spring next with one of our alumni who joins us, Keith White's here, the executive vice president and general manager of GreenLake Cloud Services. Welcome back. >> Great. You all thanks for having me. It's fantastic that you're here and you're right, the energy is crazy at this show. It's been a lot of pent up demand, but I think what you heard from Antonio today is our strategy's changing dramatically and it's really embracing our customers and our partners. So it's great. >> Embracing the customers and the partners, the ecosystem expansion is so critical, especially the last couple of years with the acceleration of digital transformation. So much challenge in every industry, but lots of momentum on the GreenLake side, I was looking at the Q2 numbers, triple digit growth in orders, 65,000 customers over 70 services, eight new services announced just this morning. Talk to us about the momentum of GreenLake. >> The momentum's been fantastic. I mean, I'll tell you, the fact that customers are really now reaccelerating their digital transformation, you probably heard a lot, but there was a delay as we went through the pandemic. So now it's reaccelerating, but everyone's going to a hybrid, multi-cloud environment. Data is the new currency. And obviously, everyone's trying to push out to the Edge and GreenLake is that edge to cloud platform. So we're just seeing tons of momentum, not just from the customers, but partners, we've enabled the platform so partners can plug into it and offer their solutions to our customers as well. So it's exciting and it's been fun to see the momentum from an order standpoint, but one of the big numbers that you may not be aware of is we have over a 96% retention rate. So once a customer's on GreenLake, they stay on it because they're seeing the value, which has been fantastic. >> The value is absolutely critically important. We saw three great big name customers. The Home Depot was on stage this morning, Oak Ridge National Laboratory was as well, Evil Geniuses. So the momentum in the enterprise is clearly present. >> Yeah. It is. And we're hearing it from a lot of customers. And I think you guys talk a lot about, hey, there's the cloud, data and Edge, these big mega trends that are happening out there. And you look at a company like Barclays, they're actually reinventing their entire private cloud infrastructure, running over a hundred thousand workloads on HPE GreenLake. Or you look at a company like Zenseact, who's basically they do autonomous driving software. So they're doing massive parallel computing capabilities. They're pulling in hundreds of petabytes of data to then make driving safer and so you're seeing it on the data front. And then on the Edge, you look at anyone like a Patrick Terminal, for example. They run a whole terminal shipyard. They're getting data in from exporters, importers, regulators, the works and they have to real-time, analyze that data and say, where should this thing go? Especially with today's supply chain challenges, they have to be so efficient, that it's just fantastic. >> It was interesting to hear Fidelma, Keith, this morning on stage. It was the first time I'd really seen real clarity on the platform itself and that it's obviously her job is, okay, here's the platform, now, you guys got to go build on top of it. Both inside of HPE, but also externally, so your ecosystem partners. So, you mentioned the financial services companies like Barclays. We see those companies moving into the digital world by offering some of their services in building their own clouds. >> Keith: That's right. >> What's your vision for GreenLake in terms of being that platform, to assist them in doing that and the data component there? >> I think that was one of the most exciting things about not just showcasing the platform, but also the announcement of our private cloud enterprise, Cloud Service. Because in essence, what you're doing is you're creating that framework for what most companies are doing, which is they're becoming cloud service providers for their internal business units. And they're having to do showback type scenarios, chargeback type scenarios, deliver cloud services and solutions inside the organization so that open platform, you're spot on. For our ecosystem, it's fantastic, but for our customers, they get to leverage it as well for their own internal IT work that's happening. >> So you talk about hybrid cloud, you talk about private cloud, what's your vision? You know, we use this term Supercloud. This in a layer that goes across clouds. What's your thought about that? Because you have an advantage at the Edge with Aruba. Everybody talks about the Edge, but they talk about it more in the context of near Edge. >> That's right. >> We talked to Verizon and they're going far Edge, you guys are participating in that, as well as some of your partners in Red Hat and others. What's your vision for that? What I call Supercloud, is that part of the strategy? Is that more longer term or you think that's pipe dream by Dave? >> No, I think it's really thoughtful, Dave, 'cause it has to be part of the strategy. What I hear, so for example, Ford's a great example. They run Azure, AWS, and then they made a big deal with Google cloud for their internal cars and they run HPE GreenLake. So they're saying, hey, we got four clouds. How do we sort of disaggregate the usage of that? And Chris Lund, who is the VP of information technology at Liberty Mutual Insurance, he talked about it today, where he said, hey, I can deliver these services to my business unit. And they don't know, am I running on the public cloud? Am I running on our HPE GreenLake cloud? Like it doesn't matter to the end user, we've simplified that so much. So I think your Supercloud idea is super thoughtful, not to use the super term too much, that I'm super excited about because it's really clear of what our customers are trying to accomplish, which it's not about the cloud, it's about the solution and the business outcome that gets to work. >> Well, and I think it is different. I mean, it's not like the last 10 years where it was like, hey, I got my stuff to work on the different clouds and I'm replicating as much as I can, the cloud experience on-prem. I think you guys are there now and then to us, the next layer is that ecosystem enablement. So how do you see the ecosystem evolving and what role does Green Lake play there? >> Yeah. This has been really exciting. We had Tarkan Maner who runs Nutanix and Karl Strohmeyer from Equinix on stage with us as well. And what's happening with the ecosystem is, I used to say, one plus one has to equal three for our customers. So when you bring these together, it has to be that scenario, but we are joking that one plus one plus one equals five now because everything has a partner component to it. It's not about the platform, it's not about the specific cloud service, it's actually about the solution that gets delivered. And that's done with an ISV, it's done with a Colo, it's done even with the Hyperscalers. We have Azure Stack HCI as a fully integrated solution. It happens with managed service providers, delivering managed services out to their folks as well. So that platform being fully partner enabled and that ecosystem being able to take advantage of that, and so we have to jointly go to market to our customers for their business needs, their business outcomes. >> Some of the expansion of the ecosystem. we just had Red Hat on in the last hour talking about- >> We're so excited to partner with them. >> Right, what's going on there with OpenShift and Ansible and Rel, but talk about the customer influence in terms of the expansion of the ecosystem. We know we've got to meet customers where they are, they're driving it, but we know that HPE has a big presence in the enterprise and some pretty big customer names. How are they from a demand perspective? >> Well, this is where I think the uniqueness of GreenLake has really changed HPE's approach with our customers. Like in all fairness, we used to be a vendor that provided hardware components for, and we talked a lot about hardware costs and blah, blah, blah. Now, we're actually a partner with those customers. What's the business outcome you're requiring? What's the SLA that we offer you for what you're trying to accomplish? And to do that, we have to have it done with partners. And so even on the storage front, Qumulo or Cohesity. On the backup and recovery disaster recovery, yes, we have our own products, but we also partner with great companies like Veeam because it's customer choice, it's an open platform. And the Red Hat announcement is just fantastic. Because, hey, from a container platform standpoint, OpenShift provides 5,000 plus customers, 90% of the fortune 500 that they engage with, with that opportunity to take GreenLake with OpenShift and implement that container capabilities on-prem. So it's fantastic. >> We were talking after the keynote, Keith Townsend came on, myself and Lisa. And he was like, okay, what about startups? 