Harveer Singh, Western Union | Western Union When Data Moves Money Moves
(upbeat music) >> Welcome back to Supercloud 2, which is an open industry collaboration between technologists, consultants, analysts, and of course, practitioners, to help shape the future of cloud. And at this event, one of the key areas we're exploring is the intersection of cloud and data, and how building value on top of hyperscale clouds and across clouds is evolving, a concept we call supercloud. And we're pleased to welcome Harvir Singh, who's the chief data architect and global head of data at Western Union. Harvir, it's good to see you again. Thanks for coming on the program. >> Thanks, David, it's always a pleasure to talk to you. >> So many things stand out from when we first met, and one of the most gripping for me was when you said to me, "When data moves, money moves." And that's the world we live in today, and really have for a long time. Money has moved as bits, and when it has to move, we want it to move quickly, securely, and in a governed manner. And the pressure to do so is only growing. So tell us how that trend is evolved over the past decade in the context of your industry generally, and Western Union, specifically. Look, I always say to people that we are probably the first ones to introduce digital currency around the world because, hey, somebody around the world needs money, we move data to make that happen. That trend has actually accelerated quite a bit. If you look at the last 10 years, and you look at all these payment companies, digital companies, credit card companies that have evolved, majority of them are working on the same principle. When data moves, money moves. When data is stale, the money goes away, right? I think that trend is continuing, and it's not just the trend is in this space, it's also continuing in other spaces, specifically around, you know, acquisition of customers, communication with customers. It's all becoming digital, and it's, at the end of the day, it's all data being moved from one place or another. At the end of the day, you're not seeing the customer, but you're looking at, you know, the data that he's consuming, and you're making actionable items on it, and be able to respond to what they need. So I think 10 years, it's really, really evolved. >> Hmm, you operate, Western Union operates in more than 200 countries, and you you have what I would call a pseudo federated organization. You're trying to standardize wherever possible on the infrastructure, and you're curating the tooling and doing the heavy lifting in the data stack, which of course lessens the burden on the developers and the line of business consumers, so my question is, in operating in 200 countries, how do you deal with all the diversity of laws and regulations across those regions? I know you're heavily involved in AWS, but AWS isn't everywhere, you still have some on-prem infrastructure. Can you paint a picture of, you know, what that looks like? >> Yeah, a few years ago , we were primarily mostly on-prem, and one of the biggest pain points has been managing that infrastructure around the world in those countries. Yes, we operate in 200 countries, but we don't have infrastructure in 200 countries, but we do have agent locations in 200 countries. United Nations says we only have like 183 are countries, but there are countries which, you know, declare themselves countries, and we are there as well because somebody wants to send money there, right? Somebody has an agent location down there as well. So that infrastructure is obviously very hard to manage and maintain. We have to comply by numerous laws, you know. And the last few years, specifically with GDPR, CCPA, data localization laws in different countries, it's been a challenge, right? And one of the things that we did a few years ago, we decided that we want to be in the business of helping our customers move money faster, security, and with complete trust in us. We don't want to be able to, we don't want to be in the business of managing infrastructure. And that's one of the reasons we started to, you know, migrate and move our journey to the cloud. AWS, obviously chosen first because of its, you know, first in the game, has more locations, and more data centers around the world where we operate. But we still have, you know, existing infrastructure, which is in some countries, which is still localized because AWS hasn't reached there, or we don't have a comparable provider there. We still manage those. And we have to comply by those laws. Our data privacy and our data localization tech stack is pretty good, I would say. We manage our data very well, we manage our customer data very well, but it comes with a lot of complexity. You know, we get a lot of requests from European Union, we get a lot of requests from Asia Pacific every pretty much on a weekly basis to explain, you know, how we are taking controls and putting measures in place to make sure that the data is secured and is in the right place. So it's a complex environment. We do have exposure to other clouds as well, like Google and Azure. And as much as we would love to be completely, you know, very, very hybrid kind of an organization, it's still at a stage where we are still very heavily focused on AWS yet, but at some point, you know, we would love to see a world which is not reliant on a single provider, but it's more a little bit more democratized, you know, as and when what I want to use, I should be able to use, and pay-per-use. And the concept started like that, but it's obviously it's now, again, there are like three big players in the market, and, you know, they're doing their own thing. Would love to see them come collaborate at some point. >> Yeah, wouldn't we all. I want to double-click on the whole multi-cloud strategy, but if I understand it correctly, and in a perfect world, everything on-premises would be in the cloud is, first of all, is that a correct statement? Is that nirvana for you or not necessarily? >> I would say it is nirvana for us, but I would also put a caveat, is it's very tricky because from a regulatory perspective, we are a regulated entity in many countries. The regulators would want to see some control if something happens with a relationship with AWS in one country, or with Google in another country, and it keeps happening, right? For example, Russia was a good example where we had to switch things off. We should be able to do that. But if let's say somewhere in Asia, this country decides that they don't want to partner with AWS, and majority of our stuff is on AWS, where do I go from there? So we have to have some level of confidence in our own infrastructure, so we do maintain some to be able to fail back into and move things it needs to be. So it's a tricky question. Yes, it's nirvana state that I don't have to manage infrastructure, but I think it's far less practical than it said. We will still own something that we call it our own where we have complete control, being a financial entity. >> And so do you try to, I'm sure you do, standardize between all the different on-premise, and in this case, the AWS cloud or maybe even other clouds. How do you do that? Do you work with, you know, different vendors at the various places of the stack to try to do that? Some of the vendors, you know, like a Snowflake is only in the cloud. You know, others, you know, whether it's whatever, analytics, or storage, or database, might be hybrid. What's your strategy with regard to creating as common an experience as possible between your on-prem and your clouds? >> You asked a question which I asked when I joined as well, right? Which question, this is one of the most important questions is how soon when I fail back, if I need to fail back? And how quickly can I, because not everything that is sitting on the cloud is comparable to on-prem or is backward compatible. And the reason I say backward compatible is, you know, there are, our on-prem cloud is obviously behind. We haven't taken enough time to kind of put it to a state where, because we started to migrate and now we have access to infrastructure on the cloud, most of the new things are being built there. But for critical application, I would say we have chronology that could be used to move back if need to be. So, you know, technologies like Couchbase, technologies like PostgreSQL, technologies like Db2, et cetera. We still have and maintain a fairly large portion of it on-prem where critical applications could potentially be serviced. We'll give you one example. We use Neo4j very heavily for our AML use cases. And that's an important one because if Neo4j on the cloud goes down, and it's happened in the past, again, even with three clusters, having all three clusters going down with a DR, we still need some accessibility of that because that's one of the biggest, you know, fraud and risk application it supports. So we do still maintain some comparable technology. Snowflake is an odd one. It's obviously there is none on-prem. But then, you know, Snowflake, I also feel it's more analytical based technology, not a transactional-based technology, at least in our ecosystem. So for me to replicate that, yes, it'll probably take time, but I can live with that. But my business will not stop because our transactional applications can potentially move over if need to. >> Yeah, and of course, you know, all these big market cap companies, so the Snowflake or Databricks, which is not public yet, but they've got big aspirations. And so, you know, we've seen things like Snowflake do a deal with Dell for on-prem object store. I think they do the same thing with Pure. And so over time, you see, Mongo, you know, extending its estate. And so over time all these things are coming together. I want to step out of this conversation for a second. I just ask you, given the current macroeconomic climate, what are the priorities? You know, obviously, people are, CIOs are tapping the breaks on spending, we've reported on that, but what is it? Is it security? Is it analytics? Is it modernization of the on-prem stack, which you were saying a little bit behind. Where are the priorities today given the economic headwinds? >> So the most important priority right now is growing the business, I would say. It's a different, I know this is more, this is not a very techy or a tech answer that, you know, you would expect, but it's growing the business. We want to acquire more customers and be able to service them as best needed. So the majority of our investment is going in the space where tech can support that initiative. During our earnings call, we released the new pillars of our organization where we will focus on, you know, omnichannel digital experience, and then one experience for customer, whether it's retail, whether it's digital. We want to open up our own experience stores, et cetera. So we are investing in technology where it's going to support those pillars. But the spend is in a way that we are obviously taking away from the things that do not support those. So it's, I would say it's flat for us. We are not like in heavily investing or aggressively increasing our tech budget, but it's more like, hey, switch this off because it doesn't make us money, but now switch this on because this is going to support what we can do with money, right? So that's kind of where we are heading towards. So it's not not driven by technology, but it's driven by business and how it supports our customers and our ability to compete in the market. >> You know, I think Harvir, that's consistent with what we heard in some other work that we've done, our ETR partner who does these types of surveys. We're hearing the same thing, is that, you know, we might not be spending on modernizing our on-prem stack. Yeah, we want to get to the cloud at some point and modernize that. But if it supports revenue, you know, we'll invest in that, and get the, you know, instant ROI. I want to ask you about, you know, this concept of supercloud, this abstracted layer of value on top of hyperscale infrastructure, and maybe on-prem. But we were talking about the integration, for instance, between Snowflake and Salesforce, where you got different data sources and you were explaining that you had great interest in being able to, you know, have a kind of, I'll say seamless, sorry, I know it's an overused word, but integration between the data sources and those two different platforms. Can you explain that and why that's attractive to you? >> Yeah, I'm a big supporter of action where the data is, right? Because the minute you start to move, things are already lost in translation. The time is lost, you can't get to it fast enough. So if, for example, for us, Snowflake, Salesforce, is our actionable platform where we action, we send marketing campaigns, we send customer communication via SMS, in app, as well as via email. Now, we would like to be able to interact with our customers pretty much on a, I would say near real time, but the concept of real time doesn't work well with me because I always feel that if you're observing something, it's not real time, it's already happened. But how soon can I react? That's the question. And given that I have to move that data all the way from our, let's say, engagement platforms like Adobe, and particles of the world into Snowflake first, and then do my modeling in some way, and be able to then put it back into Salesforce, it takes time. Yes, you know, I can do it in a few hours, but that few hours makes a lot of difference. Somebody sitting on my website, you know, couldn't find something, walked away, how soon do you think he will lose interest? Three hours, four hours, he'll probably gone, he will never come back. I think if I can react to that as fast as possible without too much data movement, I think that's a lot of good benefit that this kind of integration will bring. Yes, I can potentially take data directly into Salesforce, but I then now have two copies of data, which is, again, something that I'm not a big (indistinct) of. Let's keep the source of the data simple, clean, and a single source. I think this kind of integration will help a lot if the actions can be brought very close to where the data resides. >> Thank you for that. And so, you know, it's funny, we sometimes try to define real time as before you lose the customer, so that's kind of real time. But I want to come back to this idea of governed data sharing. You mentioned some other clouds, a little bit of Azure, a little bit of Google. In a world where, let's say you go more aggressively, and we know that for instance, if you want to use Google's AI tools, you got to use BigQuery. You know, today, anyway, they're not sort of so friendly with Snowflake, maybe different for the AWS, maybe Microsoft's going to be different as well. But in an ideal world, what I'm hearing is you want to keep the data in place. You don't want to move the data. Moving data is expensive, making copies is badness. It's expensive, and it's also, you know, changes the state, right? So you got governance issues. So this idea of supercloud is that you can leave the data in place and actually have a common experience across clouds. Let's just say, let's assume for a minute Google kind of wakes up, my words, not yours, and says, "Hey, maybe, you know what, partnering with a Snowflake or a Databricks is better for our business. It's better for the customers," how would that affect your business and the value that you can bring to your customers? >> Again, I would say that would be the nirvana state that, you know, we want to get to. Because I would say not everyone's perfect. They have great engineers and great products that they're developing, but that's where they compete as well, right? I would like to use the best of breed as much as possible. And I've been a person who has done this in the past as well. I've used, you know, tools to integrate. And the reason why this integration has worked is primarily because sometimes you do pick the best thing for that job. And Google's AI products are definitely doing really well, but, you know, that accessibility, if it's a problem, then I really can't depend on them, right? I would love to move some of that down there, but they have to make it possible for us. Azure is doing really, really good at investing, so I think they're a little bit more and more closer to getting to that state, and I know seeking our attention than Google at this point of time. But I think there will be a revelation moment because more and more people that I talk to like myself, they're also talking about the same thing. I'd like to be able to use Google's AdSense, I would like to be able to use Google's advertising platform, but you know what? I already have all this data, why do I need to move it? Can't they just go and access it? That question will keep haunting them (indistinct). >> You know, I think, obviously, Microsoft has always known, you know, understood ecosystems. I mean, AWS is nailing it, when you go to re:Invent, it's all about the ecosystem. And they think they realized they can make a lot more money, you know, together, than trying to have, and Google's got to figure that out. I think Google thinks, "All right, hey, we got to have the best tech." And that tech, they do have the great tech, and that's our competitive advantage. They got to wake up to the ecosystem and what's happening in the field and the go-to-market. I want to ask you about how you see data and cloud evolving in the future. You mentioned that things that are driving revenue are the priorities, and maybe you're already doing this today, but my question is, do you see a day when companies like yours are increasingly offering data and software services? You've been around for a long time as a company, you've got, you know, first party data, you've got proprietary knowledge, and maybe tooling that you've developed, and you're becoming more, you're already a technology company. Do you see someday pointing that at customers, or again, maybe you're doing it already, or is that not practical in your view? >> So data monetization has always been on the charts. The reason why it hasn't seen the light is regulatory pressure at this point of time. We are partnering up with certain agencies, again, you know, some pilots are happening to see the value of that and be able to offer that. But I think, you know, eventually, we'll get to a state where our, because we are trying to build accessible financial services, we will be in a state that we will be offering those to partners, which could then extended to their customers as well. So we are definitely exploring that. We are definitely exploring how to enrich our data with other data, and be able to complete a super set of data that can be used. Because frankly speaking, the data that we have is very interesting. We have trends of people migrating, we have trends of people migrating within the US, right? So if a new, let's say there's a new, like, I'll give you an example. Let's say New York City, I can tell you, at any given point of time, with my data, what is, you know, a dominant population in that area from migrant perspective. And if I see a change in that data, I can tell you where that is moving towards. I think it's going to be very interesting. We're a little bit, obviously, sometimes, you know, you're scared of sharing too much detail because there's too much data. So, but at the end of the day, I think at some point, we'll get to a state where we are confident that the data can be used for good. One simple example is, you know, pharmacies. They would love to get, you know, we've been talking to CVS and we are talking to Walgreens, and trying to figure out, if they would get access to this kind of data demographic information, what could they do be better? Because, you know, from a gene pool perspective, there are diseases and stuff that are very prevalent in one community versus the other. We could probably equip them with this information to be able to better, you know, let's say, staff their pharmacies or keep better inventory of products that could be used for the population in that area. Similarly, the likes of Walmarts and Krogers, they would like to have more, let's say, ethnic products in their aisles, right? How do you enable that? That data is primarily, I think we are the biggest source of that data. So we do take pride in it, but you know, with caution, we are obviously exploring that as well. >> My last question for you, Harvir, is I'm going to ask you to do a thought exercise. So in that vein, that whole monetization piece, imagine that now, Harvir, you are running a P&L that is going to monetize that data. And my question to you is a there's a business vector and a technology vector. So from a business standpoint, the more distribution channels you have, the better. So running on AWS cloud, partnering with Microsoft, partnering with Google, going to market with them, going to give you more revenue. Okay, so there's a motivation for multi-cloud or supercloud. That's indisputable. But from a technical standpoint, is there an advantage to running on multiple clouds or is that a disadvantage for you? >> It's, I would say it's a disadvantage because if my data is distributed, I have to combine it at some place. So the very first step that we had taken was obviously we brought in Snowflake. The reason, we wanted our analytical data and we want our historical data in the same place. So we are already there and ready to share. And we are actually participating in the data share, but in a private setting at the moment. So we are technically enabled to share, unless there is a significant, I would say, upside to moving that data to another cloud. I don't see any reason because I can enable anyone to come and get it from Snowflake. It's already enabled for us. >> Yeah, or if somehow, magically, several years down the road, some standard developed so you don't have to move the data. Maybe there's a new, Mogli is talking about a new data architecture, and, you know, that's probably years away, but, Harvir, you're an awesome guest. I love having you on, and really appreciate you participating in the program. >> I appreciate it. Thank you, and good luck (indistinct) >> Ah, thank you very much. This is Dave Vellante for John Furrier and the entire Cube community. Keep it right there for more great coverage from Supercloud 2. (uplifting music)
SUMMARY :
Harvir, it's good to see you again. a pleasure to talk to you. And the pressure to do so is only growing. and you you have what I would call But we still have, you know, you or not necessarily? that I don't have to Some of the vendors, you and it's happened in the past, And so, you know, we've and our ability to compete in the market. and get the, you know, instant ROI. Because the minute you start to move, and the value that you can that, you know, we want to get to. and cloud evolving in the future. But I think, you know, And my question to you So the very first step that we had taken and really appreciate you I appreciate it. Ah, thank you very much.