'Cause that's kind of a hallmark of cloud. And we felt like, okay, startups are not the ideal customer profile necessarily for HPE. Although we saw Evil Geniuses up on stage, but I threw out and I'd love to get your thoughts on this that within companies, incumbents, you have entrepreneurs, they're trying to build their own clouds or Superclouds as I use the term, is that really the target for the developer audience? We've talked a lot about OpenShift with their other platforms, who says as a partner- >> We just announced another extension with Rancher and- >> Yeah. I saw that. And you have to have optionality for developers. Is that the way we should think about the target audience from a developer standpoint? >> I think it will be as we go forward. And so what Fidelma presented on stage was the new developer platform, because we have come to realize, we have to engage with the developers. They're the ones building the apps. They're the ones that are delivering the solutions for the most part. So yeah, I think at the enterprise space, we have a really strong capability. I think when you get into the sort of mid-market SMB standpoint, what we're doing is we're going directly to the managed service and cloud service providers and directly to our Disty and VARS to have them build solutions on top of GreenLake, powered by GreenLake, to then deliver to their customers because that's what the customer wants. I think on the developer side of the house, we have to speak their language, we have to provide their capabilities because they're going to start articulating apps that are going to use both the public cloud and our on-prem capabilities with GreenLake. And so that's got to work very well. And so you've heard us talk about API based and all of that sort of scenario. So it's an exciting time for us, again, moving HPE strategy into something very different than where we were before. >> Well, Keith, that speaks to ecosystem. So I don't know if you were at Microsoft, when the sweaty Steve Ballmer was working with the developers, developers. That's about ecosystem, ecosystem, ecosystem. I don't expect we're going to see Antonio replicating that. But that really is the sort of what you just described is the ecosystem developing on top of GreenLake. That's critical. >> Yeah. And this is one of the things I learned. So, being at Microsoft for as long as I was and leading the Azure business from a commercial standpoint, it was all about the partner and I mean, in all fairness, almost every solution that gets delivered has some sort of partner component to it. Might be an ISV app, might be a managed service, might be in a Colo, might be with our hybrid cloud, with our Hyperscalers, but everything has a partner component to it. And so one of the things I learned with Azure is, you have to sell through and with your ecosystem and go to that customer with a joint solution. And that's where it becomes so impactful and so powerful for what our customers are trying to accomplish. >> When we think about the data gravity and the value of data that put massive potential that it has, even Antonio talked about it this morning, being data rich but insights poor for a long time. >> Yeah. >> Every company in today's day and age has to be a data company to be competitive, there's no more option for that. How does GreenLake empower companies? GreenLake and its ecosystem empower companies to really live being data companies so that they can meet their customers where they are. >> I think it's a really great point because like we said, data's the new currency. Data's the new gold that's out there and people have to get their arms around their data estate. So then they can make these business decisions, these business insights and garner that. And Dave, you mentioned earlier, the Edge is bringing a ton of new data in, and my Zenseact example is a good one. But with GreenLake, you now have a platform that can do data and data management and really sort of establish and secure the data for you. There's no data latency, there's no data egress charges. And which is what we typically run into with the public cloud. But we also support a wide range of databases, open source, as well as the commercial ones, the sequels and those types of scenarios. But what really comes to life is when you have to do analytics on that and you're doing AI and machine learning. And this is one of the benefits I think that people don't realize with HPE is, the investments we've made with Cray, for example, we have and you saw on stage today, the largest supercomputer in the world. That depth that we have as a company, that then comes down into AI and analytics for what we can do with high performance compute, data simulations, data modeling, analytics, like that is something that we, as a company, have really deep, deep capabilities on. So it's exciting to see what we can bring to customers all for that spectrum of data. >> I was excited to see Frontier, they actually achieve, we hosted an event, co-produced event with HPE during the pandemic, Exascale day. >> Yeah. >> But we weren't quite at Exascale, we were like right on the cusp. So to see it actually break through was awesome. So HPC is clearly a differentiator for Hewlett Packard Enterprise. And you talk about the egress. What are some of the other differentiators? Why should people choose GreenLake? >> Well, I think the biggest thing is, that it's truly is a edge to cloud platform. And so you talk about Aruba and our capabilities with a network attached and network as a service capabilities, like that's fairly unique. You don't see that with the other companies. You mentioned earlier to me that compute capabilities that we've had as a company and the storage capabilities. But what's interesting now is that we're sort of taking all of that expertise and we're actually starting to deliver these cloud services that you saw on stage, private cloud, AI and machine learning, high performance computing, VDI, SAP. And now we're actually getting into these industry solutions. So we talked last year about electronic medical records, this year, we've talked about 5g. Now, we're talking about customer loyalty applications. So we're really trying to move from these sort of baseline capabilities and yes, containers and VMs and bare metal, all that stuff is important, but what's really important is the services that you run on top of that, 'cause that's the outcomes that our customers are looking at. >> Should we expect you to be accelerating? I mean, look at what you did with Azure. You look at what AWS does in terms of the feature acceleration. Should we expect HPE to replicate? Maybe not to that scale, but in a similar cadence, we're starting to see that. Should we expect that actually to go faster? >> I think you couched it really well because it's not as much about the quantity, but the quality and the uses. And so what we've been trying to do is say, hey, what is our swim lane? What is our sweet spot? Where do we have a superpower? And where are the areas that we have that superpower and how can we bring those solutions to our customers? 'Cause I think, sometimes, you get over your skis a bit, trying to do too much, or people get caught up in the big numbers, versus the, hey, what's the real meat behind it. What's the tangible outcome that we can deliver to customers? And we see just a massive TAM. I want to say my last analysis was around $42 billion in the next three years, TAM and the Azure service on-prem space. And so we think that there's nothing but upside with the core set of workloads, the core set of solutions and the cloud services that we bring. So yeah, we'll continue to innovate, absolutely, amen, but we're not in a, hey we got to get to 250 this and 300 that, we want to keep it as focused as we can. >> Well, the vast majority of the revenue in the public cloud is still compute. I mean, not withstanding, Microsoft obviously does a lot in SaaS, but I'm talking about the infrastructure and service. Still, well, I would say over 50%. And so there's a lot of the services that don't make any revenue and there's that long tail, if I hear your strategy, you're not necessarily going after that. You're focusing on the quality of those high value services and let the ecosystem sort of bring in the rest. >> This is where I think the, I mean, I love that you guys are asking me about the ecosystem because this is where their sweet spot is. They're the experts on hyper-converged or databases, a service or VDI, or even with SAP, like they're the experts on that piece of it. So we're enabling that together to our customers. And so I don't want to give you the impression that we're not going to innovate. Amen. We absolutely are, but we want to keep it within that, that again, our swim lane, where we can really add true value based on our expertise and our capabilities so that we can confidently go to customers and say, hey, this is a solution that's going to deliver this business value or this capability for you. >> The partners might be more comfortable with that than, we only have one eye sleep with one eye open in the public cloud, like, okay, what are they going to, which value of mine are they grab next? >> You're spot on. And again, this is where I think, the power of what an Edge to cloud platform like HPE GreenLake can do for our customers, because it is that sort of, I mentioned it, one plus one equals three kind of scenario for our customers so. >> So we can leave your customers, last question, Keith. I know we're only on day one of the main summit, the partner growth summit was yesterday. What's the feedback been from the customers and the ecosystem in terms of validating the direction that HPE is going? >> Well, I think the fantastic thing has been to hear from our customers. So I mentioned in my keynote recently, we had Liberty Mutual and we had Texas Children's Hospital, and they're implementing HPE GreenLake in a variety of different ways, from a private cloud standpoint to a data center consolidation. They're seeing sustainability goals happen on top of that. They're seeing us take on management for them so they can take their limited resources and go focus them on innovation and value added scenarios. So the flexibility and cost that we're providing, and it's just fantastic to hear this come to life in a real customer scenario because what Texas Children is trying to do is improve patient care for women and children like who can argue with that. >> Nobody. >> So, yeah. It's great. >> Awesome. Keith, thank you so much for joining Dave and me on the program, talking about all of the momentum with HPE Greenlake. >> Always. >> You can't walk in here without feeling the momentum. We appreciate your insights and your time. >> Always. Thank you you for the time. Yeah. Great to see you as well. >> Likewise. >> Thanks. >> For Keith White and Dave Vellante, I'm Lisa Martin. You're watching theCube live, day one coverage from the show floor at HPE Discover '22. We'll be right back with our next guest. (gentle music)