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Wendi Whitmore, Palo Alto Networks | Palo Alto Networks Ignite22
>>The Cube presents Ignite 22, brought to you by Palo Alto Networks. >>Welcome back to Vegas. Guys. We're happy that you're here. Lisa Martin here covering with Dave Valante, Palo Alto Networks Ignite 22. We're at MGM Grand. This is our first day, Dave of two days of cube coverage. We've been having great conversations with the ecosystem with Palo Alto executives, with partners. One of the things that they have is unit 42. We're gonna be talking with them next about cyber intelligence. And the threat data that they get is >>Incredible. Yeah. They have all the data, they know what's going on, and of course things are changing. The state of play changes. Hold on a second. I got a text here. Oh, my Netflix account was frozen. Should I click on this link? Yeah. What do you think? Have you had a, it's, have you had a little bit more of that this holiday season? Yeah, definitely. >>Unbelievable, right? A lot of smishing going on. >>Yeah, they're very clever. >>Yeah, we're very pleased to welcome back one of our alumni to the queue. Wendy Whitmore is here, the SVP of Unit 42. Welcome back, Wendy. Great to have >>You. Thanks Lisa. So >>Unit 42 created back in 2014. One of the things that I saw that you said in your keynote this morning or today was everything old is still around and it's co, it's way more prolific than ever. What are some of the things that Unit 42 is seeing these days with, with respect to cyber threats as the landscape has changed so much the last two years alone? >>You know, it, it has. So it's really interesting. I've been responding to these breaches for over two decades now, and I can tell you that there are a lot of new and novel techniques. I love that you already highlighted Smishing, right? In the opening gate. Right. Because that is something that a year ago, no one knew what that word was. I mean, we, it's probably gonna be invented this year, right? But that said, so many of the tactics that we have previously seen, when it comes to just general espionage techniques, right? Data act filtration, intellectual property theft, those are going on now more than ever. And you're not hearing about them as much in the news because there are so many other things, right? We're under the landscape of a major war going on between Russia and Ukraine of ransomware attacks, you know, occurring on a weekly basis. And so we keep hearing about those, but ultimately these nations aid actors are using that top cover, if you will, as a great distraction. It's almost like a perfect storm for them to continue conducting so much cyber espionage work that like we may not be feeling that today, but years down the road, they're, the work that they're doing today is gonna have really significant impact. >>Ransomware has become a household word in the last couple of years. I think even my mom knows what it is, to some degree. Yeah. But the threat actors are far more sophisticated than they've ever written. They're very motivated. They're very well funded. I think I've read a stat recently in the last year that there's a ransomware attack once every 11 seconds. And of course we only hear about the big ones. But that is a concern that goes all the way up to the board. >>Yeah. You know, we have a stat in our ransomware threat report that talks about how often victims are posted on leak sites. And I think it's once every seven minutes at this point that a new victim is posted. Meaning a victim has had their data, a victim organization had their data stolen and posted on some leak site in the attempt to be extorted. So that has become so common. One of the shifts that we've seen this year in particular and in recent months, you know, a year ago when I was at Ignite, which was virtual, we talked about quadruple extortion, meaning four different ways that these ransomware actors would go out and try to make money from these attacks in what they're doing now is often going to just one, which is, I don't even wanna bother with encrypting your data now, because that means that in order to get paid, I probably have to decrypt it. Right? That's a lot of work. It's time consuming. It's kind of painstaking. And so what they've really looked to do now is do the extortion where they simply steal the data and then threaten to post it on these leak sites, you know, release it other parts of the web and, and go from there. And so that's really a blending of these techniques of traditional cyber espionage with intellectual property theft. Wow. >>How trustworthy are those guys in terms of, I mean, these are hackers, right? In terms of it's really the, the hacker honor system, isn't it? I mean, if you get compromised like that, you really beholden to criminals. And so, you >>Know, so that's one of the key reasons why having the threat intelligence is so important, right? Understanding which group that you're dealing with and what their likelihood of paying is, what's their modus operandi. It's become even more important now because these groups switch teams more frequently than NFL trades, you know, free agents during the regular season, right? Or players become free agents. And that's because their infrastructure. So the, you know, infrastructure, the servers, the systems that they're using to conduct these attacks from is actually largely being disrupted more from law enforcement, international intelligence agencies working together with public private partnerships. So what they're doing is saying, okay, great. All that infrastructure that I just had now is, is burned, right? It's no longer effective. So then they'll disband a team and then they'll recruit a new team and it's constant like mixing and matching in players. >>All that said, even though that's highly dynamic, one of the other areas that they pride themselves on is customer service. So, and I think it's interesting because, you know, when I said they're not wanting to like do all the decryption? Yeah. Cuz that's like painful techni technical slow work. But on the customer service side, they will create these customer service portals immediately stand one up, say, you know, hey it's, it's like an Amazon, you know, if you've ever had to return a package on Amazon for example, and you need to click through and like explain, you know, Hey, I didn't receive this package. A portal window pops up, you start talking to either a bot or a live agent on the backend. In this case they're hu what appeared to be very much humans who are explaining to you exactly what happened, what they're asking for, super pleasant, getting back within minutes of a response. And they know that in order for them to get paid, they need to have good customer service because otherwise they're not going to, you know, have a business. How, >>So what's the state of play look like from between nation states, criminals and how, how difficult or not so difficult is it for you to identify? Do you have clear signatures? My understanding in with Solar Winds it was a little harder, but maybe help us understand and help our audience understand what the state of play is right now. >>One of the interesting things that I think is occurring, and I highlighted this this morning, is this idea of convergence. And so I'll break it down for one example relates to the type of malware or tools that these attackers use. So traditionally, if we looked at a nation state actor like China or Russia, they were very, very specific and very strategic about the types of victims that they were going to go after when they had zero day. So, you know, new, new malware out there, new vulnerabilities that could be exploited only by them because the rest of the world didn't know about it. They might have one organization that they would target that at, at most, a handful and all very strategic for their objective. They wanted to keep that a secret as long as possible. Now what we're seeing actually is those same attackers going towards one, a much larger supply chain. >>So, so lorenzen is a great example of that. The Hafnia attacks towards Microsoft Exchange server last year. All great examples of that. But what they're also doing is instead of using zero days as much, or you know, because those are expensive to build, they take a lot of time, a lot of funding, a lot of patience and research. What they're doing is using commercially available tools. And so there's a tool that our team identified earlier this year called Brute Rael, C4 or BRC four for short. And that's a tool that we now know that nation state actors are using. But just two weeks ago we invested a ransomware attack where the ransomware actor was using that same piece of tooling. So to your point, yak can get difficult for defenders when you're looking through and saying, well wait, they're all using some of the same tools right now and some of the same approaches when it comes to nation states, that's great for them because they can blend into the noise and it makes it harder to identify as >>Quickly. And, and is that an example of living off the land or is that B BRC four sort of a homegrown hacker tool? Is it, is it a, is it a commercial >>Off the shelf? So it's a tool that was actually, so you can purchase it, I believe it's about 2,500 US dollars for a license. It was actually created by a former Red teamer from a couple well-known companies in the industry who then decided, well hey, I built this tool for work, I'm gonna sell this. Well great for Red teamers that are, you know, legitimately doing good work, but not great now because they're, they built a, a strong tool that has the ability to hide amongst a, a lot of protocols. It can actually hide within Slack and teams to where you can't even see the data is being exfiltrated. And so there's a lot of concern. And then now the reality that it gets into the wrong hands of nation state actors in ransomware actors, one of the really interesting things about that piece of malware is it has a setting where you can change wallpaper. And I don't know if you know offhand, you know what that means, but you know, if that comes to mind, what you would do with it. Well certainly a nation state actor is never gonna do something like that, right? But who likes to do that are ransomware actors who can go in and change the background wallpaper on a desktop that says you've been hacked by XYZ organization and let you know what's going on. So pretty interesting, obviously the developer doing some work there for different parts of the, you know, nefarious community. >>Tremendous amount of sophistication that's gone on the last couple of years alone. I was just reading that Unit 42 is now a founding member of the Cyber Threat Alliance includes now more than 35 organizations. So you guys are getting a very broad picture of today's threat landscape. How can customers actually achieve cyber resilience? Is it achievable and how do you help? >>So I, I think it is achievable. So let me kind of parse out the question, right. So the Cyber Threat Alliance, the J C D C, the Cyber Safety Review Board, which I'm a member of, right? I think one of the really cool things about Palo Alto Networks is just our partnerships. So those are just a handful. We've got partnerships with over 200 organizations. We work closely with the Ukrainian cert, for example, sharing information, incredible information about like what's going on in the war, sharing technical details. We do that with Interpol on a daily basis where, you know, we're sharing information. Just last week the Africa cyber surge operation was announced where millions of nodes were taken down that were part of these larger, you know, system of C2 channels that attackers are using to conduct exploits and attacks throughout the world. So super exciting in that regard and it's something that we're really passionate about at Palo Alto Networks in terms of resilience, a few things, you know, one is visibility, so really having a, an understanding of in a real, as much of real time as possible, right? What's happening. And then it goes into how you, how can we decrease operational impact. So that's everything from network segmentation to wanna add the terms and phrases I like to use a lot is the win is really increasing the time it takes for the attackers to get their work done and decreasing the amount of time it takes for the defenders to get their work done, right? >>Yeah. I I call it increasing the denominator, right? And the ROI equation benefit over or value, right? Equals equals or benefit equals value over cost if you can increase the cost to go go elsewhere, right? Absolutely. And that's the, that's the game. Yeah. You mentioned Ukraine before, what have we learned from Ukraine? I, I remember I was talking to Robert Gates years ago, 2016 I think, and I was asking him, yeah, but don't we have the best cyber technology? Can't we attack? He said, we got the most to lose too. Yeah. And so what have we learned from, from Ukraine? >>Well, I, I think that's part of the key point there, right? Is you know, a great offense essentially can also be for us, you know, deterrent. So in that aspect we have as an, as a company and or excuse me, as a country, as a company as well, but then as partners throughout all parts of the world have really focused on increasing the intelligence sharing and specifically, you know, I mentioned Ukrainian cert. There are so many different agencies and other sorts throughout the world that are doing everything they can to share information to help protect human life there. And so what we've really been concerned with, with is, you know, what cyber warfare elements are going to be used there, not only how does that impact Ukraine, but how does it potentially spread out to other parts of the world critical infrastructure. So you've seen that, you know, I mentioned CS rrb, but cisa, right? >>CISA has done a tremendous job of continuously getting out information and doing everything they can to make sure that we are collaborating at a commercial level. You know, we are sharing information and intelligence more than ever before. So partners like Mania and CrowdStrike, our Intel teams are working together on a daily basis to make sure that we're able to protect not only our clients, but certainly if we've got any information relevant that we can share that as well. And I think if there's any silver lining to an otherwise very awful situation, I think the fact that is has accelerated intelligence sharing is really positive. >>I was gonna ask you about this cause I think, you know, 10 or so years ago, there was a lot of talk about that, but the industry, you know, kind of kept things to themselves, you know, a a actually tried to monetize some of that private data. So that's changing is what I'm hearing from you >>More so than ever more, you know, I've, I mentioned I've been in the field for 20 years. You know, it, it's tough when you have a commercial business that relies on, you know, information to, in order to pay people's salaries, right? I think that has changed quite a lot. We see the benefit of just that continuous sharing. There are, you know, so many more walls broken down between these commercial competitors, but also the work on the public private partnership side has really increased some of those relationships. Made it easier. And you know, I have to give a whole lot of credit and mention sisa, like the fact that during log four J, like they had GitHub repositories, they were using Slack, they were using Twitter. So the government has really started pushing forward with a lot of the newer leadership that's in place to say, Hey, we're gonna use tools and technology that works to share and disseminate information as quickly as we can. Right? That's fantastic. That's helping everybody. >>We knew that every industry, no, nobody's spared of this. But did you notice in the last couple of years, any industries in particular that are more vulnerable? Like I think of healthcare with personal health information or financial services, any industries kind of jump out as being more susceptible than others? >>So I think those two are always gonna be at the forefront, right? Financial services and healthcare. But what's been really top of mind is critical infrastructure, just making sure right? That our water, our power, our fuel, so many other parts of right, the ecosystem that go into making sure that, you know, we're keeping, you know, houses heated during the winter, for example, that people have fresh water. Those are extremely critical. And so that is really a massive area of focus for the industry right now. >>Can I come back to public-private partnerships? My question is relates to regulations because the public policy tends to be behind tech, the technology industry as an understatement. So when you take something like GDPR is the obvious example, but there are many, many others, data sovereignty, you can't move the data. Are are, are, is there tension between your desire as our desire as an industry to share data and government's desire to keep data private and restrict that data sharing? How is that playing out? How do you resolve that? >>Well I think there have been great strides right in each of those areas. So in terms of regulation when it comes to breaches there, you know, has been a tendency in the past to do victim shaming, right? And for organizations to not want to come forward because they're concerned about the monetary funds, right? I think there's been tremendous acceleration. You're seeing that everywhere from the fbi, from cisa, to really working very closely with organizations to, to have a true impact. So one example would be a ransomware attack that occurred. This was for a client of ours within the United States and we had a very close relationship with the FBI at that local field office and made a phone call. This was 7:00 AM Eastern time. And this was an organization that had this breach gone public, would've made worldwide news. There would've been a very big impact because it would've taken a lot of their systems offline. >>Within the 30 minutes that local FBI office was on site said, we just saw this piece of malware last