Published Date : Jun 28 2022

SUMMARY :

brought to you by HPE. This is the first Discover in three years I think I've been to 14 Discovers a spring in the step and the energy is crazy at this show. and the partners, and GreenLake is that So the momentum in the And I think you guys talk a lot about, on the platform itself and and solutions inside the organization at the Edge with Aruba. that part of the strategy? and the business outcome I mean, it's not like the last and so we have to jointly go Some of the expansion of the ecosystem. to partner with them. in terms of the expansion What's the SLA that we offer you that really the target Is that the way we should and all of that sort of scenario. But that really is the sort and leading the Azure business gravity and the value of data so that they can meet their and secure the data for you. with HPE during the What are some of the and the storage capabilities. in terms of the feature acceleration. and the cloud services that we bring. and let the ecosystem I love that you guys are the power of what an and the ecosystem in terms So the flexibility and It's great. about all of the momentum We appreciate your insights and your time. Great to see you as well. from the show floor at HPE Discover '22.

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Ryan King & Laurie Fontaine, Red Hat | HPE Discover 2022


 

>>The cube presents HPE discover 2022 brought to you by HPE. >>Hey everyone. Welcome back to the Cube's day one coverage of HPE. Discover 22 live from Las Vegas. Lisa Martin, here with Dave Velante of a couple of guests from red hat. You may have seen some news yesterday. We're gonna be talking about that. Please. Welcome Ryan King, the senior director of hardware partner ecosystem, and Lori Fontine joins us as well. The senior director of global commercial partner ecosystem. Welcome to the program guys. >>Thanks for having us. Yeah, >>Thank you so great to be back in person and nobody word has summit was just last month or so. That's right. Ryan. Talk about hybrid cloud. It's all the buzz. We've been talking a lot about it in the last hour and a half alone. What are some of the trends that, that red hat is seen with respect to hybrid cloud? >>Well, I, I mean, hybrid cloud of red hat has been a trend for quite some time. In fact, we were very early in setting our course towards hybrid cloud with our products and platforms. And that's been a key part of our strategy in terms of the number of transformations have been happening in the enterprise. And with HPE, we're super excited about, you know, we're hitting our stride with OpenShift. I've been working with OpenShift for the better part of my 10 years here at 12 years at red hat, 10 years with OpenShift. And we're very excited about seeing the pattern of going where customers want to build their cloud. It's very important that where, where the market is going. So we're seeing trends from the public cloud now go into edge and telco and 5g and really exceed, see them expanding their infrastructure footprint out to those use cases. And again, we see REL everywhere. So re has continued to expand as well. And then Ansible automation platform has also been a great means of kind of bringing together community for that last mile of automating your entire infrastructure. >>Well, the Lin, the functionality of Linux continues to improve OpenShift is everywhere. I mean, I remember at the red hat summit, I mean, well, we, we, we coined this term super cloud, which is this layer that floats, you know, on-prem took across clouds out to the edge we had Verizon on. They were talking about, you know, 5g developers and how they're developing using, you know, a combination of, of, of OpenShift. So guys have been really crushing it with, with OpenShift. I remember, gosh, I mean, we've been covering, you know, red hat summits for a long time now. And just to see that evolution is actually quite amazing. >>Yeah. It's actually really neat to see our CEOs align too. Right. So the messaging that we've had around hybrid cloud from red hat, like you said, we were kind of the pioneers, honestly, this we've been talking about hybrid cloud from the very beginning. We always knew that it wasn't gonna be public cloud or private cloud. We had to have, you know, hybrid. And, and it's interesting to see that Antonio, you know, took that on and wanted to say, we're gonna do everything as a service right. A few years ago. And, and the whole theme was around hybrid cloud and giving customers that choice. Right? So it's exciting for us to see all of that come together. And I actually worked for HP for like 17 and a half years. So it's really fun for me to be on this side now with red hat and see the messaging come together, the vision come together and just really being able to align and move forward on >>This tremendous amount of transformation in the last few years >>Alone. Oh my gosh, we >>Talk about, you know, customers need choice. They want choice, but you also talked about, we have to meet customers where they are. That seems the last few years to have accelerated, there is no more option for companies. You've gotta meet the customers where they are. >>Exactly. Yeah. And it's all about choice, like you said, and it, everybody's got, you know, their own way to do everything as far as consumption goes and we have to be available and spot on with it, you know, and be able to move quickly with these trends that we're seeing. And so it's great to be aligned. And >>From a partnership standpoint, I mean, you, you mentioned H HP 17 years. I mean, it was, it was a hard to follow company. You had, you had PCs over here, you had services, the kind of the old EDS business. Now there's such a focus absolutely. On this mission, absolutely. Of as a service. And, you know, obviously a key part of that is having optionality and bringing open source tooling into that. I mean, we heard about this in, in spades, at, at red hat summit, which is really interesting this year. It was a smaller VIP event in Boston. And I, and I loved it, you know, cuz it was really manageable. We had all the execs on and customers and partners. It was awesome. What's new since red hat summit. >>Well, I mean, I would say that obviously GreenLake and what we've announced this week is a big new thing for us, but really like we're just continuing on our pattern. We are. Now, if you look at the Q1 report from IBM, you'll see that the growth of the customer base for OpenShift that they reported just continues to go up into the right. You'll see that now, like AMIA is saying that we're like 47.8% of the containers market for the enterprise. You'll see that like we're now in 65% of the fortune 500 with OpenShift, 90% with red hat in general. So we've established our footprint. And when you establish your footprint and customers start taking you out to the edge, we're going into these 5g use cases, we're, we've got an incredible amount happening in the AI space, all these emerging areas of where people are building their cloud, like we're now going to that next level of saying, how do they want to consume it? >>So what's really important to me about that is, is so Omni data around 50% of the market is, is open shift. A people may not realize a lot of people use, you know, do Kubernetes for free, you know, Hey, we're doing Kubernetes, but they don't have that application development framework and all the recovery and all the, the tooling around it. And the reason why I think that's so important, Laurie is ecosystems wanna monetize. So people are paying for things that becomes more interesting and it actually starts to attract people just naturally. >>Yeah, absolutely. And speaking of ecosystem, I mean, that's the beauty of what we're doing with GreenLake too. We're taking on a building block approach. So we're really, it's kind of ISV as a service if you will. And you know, personally, I, this was my baby for the past couple years, trying to make sure that we took into consideration every partner use case, every customer use case. So we created an agreement that would make sense to be able to scale, but also to meet all the demands of our customers. And so the, the what's really exciting about this is now we have a chance to take this building block approach, scale it out to all types of partner types, right throughout the entire ecosystem and build offerings together. That is really exciting for us. And that's where we see the real potential here with GreenLake and with red hat, >>What's actually available inside a GreenLake. >>So we are starting with OpenShift. So OpenShift will be available in Q3 that will follow in Q4 with re and then after that Ansible. So we're, we're moving very quickly to bring our platforms into it and it's really our strategic platforms, but it's all based on customer demand. We know we're seeing amazing transformation of customers moving to Kubernetes. You said, you know, OpenShift is Kubernetes with useful additions to it and an ecosystem around it, right? So that transformation is also happening at the bare metal layer. So we're seeing people move into Kubernetes bare metal, which is an amazing growth market for us. >>Explain those useful additions if you would. So why shouldn't I just go out and, and get the free version of Kubernete? Why should I engage red hat and, and OpenShift? What do I get? >>So you get all the day, two management stuff, you get, we have a whole set of additional stuff you can purchase around it, OpenShift platform. Plus you can get our ACM, our advanced cluster management. So you wanna manage multiple clusters, right? You get the ACS, the security side of it. You can also get ODF. So you get storage built into it as well. And we've done all these integrations. You can manage the whole thing as a cluster or as multiple clusters with the whole enterprise support and the long term support that we provide for these things up to 10 years. So >>When you look at the early days lease of, of Kubernetes, it was really, the focus was on simplicity. You had other platforms that were actually doing more sophisticated cluster management. And the, the committers that in Kubernetes said, you know, we're not gonna do that. We're gonna keep it simple. And so that leave some holes and gaps and you know, they're starting to fill those, but what if, if correct me if I'm wrong, but what red hat has done is said, okay, we're gonna accelerate, you know, the, the, the closing of those gaps and stay ahead and actually offer incremental value. And that's why you're winning in the marketplace. >>Well, we're an open company, so we're still doing everything upstream and open source as we do, of course, sticking with, you know, the APIs and APIs to make this all work, both, you know, in terms of what the community's trying to drive, what we're trying to drive for our customers on their behalf. And then just where things are going from a technology basis, make it a lot of investment, >>But you have to, you have to make a red hat, has to make a choice as to where it puts its commitments. You can't spread yourself too thin, so you gotta pick your spots. And you've, you've proven that you're pretty adept at doing that. >>That just comes back to customer centricity, right. And just knowing where our customers need to take the platform. That's, >>That's easy to say, but it's, it's an art form. And a little bit of science. >>Remember these customers have experts that are deep in this space. So it's like, you know, those experts trust us with where they needed to go. And they trust us to help shepherd that and deliver that as a platform to them. So it's not like anybody tell us what you want, right? Like it's really about like, knowing what's the best way to do it. And working with the people that can help you understand how to apply that to their use case >>And within the customer environment, who are you working with? Who is that key constituent or constituents that are guiding red hat in this direction? >>Well, it's certainly infrastructure folks. So it's your, it's your standard folks that are looking at the, how do we lay down our infrastructure? How do we manage it? How do we grow it? It goes out to the application developers. They're trying to deliver this in a cloud native way. And we have new personas, you know, coming in with the AI practitioners, right? So we've announced at before summit at Invidia's event, their new offering called Invidia AI enterprise. And so that's them bringing in enterprise support for GPU, for Kuda and for a software stack above that to start offering some more support there. So they're certifying OpenShift, we're both certifying the servers that run underneath it, and then they're offering support for their stuff on top of it. And that's a whole new use case for us. >>And, you know, I should also mention that even though this paper use with the GreenLake is new for us, and we just had this big announcement, we have done GreenLake deals though. We've done numerous GreenLake deals with our annual subs, right? So I, so even though this is new to us, as far as, you know, monthly utilization and being able to do this cloud consumption this isn't new to us as two companies coming together, we've been doing GreenLake deals for the past couple years. It's just, now we have this cloud consumption availability, which is really gonna make this thing launch. So, >>So what have been some of the customer benefits so far, you've been doing it for a couple years. The announcement was yesterday, but there's obviously feed on the street going on. What are some of the, the big outcomes that you're seeing customers actually bring to reality? >>I think speed and agility, right? That's the biggest thing with, with our products, being able to have it everything predictable and being able to have it consumed one way, instead of having this fragmented customer experience, which is, you know, what we've seen in the past. So I think that's the biggest thing is speed agility and just, you know, a really good customer experience at this point. >>Go get it, please. >>I would say the customer experience is critical. Yes. That's one of the things that we know that in terms of, of patients wearing thin the last couple of years, people expect to have a really strong consumer experience regardless of what you're doing, regardless of what industry and so attention and mind on that is a differentiator in my opinion. >>Absolutely. Yeah. And we've gotta constantly keep our eye on that. I mean, that's, that's our north star, if you will. Right. So, and Lori, >>I know you've saying you're, you've done GreenLake deals in the past, but what feels different to me now in that it's actually coalescing some of the things that Alma Russo announced this morning, the platform on which, you know, ISV is a service. I think you, you called it. Yeah. You, it, it now seems like, you know, look a couple years ago, HP said, okay, this is the direction that we're going. Yeah. They weren't there at that time. And they're still not there. There's a lot of work to be, to be done. But now it's starting to form. You're seeing, you know, the pieces come together, the puzzle pieces that sort of substrate being laid out. And now you're hoping that we see the steep part of the S-curve and that's what customers I think are expecting. >>Right. And it's bringing that operating model to move to a monthly model so they can do pay as you go. Right. And that pairs up nicely with like the cloud native capabilities we're bringing to OpenShift and hybrid cloud in general. So it's, it just shows like we're already getting demand from customers. It's saying like, this is part of our model. Like we know a certain amount of infrastructure we wanna own, and we just wanna own it outright, but there's a lot that they want to have flexibility on. And so being able to add that portion to it is just, you know, gonna help us both. >>And you think about the critical aspects of, of the cloud operating model. It's obviously pay as you go it's, you know, massive scale it's ecosystem enablement, and also automation. I mean, that is, that is a key, what's your point of view on that? You guys with Ansible, you, you, you know, you go back to a couple years ago and it was, you know, there was this, there were a lot of other tooling, but now, I mean, Ansible is really taken off. Yeah. >>It's just, you know, Cinderella story, right? Like it really an amazing community driven thing where we just knew, we all know this, right. You have, when you get to the very last mile of doing infrastructure management, there's a variety of devices, there's variety, a variety of vendors. And then you have like the variety of skills of the people that have to figure out how to do automate all of this. And what Ansible did is it provided a common language across all of that. And so what we do with automation, our, an ible automation platform is we make it. So now teams can manage all of this together and they can share their playbooks and they can host that privately for all their enterprise stuff that they need to do. So it's just, you know, it fits our DNA so well to have something so community driven now with a really nice enterprise message wrapped around it. And it's playing out very well for where, you know, hybrid cloud. Right. Cause there's some more additional variety. You need to be able to manage, you know, across all of your different footprints, because really it's like, it's not just about flexibility and scale up scale down it's where do you need it to run at what time? Right. And that, that last leg Ansible plays a key role in that. >>And we actually, Ansible will be coming further down the, you know, the patch. I know we're gonna talk a little bit about what's available today versus what's available down the road, but yeah, we have that on the radar. So right outta the gate, we're working on OpenShift, obviously bare metal. And we see that happening in Q3 and then behind that as well in Q4 and then Ansible is gonna be right behind that. So that's kind of the order that, and there's other pieces, right? So our whole portfolio is basically available to HP right now. It's just making sure that we can operationalize everything and have the best experience >>All inside of GreenLake, >>All inside a GreenLake. Yeah. Pretty neat. Lori >>Question for you. You've been, you were with HP for a very long time. This is obviously the first discover in three years in person. Exactly. You know, three years ago, Antonio near stood on stage and said, we are going to buy 20, 22. And here we are deliver everything as a service, as a partner and as a former HP, what are you seeing at this discover 22? >>It's it's so interesting. I it's such a sea change if you will. Right. And having come from HPE, I actually led the software as a service organization for a while on the software side of things. And we thought that was like state of the art and cutting edge that was 10, 11, 12 years ago. Right. So to actually see this come to life, because we were all thinking really, everything is a service. How are you gonna do that? Like your entire portfolio is gonna be available. Like that is lofty. Right. And having worked at HP, I thought, wow, I don't, you know, I know things take time. And, but actually just even being around the showcase here and watching everything come to life is amazing. Cause I, I, you know, I, I was very positive about it, but at the same time, it's like that, that was a big goal three years. Right. And it's, I'm seeing it happen >>A big goal in two of those years during a pandemic. Right. So right. Talk about lofty. Oh my gosh. Quite a bit of accomplishments guys. Thank you so much for joining David me on the program talking about actually guys, this is great. What red hat and HPE are doing your power partnership, power ship. Is that a word? It is now your power. >>I like >>That with GreenLake. We appreciate that. We'll look forward to having you guys back on. >>Thank you so much, guys. >>All right. For our guests. I'm Lisa Martin. He's Dave ante. We are at HPE discover 22 live from the show floor in Las Vegas. This is just day one of our cupboards stick around. We'll be right back with our next guest.

Published Date : Jun 28 2022

SUMMARY :

the senior director of hardware partner ecosystem, and Lori Fontine joins us as well. Thanks for having us. Thank you so great to be back in person and nobody word has summit was just last month or so. And with HPE, we're super excited about, you know, I remember, gosh, I mean, we've been covering, you know, red hat summits for a long time And, and it's interesting to see that Antonio, you know, took that on and wanted to Oh my gosh, we Talk about, you know, customers need choice. with it, you know, and be able to move quickly with these trends that we're seeing. And I, and I loved it, you know, cuz it was really manageable. And when you establish your you know, do Kubernetes for free, you know, Hey, we're doing Kubernetes, but they don't have And you know, personally, I, this was my baby for the past couple years, trying to make sure that we took into You said, you know, OpenShift is Kubernetes with useful additions to it and an ecosystem Explain those useful additions if you would. So you get all the day, two management stuff, you get, we have a whole set of additional stuff you And the, the committers that in Kubernetes said, you know, we're not gonna do that. sticking with, you know, the APIs and APIs to make this all work, both, you know, in terms of what the community's trying But you have to, you have to make a red hat, has to make a choice as to where it puts its commitments. And just knowing where our customers need to take the platform. And a little bit of science. So it's like, you know, those experts trust us with And we have new personas, you know, this is new to us, as far as, you know, monthly utilization and being able to do this cloud consumption this So what have been some of the customer benefits so far, you've been doing it for a couple years. So I think that's the biggest thing is speed agility and just, you know, a really good customer experience at this point. That's one of the things that we know that in terms of, if you will. You're seeing, you know, the pieces come together, the puzzle pieces that sort of substrate being And it's bringing that operating model to move to a monthly model so they can do pay as you go. And you think about the critical aspects of, of the cloud operating model. So it's just, you know, it fits our DNA so well to have something so community driven now And we actually, Ansible will be coming further down the, you know, the patch. All inside a GreenLake. what are you seeing at this discover 22? I don't, you know, I know things take time. Thank you so much for joining David me on the program talking about actually guys, We'll look forward to having you guys back on. We are at HPE discover 22 live from the show floor in Las Vegas.