week, we have a decryptor for it from another organization who shared it with us. Here you go. And within 60 minutes, every system was back up and running. Our teams were able to respond and get that disseminated quickly. So efforts like that, I think the government has made a tremendous amount of headway into improving relationships. Is there always gonna be some tension between, you know, competing, you know, organizations? Sure. But I think that we're doing a whole lot to progress it, >>But governments will make exceptions in that case. Especially for something as critical as the example that you just gave and be able to, you know, do a reach around, if you will, on, on onerous regulations that, that ne aren't helpful in that situation, but certainly do a lot of good in terms of protecting privacy. >>Well, and I think there used to be exceptions made typically only for national security elements, right? And now you're seeing that expanding much more so, which I think is also positive. Right. >>Last question for you as we are wrapping up time here. What can organizations really do to stay ahead of the curve when it comes to, to threat actors? We've got internal external threats. What can they really do to just be ahead of that curve? Is that possible? >>Well, it is now, it's not an easy task so I'm not gonna, you know, trivialize it. But I think that one, having relationships with right organizations in advance always a good thing. That's a, everything from certainly a commercial relationships, but also your peers, right? There's all kinds of fantastic industry spec specific information sharing organizations. I think the biggest thing that impacts is having education across your executive team and testing regularly, right? Having a plan in place, testing it. And it's not just the security pieces of it, right? As security responders, we live these attacks every day, but it's making sure that your general counsel and your head of operations and your CEO knows what to do. Your board of directors, do they know what to do when they receive a phone call from Bloomberg, for example? Are they supposed supposed to answer? Do your employees know that those kind of communications in advance and training can be really critical and make or break a difference in an attack. >>That's a great point about the testing but also the communication that it really needs to be company wide. Everyone at every level needs to know how to react. Wendy, it's been so great having, >>Wait one last question. Sure. Do you have a favorite superhero growing up? >>Ooh, it's gotta be Wonder Woman. Yeah, >>Yeah, okay. Yeah, so cuz I'm always curious, there's not a lot of women in, in security in cyber. How'd you get into it? And many cyber pros like wanna save the world? >>Yeah, no, that's a great question. So I joined the Air Force, you know, I, I was a special agent doing computer crime investigations and that was a great job. And I learned about that from, we had an alumni day and all these alumni came in from the university and they were in flight suits and combat gear. And there was one woman who had long blonde flowing hair and a black suit and high heels and she was carrying a gun. What did she do? Because that's what I wanted do. >>Awesome. Love it. We >>Blonde >>Wonder Woman. >>Exactly. Wonder Woman. Wendy, it's been so great having you on the program. We, we will definitely be following unit 42 and all the great stuff that you guys are doing. Keep up the good >>Work. Thanks so much Lisa. Thank >>You. Day our pleasure. For our guest and Dave Valante, I'm Lisa Martin, live in Las Vegas at MGM Grand for Palo Alto Ignite, 22. You're watching the Cube, the leader in live enterprise and emerging tech coverage.
SUMMARY :
The Cube presents Ignite 22, brought to you by Palo Alto One of the things that they have is unit Have you had a, it's, have you had a little bit more of that this holiday season? A lot of smishing going on. Wendy Whitmore is here, the SVP One of the things that I saw that you said in your keynote this morning or I love that you already highlighted Smishing, And of course we only hear about the big ones. the data and then threaten to post it on these leak sites, you know, I mean, if you get compromised like that, you really So the, you know, infrastructure, the servers, the systems that they're using to conduct these attacks from immediately stand one up, say, you know, hey it's, it's like an Amazon, you know, if you've ever had to return a or not so difficult is it for you to identify? One of the interesting things that I think is occurring, and I highlighted this this morning, days as much, or you know, because those are expensive to build, And, and is that an example of living off the land or is that B BRC four sort of a homegrown for Red teamers that are, you know, legitimately doing good work, but not great So you guys are getting a very broad picture of today's threat landscape. at Palo Alto Networks in terms of resilience, a few things, you know, can increase the cost to go go elsewhere, right? And so what we've really been concerned with, with is, you know, And I think if there's any silver lining to an otherwise very awful situation, I was gonna ask you about this cause I think, you know, 10 or so years ago, there was a lot of talk about that, but the industry, And you know, I have to give a whole lot of credit and mention sisa, like the fact that during log four But did you notice in the last couple of years, making sure that, you know, we're keeping, you know, houses heated during the winter, is the obvious example, but there are many, many others, data sovereignty, you can't move the data. of regulation when it comes to breaches there, you know, has been a tendency in the past to Is there always gonna be some tension between, you know, competing, you know, Especially for something as critical as the example that you just And now you're seeing that expanding much more so, which I think is also positive. Last question for you as we are wrapping up time here. Well, it is now, it's not an easy task so I'm not gonna, you know, That's a great point about the testing but also the communication that it really needs to be company wide. Wait one last question. Yeah, How'd you get into it? So I joined the Air Force, you know, I, I was a special agent doing computer We Wendy, it's been so great having you on the program. For our guest and Dave Valante, I'm Lisa Martin, live in Las Vegas at MGM
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Krishnaprasath Hari & Sid Sharma, Hitachi Vantara | AWS re:Invent 2022
(upbeat music) >> Hello, brilliant cloud community, and welcome back to AWS re:Invent. We are here in Las Vegas, Nevada. I'm Savannah Peterson, joined by my co-host Dave Vellante. Dave, how you doing? >> I'm doing well, thanks, yeah. >> Yeah, I feel like... >> I'm hanging in there. >> you've got a lot of pep in your step today for the fourth day. >> I think my voice is coming back, actually. >> (laughs) Look at you, resilient. >> I was almost lost yesterday, yeah. >> Yeah. (laughs) >> So, I actually, at a Hitachi event one time almost completely lost my voice. The production guys pulled me off. They said, "You're done." (Savannah laughing) They gave me the hook. >> You got booted? >> Dave: Yeah, yeah. >> Yeah, yeah, you actually (laughs) got the hook, wow. >> So, I have good memories of Hitachi. >> I was going to say (Dave laughing) interesting that you mentioned Hitachi. Our two guests this morning are from Hitachi. Sid and KP, welcome to the show. >> Thank you. >> Savannah: How you guys doing? Looking great for day four. >> Great. Thank you. >> Great. >> Hanging in there. >> Thank you, Dave and Savannah. (Savannah laughing) >> Dave: Yeah, cool. >> Savannah: Yeah. (laughs) >> Yeah, it was actually a Pentaho thing, right? >> Oh, Pentaho? Yeah. >> Which kind of you guys into that software edge. It was right when you announced the name change to Hitachi Vantara, which is very cool. I had Brian Householder on. You remember Brian? >> Yeah, I know. >> He was explaining the vision, and yeah (indistinct). >> Yeah. Well, look at you a little Hitachi (indistinct). >> Yeah, I've been around a long time, yeah. >> Yeah, all right. (Dave laughing) >> Just a casual flex to start us off there, Dave. I love it. I love it. Sid, we've talked a lot on the show about delivering outcomes. It's a hot theme. Everyone wants to actually have tangible business outcomes from all of this. How are customers realizing value from the cloud? What does that mean? >> See, still 2007, 2008, it was either/or kind of architecture. Either I'm going to execute my use cases on cloud or I'm going to keep my use cases and outcomes through edge. But in the last four or five years and specifically we are in re:Invent, I would talk about AWS. Lot of the power of hyperscalers has been brought to edge. If you talk about the snowball family of AWS, if you talk about monitor on edge devices, if you talk about the entire server list being brought into Lambda coupled inside snowball, now the architecture premise, if I talk about logical shift is end. Now the customers are talking about executing the use cases between edge and cloud. So, there is a continuum rather than a binary bullion decision. So, if you are talking about optimizing a factory, earlier I'll do the analytics at cloud, and I'll do machine on edge. Now it is optimization of a factory outcome at scale across my entire manufacturing where edge, private cloud, AWS, hyperscalers, everything is a continuum. And the customer is not worried about where, which part of my data ops, network ops, server ops storage ops is being executed. >> Savannah: It's like (indistinct). >> The customer is enjoying the use cases. And the orchestration is abstracted through an industrial player like Hitachi working very collaboratively with AWS. So, that is how we are working on industrial use cases right now. >> You brought up manufacturing. I don't think there's been a hotter conversation around supply chain and manufacturing than there has been the last few years. I can imagine taking that guessing game out for customers is a huge deal for you guys. >> Big because if you look at the world today, right from a safety pin, to a cell phone jacket, to a cell phone, the entire supply chain is throttled. The supply chain is throttled because there are various choke points. >> Savannah: Yeah. >> And each choke points is surrounded by different kind of supply and geopolitical issues. >> Savannah: 100%. >> Now, if we talk about the wheat crisis happening because of the Ukraine-Russia war, but the wheat crisis actually creates a multiple string of impacts which impact everything. Silicon, now we talk about silicon, but we then forget about nickel. Nickel is also controlled in one part of that geopolitical conflict. So, everything is getting conflagrated into a very big supply issue. So, if your factories are not performing beyond optimum, if they are not performing at real, I'm, we are talking about factory, hyperscale of the factory. The factory needs to perform at hyperscale to provide what the world needs today. So, we are in a very different kind of a scenario. Some of the economists call it earlier the recession was because of a demand constraint. The demand used to go down. Today's recession is because the supply is going down. The demand is there, but the supply is going down. And there is a different kind of recession in the world. The supply is what is getting throttled. >> And the demand is somewhat unpredictable too. People, you know, retailers, they've... >> Especially right now. >> kind of messed up their inventory. And so, the data is still siloed. And that's where, you know, you get to, okay, can I have the same experience across clouds, on-prem, out to the edge? Kind of bust those silos. >> Yep. >> You know, I dunno if it's, it's certainly not entirely a data problem. There's (laughs), like you say, geopolitical and social issues. >> Savannah: There's so much complexity. >> But there's a data problem too. >> Yes. >> Big. >> So, I wonder if you could talk about your sort of view of, point of view on that cross-cloud, hybrid, out to the edge, what I call super cloud? >> Absolutely. So, today, if you look at how enterprises are adopting cloud or how they're leveraging cloud, it's not just a hosting platform, right? It is the platform from where they can draw business capabilities. You heard in the re:Invent that Amazon is coming up with a supply chain service out of the box in the cloud. That's the kind of capabilities that business wants to draw from cloud today. So, the kind of multicloud or like hybrid cloud, public cloud, private cloud, those are the things which are kind of going to be behind the scenes. At the end of the day, the cloud needs to be able to support businesses by providing their services closer to their consumers. So, the challenges are going to be there in terms of like reliability, resilience, cost, security. Those are the ones that, you know, many of the enterprises are grappling with in terms of the challenges. And the way to solve that, the way how we approach our customers and work with them is to be able to bring resilience into the cloud, into the services which are running in cloud, and by driving automation, making autonomous in everything that you do, how you are monitoring your services, how we are making it available, how we are securing it, how we are making it very cost-effective as well. It cannot be manually executed; it has to be automated. So, automation is the key in terms of making the services leveraged from all of this cloud. >> That's your value add. >> Absolutely. >> And how do I consume that value add? Is it sort of embedded into infrastructure? Is it a service layer on top? >> Yeah, so everything that we do today in terms of like how these services have to be provided, how the services have to be consumed, there has to be a modern operating model, right? I think this is where Hitachi has come up with what we are calling as Hitachi Application Reliability Center and Services. That is focusing on modern operating, modern ways of like, you know, how you support these cloud workloads and driving this automation. So, whether we provide a hyper-converged infrastructure that is going to be at the edge location, or we are going to be able to take a customer through the journey of modernization or migrating onto cloud, the operating model that is going to be able to establish the foundation on cloud and then to be able to operate with the right levels of reliability, security, cost is the key. And that's the value added service that we provide. And then the way we do that is essentially by looking at three principles: one, to look at the service in totality. Gone are the days you look at infrastructure separately, applications separately, data and security separately, right? >> Savannah: No more silos. >> No more silos. You look at it as a workload, and you look at it as a service. And number two is to make sure that the DevOps that you bring and what you do at the table is totally integrated and it's end to end. It's not a product team developing a feature and then ops team trying to keep the lights on. It has to be a common backlog with the error budget that looks at you know, product releases, product functionalities, and even what ops needs to do to evolve the product as well. And then the third is to make sure that reliability and resiliency is inbuilt. Cloud offers native durability, native availability. But if your service doesn't take advantage of that, it's kind of going to still be not available. So, how do you kind of ingrain and embed all of these things as a value add that we provide? >> There's a lot of noise. We've got hybrid cloud. We've got multicloud. We've got a lot going on. It adds to the complexity. How do you help customers solve that complexity as they begin their transformation journey? I mean, I'm sure you're working with the biggest companies, making really massive change. How do you guide them through that process? >> So, it is to look at the outcome working backwards, like what AWS does, right? Like, you know, how do you look at the business outcome? What is the value that you're looking to drive? Again, it's not to be pinned through one particular cloud. I know there is lot of technology choices that you can make and lot of deployment models that you can choose from. But at the end of the day, having a common operating model which is kind of like modern, agile, and it is kind of like keeping the outcomes in the mind, that is what we do with our customers to be able to create that operating model, which completes the transformation, by the way. And cloud is just one part of the LEGO blocks which provides that overall scheme and then the view for driving that overall transformation. >> So, let's paint a picture. Let's say you've got this resilient foundation; you've kind of helped the customers build that out. How do they turn that into value for their customers? Do you have any examples that you can share? That'd be great. >> Yeah, I can start with what we're doing for one of the, you know, world's largest facility, infrastructure, power, cooling, security, monitoring company that has their products deployed in 2,000 locations across the globe. For them, and always on business means you are monitoring the temperature. You are monitoring the safety of people who are within the facility, right? A temperature shift of one to two degree can affect even the sustainability goals of NARC, our customer, but also their end consumers. So, how do you monitor these kind of like critical parameters? How do you have a platform? >> Savannah: Great example, yeah. >> How you have cloud resources that are going to be always on, that are going to be reliable, that are going to be cost-effective as well is what we are doing for one of our customers. Sid can talk about another example as well. >> Great. >> Yeah, go for it, Sid. >> So, there are examples: rail. We are working with a group in England; it's called West Coast Partnership. And they had a edge device which was increasing in size. Now, this edge device was becoming big because the parameters which go into the edge device were increasing because of regulation and because the rail is part of national security infrastructure. We have worked with West Coast Partnership and Hitachi Rail, which is a group company, to create a miniaturization of this edge device, because if the size of the edge device is increasing on the train, then the weight of the train increases, and the speed profile, velocity profile, everything goes down. So, we have miniaturized the edge device. Secondly, all the data profiles, signal control, traction control, traction motors, direction control, timetable compliance, everything has been kept uniform. And we have done analytics on cloud. So, what is the behavior of the driver? What is a big breaking parameter of the driver? If the timetable has being missed, is there an erratic behavior being demonstrated by the driver to just meet the timetable? And the timetable is a pretty important criteria in rail because if you miss one, then... So, what we have done is we have created an edge-to-cloud environment where the entire rail analytics is happening. Similarly, in another group company, Hitachi Energy, they had a problem that arguably one of the largest transformer manufacturer in the world. The transformer is a pretty common name now because you're seeing what is happening in Ukraine. Russia went after the transformers and substations before the start of the winter so that their district heating can be meddled with. Now, the transformer, it had a lead time of 17 weeks before COVID. So, if you put me an order of a three-phase transformer, I can deliver it to you in 17 weeks. After and during COVID, the entire lead time increased to 57 to 58 weeks. In cases of a complex transformer, it even went up to something like two years. >> Savannah: Ooh! >> Now, they wanted to increase the productivity of their existing plant because there is only that much sheet metal, that much copper for solenoid, that much microprocessor and silicon. So, they wanted to increase the output of their factory from 95 to 105, 10 more transformers every day, which is 500 and, which is 3,650 every- >> Savannah: Year. >> Year. Now, to do that, we went to a very complex machine; it's called a guard machine. And we increased the productivity of the guard machine by just analyzing all the throttles and all the wastages which are happening there. There are multiple case studies because, see, Hitachi is an industrial giant with 105 years of body of work. KP and I just represent the tip of the digital tip of the arrow. But what we are trying to do through HARC, through industry cloud, through partnership with AWS is basically containerizing and miniaturizing our entire body of work into a democratized environment, an industrial app store, if I may say, where people can come and take their industrial outcomes at ease without worrying about their computational and network orchestration between edge and cloud. That's what we are trying to do. >> I love that analogy of an industrial app cloud. Makes it feel easier in decreasing the complexity of all the different things that everyone's factoring into making their products, whatever they're making. So, we have a new challenge here on theCUBE at AWS re:Invent, where we are looking for your 30-second hot take, your Instagram reel, sound bite. What's the most important story or theme either for you as a team or coming out of the show? You can ponder it for a second. >> It might be different. See, for me, it is industrial security. Industrial OT security should be the theme of the Western world. Western world is on the crosshairs of multiple bad actors. And the industrial security is in the chemical plants, is in the industrial plants, is in the power grids, is in our postal networks and our rail networks. They need to be secured; otherwise, we are geopolitically very weak. Gone are the days when anyone is going to pick up a battle with America or Western world on a field. The battle is going to be pretty clandestine on an cyber world. And that is why industrial security is very important. >> Critical infrastructure and protecting it. >> Absolutely. >> Well said, Sid. KP, what's your hot take? >> My take is going to be a modern operating model, which is going to complete the transformation and to be able to tap into business services from cloud. So, a modern operating model through HARC, that is going to be my take. >> Fantastic. Well, can't wait to see what comes out of Hitachi next. Sid, KP... >> KP: Thank you. >> thank you so much for being here. >> Sid: Thank you. >> Absolutely. >> Dave: Thanks, guys. >> Savannah: This is I could talk to you all about supply chain all day long. And thank all of you for tuning in to our continuous live coverage here from AWS re:Invent in fantastic Sin City. I'm Savannah. Oh, excuse me. With Dave Vellante, I'm Savannah Peterson. You're watching theCUBE, the leader in high tech coverage. (digital xylophone music)
SUMMARY :
Dave, how you doing? for the fourth day. I think my voice is They gave me the hook. (laughs) got the hook, wow. interesting that you mentioned Hitachi. Savannah: How you guys doing? Thank you. Thank you, Dave and Savannah. Yeah. announced the name change He was explaining the Well, look at you a little Yeah, I've been Yeah, all right. to start us off there, Dave. Lot of the power of hyperscalers The customer is enjoying the use cases. for customers is a huge deal for you guys. look at the world today, by different kind of supply of recession in the world. And the demand is And so, the data is still siloed. There's (laughs), like you say, So, the challenges are going to be there how the services have to be consumed, that the DevOps that you the biggest companies, What is the value that that you can share? You are monitoring the safety that are going to be always on, by the driver to just meet the timetable? the output of their factory of the guard machine by just of all the different things of the Western world. and protecting it. KP, what's your hot take? that is going to be my take. Well, can't wait to see what could talk to you all
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Day 4 Keynote Analysis | AWS re:Invent 2022
(upbeat music) >> Good morning everybody. Welcome back to Las Vegas. This is day four of theCUBE's wall-to-wall coverage of our Super Bowl, aka AWS re:Invent 2022. I'm here with my co-host, Paul Gillin. My name is Dave Vellante. Sanjay Poonen is in the house, CEO and president of Cohesity. He's sitting in as our guest market watcher, market analyst, you know, deep expertise, new to the job at Cohesity. He was kind enough to sit in, and help us break down what's happening at re:Invent. But Paul, first thing, this morning we heard from Werner Vogels. He was basically given a masterclass on system design. It reminded me of mainframes years ago. When we used to, you know, bury through those IBM blue books and red books. You remember those Sanjay? That's how we- learned back then. >> Oh God, I remember those, Yeah. >> But it made me think, wow, now you know IBM's more of a systems design, nobody talks about IBM anymore. Everybody talks about Amazon. So you wonder, 20 years from now, you know what it's going to be. But >> Well- >> Werner's amazing. >> He pulled out a 24 year old document. >> Yup. >> That he had written early in Amazon's evolution about synchronous design or about essentially distributed architectures that turned out to be prophetic. >> His big thing was nature is asynchronous. So systems are asynchronous. Synchronous is an illusion. It's an abstraction. It's kind of interesting. But, you know- >> Yeah, I mean I've had synonyms for things. Timeless architecture. Werner's an absolute legend. I mean, when you think about folks who've had, you know, impact on technology, you think of people like Jony Ive in design. >> Dave: Yeah. >> You got to think about people like Werner in architecture and just the fact that Andy and the team have been able to keep him engaged that long... I pay attention to his keynote. Peter DeSantis has obviously been very, very influential. And then of course, you know, Adam did a good job, you know, watching from, you know, having watched since I was at the first AWS re:Invent conference, at time was President SAP and there was only a thousand people at this event, okay? Andy had me on stage. I think I was one of the first guest of any tech company in 2011. And to see now this become like, it's a mecca. It's a mother of all IT events, and watch sort of even the transition from Andy to Adam is very special. I got to catch some of Ruba's keynote. So while there's some new people in the mix here, this has become a force of nature. And the last time I was here was 2019, before Covid, watched the last two ones online. But it feels like, I don't know 'about what you guys think, it feels like it's back to 2019 levels. >> I was here in 2019. I feel like this was bigger than 2019 but some people have said that it's about the same. >> I think it was 60,000 versus 50,000. >> Yes. So close. >> It was a little bigger in 2019. But it feels like it's more active. >> And then last year, Sanjay, you weren't here but it was 25,000, which was amazing 'cause it was right in that little space between Omicron, before Omicron hit. But you know, let me ask you a question and this is really more of a question about Amazon's maturity and I know you've been following them since early days. But the way I get the question, number one question I get from people is how is Amazon AWS going to be different under Adam than it was under Andy? What do you think? >> I mean, Adam's not new because he was here before. In some senses he knows the Amazon culture from prior, when he was running sales and marketing prior. But then he took the time off and came back. I mean, this will always be, I think, somewhat Andy's baby, right? Because he was the... I, you know, sent him a text, "You should be really proud of what you accomplished", but you know, I think he also, I asked him when I saw him a few weeks ago "Are you going to come to re:Invent?" And he says, "No, I want to leave this to be Adam's show." And Adam's going to have a slightly different view. His keynotes are probably half the time. It's a little bit more vision. There was a lot more customer stories at the beginning of it. Taking you back to the inspirational pieces of it. I think you're going to see them probably pulling up the stack and not just focused in infrastructure. Many of their platform services are evolved. Many of their, even application services. I'm surprised when I talk to customers. Like Amazon Connect, their sort of call center type technologies, an app layer. It's getting a lot. I mean, I've talked to a couple of Fortune 500 companies that are moving off Ayer to Connect. I mean, it's happening and I did not know that. So it's, you know, I think as they move up the stack, the platform's gotten more... The data centric stack has gotten, and you know, in the area we're working with Cohesity, security, data protection, they're an investor in our company. So this is an important, you know, both... I think tech player and a partner for many companies like us. >> I wonder the, you know, the marketplace... there's been a big push on the marketplace by all the cloud companies last couple of years. Do you see that disrupting the way softwares, enterprise software is sold? >> Oh, for sure. I mean, you have to be a ostrich with your head in the sand to not see this wave happening. I mean, what's it? $150 billion worth of revenue. Even though the growth rates dipped a little bit the last quarter or so, it's still aggregatively between Amazon and Azure and Google, you know, 30% growth. And I think we're still in the second or third inning off a grand 1 trillion or 2 trillion of IT, shifting not all of it to the cloud, but significantly faster. So if you add up all of the big things of the on-premise world, they're, you know, they got to a certain size, their growth is stable, but stalling. These guys are growing significantly faster. And then if you add on top of them, platform companies the data companies, Snowflake, MongoDB, Databricks, you know, Datadog, and then apps companies on top of that. I think the move to the Cloud is inevitable. In SaaS companies, I don't know why you would ever implement a CRM solution on-prem. It's all gone to the Cloud. >> Oh, it is. >> That happened 15 years ago. I mean, begin within three, five years of the advent of Salesforce. And the same thing in HR. Why would you deploy a HR solution now? You've got Workday, you've got, you know, others that are so some of those apps markets are are just never coming back to an on-prem capability. >> Sanjay, I want to ask you, you built a reputation for being able to, you know, forecast accurately, hit your plan, you know, you hit your numbers, you're awesome operator. Even though you have a, you know, technology degree, which you know, that's a two-tool star, multi-tool star. But I call it the slingshot economy. This is like, I mean I've seen probably more downturns than anybody in here, you know, given... Well maybe, maybe- >> Maybe me. >> You and I both. I've never seen anything like this, where where visibility is so unpredictable. The economy is sling-shotting. It's like, oh, hurry up, go Covid, go, go go build, build, build supply, then pull back. And now going forward, now pulling back. Slootman said, you know, on the call, "Hey the guide, is the guide." He said, "we put it out there, We do our best to hit it." But you had CrowdStrike had issues you know, mid-market, ServiceNow. I saw McDermott on the other day on the, on the TV. I just want to pay, you know, buy from the guy. He's so (indistinct) >> But mixed, mixed results, Salesforce, you know, Octa now pre-announcing, hey, they're going to be, or announcing, you know, better visibility, forward guide. Elastic kind of got hit really hard. HPE and Dell actually doing really well in the enterprise. >> Yep. >> 'Course Dell getting killed in the client. But so what are you seeing out there? How, as an executive, do you deal with such poor visibility? >> I think, listen, what the last two or three years have taught us is, you know, with the supply chain crisis, with the surge that people thought you may need of, you know, spending potentially in the pandemic, you have to start off with your tech platform being 10 x better than everybody else. And differentiate, differentiate. 'Cause in a crowded market, but even in a market that's getting tougher, if you're not differentiating constantly through technology innovation, you're going to get left behind. So you named a few places, they're all technology innovators, but even if some of them are having challenges, and then I think you're constantly asking yourselves, how do you move from being a point product to a platform with more and more services where you're getting, you know, many of them moving really fast. In the case of Roe, I like him a lot. He's probably one of the most savvy operators, also that I respect. He calls these speedboats, and you know, his core platform started off with the firewall network security. But he's built now a very credible cloud security, cloud AI security business. And I think that's how you need to be thinking as a tech executive. I mean, if you got core, your core beachhead 10 x better than everybody else. And as you move to adjacencies in these new platforms, have you got now speedboats that are getting to a point where they are competitive advantage? Then as you think of the go-to-market perspective, it really depends on where you are as a company. For a company like our size, we need partners a lot more. Because if we're going to, you know, stand on the shoulders of giants like Isaac Newton said, "I see clearly because I stand on the shoulders giants." I need to really go and cultivate Amazon so they become our lead partner in cloud. And then appropriately Microsoft and Google where I need to. And security. Part of what we announced last week was, last month, yeah, last couple of weeks ago, was the data security alliance with the biggest security players. What was I trying to do with that? First time ever done in my industry was get Palo Alto, CrowdStrike, Wallace, Tenable, CyberArk, Splunk, all to build an alliance with me so I could stand on their shoulders with them helping me. If you're a bigger company, you're constantly asking yourself "how do you make sure you're getting your, like Amazon, their top hundred customers spending more with that?" So I think the the playbook evolves, and I'm watching some of these best companies through this time navigate through this. And I think leadership is going to be tested in enormously interesting ways. >> I'll say. I mean, Snowflake is really interesting because they... 67% growth, which is, I mean, that's best in class for a company that's $2 billion. And, but their guide was still, you know, pretty aggressive. You know, so it's like, do you, you know, when it when it's good times you go, "hey, we can we can guide conservatively and know we can beat it." But when you're not certain, you can't dial down too far 'cause your investors start to bail on you. It's a really tricky- >> But Dave, I think listen, at the end of the day, I mean every CEO should not be worried about the short term up and down in the stock price. You're building a long-term multi-billion dollar company. In the case of Frank, he has, I think I shot to a $10 billion, you know, analytics data warehousing data management company on the back of that platform, because he's eyeing the market that, not just Teradata occupies today, but now Oracle occupies or other databases, right? So his tam as it grows bigger, you're going to have some of these things, but that market's big. I think same with Palo Alto. I mean Datadog's another company, 75% growth. >> Yeah. >> At 20% margins, like almost rule of 95. >> Amazing. >> When they're going after, not just the observability market, they're eating up the sim market, security analytics, the APM market. So I think, you know, that's, you look at these case studies of companies who are going from point product to platforms and are steadily able to grow into new tams. You