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Manoj Suvarna, Deloitte LLP & Arte Merritt, AWS | Amazon re:MARS 2022


 

(upbeat music) >> Welcome back, everyone. It's theCUBE's coverage here in Las Vegas. I'm John Furrier, your host of theCUBE with re:MARS. Amazon re:MARS stands for machine learning, automation, robotics, and space. Lot of great content, accomplishment. AI meets meets robotics and space, industrial IoT, all things data. And we've got two great guests here to unpack the AI side of it. Manoj Suvarna, Managing Director at AI Ecosystem at Deloitte and Arte Merritt, Conversational AI Lead at AWS. Manoj, it's great to see you CUBE alumni. Art, welcome to theCUBE. >> Thanks for having me. I appreciate it. >> So AI's the big theme. Actually, the big disconnect in the industry has been the industrial OT versus IT, and that's happening. Now you've got space and robotics meets what we know is machine learning and AI which we've been covering. This is the confluence of the new IoT market. >> It absolutely is. >> What's your opinion on that? >> Yeah, so actually it's taking IoT beyond the art of possible. One area that we have been working very closely with AWS. We're strategic alliance with them. And for the past six years, we have been investing a lot in transformations. Transformation as it relate to the cloud, transformation as it relate to data modernization. The new edge is essentially on AI and machine learning. And just this week, we announced a new solution which is more focused around enhancing contact center intelligence. So think about the edge of the contact center, where we all have experiences around dealing with customer service and how to really take that to the next level, challenges that clients are facing in every part of that business. So clearly. >> Well, Conversational AI is a good topic. Talk about the relationship with Deloitte and Amazon for a second around AI because you guys have some great projects going on right now. That's well ahead of the curve on solving the scale problem 'cause there's a scale and problem, practical problem and then scale. What's the relationship with Amazon and Deloitte? >> We have a great alliance and relationship. Deloitte brings that expertise to help folks build high quality, highly effective conversational AI and enterprises are implementing these solutions to really try to improve the overall customer experience. So they want to help agents improve productivity, gain insights into the reasons why folks are calling but it's really to provide that better user experience being available 24/7 on channels users prefer to interact. And the solutions that Deloitte is building are highly advanced, super exciting. Like when we show demos of them to potential customers, the eyes light up and they want those solutions. >> John: Give an example when their eyes light up. What are you showing there? >> One solution, it's called multimodal interfaces. So what this is, is when you're call into like a voice IVR, Deloitte's solution will send the folks say a mobile app or a website. So the person can interact with both the phone touching on the screen and the voice and it's all kept in sync. So imagine you call the doctor's office or say I was calling a airline and I want to change my flight or sorry, change the seat. If they were to say, seat 20D is available. Well, I don't know what that means, but if you see the map while you're talking, you can say, oh, 20D is the aisle. I'm going to select that. So Deloitte's doing those kind of experiences. It's incredible. >> Manoj, this is where the magic comes into play when you bring data together and you have integration like this. Asynchronously or synchronously, it's all coming together. You have different platforms, phone, voice, silo databases potentially, the old way. Now, the new ways integrating. What makes it all work? What's the key to success? >> Yeah, it's certainly not a trivial feat. Bringing together all of these ecosystems of relationships, technologies all put together. We cannot do it alone. This is where we partner with AWS with some of our other partners like Salesforce and OneReach and really trying to bring a symphony of some of these solutions to bear. When you think about, going back to the example of contact center, the challenges that the pandemic posed in the last couple of years was the fact that who's a humongous rise in volume of number of calls. You can imagine people calling in asking for all kinds of different things, whether it's airlines whether it is doctor's office and retail. And then couple with that is the fact that there's the labor shortage. And how do you train agents to get them to be productive enough to be able to address hundreds or thousands of these calls? And so that's where we have been starting to, we have invested in those solutions bringing those technologies together to address real client problems, not just slideware but actual production environments. And that's where we launched this solution called TrueServe as of this week, which is really a multimodal solution that is built with preconceived notions of technologies and libraries where we can then be industry agnostic and be able to deliver those experiences to our clients based on whatever vertical or industry they're in. >> Take me through the client's engagement here because I can imagine they want to get a practical solution. They're going to want to have it up and running, not like a just a chatbot, but like they completely integrated system. What's the challenge and what's the outcome first set of milestones that you see that they do first? Do they just get the data together? Are they deploying a software solution? What's the use cases? >> There's a couple different use cases. We see there's the self-service component that we're talking about with the chatbots or voice IVR solutions. There's also use cases for helping the agents, so real-time agent assist. So you call into a contact center, it's transcribed in real time, run through some sort of knowledge base to give the agents possible answers to help the user out, tying in, say the Salesforce data, CRM data, to know more about the user. Like if I was to call the airline, it's going to say, "Are you calling about your flight to San Francisco tomorrow?" It knows who I am. It leverages that stuff. And then the key piece is the analytics knowing why folks are calling, not just your metrics around, length of calls or deflections, but what were the reasons people were calling in because you can use that data to improve your underlying products or services. These are the things that enterprise are looking for and this is where someone like Deloitte comes in, brings that expertise, speeds up the time to market and really helps the customers. >> Manoj, what was the solution you mentioned that you guys announced? >> Yeah, so this is called Deloitte TrueServe. And essentially, it's a combination of multiple different solutions combinations from AWS, from Salesforce, from OneReach. All put together with our joint engineering and really delivering that capability. Enhancing on that is the analytics component, which is really critical, especially because when you think about the average contact center, less than 10% of the data gets analyzed today, and how do you then extract value out of that data and be able to deliver business outcomes. >> I was just talking to some of the other day about Zoom. Everyone records their zoom meetings, and no one watches them. I mean, who's going to wade through that. Call center is even more high volume. We're talking about massive data. And so will you guys automate that? Do you go through every single piece of data, every call and bring it down? Is that how it works? >> Go ahead. >> There's just some of the things you can do. Analyze the calls for common themes, like figuring out like topic modeling, what are the reasons people are calling in. Summarizing that stuff so you can see what those underlying issues are. And so that could be, like I was mentioning, improving the product or service. It could also be for helping train the agents. So here's how to answer that question. And it could even be reinforcing positive experiences maybe an agent had a particular great call and that could be a reference for other folks. >> Yeah, and also during the conversation, when you think about within 60 to 90 seconds, how do you identify the intonation, the sentiments of the client customer calling in and be able to respond in real time for the challenges that they might be facing and the ability to authenticate the customer at the same time be able to respond to them. I think that is the advancements that we are seeing in the market. >> I think also your point about the data having residual values also excellent because this is a long tail of value in this data, like for predictions and stuff. So NASA was just on before you guys came on, talking about the Artemis project and all the missions and they have to run massive amounts of simulations. And this is where I've kind of seen the dots connect here. You can run with AI, run all the heavy lifting without human touching it to get that first ingestion or analysis, and then iterating on the data based upon what else happens. >> Manoj: Absolutely. >> This is now the new normal, right? Is this? >> It is. And it's transverse towards across multiple domains. So the example we gave you was around Conversational AI. We're now looking at that for doing predictive analytics. Those are some examples that we are doing jointly with AWS SageMaker. We are working on things like computer vision with some of the capabilities and what computer vision has to offer. And so when you think about the continuum of possibilities of what we can bring together from a tools, technology, services perspective, really the sky is the limit in terms of delivering these real experiences to our clients. >> So take me through a customer. Pretending I'm a customer, I get it. I got to do this. It's a competitive advantage. What are the outcomes that they are envisioning? What are some of the patterns you're seeing with customers? What outcomes are they expecting and what kind of high level upside you see them envisioning coming out of the data? >> So when you think about the CxOs today and the board, a lot of them are thinking about, okay, how do you build more efficiency in those system? How do you enable a technology or solution for them to not only increase their top line but as well as their bottom line? How do you enhance the customer experience, which in this case is spot on because when you think about, when customers go repeat to a vendor, it's based on quality, it's based on price. Customer experience is now topping that where your first experience, whether it's through a chat or a virtual assistant or a phone call is going to determine the longevity of that customer with you as a vendor. And so clearly, when you think about how clients are becoming AI fuel, this is where we are bringing in new technologies, new solutions to really push the art to the limit and the art of possible. >> You got a playbook too to do this? >> Yeah, yeah, absolutely. We have done that. And in fact, we are now taking that to the next level up. So something that I've mentioned about this before, which is how do you trust an AI system as it's building up. >> Hold on, I need to plug in. >> Yeah, absolutely. >> I put this here for a reason to remind me. No, but also trust is a big thing. Just put that trustworthy. This is an AI ethics question. >> Arte: It's a big. >> Let's get into it. This is huge. Data's data. Data can be biased from coming in >> Part of it, there are concerns you have to look at the bias in the data. It's also how you communicate through these automated channels, being empathetic, building trust with the customer, being concise in the answers and being accessible to all sorts of different folks and how they might communicate. So it's definitely a big area. >> I mean, you think about just normal life. We all lived situations where we got a text message from a friend or someone close to us where, what the hell, what are you saying? And they had no contextual bad feelings about it or, well, there's misunderstandings 'cause the context isn't there 'cause you're rapid fire them on the subway. I'm riding my bike. I stop and text, okay, I'm okay. Church response could mean I'm busy or I'm angry. Like this is now what you said about empathy. This is now a new dynamic in here. >> Oh, the empathy is huge, especially if you're say a financial institution or building that trust with folks and being empathetic. If someone's reaching out to a contact center, there's a good chance they're upset about something. So you have to take that. >> John: Calm them down first. >> Yeah, and not being like false like platitude kind of things, like really being empathetic, being inclusive in the language. Those are things that you have conversation designers and linguistics folks that really look into that. That's why having domain expertise from folks like Deloitte come in to help with that. 'Cause maybe if you're just building the chat on your own, you might not think of those things. But the folks with the domain expertise will say like, Hey, this is how you script it. It's the power of words, getting that message across clearly. >> The linguistics matter? >> Yeah, yeah. >> It does. >> By vertical too, I mean, you could pick any the tribe, whatever orientation and age, demographics, genders. >> All of those things that we take for granted as a human. When you think about trust, when you think about bias, when you think about ethics, it just gets amplified. Because now you're dealing with millions and millions of data points that may or may not be the right direction in terms of somebody's calling in depending on what age group they're in. Some questions might not be relevant for that age group. Now a human can determine that, but a bot cannot. And so how do you make sure that when you look at this data coming in, how do you build models that are ethically aware of the contextual algorithms and the alignment with it and also enabling that experience to be much enhanced than taking it backwards, and that's really. >> I can imagine it getting better with as people get scaled up a bit 'cause then you're going to have to start having AI to watch the AI at some point, as they say. Where are we in the progress in the industry right now? Because I know there's been a lot of news stories around, ethics and AI and bias and it's a moving train actually, but still problems are going to be solved. Are we at the tipping point yet? Are we still walking in before we crawl or crawling before we walk? I should say, I mean, where are we? >> I think we are in between a crawling or walk phase. And the reason for that is because it varies depending on whether you're regulated industry or unregulated. In the regulated industry, there are compliance regulations requirements, whether it's government whether it's banking, financial institutions where they have to meet Sarbanes-Oxley and all kinds of compliance requirements, whereas an unregulated industry like retail and consumer, it is anybody's gain. And so the reality of it is that there is more of an awareness now. And that's one of the reasons why we've been promoting this jointly with AWS. We have a framework that we have established where there are multiple pillars of trust, bias, privacy, and security that companies and organizations need to think about. Our data scientists, ML engineers need to be familiar with it, but because while they're super great in terms of model building and development, when it comes to the business, when it comes to the client or a customer, it is super important for them to trust this platform, this algorithm. And that is where we are trying to build that momentum, bring that awareness. One of my colleagues has written this book "Trustworthy AI". We're trying to take the message out to the market to say, there is a framework. We can help you get there. And certainly that's what we are doing. >> Just call Deloitte up and you're going to take care of them. >> Manoj: Yeah. >> On the Amazon side, Amazon Web Services. I always interview Swami every year at re:Invent and he always get the updates. He's been bullish on this for a long time on this Conversational AI. What's the update on the AWS side? Where are you guys at? What's the current trends that you're riding? What wave are you riding right now? >> So some of the trends we see in customer interest, there's a couple of things. One is the multimodal interfaces we we're just chatting about where the voice IVA is synced with like a web or mobile experience, so you take that full advantage of the device. The other is adding additional AI into the Conversational AI. So one example is a customer that included intelligent document processing as part of the chatbot. So instead of typing your name and address, take a photo of your driver's license. It was an insurance onboarding chatbot, so you could take a photo of your existing insurance policy. It'll extract that information to build the new insurance policy. So folks get excited about that. And the third area we see interest is what's called multi-bot orchestration. And this is where you can have one main chatbot. Marshall user across different sub-chatbots based on the use case persona or even language. So those things get people really excited and then AWS is launching all sorts of new features. I don't know which one is coming out. >> I know something's coming out tomorrow. He's right at corner. He's big smile on his face. He wouldn't tell me. It's good. >> We have for folks like the closer alliance relationships, we we're able to get previews. So there a preview of all the new stuff. And I don't know what I could, it's pretty exciting stuff. >> You get in trouble if you spill the beans here. Don't, be careful. I'll watch you. We'll talk off camera. All exciting stuff. >> Yeah, yeah. I think the orchestrator bot is interesting. Having the ability to orchestrate across different contextual datasets is interesting. >> One of the areas where it's particularly interesting is in financial services. Imagine a bank could have consumer accounts, merchant accounts, investment banking accounts. So if you were to chat with the chatbot and say I want to open account, well, which account do you mean? And so it's able to figure out that context to navigate folks to those sub-chatbots behind the scenes. And so it's pretty interesting style. >> Awesome. Manoj while we're here, take a minute to quickly give a plug for Deloitte. What your program's about? What customers should expect if they work with you guys on this project? Give a quick commercial for Deloitte. >> Yeah, no, absolutely. I mean, Deloitte has been continuing to lead the AI field organization effort across our client base. If you think about all the Fortune 100, Fortune 500, Fortune 2000 clients, we certainly have them where they are in advanced stages of multiple deployments for AI. And we look at it all the way from strategy to implementation to operational models. So clients don't have to do it alone. And we are continuing to build our ecosystem of relationships, partnerships like the alliances that we have with AWS, building the ecosystem of relationships with other emerging startups, to your point about how do you continue to innovate and bring those technologies to your clients in a trustworthy environment so that we can deliver it in production scale. That is essentially what we're driving. >> Well, Arte, there's a great conversation and the AI will take over from here as we end the segment. I see a a bot coming on theCUBE later and there might be CUBE be replaced with robots. >> Right, right, right, exactly. >> I'm John Furrier, calling from Palo Alto. >> Someday, CUBE bot. >> You can just say, Alexa do my demo for me or whatever it is. >> Or digital twin for John. >> We're going to have a robot on earlier do a CUBE interview and that's Dave Vellante. He'd just pipe his voice in and be fun. Well, thanks for coming on, great conversation. >> Thank you. Thanks for having us. >> CUBE coverage here at re:MARS in Las Vegas. Back to the event circle. We're back in the line. Got re:Inforce and don't forget re:Invent at the end of the year. CUBE coverage of this exciting show here. Machine learning, automation, robotics, space. That's MARS, it's re:MARS. I'm John Furrier. Thanks for watching. (gentle music)

Published Date : Jun 24 2022

SUMMARY :

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Omer Singer, Snowflake & Julie Chickillo, Guild Education | Snowflake Summit 2022


 

>>Hey everyone. Welcome back to the queue of Lisa Martin with Dave Valante and we're live in Vegas. This is snowflake summit, 22, their fourth annual event. A lot of people here, a lot of news, a lot to unpack so far, and this is only day, day one. We've got two guests here with us to talk about, uh, cyber security, a very important topic, please welcome Omar singer the head of cyber security strategy at snowflake and Julie Chilo VP of security at Guild education. Welcome. Thank >>You. Thank you >>For having all of >>Our favorite topics. Yeah. Oh >>One. It's not boring. >>You know this much and you have so much more to learn now. So here >>We go. Cybersecurity is, is not to say it's boring. Not boring is an understatement. Yeah. Omar, I wanna start with you so much news coming out today. Talk to us about what's new with cybersecurity. Workload is snowflakes. Flywheel of innovation just seems to be getting bigger and faster. >>Yeah. Yeah. Well, well, I'll tell you it's been a long road to get to where we are today. Um, my initial role at snowflake was to lead security engineering. So I've actually been using snowflake as the home for security data, basically from day one. And we saw that it worked, it worked really well. And we started hearing from customers that they were dealing with some of the same challenges that we faced as an internal security team. And we decided as snowflake that we wanna bring the benefits of the data cloud to cyber security teams at all of our customers. And that's what the workload is all about. >>Talk to us about the, the voice of the customer. Obviously we saw a lot of customer stories heard your customer. We're gonna be talking about Guild education in a minute, but in the voice of the customer, in terms of being influential, obviously you were an internal customer drinking that champagne like this tastes really good. This is better of the Flaco <laugh>, but how is the voice of the customer influential in terms of the, the cybersecurity workload, as we've seen the threat landscape change so much in the last two years alone? >>Sure, sure. And you know, security, it's a really hard problem. We like to think of it as a data problem. And when you start thinking about it, that way snowflake is re very relevant for it. But many security teams don't yet think about their challenge as a data challenge. And so they're struggling with a very fragmented data landscape. The facts are all over the place and they're not able to ask the kind of questions that they need to understand. Where are my risks? How are the bad guys gonna try to get into my network? And they can't reflect that to leadership to everybody that really cares about cyber security. This is a board level concern today without the unified data and without the analytics. Um, they really can't do any of that. And, and yeah, representing the customer is, is a big part of what I do. And we have great customers like, like Julie, who's been kind of with us on this journey. She's, she's a part of the movement. I mean, Julie, what, what has it been like, uh, for, for you? >>Oh, it's been, uh, it's been game changer for, for Guild for sure. When we first, uh, started, I didn't one, I didn't know this was a concept <laugh> so when I first started talking O me and, um, snowflake, uh, I had just heard through the grapevine that, that you could do, like, this was a thing you could use the data, you could get everything you needed in one place. And, um, it's been game changing for my team. Uh, we, we were in many different security tools. They were all isolated, siloed, and we're now able to move everything into one, uh, one area, uh, and get we're getting close to the one pane of glass, which I, um, I just heard was a mythical concept for >>Security for >>A long time. Yeah. For a long time. Um, so it's, uh, it's just been amazing and it's, uh, brought us closer to our data ops team. So I'm here this week, uh, with somebody from data ops, actually, that's awesome to help us out. >>So can you describe that further? I'm I'm, I'm, I'm amazed and skeptical the, the, the I'm imagining, you know, the Optiv chart that says eight, 8 million security tools on there, are you actually able, uh, describe how you're able to consolidate your tooling? >>So, one of, one of the biggest problem, one of the biggest problems we were facing initially was our SIM, um, the security incident and event management tool could not take anything from our DevSecOps tools. And so any security that we had in a developer pipeline was really isolated to that tool, and we could never get it into a SIM Sims just aren't meant they're not built to handle that they're built to handle, um, not, not really old school networks and, and data center traffic and everything I have is in the cloud. And so we were really, I, everything was isolated. So with snowflake, what we do is we, um, worked with our data ops team. We can move things from, um, like our, our scanning tools for, for the developer pipelines into snowflake. We can use then correlate different things such as, from like eight year ADP. Like if a, do you have somebody pushing code to production who's out on vacation, you can actually do that correlation with snowflake that was never available before. These are things we could never do before. And we're able to, um, just do correlations. You could not get in that you cannot get in a SIM. >>Why couldn't I just throw those into any old, you know, run of the mill cloud data warehouse? >>Well, you know, it's not just the scale, it's the complexity of the data. I think snowflake how we have the, the sche on read and then all of the kind of things that make snowflake really good for other departments turns out, works really well for security. And it's the ecosystem too. Nobody else has this ecosystem approach. You know, you heard on the keynote today that snowflake is the, this disrupting, um, the, the software application development, right? All, all that kind of focus. The tool consolidation doesn't need to mean that you only have one tool you can actually have best of breed, choose the tool you want. As long as the data's consolidated, you're not building more silos. And that's what our partners are doing. They're separating the application from the data. They're bringing the work to the data, and that's what you hear here. So Julie's team can still choose to use a variety of tools that get the job done, but all those tools are working off of the single source of truth. And that, that is unique to what snowflake >>Can enable. So we, we are Reiss. Uh, we should have asked you about Guild education, explain your, your, your organization. >>Oh, what does Guild do? Uh, so we're a late stage startup. Uh, we manage education as a benefit for, for large companies. So we, we house data from very large organizations with like their workforce and, and help students help, help their workforce go back to school. >>Okay. So unpacking some of the things you said, schema on Reed, but not necessarily no schema on, right. It's a little different, right. Because you're ingesting. Yeah. And then you're determining the scheme on read that's right. Right. Okay. So that makes it simple and fast for zoom, but you get data in and then you figure it out, bringing work to data. Can we just double click on that a little bit? Cuz I think when I think about that, we've heard terms like over the years bring compute to the data. That's what Hadoop was supposed to do. And it didn't, you know, it was like, everything was mm-hmm <affirmative> shoved. So what do you mean by that? How, how, what, what actually does that >>Mean? Yeah. So if you think about the traditional SAS solution, the vendor needed to invest in a data center and to have a data platform that would be scalable and robust because their service dependent on it and they couldn't trust that the customer would have that kind of data platform on the customer's side. What Snowflake's data cloud has done has democratized the data platform. So now you have startups to fortune 500 S the vendors, the customers, they're all uneven footing when it comes to the data platform. So now the vendors can say, bring your own snowflake. Why not? You know, and they can focus on building the best application to solve the real challenges that security teams have. But by the way, not only cybersecurity, we see this and for example, the, um, customer data space as well. So we're seeing more and more kind of SaaS industries seeing this approach and the applications are gonna come yeah. To the data platform of choice, uh, for the practitioner. >>Julie, can we talk about some of the outcomes that Guild education has achieved so far by working with this solution in terms of, we look at the threat landscape and how it's changed so much the last couple of years and how it's a matter of if, or sorry, when not, if I get hit with an attack, how, what are some of the key outcomes that a snowflake partnership and technology has enabled you to achieve? >>So the, the biggest one, again, it's around the Def sec ops program, um, where you see so many attacks these days happening in the code base. So you really have to be careful with your, your pipeline where the code's getting moved through, who has access, who can move code into production. Um, and these are so the, like if you're using GitHub or, um, like using a scanning tool called snake, they're, they're separate, like they're completely separate the only way that we can see who's moving code into production, or if there was a vulnerability or somebody turned off, the security tool is to move these logs, this data into snowflake, uh, and our engineering teams were already using snowflake. Uh, so that made it, that was an easy transition for us. I didn't have to go out and convince another team to support us somewhere else, but a great example where we were, we're seeing great, um, savings, not only in people time, but, but for security, um, we were having problems or the security or the <laugh>, the engineers were turning off our secure codes scanner. >>And we didn't find out until a little bit later. Uh, oh yeah. Yeah. So found out we, my team, we had a team, we spent about 160 hours going through a thousand pole requests manually. And I said, no, no more go find the go figure out where this data exists. We put it in a snowflake and we can create an automatic, uh, ping to the security team saying, Hey, they turned off the, the scanner, go check and see what, why did the scanner get turned off? So it's an immediate response from my team instead of finding out two months later. And this is just, isn't something you can do right now. That's you can't set it up. So, um, makes it so easy. Ping goes to slack. We can go to the, immediately to the engineering team and say, why did you >>Using using automation? >>Yeah. Did you, did you turn this off? Why did you turn it off? Get an exception in so one, it like helps with compliance, so we're not messing up our SOC two audit. Uh, and then two, from a security perspective, we are able to, to trust, but verify, um, which is a big part of the DevSecOps landscape, where they need code to move into production. They need a scan to run in under five minutes. My team can't be there to scan, you know, 10, like 10 times a day or a hundred times a day. So we have to automate all of that and then just get information as it comes in. >>Is it accurate to say that, um, you're not like shutting off your tools, you're just taking advantage of them and compressing the time to get value out of them or are you actually reducing the tool sets? >>No, we don't. Well, no, we, our goal wasn't to reduce the tool set. I mean, we did actually get rid of the SIM we were using. Uh, so we were partnering with one of, um, uh, snowflakes partners, um, >>Because yeah, but you still have a SIM, >>We still have it. It's just minimized what goes to the SIM, because most of what I care about, isn't actually going to a SIM. Yeah. It's all the other pieces that are in a cloud because we use all like, we're, we're a hundred percent in the cloud. I don't have servers, I don't have firewalls. We don't have routes routers or switches. So all the things I care about live in a cloud somewhere. And, and I want that information. And so a lot of times, um, especially when it comes to the engineering tools, they were already sending the information to snowflake or they're also interested. And so we're partnering like it's, we're doubling up on the use of the >>Data. Okay. And you couldn't get that outta your SIM. Maybe you're asking your SIM to do too much, or it just didn't deliver. >>No systems are built on search engines. You know, they don't, >>They, they can't do it. >>You kind of knew what you were looking for and you say, Hey, where did I see this? Where did I see that? Very different from data analytics and the kinds of question that security teams really want to ask. These are emergent properties. You need context, you need sequel, you need Python. That's how you ask the questions that security teams really want to ask the legacy Sims. They don't let you ask that kind of question. They weren't built with that in mind. And they're so expensive that by moving off of them, to this approach, you kind of pay for all these other solutions that, that then you can bring on. >>That seems to make the, what you just said. There was brilliant. It seems to make the customer conversation quite easy if they're saying, well, why should I replace my SIM? It's doing just fine. You just nailed it with, with what you said there. >>So, yeah. And we're, and we're seeing that happen extensively. And I'm excited that we have customers here at summit talking about their experience, moving off of a legacy SIM where the security team was off to the side, away from the rest of the company to a unified approach, the SIM and the other security solutions working on top of the snowflake and a collaboration between security and the data >>Team. So what does your security ecosystem look like? You've got SIM partners. Do you have identity access partners, endpoint partner. Absolutely. >>Describe that compliance automation ass. Yeah. We hear about companies really struggling to meet all the compliance requirements. Well, if all the data's already centralized, then I can kind of prove to my auditors and not just once a quarter, but once a day, I can make sure that all the environment is in compliance with whatever standard I have. So we see a lot of that cloud security is another big one because there's just 10 times more things happening in the cloud environment than in the data center. Everything is so heavily instrumented. And so we see cloud security solutions as significant as well. And the identity space, the list goes on and on. We do see the future being the entire security program uses connected applications with a single source of truth in the company's snowflake. And >>Would you say centralized, you, you it's logically centralized, right? I mean, it's virtually centralized, right? It's not, >>Well, that's >>Not shoved into one container, right? >>I mean, it's right. Well, that's the beauty of the data cloud, right? We, everybody that's on the data cloud is able to collaborate. And so whether it's in the same account or table or database, you know, that's really besides the point because all of the platform investments that snowflake is making on cross region, cross cloud collaboration means that once it's in snowflake, then it is unified and can be used together. But >>I think people misunderstand that sometimes. And BEWA made this point, uh, as the Christian about the global nature of, of snowflake and it's globally distributed, but it's logically a data cloud. >>Yeah. I like to call it one big database in the sky. You know, that's how I explain to security teams that are kind of new to the concept, but >>It's not, it's could be a lot of little databases, but it, but having the same framework, the same governance structure, the same security >>You're right. I think that's how it's achieved is what you're describing. You know, I think from the outcome, what the security team needs to know is that when there's some breach hitting the headline and they need to go to their leadership and say, I can assure you, we were not affected. They can be confident in that answer because they have access to the data, wherever it is in the world, they have access to ask you the questions they need to ask. >>And that confidence is critical. These days as that threat landscape just continues to change. Thank you both so much for joining us. Thank you. Talking about from a cyber security perspective, some of the things that are new, new at snowflake, what you guys are doing at Guild education and how you're really transforming the organization with the data cloud, we appreciate your insights. Thank you for having us. Thank you. Thanks you guys for our guests and Dave ante. I'm Lisa Martin. You're watching the queue live from Las Vegas on the show floor of snowflake summit 22. We'll be right back with our next guest.

Published Date : Jun 14 2022

SUMMARY :

Welcome back to the queue of Lisa Martin with Dave Valante and we're live in Vegas. You know this much and you have so much more to learn now. Omar, I wanna start with you so much news coming out today. And we decided as snowflake that we wanna bring the benefits of the data cloud to cyber This is better of the Flaco <laugh>, but how is the voice of the customer influential The facts are all over the place and they're not able to ask the kind of questions that they need to that you could do, like, this was a thing you could use the data, you could get everything you needed in one place. actually, that's awesome to help us out. And so any security that we had in a developer pipeline was doesn't need to mean that you only have one tool you can actually have best of breed, Uh, we should have asked you about Guild education, Uh, we manage education as And it didn't, you know, it was like, everything was mm-hmm <affirmative> shoved. So now you have startups to fortune 500 S the vendors, So the, the biggest one, again, it's around the Def sec ops program, um, where you see so many And this is just, isn't something you can do right now. to scan, you know, 10, like 10 times a day or a hundred times a Uh, so we were partnering with one of, So all the things I care about live Maybe you're asking your SIM to do too much, or it just didn't deliver. You know, they don't, You kind of knew what you were looking for and you say, Hey, where did I see this? That seems to make the, what you just said. And I'm excited that we have customers here at summit talking about Do you have identity access Well, if all the data's already centralized, then I can kind of prove to my auditors and We, everybody that's on the data cloud is able to collaborate. And BEWA made this point, uh, as the Christian about the You know, that's how I explain to security teams that are kind of new to the concept, They can be confident in that answer because they have access to the new at snowflake, what you guys are doing at Guild education and how you're really transforming the organization

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Shishir Shrivastava, TEKsystems & Devang Pandya, TEKsystems | Snowflake Summit 2022


 