know, to me that's very inspiring. >> I get it. >> Sanjay: That's what I seek to do at our com. >> I get that it's a marathon, but you know, when you're at VMware, weren't you looking at the stock price every day just out of curiosity? I mean listen, you weren't micromanaging it. >> You do, but at the end of the day, and you certainly look at the days of earnings and so on so forth. >> Yeah. >> Because you want to create shareholder value. >> Yeah. >> I'm not saying that you should not but I think in obsession with that, you know, in a short term, >> Going to kill ya. >> Makes you, you know, sort of myopically focused on what may not be the right thing in the long term. Now in the long arc of time, if you're not creating shareholder value... Look at what happened to Steve Bomber. You needed Satya to come in to change things and he's created a lot of value. >> Dave: Yeah, big time. >> But I think in the short term, my comments were really on the quarter to quarter, but over a four a 12 quarter, if companies are growing and creating profitable growth, they're going to get the valuation they deserve. >> Dave: Yeah. >> Do you the... I want to ask you about something Arvind Krishna said in the previous IBM earnings call, that IT is deflationary and therefore it is resistant to the macroeconomic headwinds. So IT spending should actually thrive in a deflation, in a adverse economic climate. Do you think that's true? >> Not all forms of IT. I pay very close attention to surveys from, whether it's the industry analysts or the Morgan Stanleys, or Goldman Sachs. The financial analysts. And I think there's a gluc in certain sectors that will get pulled back. Traditional view is when the economies are growing people spend on the top line, front office stuff, sales, marketing. If you go and look at just the cloud 100 companies, which are the hottest private companies, and maybe with the public market companies, there's way too many companies focused on sales and marketing. Way too many. I think during a downsizing and recession, that's going to probably shrink some, because they were all built for the 2009 to 2021 era, where it was all about the top line. Okay, maybe there's now a proposition for companies who are focused on cost optimization, supply chain visibility. Security's been intangible, that I think is going to continue to an investment. So I tell, listen, if you are a tech investor or if you're an operator, pay attention to CIO priorities. And right now, in our business at Cohesity, part of the reason we've embraced things like ransomware protection, there is a big focus on security. And you know, by intelligently being a management and a security company around data, I do believe we'll continue to be extremely relevant to CIO budgets. There's a ransomware, 20 ransomware attempts every second. So things of that kind make you relevant in a bank. You have to stay relevant to a buying pattern or else you lose momentum. >> But I think what's happening now is actually IT spending's pretty good. I mean, I track this stuff pretty closely. It's just that expectations were so high and now you're seeing earnings estimates come down and so, okay, and then you, yeah, you've got the, you know the inflationary factors and your discounted cash flows but the market's actually pretty good. >> Yeah. >> You know, relative to other downturns that if this is not a... We're not actually not in a downturn. >> Yeah. >> Not yet anyway. It may be. >> There's a valuation there. >> You have to prepare. >> Not sales. >> Yeah, that's right. >> When I was on CNBC, I said "listen, it's a little bit like that story of Joseph. Seven years of feast, seven years of famine." You have to prepare for potentially your worst. And if it's not the worst, you're in good shape. So will it be a recession 2023? Maybe. You know, high interest rates, inflation, war in Russia, Ukraine, maybe things do get bad. But if you belt tightening, if you're focused in operational excellence, if it's not a recession, you're pleasantly surprised. If it is one, you're prepared for it. >> All right. I'm going to put you in the spot and ask you for predictions. Expert analysis on the World Cup. What do you think? Give us the breakdown. (group laughs) >> As my... I wish India was in the World Cup, but you can't get enough Indians at all to play soccer well enough, but we're not, >> You play cricket, though. >> I'm a US man first. I would love to see one of Brazil, or Argentina. And as a Messi person, I don't know if you'll get that, but it would be really special for Messi to lead, to end his career like Maradonna winning a World Cup. I don't know if that'll happen. I'm probably going to go one of the Latin American countries, if the US doesn't make it far enough. But first loyalty to the US team, and then after one of the Latin American countries. >> And you think one of the Latin American countries is best bet to win or? >> I don't know. It's hard to tell. They're all... What happens now at this stage >> So close, right? >> is anybody could win. >> Yeah. You just have lots of shots of gold. I'm a big soccer fan. It could, I mean, I don't know if the US is favored to win, but if they get far enough, you get to the finals, anybody could win. >> I think they get Netherlands next, right? >> That's tough. >> Really tough. >> But... The European teams are good too, but I would like to see US go far enough, and then I'd like to see Latin America with team one of Argentina, or Brazil. That's my prediction. >> I know you're a big Cricket fan. Are you able to follow Cricket the way you like? >> At god unearthly times the night because they're in Australia, right? >> Oh yeah. >> Yeah. >> I watched the T-20 World Cup, select games of it. Yeah, you know, I'm not rapidly following every single game but the World Cup games, I catch you. >> Yeah, it's good. >> It's good. I mean, I love every sport. American football, soccer. >> That's great. >> You get into basketball now, I mean, I hope the Warriors come back strong. Hey, how about the Warriors Celtics? What do we think? We do it again? >> Well- >> This year. >> I'll tell you what- >> As a Boston Celtics- >> I would love that. I actually still, I have to pay off some folks from Palo Alto office with some bets still. We are seeing unprecedented NBA performance this year. >> Yeah. >> It's amazing. You look at the stats, it's like nothing. I know it's early. Like nothing we've ever seen before. So it's exciting. >> Well, always a pleasure talking to you guys. >> Great to have you on. >> Thanks for having me. >> Thank you. Love the expert analysis. >> Sanjay Poonen. Dave Vellante. Keep it right there. re:Invent 2022, day four. We're winding up in Las Vegas. We'll be right back. You're watching theCUBE, the leader in enterprise and emerging tech coverage. (lighthearted soft music)
SUMMARY :
When we used to, you know, Yeah. So you wonder, 20 years from now, out to be prophetic. But, you know- I mean, when you think you know, watching from, I feel like this was bigger than 2019 I think it was 60,000 But it feels like it's more active. But you know, let me ask you a question So this is an important, you know, both... I wonder the, you I mean, you have to be a ostrich you know, others that are so But I call it the slingshot economy. I just want to pay, you or announcing, you know, better But so what are you seeing out there? I mean, if you got core, you know, pretty aggressive. I think I shot to a $10 billion, you know, like almost rule of 95. So I think, you know, that's, I seek to do at our com. I mean listen, you and you certainly look Because you want to Now in the long arc of time, on the quarter to quarter, I want to ask you about And you know, by intelligently But I think what's happening now relative to other downturns It may be. But if you belt tightening, to put you in the spot but you can't get enough Indians at all But first loyalty to the US team, It's hard to tell. if the US is favored to win, and then I'd like to see Latin America the way you like? Yeah, you know, I'm not rapidly I mean, I love every sport. I mean, I hope the to pay off some folks You look at the stats, it's like nothing. talking to you guys. Love the expert analysis. in enterprise and emerging tech coverage.
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Rob Enslin, UiPath & Daniel Dines, UiPath | UiPath Forward 5
>> Male: TheCUBE presents, UIPATH, Forward 5 brought to you by, UIPATH. >> Okay the party has started here at forward 5 UIPATH big customer event if you're watching the cube. We're wrapping up day one with the co-CE0 segment. Daniel Dines is here. He's the founder and Co-CEO of UIPATH and Rob Enslin, is co-CEO. Gents, great to see you. Thanks for spending some time with us. I know you're super busy. >> Thanks Dave. >> So I've been looking forward to this. Daniel you know I've followed the company for a long time. The really interesting path you took, to get to where you are today. How did you guys meet? And why did you decide to hire Rob? >> Male: (laughs) >> Rob: Well let me start. I uh, I was looking for a partner. Actually, in our work to your stand here, we are talking about how, how you feel in this job. You feel so alone. Because you are the center of all pressure points. And having a partner, having someone that has your back, it's kind of awesome. So I was looking for a partner. And our current friend, Carl Escenbach, he introduced us to each other, and we instantly clicked. And this is the type of job where it's uh either work well or it doesn't. It cannot be anything in the middle. >> Right, okay with Carl, we know Carl well. Awesome operator. Knows the business super well. So Rob, what attracted you to UIPATH? You had a great situation at google. You guys were growing like crazy. Why did you decide to come here? What did you see that attracted you? >> Yeah you know when I, when I went to google, I went to google because I really believed that data and AI was necessary for companies. And business is to be competitive in the future. And we did some great stuff at google cloud in the 3 years. But I knew UIPATH from a couple of years ago when they were mainly a RPA space. And I just felt that there was a place in time when automation was going expand. And as I sat down with Carl a couple of times, spoke to carl. And then I sat down with Daniel, I knew that there was something special with UIPATH, that could be a generational opportunity. Not any for myself but for the company in the future. And then I, you know I got to know Daniel. And at this stage of my career I was like, I'm pretty fussy about what I want to do and what I want and where I want to go. First of all, I want to go to a company that had great product, had a great culture, and I wanted to work with somebody that we could shake the future together and you know, Daniel and I just hit it off from the very first time we met. He got to meet my family, my dogs and we did the whole, we did the whole courting thing before we actually decided this was going to be a good thing for both of us. >> Dave: That's good. >> Rob: Yeah. >> Dave: You got to meet the family. That's very good. >> We just had, John Furrier and I just had, Mohit Aron and Sanjay Poonen into out studio. Cause Mohit, you know, formal google. Long time. And they decided to kind of split duties. Mohit's going into product, he didn't keep his CEO title. He walked. How are you guys splitting you time? What are each of you going to, responsible for? >> Daniel: Well its, its kind of similar. On a day by day operation I, I rely heavily on Rob. We do it together. Strategic decisions about the company's destiny. I'm doing mostly the product these days. Which is a big relief for me. And I think we also split a bit of customers visit. Which is great. I still enjoy meeting customers. I need, customers are food for my cause. >> Dave: (laughs) yeah and your awesome product visionary. You've been there since day one. Now Rob, you said in the key note today that you've seen around about a hundred customers. You've transverse the world. What did you learn from them that informed you? That gave you confidence that the the move to the internet platform, even though you had already started that. >> Male: Yeah. >> But you're really doubling down on that >> Rob: You know when I... >> from a stand point. >> Rob: You know Dave, when you think about it, like I was, I was so impressed that Daniel had the vision to create a platform 3 years ago. >> Dave: Yeah. >> All right. And as we went around the world. As I went around the world, and it was one of the very first things I've seen. I've got to understand how customers see UIPATH, from their advantage point. What are they looking for from us? Why is this company, why doe customers like this company so much? And as I went around the world. I went to Asia a couple, I went to Asia, Australia, Singapore, Japan. I was in Europe twice. We did the trip together. We went to visit customers. And it was very much the same thing. Helps us expand automation faster. And we are so surprise, at the break of your platform. We never knew that. And so it kind of just had, for me, it was conviction. It's like, this walls is the right decision you've made. There's so much opportunity there. And that's, you know that's kind of what I've learned through the last four five months. >> Dave: Now as you know Daniel, I've written a lot about your company. One of the things I've said is that, that start ups, if I can call you that back pre-IPO, typically don't have as much international exposure as UIPATH had. I mean you sort of, you sort of started as an international company and became more US centric. You said, in the, in the key note today, you're talking to Ray Wong about people may don't understand that challenges of FX. Point being, when you convert international dollars into US dollars there are less of them cause the dollars stronger. But still, I've always felt like that international footprint is an advantage. Rob you came from SAP, you know, again European based company. I don't, (stutters), do you regret that? Now? I mean I know it's technical, I'm sure you don't, but talk about that sort of international exposure? Why that's a long term benefit. >> Well, you, first of all, you expand faster. I think we expanded faster than our competition because our global footprint was larger. And we had the courage. Go in Japan, for instance. Everybody told me, it's impossible to make for such a small starter. It's impossible to make a business in Japan. But we didn't believe it. We're just crazy and we went there, and be built a very sizable business in Japan. Fifty-five percent of our revenue, even today, it's outside U.S. Now of course that has a down side. When uh, When the local currencies, you know, are losing the value compared to the dollars, we're impacted. As we go to... to investors, until now, so we are seeing like a (indistinct) in terms of ARI. It's huge. Only because (indistinct) and losing the business in Russia. But it still, it's the strength of our company. Things will come back. And then, you know, the growth engine will re-accelerate again. >> Dave: Yeah but when the dollars weakens that'll be in your favor. Rob I want to pick up on something you said today in your keynote. You went back and started, you know the cycles of ERP and you know, internet, et cetera. I kind of have a love hate with ERP. I have to be honest. >> Male: (laughing) >> But it, but but (chuckles) but if I go back to that. Late eighties nineties, you wouldn't have be able to pick SAP as the winner. And then SAP emerged. You know, very clearly. But the more interesting thing, is that the customers who are implementing ERP well. The practitioners did better than their peers, and dominated their industries. And their stocks went up. Their evaluations went up. Different worlds obviously but, do you see the same thing happening with RPA and automation? What gives you confidence that that's the case? >> I absolutely do see the same thing happening with automation and RPA being a part of, in being a part of that. The reason, the reason I believe that is speed is so critical. (stutters) And if you think about how hard it is for a CIO or a c level executive to consume the technology coming at them, plus all the changes in the world being thrown at them. It's compiling and compiling and compiling. We have an incredible solution, that can help companies. And there comes certain times, the love outcomes to the business. Like no one else gets. And when I see that, I view that as just like the beginning of what's going to happen in the future so, in many ways, and I've said this to many of my friends, it feels like 1992, 1993 to me. And it's interesting because no one really understood then why SAP would be great in 1992 and 93. And they got a couple of things right. They got the eco system right. Their new partners were important. And the knew they needed to drive business outcome for companies, in which they did. And so I feel like we are in a very similar place. Very different technology obviously. And the speed of change now is so dramatic, compared to what it was. And there's very few technology that can provide that level of speed and accomodation to their customers. >> All right, let's talk about priorities. You guys got a lot of work to do and you've, you've laid it out to the financial community. You've got to have profitable growth, because of FX, it part, you've lowered your forecast. But I think there's some conservative in their as well. Um, but you got to do that balance. You've given some guidance on gross margins. Cloud maybe brings that down a little bit. RnD I saw wide range. Thirteen to seventeen percent. I hope you keep spending on RnD. Big fan of that. You know stock buybacks and, RnD if in your position are going to be better. And the product priorities, continue to build that out. But question, let's start with the product. So you've got an on-prem stack and you've got a cloud stack that's emerging, how do you balance those out? How do you do the integration? You've done a great job with the integration. Does it, are you concerned about your ability to continue to work at that speed with two code bases? I wonder if you could address that? >> Daniel: We've become a cloud first company. We deliver all of our products first in the cloud. We've deliver on the two week (indistinct) in the cloud. So that helps us integrate quite fast. I think we made a very good business decision to build our cloud team in Seattle. In Bellevue to be specific. And we have access to great talent that knows how to build serious cloud service. Which is hard to find dollar. And uh, so, and also we, we have, we benef- one of our only benefits was, we have the really good architecture. We have an architecture that work easily on-prem and on the cloud. And even today, our work flow foundation, our local designers, were easy to modernize. So right now we are launching studio weapon. But behind the scene, it's the same workflow engine. Our customers don't have to rewrite anything. It just works. And it does the same to take our own brand product and brand it in the multicloud. So, it's, there is no friction at all. Actually cloud is just helping us accelerate. But we benefit then again of a really solid architectural foundation. >> Daniel: Architecture matters. We've seen that in this industry. We got the B52s rocking out in the background, I love it, but I've got so many questions for you guys. I want to talk about the go to market. Because Rob, it's obviously a strength of yours. You've come in. You've communicated to the street, that you're reshaping the sales floors. Are they lowering the ratios of sales? People, the customers at the high end, mid range as well, using digital. I mean the numbers are one to ten now. At the top. One to maybe fifty at the mid range. Where are you in terms of that journey? You've got to find people, you got to train them, how do you get the productivity out of those guys? Take us through your thinking there? >> Rob: Yeah firstly, I think we have enough resources. Having resources is not an issue. Um, we have an incredible vehicle to acquire customers inside the company. Our digital sales motion, it's probably the best I've seen. And so we have the ability to acquire customers really fast. And we get the first workload in really fast. The challenge is we need to, we need to be able to drive a (indistinct) model and we graduate customs when we acquire them into the direct sales floors. And then direct sales floors, we're not going to go one to thirty, we're talking one to ten for the direct sales floor. And even the high up in the pyramid, we want to have an even denser model than that. And the whole purpose is to drive the time to consumption much quicker, much faster. So we know exactly if we acquire a customer, will they spend? Do they have a (indistinct) spend? On what level do they have a (indistinct) spend? And therefore when we capture them, we can immediately surround them, and put the right resources so we can grow faster. We think this will have a significant impact on the organization. We'll start to implement certain pieces in the next quarter. Um, things like packaging solutions. Putting them in, enabling the sales organization. And buy the beginning of next year, we'll be ready to actually go full board, globally. We already put some pieces in place when I joined. Chris Weber, my chief business officer, did a great job doing some of those pieces. So we're on the journey already. >> Dave: Yeah and even before you guys were public and you weren't publishing your NRR numbers. Our ETR survey partner, we, we always thought you had very low churn. And I think you broke out just yesterday. The, the NRR for overseas vs U.S, U.S I think was 140 plus percent. >> Male: Yeah >> Very very strong. A little, a little less overseas but the churn is still very low. >> Male: Yep. >> Okay so that's super positive. Customer affinity, I was wanted to code these events. I listen to the key notes very carefully, and then interview customers on the cube, and I try to identify, is there alignment there? And I see very strong alignment, I have to say, and strong customer affinity. So that's in your favor. I have, Daniel, I got another question for you on product. What is Symantec automation? What the heck is that? Can you explain that? I don't understand >> Dave, have you seen the demo in my (indistinct)? >> Dave: You know, I had to leave and do interviews, so I, uh, I missed it. >> I think, I think that demo answer complete your question. So in the s-, you know there saying that great, you can not distinguish great technology by magic. I think technology should be simple. And we, we show today, one of the simplest demo that you can imagine. But it's so, such a complex technology behind the scene, that you also can not imagine. So what was demo? We show how one business user, without any technical skills, can build any type of document. Can be a passport, can be an invoice, can be a legal (indistinct), and just go, "I want to copy data from here, and I want to paste data there". Can be a spreadsheet, can be another obligation, and like a human user, without understanding, without having prior knowledge about data, document layout, about screens, screens layouts, nothing, we analyze real time. Document. We discover, we discover the meaning of the information. We analyze the screen. We understand the screen but we understand the meaning of the screen. And we understand how the information in one side relate to the other side. And we just connects the dots and we copy the information and we paste it. A job that you'll do as a human user, maybe three minutes, is done in ten seconds. This is powerful. >> Yeah that is powerful. Thank you for that. I mean, and you take the date, whether it's transaction data or unstructured data and and and bring meaning out of it. That's powerful. Last question and I'll let you guys go. Rob, you got traders, and you've got long term investors. All right traders going to be defensive, today. I get that. Make the case for UIPATH, for long term investors. >> Rob: I think we're going to be a multi-gern- multi-billion company and we're going to be a generational company of our time. And we will define enterprise automation. And it's going to be a long term game and we feel like really strong that we'll be the lead in that game. >> Dave: Guys, thanks so much for coming to the cube. Great show. Always fun at UiPath Forward. Really appreciate your time. Thank you. >> Thanks dave. >> Appreciate it as well. >> Okay wrap it up, day one, we're here tomorrow, first thing, Dave Vellante and Dave Nicholson. Thanks for watching, forward 5, Uipath big customer event, we'll see you tomorrow. (music)
SUMMARY :
brought to you by, UIPATH. Okay the party has started to get to where you are today. It cannot be anything in the middle. So Rob, what attracted you to UIPATH? And then I, you know I got to know Daniel. Dave: You got to meet the And they decided to kind of split duties. And I think we also split the move to the internet platform, that Daniel had the vision And that's, you know that's I mean you sort of, you sort of started When the local currencies, you know, I have to be honest. is that the customers who the love outcomes to the business. And the product priorities, And it does the same to I mean the numbers are one And so we have the ability to And I think you broke out just yesterday. but the churn is still very low. I listen to the key notes very carefully, to leave and do interviews, And we just connects the dots I mean, and you take the date, And it's going to be a long term game much for coming to the cube. we'll see you tomorrow.
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Adam Meyers, CrowdStrike | CrowdStrike Fal.Con 2022
>> We're back at the ARIA Las Vegas. We're covering CrowdStrike's Fal.Con 22. First one since 2019. Dave Vellante and Dave Nicholson on theCUBE. Adam Meyers is here, he is the Senior Vice President of Intelligence at CrowdStrike. Adam, thanks for coming to theCUBE. >> Thanks for having me. >> Interesting times, isn't it? You're very welcome. Senior Vice President of Intelligence, tell us what your role is. >> So I run all of our intelligence offerings. All of our analysts, we have a couple hundred analysts that work at CrowdStrike tracking threat actors. There's 185 threat actors that we track today. We're constantly adding more of them and it requires us to really have that visibility and understand how they operate so that we can inform our other products: our XDR, our Cloud Workload Protections and really integrate all of this around the threat actor. >> So it's that threat hunting capability that CrowdStrike has. That's what you're sort of... >> Well, so think of it this way. When we launched the company 11 years ago yesterday, what we wanted to do was to tell customers, to tell people that, well, you don't have a malware problem, you have an adversary problem. There are humans that are out there conducting these attacks, and if you know who they are what they're up to, how they operate then you're better positioned to defend against them. And so that's really at the core, what CrowdStrike started with and all of our products are powered by intelligence. All of our services are our OverWatch and our Falcon complete, all powered by intelligence because we want to know who the threat actors are and what they're doing so we can stop them. >> So for instance like you can stop known malware. A lot of companies can stop known malware, but you also can stop unknown malware. And I infer that the intelligence is part of that equation, is that right? >> Absolutely. That that's the outcome. That's the output of the intelligence but I could also tell you who these threat actors are, where they're operating out of, show you pictures of some of them, that's the threat intel. We are tracking down to the individual persona in many cases, these various threats whether they be Chinese nation state, Russian threat actors, Iran, North Korea, we track as I said, quite a few of these threats. And over time, we develop a really robust deep knowledge about who they are and how they operate. >> Okay. And we're going to get into some of that, the big four and cyber. But before we do, I want to ask you about the eCrime index stats, the ECX you guys call it a little side joke for all your nerds out there. Maybe you could explain that Adam >> Assembly humor. >> Yeah right, right. So, but, what is that index? You guys, how often do you publish it? What are you learning from that? >> Yeah, so it was modeled off of the Dow Jones industrial average. So if you look at the Dow Jones it's a composite index that was started in the late 1800s. And they took a couple of different companies that were the industrial component of the economy back then, right. Textiles and railroads and coal and steel and things like that. And they use that to approximate the overall health of the economy. So if you take these different stocks together, swizzle 'em together, and figure out some sort of number you could say, look, it's up. The economy's doing good. It's down, not doing so good. So after World War II, everybody was exuberant and positive about the end of the war. The DGI goes up, the oil crisis in the seventies goes down, COVID hits goes up, sorry, goes down. And then everybody realizes that they can use Amazon still and they can still get the things they need goes back up with the eCrime index. We took that approach to say what is the health of the underground economy? When you read about any of these ransomware attacks or data extortion attacks there are criminal groups that are working together in order to get things spammed out or to buy credentials and things like that. And so what the eCrime index does is it takes 24 different observables, right? The price of a ransom, the number of ransom attacks, the fluctuation in cryptocurrency, how much stolen material is being sold for on the underground. And we're constantly computing this number to understand is the eCrime ecosystem healthy? Is it thriving or is it under pressure? And that lets us understand what's going on in the world and kind of contextualize it. Give an example, Microsoft on patch Tuesday releases 56 vulnerabilities. 11 of them are critical. Well guess what? After hack Tuesday. So after patch Tuesday is hack Wednesday. And so all of those 11 vulnerabilities are exploitable. And now you have threat actors that have a whole new array of weapons that they can deploy and bring to bear against their victims after that patch Tuesday. So that's hack Wednesday. Conversely we'll get something like the colonial pipeline. Colonial pipeline attack May of 21, I think it was, comes out and all of the various underground forums where these ransomware operators are doing their business. They freak out because they don't want law enforcement. President Biden is talking about them and he's putting pressure on them. They don't want this ransomware component of what they're doing to bring law enforcement, bring heat on them. So they deplatform them. They kick 'em off. And when they do that, the ransomware stops being as much of a factor at that point in time. And the eCrime index goes down. So we can look at holidays, and right around Thanksgiving, which is coming up pretty soon, it's going to go up because there's so much online commerce with cyber Monday and such, right? You're going to see this increase in online activity; eCrime actors want to take advantage of that. When Christmas comes, they take vacation too; they're going to spend time with their families, so it goes back down and it stays down till around the end of the Russian Orthodox Christmas, which you can probably extrapolate why that is. And then it goes back up. So as it's fluctuating, it gives us the ability to really just start tracking what that economy looks like. >> Realtime indicator of that crypto. >> I mean, you talked about, talked about hack Wednesday, and before that you mentioned, you know, the big four, and I think you said 185 threat actors that you're tracking, is 180, is number 185 on that list? Somebody living in their basement in their mom's basement or are the resources necessary to get on that list? Such that it's like, no, no, no, no. this is very, very organized, large groups of people. Hollywood would have you believe that it's guy with a laptop, hack Wednesday, (Dave Nicholson mimics keyboard clacking noises) and everything done. >> Right. >> Are there individuals who are doing things like that or are these typically very well organized? >> That's a great question. And I think it's an important one to ask and it's both it tends to be more, the bigger groups. There are some one-off ones where it's one or two people. Sometimes they get big. Sometimes they get small. One of the big challenges. Have you heard of ransomware as a service? >> Of course. Oh my God. Any knucklehead can be a ransomwarist. >> Exactly. So we don't track those knuckleheads as much unless they get onto our radar somehow, they're conducting a lot of operations against our customers or something like that. But what we do track is that ransomware as a service platform because the affiliates, the people that are using it they come, they go and, you know, it could be they're only there for a period of time. Sometimes they move between different ransomware services, right? They'll use the one that's most useful for them that that week or that month, they're getting the best rate because it's rev sharing. They get a percentage that platform gets percentage of the ransom. So, you know, they negotiate a better deal. They might move to a different ransomware platform. So that's really hard to track. And it's also, you know, I think more important for us to understand the platform and the technology that is being used than the individual that's doing it. >> Yeah. Makes sense. Alright, let's talk about the big four. China, Iran, North Korea, and Russia. Tell us about, you know, how you monitor these folks. Are there different signatures for each? Can you actually tell, you know based on the hack who's behind it? >> So yeah, it starts off, you know motivation is a huge factor. China conducts espionage, they do it for diplomatic purposes. They do it for military and political purposes. And they do it for economic espionage. All of these things map to known policies that they put out, the Five Year Plan, the Made in China 2025, the Belt and Road Initiative, it's all part of their efforts to become a regional and ultimately a global hegemon. >> They're not stealing nickels and dimes. >> No they're stealing intellectual property. They're stealing trade secrets. They're stealing negotiation points. When there's, you know a high speed rail or something like that. And they use a set of tools and they have a set of behaviors and they have a set of infrastructure and a set of targets that as we look at all of these things together we can derive who they are by motivation and the longer we observe them, the more data we get, the more we can get that attribution. I could tell you that there's X number of Chinese threat groups that we track under Panda, right? And they're associated with the Ministry of State Security. There's a whole other set. That's too associated with the People's Liberation Army Strategic Support Force. So, I mean, these are big operations. They're intelligence agencies that are operating out of China. Iran has a different set of targets. They have a different set of motives. They go after North American and Israeli businesses right now that's kind of their main operation. And they're doing something called hack and lock and leak. With a lock and leak, what they're doing is they're deploying ransomware. They don't care about getting a ransom payment. They're just doing it to disrupt the target. And then they're leaking information that they steal during that operation that brings embarrassment. It brings compliance, regulatory, legal impact for that particular entity. So it's disruptive >> The chaos creators that's.. >> Well, you know I think they're trying to create a they're trying to really impact the legitimacy of some of these targets and the trust that their customers and their partners and people have in them. And that is psychological warfare in a certain way. And it, you know is really