>>Welcome back everyone to the Cube's live coverage of snowflake summit 22, we are live in Las Vegas. Caesar's forum, Lisa Martin, Dave Valante, Dave. This is day one of a lot of wall action on the, >>Yeah. A lot of content on day one. It, it feels like, you know, the, the reinvent fire hose yes. Of announcements feels like a little mini version of that. >>It does. That's a good, that's a good way of putting it. We've been unpacking a lot of the news. That's come out, stick around, lots more coming. We've got two guests joining us from tech systems global services. Please welcome Devon. Pania managing director and Shai Sheva of us senior and Shire. Shrivastava senior manager, guys. Great to have you on the cube. >>Thank you so much. Good to see you. And it's great to be in person. Finally, it's been a long UE, so excited to be here. >>Agree. The keynote this morning was not only standing room only, but there was an overflow area. >>Oh my goodness. We have a hard time getting in and it is unbelievable announcement that we have heard looking forward for an exciting time. Next two days here >>Absolutely exciting. The, the cannon shotgun of announcements this morning was amazing. The innovation that has been happening at snowflake and you know, this clearly as partner has been, it just seems like it's the innovation flywheel is getting faster and faster and faster. Talk to us a little bit, Devon about tech systems. Give us the audience a little bit of an overview of the company, and then talk to us about the partnership with snowflake. >>Sure. Thank you. Lisa tech system global services is a full stack global system integrator working with 8% of fortune 500 customers helping in accelerating their business as well as technology modernization journey. We have been a snowflake partner since 2019, and we are one of the highest accredited sales and technical certification with snowflake. And that's what we have earned as a elite partner or sorry, emerging partner with snowflake last year. And we are one of the top elite partner as well. >>Yeah. So since 2019, I mean, in the keynote this morning, Frank showed it. I think Christian showed it as well in terms of the amount of, of change innovation that's happened since 2019 Ellen, we were talking before we went live to share about the, the last two years, the acceleration of innovation cloud adoption digital transformation. The last two years is kind of knock your head back. You need a yeah. A whiplash collar to deal with that. Talk about what you've seen in the last three years, particularly with the partnership and how quickly they are moving and listening to their customers. >>Yeah. Yeah. I think last two years really has given pretty much every organization, including us and our customers a complete different perspective. And that's, that's the exact thing which Christian was talking about, you know, disruption, that's the that's that has been the core message, which we have seen and we've got it from the customers. And we have worked on that right from the get go. We have, you know, all our tools and technology. We are working hand in hand with snowflake in terms of our offerings, working with customers, we have tools. We talk about, you know, accelerators quote unquote that's that helps our customers, you know, to take it from on-prem systems to all the way to the snowflake data cloud and that too, you know, fraction of seconds. You talk about data, you talk about, you know, code conversion, you talk about data validation. So, you know, there are ample amount of things, you know, in terms of, you know, innovation, all workload, I've heard, you know, those are the buzzwords today, and those are like such an exciting time out here. >>So before the pandemic, you know, digital transformation, it was, it was sort of a thing, but it was, it was also a lot of complacency around it. And then of course, if you weren't in a digital business, you were out of the business and boom. So you talked to bang about the stack. You guys obviously do a lot in cloud migration. What's changed in cloud migration. And how is the stack evolving to accommodate that? >>That's a great question there when last two years, it's absolutely a game changer in terms of the digital transformation. Can we believe that 90% of world's data that we have produced and captured is in last two years? It's, isn't that amazing? Right. And what IDC is predicting by 20 25, 200 terabytes of data is going to be generated. And most of them is going to be unstructured. And what we are fascinated about is only 0.5% of unstructured data is currently analyzed by the organization to look at the immense opportunity in front of us and with Snowflake's data cloud, as well as some of the retail data cloud finance and healthcare data cloud launching, it's going to immensely help in processing that unstructured data and really bring life to the data in making organization and market leader. >>Quick, quick fall, if I could, why is, is such a small, why is so much data dark and not accessible to organizations? What's >>The, that's a, that's a great question. I think it's a legacy that we have been trained such a way that data has to be structured. It needs to be modeled, but last decade or so we have seen note it hasn't required that way. And all the social media data being generated, how we communicate in a world is all arm structure, right? We don't create structured data and put it into the CSV and things like that. It's just a natural human behavior. And I think that's where we see a lot of potential in mining that dataset and bringing, you know, AI ML capabilities from descriptive to diagnostic analysis, moving forward with prescriptive and predictive analytics. And that's what we heard from snowflake in Christian announce, Hey, machine learning workload is going to be the key lot of investment happening last 10 years. Now it's going to, you know, capitalize on those ROI in making quick decisions. >>Should you talk to me about those customer conversations? Obviously they have they've transformed and evolved considerably. Yeah. But for customers that have this tremendous amount of unstructured data, a lot of potential as you talked about dung, but there's gotta be, it's gotta be a daunting task. Oh yeah. But these days, every company has to be a data company to be successful, to be competitive and to deliver the experience that the demanding consumers expect. Yeah. How do you start with customers? Where do they start? What's that conversation like and how can tech systems help them get rid of that kind of that daunting iceberg, if you will and get around >>It. Yeah, yeah, yeah, exactly. And I think you got the right point there. Unstructured data is just the tip of the iceberg we are talking about and we have just scratched little surface of it, you know, it's it's and as the one was mentioning earlier, it's, it's gone out those days, you know, where we are talking about, you know, gigabytes of data or, you know, terabytes. Now we are talking about petabytes and Zab bytes of data, and there are so many, and that's, that's the data insight we are looking for and what else, you know, what best platform you can get better than, you know, snowflake data cloud. You have everything in there. You talk about programmability today. You know, Christian was talking about snow park, you know, that, that gives you all the cutting edge languages. You talk about Java, you talk about scale, you talk about Python, you know, all those languages. >>I mean, there were days when these languages, you need to bring that data to a separate platform, process it and then connect it. Now it is right there. You can connect it and just process it. So I think that's, that's the beginning. And to start the conversation, we always, you know, go ahead and talk to the customers and, you know, understand their perspective, know where they want to start, you know, what are their pain points and where they, they want to go, you know, what's their end goal, you know, how they want to pro proceed, you know, how they want to mature in terms of, you know, data agility and flexibility and you know, how do they want to offer their customers? So that's, that's the basically, you know, that's our, the path forward and that's how we see it. >>And just, >>Just to add on top of that, Dave, sorry about that. What we have seen with our customers, the legacy mindset of creating the data silos, primarily because it's not that they wanted it that way, but there were limitations in terms of either the infrastructure or the unlimited scalability and flexibility and accent extensibility, right? That's why those kind of, you know, work around has been built. But with snowflake unified data cloud platform, you have everything in unified platform and what we are telling our customers, we need to eliminate the Datalog. Yes, data is a new oil, but we need to make sure that you eliminate the Datalog within the enterprise, as well as outside the enterprise to really combine then and get a, you know, valuable insight to be the market leader. >>You know, when the cube started, it was 2010. And I remember we went to Hadoop world and it was a lot of excitement around big data and yes, and it turned out, it didn't quite live up to the expectations. That's an understatement, but we, we learned a lot and we made some strides and, and now we're sort of entering this, this new era, but you know, the, the, the last era was largely this big batch job right now, today. You're seeing real time, you know, we've, we've projected out real time in, is gonna become more and more of a thing. How do you guys see the, the sort of data patterns changing and again, where do you see snowflake fitting in? >>Yeah. Great question. And they, what I would have to say, just in a one word is removing the complexity and moving towards the simplicity. Why the legacy solutions such as big data didn't really work out well, it had all the capabilities, but it was a complex environment. You need to really be, you know, knowing a lot of technical aspect of it. And your data analyst were struggling with that kind of a tool set. So with snowflake simplicity, you can bring citizen data scientists, you can bring your data scientists, you can bring your data analysts, all of them under one platform, and they can all mine the data because it's all sitting in the one environment, are >>You seeing organizations change the way they architect their data teams? And specifically, are you seeing a decentralization of data teams or you see, you mentioned citizen data scientists, are you seeing lines of business take more ownership of the data or is it still cuz again, that big data era created this data science role, the data engineering role, the data pipeline, and it was sort of an extension of the sort of EDW. We had a, a few people, maybe one or two experts who knew how to use the system and you build cubes. And it was sort of a, you know, in order of magnitude more complex than that could maybe do more, but are you seeing it being pushed out to the lines of business? >>That's a great question. And I think what we are seeing in the organization today is this time is absolutely both it and business coming together, hand in hand. It's not that, Hey, it, you do this data pipeline work. And then I will analyze this data. And then we'll, you know, share the dashboards to the CEO. We are seeing more and more cohesiveness within the organization in making a path forward in making the decision intelligence very, very rapid. So I think that's a great change. We don't need to operate in silos. I think it's coming together. And I think it's going to create a win-win combination for our >>Customers. Just to add one more point, what the one has mentioned. I think it's the world of data democratization we are talking about, you know, data is available there, insights. We need to pull it out and you know, just give it to every consumer of the organization and they're ready to consume it. They are, they are hungry. They are ready to take it. You know, that's, that's, that's something, you know, we need to look forward for. >>Well, absolutely look forward to it. And as you talked about, there's so much potential it's we see the tip of the iceberg, right? There's so much underneath that guys. I wish we had more time to continue unpacking this, but thank you so much for joining Dave and me on the program, talking about tech systems and snowflake, what you guys are doing together and what you're enabling those end customers to achieve. We appreciate your insights. >>Yeah. Thank you so much. It's an exciting time for us. And we have been, you know, partnering with snowflake on retail data cloud launch, as well as some upcoming opportunity with manufacturing and also the financial competency that we have earned. So I think it's a great time for us ahead in future. So >>Excellent. Lots to come from Texas systems guys. Thank you. We appreciate your time. Thank you. >>Appreciate it. Thank you. Let it snow. I would say let >>It snow, snow. Let it snow. I like that. You're heard of your life from hot Las Vegas for our guests and Dave ante. I'm Lisa Martin. We are live in Las Vegas. It's not snowing. It's very hot here. We're at the snowflake summit, 22 covering that stick around Dave and I will be joined where next guests in just a moment.

Published Date : Jun 14 2022

SUMMARY :

Welcome back everyone to the Cube's live coverage of snowflake summit 22, It, it feels like, you know, the, the reinvent fire hose yes. Great to have you on the cube. Thank you so much. The keynote this morning was not only standing room only, but there was an overflow area. We have a hard time getting in and it is unbelievable announcement that we have The innovation that has been happening at snowflake and you know, this clearly as partner has been, And we are one of the top elite partner as well. I think Christian showed it as well in terms of the amount of, of change innovation that's happened since that's the exact thing which Christian was talking about, you know, disruption, that's the that's that has been the So before the pandemic, you know, digital transformation, it was, it was sort of a thing, And most of them is going to be unstructured. in mining that dataset and bringing, you know, AI ML capabilities from descriptive a lot of potential as you talked about dung, but there's gotta be, it's gotta be a daunting task. of the iceberg we are talking about and we have just scratched little surface of it, you know, it's it's and as the one was mentioning And to start the conversation, we always, you know, go ahead and talk to the customers and, That's why those kind of, you know, work around has been built. and now we're sort of entering this, this new era, but you know, the, the, the last era was largely this big you know, knowing a lot of technical aspect of it. And it was sort of a, you know, in order of magnitude more And then we'll, you know, share the dashboards to the CEO. We need to pull it out and you know, And as you talked about, there's so much potential it's we see the And we have been, you know, partnering with snowflake on Lots to come from Texas systems guys. Let it snow. We're at the snowflake summit, 22 covering that stick around Dave and I will be

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Ahmad Khan, Snowflake & Kurt Muehmel, Dataiku | Snowflake Summit 2022


 