part of their broader initiative. Look at some of the other things that they've done they've hacked into like the missile defense system in Israel, and they've turned on the sirens, right? Those are all things that they're doing for a specific purpose, and that's not China, right? Like as you start to look at this stuff, you can start to really understand what they're up to. Russia very much been busy targeting NATO and NATO countries and Ukraine. Obviously the conflict that started in February has been a huge focus for these threat actors. And then as we look at North Korea, totally different. They're doing, there was a major crypto attack today. They're going after these crypto platforms, they're going after DeFi platforms. They're going after all of this stuff that most people don't even understand and they're stealing the crypto currency and they're using it for revenue generation. These nuclear weapons don't pay for themselves, their research and development don't pay for themselves. And so they're using that cyber operation to either steal money or steal intelligence. >> They need the cash. Yeah. >> Yeah. And they also do economic targeting because Kim Jong Un had said back in 2016 that they need to improve the lives of North Koreans. They have this national economic development strategy. And that means that they need, you know, I think only 30% of North Korea has access to reliable power. So having access to clean energy sources and renewable energy sources, that's important to keep the people happy and stop them from rising up against the regime. So that's the type of economic espionage that they're conducting. >> Well, those are the big four. If there were big five or six, I would presume US and some Western European countries would be on there. Do you track, I mean, where United States obviously has you know, people that are capable of this we're out doing our thing, and- >> So I think- >> That defense or offense, where do we sit in this matrix? >> Well, I think the big five would probably include eCrime. We also track India, Pakistan. We track actors out of Columbia, out of Turkey, out of Syria. So there's a whole, you know this problem is getting worse over time. It's proliferating. And I think COVID was also, you know a driver there because so many of these countries couldn't move human assets around because everything was getting locked down. As machine learning and artificial intelligence and all of this makes its way into the cameras at border and transfer points, it's hard to get a human asset through there. And so cyber is a very attractive, cheap and deniable form of espionage and gives them operational capabilities, not, you know and to your question about US and other kind of five I friendly type countries we have not seen them targeting our customers. So we focus on the threats that target our customers. >> Right. >> And so, you know, if we were to find them at a customer environment sure. But you know, when you look at some of the public reporting that's out there, the malware that's associated with them is focused on, you know, real bad people, and it's, it's physically like crypted to their hard drive. So unless you have sensor on, you know, an Iranian or some other laptop that might be target or something like that. >> Well, like Stuxnet did. >> Yeah. >> Right so. >> You won't see it. Right. See, so yeah. >> Well Symantec saw it but way back when right? Back in the day. >> Well, I mean, if you want to go down that route I think it actually came from a company in the region that was doing the IR and they were working with Symantec. >> Oh, okay. So, okay. So it was a local >> Yeah. I think Crisis, I think was the company that first identified it. And then they worked with Symantec. >> It Was, they found it, I guess, a logic controller. I forget what it was. >> It was a long time ago, so I might not have that completely right. >> But it was a seminal moment in the industry. >> Oh. And it was a seminal moment for Iran because you know, that I think caused them to get into cyber operations. Right. When they realized that something like that could happen that bolstered, you know there was a lot of underground hacking forums in Iran. And, you know, after Stuxnet, we started seeing that those hackers were dropping their hacker names and they were starting businesses. They were starting to try to go after government contracts. And they were starting to build training offensive programs, things like that because, you know they realized that this is an opportunity there. >> Yeah. We were talking earlier about this with Shawn and, you know, in the nuclear war, you know the Cold War days, you had the mutually assured destruction. It's not as black and white in the cyber world. Right. Cause as, as Robert Gates told me, you know a few years ago, we have a lot more to lose. So we have to be somewhat, as the United States, careful as to how much of an offensive posture we take. >> Well here's a secret. So I have a background on political science. So mutually assured destruction, I think is a deterrent strategy where you have two kind of two, two entities that like they will destroy each other if they so they're disinclined to go down that route. >> Right. >> With cyber I really don't like that mutually assured destruction >> That doesn't fit right. >> I think it's deterrents by denial. Right? So raising the cost, if they were to conduct a cyber operation, raising that cost that they don't want to do it, they don't want to incur the impact of that. Right. And think about this in terms of a lot of people are asking about would China invade Taiwan. And so as you look at the cost that that would have on the Chinese military, the POA, the POA Navy et cetera, you know, that's that deterrents by denial, trying to, trying to make the costs so high that they don't want to do it. And I think that's a better fit for cyber to try to figure out how can we raise the cost to the adversary if they operate against our customers against our enterprises and that they'll go someplace else and do something else. >> Well, that's a retaliatory strike, isn't it? I mean, is that what you're saying? >> No, definitely not. >> It's more of reducing their return on investment essentially. >> Yeah. >> And incenting them- disincening them to do X and sending them off somewhere else. >> Right. And threat actors, whether they be criminals or nation states, you know, Bruce Lee had this great quote that was "be like water", right? Like take the path of least resistance, like water will. Threat actors do that too. So, I mean, unless you're super high value target that they absolutely have to get into by any means necessary, then if you become too hard of a target, they're going to move on to somebody that's a little easier. >> Makes sense. Awesome. Really appreciate your, I could, we'd love to have you back. >> Anytime. >> Go deeper. Adam Myers. We're here at Fal.Con 22, Dave Vellante, Dave Nicholson. We'll be right back right after this short break. (bouncy music plays)
SUMMARY :
he is the Senior Vice Senior Vice President of Intelligence, so that we can inform our other products: So it's that threat hunting capability And so that's really at the core, And I infer that the intelligence that's the threat intel. the ECX you guys call it What are you learning from that? and positive about the end of the war. and before that you mentioned, you know, One of the big challenges. And it's also, you know, Tell us about, you know, So yeah, it starts off, you know and the longer we observe And it, you know is really part They need the cash. And that means that they need, you know, people that are capable of this And I think COVID was also, you know And so, you know, See, so yeah. Back in the day. in the region that was doing the IR So it was a local And then they worked with Symantec. It Was, they found it, I so I might not have that completely right. moment in the industry. like that because, you know in the nuclear war, you know strategy where you have two kind of two, So raising the cost, if they were to It's more of reducing their return and sending them off somewhere else. that they absolutely have to get into to have you back. after this short break.
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Kevin Mandia, Mandiant & Shawn Henry, CrowdStrike | CrowdStrike Fal.Con 2022
>>Welcome back to the aria in Las Vegas, Dave Valante with Dave Nicholson, Falcon 22, the Cube's continuous coverage. Sean Henry is here. He's the president of the services division and he's the chief security officer at CrowdStrike. And he's joined by Kevin mania, CEO of Mandy. Now part of Google Jens. Welcome to the cube. Thank you. Congrats on closing the Google deal. Thank you. That's great. New chapter, >>New >>Chapter coming fresh off the keynote, you and George. I really en enjoyed that. Let's start there. One of the things you talked about was the changes you've been, you've been in this business for a while. I think you were talking about, you know, doing some of these early stuff in the nineties. Wow. Things have changed a lot the queen, right? Right. You used to put the perimeter around the queen. Yeah. Build the Mo the Queen's left or castle new ballgame. But you were talking about the board level knowledge of security in the organization. Talk about that change. That's occurred in the last >>Decade. You know, boards are all about governance, right? Making sure everybody's doing the right things. And they've kind of had a haul pass on cybersecurity for a long time. Like we expect them to be great at financial diligence, they understand the financials of an organization. You're gonna see a maturity, I think in cybersecurity where I think board members all know, Hey, there's risk out there. And we're on our own to kind of defend ourselves from it, but they don't know how to quantify it. And they don't know how to express it. So bottom line boards are interested in cyber and we just have to mature as an industry to give them the tools they need to measure it appropriately. >>Sean, one of the things I wanted to ask you. So Steven Schmidt, I noticed changed his title from CISOs chief inf information security officer, the chief security officer. Your title is chief security officer. Is that a nuance that has meaning to you or is it just less acronym? >>It depends on the organization that you're in, in our organization, the chief security officer owns all risks. So I have a CISO that comes underneath me. Yep. And I've got a security folks that are handling our facilities, our personnel, those sorts of things, all, all of our offices around the globe. So it's all things security. One of the things that we've found and Kevin and I were actually talking about this earlier is this intersection between the physical world and the virtual world. And if you've got adversaries that want gain access to your organization, they might do it remotely by trying to hack into your network. But they also might try to get one of your employees to take an action on their behalf, or they might try to get somebody hired into your company to take some nefarious acts. So from a security perspective, it's about building an envelope around all things valuable and then working it in a collaborative way. So there's a lot of interface, a lot of interaction and a lot of value in putting those things together. And, >>And you're also president of the services division. Is that a P and L role or >>It is, we have a it's P P O P and L. And we have an entire organization that's doing incident response and it's a lot of the work that we're doing with, with Kevin's folks now. So I've got both of those hats today. >>Okay. So self-funded so in a way, okay. Where are companies most at risk today? >>Huh? You wanna go on that one first? Sean, you talk fast than me. So it's bigger bang for the buck. If >>You >>Talk, you know, when I, when I think about, about companies in terms of, of their risk, it's a lot of it has to do with the expansion of the network. Companies are adding new applications, new devices, they're expanding into new areas. There are new technologies that are being developed every day and that are being embraced every day. And all of those technologies, all of those applications, all of that hardware is susceptible to attack. Adversaries are looking for the vulnerabilities they can exploit. And I think just kind of that sprawl is something that is, is disconcerting to me from a security perspective, we need to know where our assets are, where the vulnerabilities lie, how do we plug the holes? And having that visibility is really critical to ensure that you're you're in, involved in mitigating that, that new architecture, >>Anything you >>Did. Yeah. I would like when I, so I can just tell you what I'm hearing from CISOs out there. They're worried about identity, the lateral movement. That's been kind of part of every impactful breach. So in identity's kind of top three of mind, I would say zero trust, whatever that means. And we all have our own definitions of migration to zero trust and supply chain risk. You know, whether they're the supplier, they wanna make sure they can prove to their customers, they have great security practices. Or if they're a consumer of a supply chain, you need to understand who's in their supply chain. What are their dependencies? How secure are they? Those are just three topics that come up all the time. >>As we extend, you know, talking about XDR the X being extend. Do you see physical security as something that's being extended into? Or is it, or is it already kind of readily accepted that physical security goes hand in hand with information security? >>I, I don't think a lot of people think that way there certainly are some and Dave mentions Amazon and Steve Schmidt as a CSO, right? There's a CSO that works for him as well. CJ's clear integration. There's an intelligence component to that. And I think that there are certain organizations that are starting to recognize and understand that when we say there's no real perimeter, it, it expands the network expands into the physical space. And if you're not protecting that, you know, if you don't protect the, the server room and somebody can actually walk in the doors unlocked, you've got a vulnerability that might be exploited. So I think to, to recognize the value of that integration from a security perspective, to be holistic and for organizations to adopt a security first philosophy that all the employees recognize they're, they're the, the first line of defense. Oftentimes not just from a fish, but by somebody catching up with them and handing 'em a thumb drive, Hey, can you take a look at this document? For me, that's a potential vulnerability as well. So those things need to be integrated. >>I thought the most interesting part of the keynote this morning is when George asked you about election security and you immediately went to the election infrastructure. I was like, yeah. Okay. Yeah. But then I was so happy to hear you. You went to the disinformation, I learned something there about your monitoring, the network effects. Sure. And, and actually there's a career stream around that. Right. The reason I had so years ago I interviewed was like, this was 2016, Robert Gates. Okay. Former defense. And I, I said, yeah, but don't we have the best cyber can't we go on the offense. He said, wait a minute, we have the most to lose. Right. But, but you gave an example where you can identify the bots. Like let's say there's disinformation out there. You could actually use bots in a positive way to disseminate the, the truth in theory. Good. Is, is that something that's actually happening >>Out there? Well, I think we're all still learning. You know, you can have deep fakes, both audible files or visual files, right. And images. And there's no question. The next generation, you do have to professionalize the news that you consume. And we're probably gonna have to professionalize the other side critical thinking because we are a marketplace of ideas in an open society. And it's hard to tell where's the line between someone's opinion and intentional deception, you know, and sometimes it could be the source, a foreign threat, trying to influence the hearts and minds of citizens, but there's gonna be an internal threat or domestic threat as well to people that have certain ideas and concepts that they're zealots about. >>Is it enough to, is it enough to simply expose where the information is coming from? Because, you know, look, I, I could make the case that the red Sox, right. Or a horrible baseball team, and you should never go to Fenway >>And your Yankees Jersey. >>Right. Right. So is that disinformation, is that misinformation? He'd say yes. Someone else would say no, but it would be good to know that a thousand bots from some troll farm, right. Are behind us. >>There's, it's helpful to know if something can be tied to identity or is totally anonymous. Start just there. Yeah. Yeah. You can still protect the identity over time. I think all of us, if you're gonna trust the source, you actually know the source. Right. So I do believe, and, and by the way, much longer conversation about anonymity versus privacy and then trust, right. And all three, you could spend this whole interview on, but we have to have a trustworthy internet as well. And that's not just in the tech and the security of it, but over time it could very well be how we're being manipulated as citizens and people. >>When you guys talk to customers and, and peers, when somebody gets breached, what's the number one thing that you hear that they wished they'd done that they didn't. >>I think we talked about this earlier, and I think identity is something that we're talking about here. How are you, how are you protecting your assets? How do you know who's authorized to have access? How do you contain the, the access that they have? And the, the area we see with, with these malware free attacks, where adversaries are using the existing capabilities, the operating system to move laterally through the network. I mean, Kevin's folks, my folks, when we respond to an incident, it's about looking at that lateral movement to try and get a full