>>Hey everyone. Welcome back to the Cube's live coverage of snowflake summit 22 live from Las Vegas. Caesar's forum. Lisa Martin here with Dave Valante. We've got a couple of guests here. We're gonna be talking about every day. AI. You wanna know what that means? You're in the right spot. Kurt UL joins us, the chief customer officer at data ICU and the mod Conn, the head of AI and ML strategy at snowflake guys. Great to have you on the program. >>It's wonderful to be here. Thank you so much. >>So we wanna understand Kurt what everyday AI means, but before we do that for the audience who might not be familiar with data, I could give them a little bit of an overview. What about what you guys do your mission and maybe a little bit about the partnership? >>Yeah, great. Uh, very happy to do so. And thanks so much for this opportunity. Um, well, data IKU, we are a collaborative platform, uh, for enterprise AI. And what that means is it's a software, you know, that sits on top of incredible infrastructure, notably snowflake that allows people from different backgrounds of data, analysts, data, scientists, data, engineers, all to come together, to work together, to build out machine learning models and ultimately the AI that's gonna be the future, uh, of their business. Um, and so we're very excited to, uh, to be here, uh, and you know, very proud to be a, a, a very close partner of snowflake. >>So Amad, what is Snowflake's AI strategy? Is it to, is it to partner? Where do, where do you pick up? And Frank said today, we, we're not doing it all. Yeah. The ecosystem by design. >>Yeah. Yeah, absolutely. So we believe in the best of breed look. Um, I think, um, we, we think that we're the best data platform and for data science and machine learning, we want our customers to really use the best tool for their use cases. Right. And, you know, data ICU is, is our leading partner in that space. And so, you know, when, when you talk about, uh, machine learning and data science, people talk about training a model, but it's really the difficult part and challenges are really, before you train the model, how do you get access to the right data? And then after you train the model, how do you then run the model? And then how do you manage the model? Uh, that's very, very important. And that's where our partnership with, with data, uh, IKU comes in place. Snowflake provides the platform that can process data at scale for the pre-processing bit and, and data IKU comes in and really, uh, simplifies the process for deploying the models and managing the model. >>Got it. Thank >>You. You talk about KD data. Aico talks about everyday AI. I wanna break that down. What do you mean by that? And how is this partnership with snowflake empowering you to deliver that to companies? >>Yeah, absolutely. So everyday AI for us is, uh, you know, kind of a future state that we are building towards where we believe that AI will become so pervasive in all of the business processes, all the decision making that organizations have to go through that it's no longer this special thing that we talk about. It's just the, the day to day life of, uh, of our businesses. And we can't do that without partners like snowflake and, uh, because they're bringing together all of that data and ensuring that there is the, uh, the computational horsepower behind that to drive that we heard that this morning in some of the keynote talking about that broad democratization and the, um, let's call it the, uh, you know, the pressure that that's going to put on the underlying infrastructure. Um, and so ultimately everyday AI for us is where companies own that AI capability. They're building it themselves very broad, uh, participation in the development of that. And all that work then is being pushed down into best of breed, uh, infrastructure, notably of course, snowflake. Well, >>You said push down, you, you guys, you there's a term in the industry push down optimization. What does that mean? How is it evolving? Why is it so important? >>So Amma, do you want to take a first step at that? >>Yeah, absolutely. So, I mean, when, when you're, you know, processing data, so saying data, um, before you train a, uh, a model, you have to do it at scale, that that, that data is, is coming from all different sources. It's human generated machine generated data, we're talking millions and billions of rows of data. Uh, and you have to make sense of it. You have to transform that data into the right kind of features into the right kind of signals that inform the machine learning model that you're trying to, uh, train. Uh, and so that's where, you know, any kind of large scale data processing is automatically pushed down by data IQ, into snowflakes, scalable infrastructure. Um, so you don't get into like memory issues. You don't get into, um, uh, situations where you're where your pipeline is running overnight, and it doesn't finish in time. Right? And so, uh, you can really take advantage of the scalable nature of cloud computing, uh, using Snowflake's infrastructure. So a lot of that processing is actually getting pushed down from data I could down into the scalable snowflake compute engine. How >>Does this affect the life of a data scientist? You always hear a data scientist spend 80% of the time wrangling data. Uh, I presume there's an infrastructure component around that you trying, we heard this morning, you're making infrastructure, my words, infrastructure, self serve, uh, does this directly address that problem and, and talk about that. And what else are you doing to address that 80% problem? >>It, it certainly does, right? Uh, that's how you solve for, uh, data scientists needing to have on demand access to computing resources, or of course, to the, uh, to the underlying data, um, is by ensuring that that work doesn't have to run on their laptop, doesn't have to run on some, you know, constrained, uh, physical machines, uh, in, in a data center somewhere. Instead it gets pushed down into snowflake and can be executed at scale with incredible parallelization. Now what's really, uh, I important is the ongoing development, uh, between the two products, uh, and within that technology. And so today snowflake, uh, announced the introduction of Python within snow park, um, which is really, really exciting, uh, because that really opens up this capability to a much wider audience. Now DataCo provides that both through a visual interface, um, in historically, uh, since last year through Java UDFs, but that's kind of the, the two extremes, right? You have people who don't code on one side, you know, very no code or a low code, uh, population, and then a very high code population. On the other side, this Python, uh, integration really allows us to, to touch really kind the, the fat center of the data science population, who, uh, who, for whom, you know, Python really is the lingua franca that they've been learning for, uh, for decades now. Sure. So >>Talking about the data scientist, I wanna elevate that a little bit because you both are enterprise customers, data ICO, and snowflake Kurt as the chief customer officer, obviously you're with customers all the time. If we look at the macro environment of all the challenges, companies have to be a data company these days, if you're not, you're not gonna be successful. It's how do we do that? Extract insights, value, action, take it. But I'm just curious if your customer conversations are elevating up to the C-suite or, or the board in terms of being able to get democratize access to data, to be competitive, new products, new services, we've seen tremendous momentum, um, on, on the, the part of customer's growth on the snowflake side. But what are you hearing from customers as they're dealing with some of these current macro pains? >>Yeah, no, I, I think it is the conversation today, uh, at that sea level is not only how do we, you know, leverage, uh, new infrastructure, right. You know, they they're, you know, most of them now are starting to have snowflake. I think Frank said, uh, you know, 50% of the, uh, fortune 500, so we can say most, um, have that in place. Um, but now the question is, how do we, how do we ensure that we're getting access to that data, to that, to that computational horsepower, to a broader group of people so that it becomes truly a transformational initiative and not just an it initiative, not just a technology initiative, but really a core business initiative. And that, that really has been a pivot. You know, I've been, you know, with my company now for almost eight years, right. Uh, and we've really seen a change in that discussion going from, you know, much more niche discussions at the team or departmental level now to truly corporate strategic level. How do we build AI into our corporate strategy? How do we really do that in practice? And >>We hear a lot about, Hey, I want to inject data into apps, AI, and machine intelligence into applications. And we've talked about, those are separate stacks. You got the data stack and analytics stack over here. You got the application development, stack the databases off in the corner. And so we see you guys bringing those worlds together. And my question is, what does that stack look like? I took a snapshot. I think it was Frank's presentation today. He had infrastructure at the lowest level live data. So infrastructure's cloud live data. That's multiple data sources coming in workload execution. You made some announcements there. Mm-hmm, <affirmative>, uh, to expend expand that application development. That's the tooling that is needed. Uh, and then marketplace, that's how you bring together this ecosystem. Yes. Monetization is how you turn data into data products and make money. Is that the stack, is that the new stack that's emerging here? Are you guys defining that? >>Absolutely. Absolutely. You talked about like the 80% of the time being spent by data scientists and part of that is actually discovering the right data. Right. Um, being able to give the right access to the right people and being able to go and discover that data. And so you, you, you go from that angle all the way to processing, training a model. And then all those predictions that are insights that are coming out of the model are being consumed downstream by data applications. And so the two major announcements I'm super excited about today is, is the ability to run Python, which is snow park, uh, in, in snowflake. Um, that will do, you know, you can now as a Python developer come and bring the processing to where the data lives rather than move the data out to where the processing lives. Right. Um, so both SQL developers, Python developers, fully enabled. Um, and then the predictions that are coming out of models that are being trained by data ICU are then being used downstream by these data applications for most of our customers. And so that's where number, the second announcement with streamlet is super exciting. I can write a complete data application without writing a single line of JavaScript CSS or HTML. I can write it completely in Python. It's it makes me super excited as, as a Python developer, myself >>And you guys have joint customers that are headed in this direction, doing this today. Where, where can you talk about >>That? Yeah, we do. Uh, you know, there's a few that we're very proud of. Um, you know, company, well known companies like, uh, like REI or emeritus. Um, but one that was mentioned today, uh, this morning by Frank again, uh, Novartis, uh, pharmaceutical company, you know, they have been extremely successful, uh, in accelerating their AI and ML development by expanding access to their data. And that's a combination of, uh, both the data ICU, uh, layer, you know, allowing for that work to be developed in that, uh, in that workspace. Um, but of course, without, you know, the, the underlying, uh, uh, platform of snowflake, right, they, they would not have been able to, to have re realized those, uh, those gains. And they were talking about, you know, very, very significant increases in inefficiency everything from data access to the actual model development to the deployment. Um, it's just really, really honestly inspiring to see. >>And it was great to see Novartis mentioned on the main stage, massive time to value there. We've actually got them on the program later this week. So that was great. Another joint customer, you mentioned re I we'll let you go, cuz you're off to do a, a session with re I, is that right? >>Yes, that's exactly right. So, uh, so we're going to be doing a fireside chat, uh, talking about, in fact, you know, much of the same, all of the success that they've had in accelerating their, uh, analytics, workflow development, uh, the actual development of AI capabilities within, uh, of course that, uh, that beloved brand. >>Excellent guys, thank you so much for joining Dave and me talking about everyday AI, what you're doing together, data ICO, and snowflake to empower organizations to actually achieve that and live it. We appreciate your insights. Thank you both. You guys. Thank you for having us for our guests and Dave ante. I'm Lisa Martin. You're watching the Cube's live coverage of snowflake summit 22 from Las Vegas. Stick around our next guest joins us momentarily.

Published Date : Jun 14 2022

SUMMARY :

Great to have you on the program. Thank you so much. What about what you guys do Um, and so we're very excited to, uh, to be here, uh, and you know, Where do, where do you pick up? And so, you know, when, Thank And how is this partnership with snowflake empowering you to deliver uh, you know, the pressure that that's going to put on the underlying infrastructure. Why is it so important? Uh, and so that's where, you know, any kind of And what else are you doing to address that 80% problem? You have people who don't code on one side, you know, very no code or a low code, Talking about the data scientist, I wanna elevate that a little bit because you both are enterprise customers, I think Frank said, uh, you know, 50% of the, uh, And so we see you guys Um, that will do, you know, you can now as a Python developer And you guys have joint customers that are headed in this direction, doing this today. And that's a combination of, uh, both the data ICU, uh, layer, you know, you go, cuz you're off to do a, a session with re I, is that right? you know, much of the same, all of the success that they've had in accelerating their, uh, analytics, Thank you both.

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