understanding of where the adversary's been, where they're going, what they're doing, and to try to, to find a root cause analysis. And it really is a, a critical part. >>So part of the reason I was asking you about, was it a P and L cuz you, you wear two hats, right? You've got revenue generation on one side and then you've got you protect, you know, the company and you've got peer relationships. So the reason I bring this up is I felt like when stucks net occurred, there was a lot of lip service around, Hey, we, as an industry are gonna work together. And then what you saw was a lot of attempts to monetize, you know, private data, sell private reports and things of that nature you were referencing today, Kevin, that you think the industry's doing a much better job of, of collaboration. Is it, can you talk about that and maybe give some examples? >>Absolutely. I mean, you know, I lived through it as a victim of a breach couple years ago. If you see something new and novel, I, I just can't imagine you getting away with keeping it a secret. I mean, I would even go, what are you doing? Harboring that if you have it, that doesn't mean you tell the whole world, you don't come on your show and say, Hey, we got something new novel, everybody panic, you start contacting the people that are most germane to fixing the problem before you tell the world. So if I see something that's new in novel, certainly con Sean and the team at CrowdStrike saying, Hey, there's because they protect so many endpoints and they defend nations and you gotta get to Microsoft. You have to talk to pan. You have to get to the companies that have a large capability to do shields up. And I think you do that immediately. You can't sit on new and novel. You get to the vendor where the vulnerability is, all these things have to happen at a great rate to speak. >>So you guys probably won't comment, but I'm betting dollars to donuts. This Uber lapses hack you guys knew about. >>I turned to you. >>No comment. I'm guessing. I'm guessing that the, that wasn't novel. My point being, let me, let me ask it in a more generic fashion that you can maybe comment you you're. I think you're my, my inference is we're com the industry is compressing the time between a zero day and a fix. Absolutely. Absolutely. Like dramatically. >>Yes. Oh, awareness of it and AIX. Yes. Yeah. >>Okay. Yeah. And a lot of the hacks that we see as lay people in the media you've known about for quite some time, is that fair or no, not necessarily. >>It's, you know, it's harder to handle an intrusion quietly and discreetly these days, especially with what you're up against and, and most CEOs, by the way, their intent isn't, let's handle it quietly and discreetly it's what do we do about it? And what's the right way to handle it. And they wanna inform their customers and they wanna inform people that might be impacted. I wouldn't say we know it all that far ahead of time >>And, and depends. And, and I, I think companies don't know it. Yeah. Companies don't know they've been breached for weeks or months or years in some cases. Right. Which talks about a couple things, first of all, some of the sophistication of the adversaries, but it also talks about the inability of companies to often detect this type of activity when we're brought in. It's typically very quickly after the company finds out because they recognize they've gotta take action. They've got liability, they've got brand protection. There, whole sorts of, of things they need to take care of. And we're brought in it may or may not be, become public, but >>CrowdStrike was founded on the premise that the unstoppable breach is a myth. Now that's a, that's a bold sort of vision. We're not there yet, obviously. And a and a, and a, a CSO can't, you know, accept that. Right. You've gotta always be vigilant, but is that something that is, that we're gonna actually see manifest, you know, in any, any time in the near term? I mean, thinking about the Falcon platform, you guys are users of that. I don't know if that is part of the answer, but part of it's technology, but without the cultural aspects, the people side of things, you're never gonna get there. >>I can tell you, I started Maning in 2004 at the premise security breaches are inevitable, far less marketable. Yeah. You know, stop breaches. >>So >>Yeah. I, I think you have to learn how to manage this, right? It's like healthcare, you're not gonna stop every disease, but there's a lot of things that you can do to mitigate the consequences of those things. The same thing with network security, there's a lot of actions that organizations can take to help protect them in a way that allows them to live and, and operate in a, in a, a strong position. If companies are lackadaisical that irresponsible, they don't care. Those are companies that are gonna suffer. But I think you can manage this if you're using the right technology, the right people, you've got the right philosophy security first >>In, in the culture. >>Well, I can tell you very quickly, three reasons why people think, why is there an intrusion? It should just go away. Well, wherever money goes, crime follows. We still have crime. So you're still gonna have intrusions, whether it has to be someone on the inside or faulty software and people being paid the right faulty software, you're gonna have war. That's gonna create war in the cyber domain. So information warriors are gonna try to have intrusions to get to command and control. So wherever you have command and control, you'll have a war fighter. And then wherever you have information, you have ESP Espino. So you're gonna have people trying to break in at all times. >>And, and to tie that up because everything Kevin said is absolutely right. And what he just said at the very end was people, there are human beings that are on the other side of every single attack. And think about this until you physically get physically get to the people that are doing it and stop them. Yes, this will go on forever because you can block them, but they're gonna move and you can block them again. They're gonna move their objectives. Don't change because the information you have, whether it's financial information, intellectual property, strategic military information, that's still there. They will always come at it, which is where that physical component comes in. If you're able to block well enough and they can't get you remotely, they might send somebody in. Well, >>I, in the keynote, I, I'm not kidding. I'm looking around the room and I'm thinking there's at least one person here that is here primarily to gather intelligence, to help them defeat. What's being talked about here. >>Well, you said it's, >>It's kind >>Of creepy. You said the adversary is, is very well equipped and motivated. Why do you Rob banks? Well, that's where the money is, but it's more than that. Now with state sponsored terrorism and, you know, exfiltration of state secrets, I mean, there's, it's high stake's games. You got, this >>Has become a tool of nation states in terms from a political perspective, from a military perspective, if you look at what happened with Ukraine and Russia, all the work that was done in advanced by the Russians to soften up the Ukrainians, not just collection of intelligence, not just denial of services, but then disruptive attacks to change the entire complexity of the battlefield. This, this is a, an area that's never going away. It's becoming ingrained in our lives. And it's gonna be utilized for nefarious acts for many, many decades to come. >>I mean, you're right, Sean, we're seeing the future of war right before us is, is there's. There is going to be, there is a cyber component now in war, >>I think it signals the cyber component signals the silent intention of nations period, the silent projection of power probably before you see kinetics. >>And this is where gates says we have a lot more to lose as a country. So it's hard for us to go on the offense. We have to be very careful about our offensive capabilities because >>Of one of the things that, that we do need to, to do though, is we need to define what the red lines are to adversaries. Because when you talk about human beings, you've gotta put a deterrent in place so that if the adversaries know that if you cross this line, this is what the response is going to be. It's the way things were done during nuclear proliferation, right? Right. During the cold war, here's what the actions are gonna be. It's gonna be, it's gonna be mutual destruction and you can't do it. And we didn't have a nuclear war. We're at a point now where adversaries are pushing the envelope constantly, where they're turning off the lights in certain countries where they're taking actions that are, are quite detrimental to the host governments and those red lines have to be very clear, very clearly defined and acted upon if they're >>Crossed as security experts. Can you always tie that signature back to say a particular country or a particular group? >>Absolutely. 100% every >>Time I know. Yeah. No, it it's. It's a great question. You, you need to get attribution right. To get to deterrence, right. And without attribution, where do you proportionate respond to whatever act you're responding to? So attribution's critical. Both our companies work hard at doing it and it, and that's why I think you're not gonna see too many false flag operations in cyberspace, but when you do and they're well crafted or one nation masquerades is another, it, it, it's one of the last rules of the playground I haven't seen broken yet. And that that'll be an unfortunate day. >>Yeah. Because that mutually assure destruction, a death spot like Putin can say, well, it wasn't wasn't me. Right. So, and ironically, >>It's human intelligence, right. That ultimately is gonna be the only way to uncover >>That human intelligence is a big component. >>For sure. Right. And, and David, like when you go back to, you were referring to Robert Gates, it's the asymmetry of cyberspace, right? One person in one nation. That's not a control by asset could still do an act. And it, it just adds to the complexity of, we have attribution it's from that nation, but was it in order? Was it done on behalf of that nation? Very complicated. >>So this is an industry of superheroes. Thank you guys for all you do and appreciate you coming on the cube. Wow. >>I love your Cape. >>Thank all right. Keep it right there. Dave Nicholson and Dave ante be right back from Falcon 22 from the area you watching the cue.
SUMMARY :
He's the president of the services division and he's One of the things you talked about was the changes you've been, you've been in this business for a while. Making sure everybody's doing the right things. meaning to you or is it just less acronym? One of the things that we've found and Kevin and I were actually talking about this earlier is And you're also president of the services division. an entire organization that's doing incident response and it's a lot of the work that we're Where are companies most at risk today? So it's bigger bang for the buck. all of that hardware is susceptible to attack. Or if they're a consumer of a supply chain, you need to understand who's in their supply chain. As we extend, you know, talking about XDR the X being extend. And I think that there are certain organizations that are starting to recognize I thought the most interesting part of the keynote this morning is when George asked you about election the news that you consume. and you should never go to Fenway So is that disinformation, is that misinformation? And all three, you could spend this whole interview on, but we have to have a trustworthy internet as well. When you guys talk to customers and, and peers, when somebody gets breached, it's about looking at that lateral movement to try and get a full understanding of where the adversary's So part of the reason I was asking you about, was it a P and L cuz you, you wear two hats, And I think you do that immediately. So you guys probably won't comment, but I'm betting dollars to donuts. let me, let me ask it in a more generic fashion that you can maybe comment you you're. Yeah. you've known about for quite some time, is that fair or no, not necessarily. It's, you know, it's harder to handle an intrusion quietly and discreetly these days, but it also talks about the inability of companies to often detect this type of activity when And a and a, and a, a CSO can't, you know, accept that. I can tell you, I started Maning in 2004 at the premise security breaches are inevitable, But I think you can manage this if you're using the right technology, And then wherever you have information, And think about this until you physically get physically get to the people that are doing it at least one person here that is here primarily to gather intelligence, you know, exfiltration of state secrets, I mean, there's, it's high stake's games. from a military perspective, if you look at what happened with Ukraine and Russia, all the work that I mean, you're right, Sean, we're seeing the future of war right before us is, is there's. the silent projection of power probably before you see kinetics. And this is where gates says we have a lot more to lose as a country. that if the adversaries know that if you cross this line, this is what the response is going to be. Can you always tie that signature back to say a Absolutely. where do you proportionate respond to whatever act you're responding to? So, and ironically, It's human intelligence, right. And, and David, like when you go back to, you were referring to Robert Gates, it's the asymmetry of cyberspace, Thank you guys for all you do and appreciate you coming on the cube. Dave Nicholson and Dave ante be right back from Falcon 22 from the area you watching the cue.
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Snehal Antani, Horizon3.ai | AWS Startup Showcase S2 E4 | Cybersecurity
(upbeat music) >> Hello and welcome to theCUBE's presentation of the AWS Startup Showcase. This is season two, episode four of the ongoing series covering the exciting hot startups from the AWS ecosystem. Here we're talking about cybersecurity in this episode. I'm your host, John Furrier here we're excited to have CUBE alumni who's back Snehal Antani who's the CEO and co-founder of Horizon3.ai talking about exploitable weaknesses and vulnerabilities with autonomous pen testing. Snehal, it's great to see you. Thanks for coming back. >> Likewise, John. I think it's been about five years since you and I were on the stage together. And I've missed it, but I'm glad to see you again. >> Well, before we get into the showcase about your new startup, that's extremely successful, amazing margins, great product. You have a unique journey. We talked about this prior to you doing the journey, but you have a great story. You left the startup world to go into the startup, like world of self defense, public defense, NSA. What group did you go to in the public sector became a private partner. >> My background, I'm a software engineer by education and trade. I started my career at IBM. I was a CIO at GE Capital, and I think we met once when I was there and I became the CTO of Splunk. And we spent a lot of time together when I was at Splunk. And at the end of 2017, I decided to take a break from industry and really kind of solve problems that I cared deeply about and solve problems that mattered. So I left industry and joined the US Special Operations Community and spent about four years in US Special Operations, where I grew more personally and professionally than in anything I'd ever done in my career. And exited that time, met my co-founder in special ops. And then as he retired from the air force, we started Horizon3. >> So there's really, I want to bring that up one, 'cause it's fascinating that not a lot of people in Silicon Valley and tech would do that. So thanks for the service. And I know everyone who's out there in the public sector knows that this is a really important time for the tactical edge in our military, a lot of things going on around the world. So thanks for the service and a great journey. But there's a storyline with the company you're running now that you started. I know you get the jacket on there. I noticed get a little military vibe to it. Cybersecurity, I mean, every company's on their own now. They have to build their own militia. There is no government supporting companies anymore. There's no militia. No one's on the shores of our country defending the citizens and the companies, they got to offend for themselves. So every company has to have their own military. >> In many ways, you don't see anti-aircraft rocket launchers on top of the JP Morgan building in New York City because they rely on the government for air defense. But in cyber it's very different. Every company is on their own to defend for themselves. And what's interesting is this blend. If you look at the Ukraine, Russia war, as an example, a thousand companies have decided to withdraw from the Russian economy and those thousand companies we should expect to be in the ire of the Russian government and their proxies at some point. And so it's not just those companies, but their suppliers, their distributors. And it's no longer about cyber attack for extortion through ransomware, but rather cyber attack for punishment and retaliation for leaving. Those companies are on their own to defend themselves. There's no government that is dedicated to supporting them. So yeah, the reality is that cybersecurity, it's the burden of the organization. And also your attack surface has expanded to not just be your footprint, but if an adversary wants to punish you for leaving their economy, they can get, if you're in agriculture, they could disrupt your ability to farm or they could get all your fruit to spoil at the border 'cause they disrupted your distributors and so on. So I think the entire world is going to change over the next 18 to 24 months. And I think this idea of cybersecurity is going to become truly a national problem and a problem that breaks down any corporate barriers that we see in previously. >> What are some of the things that inspired you to start this company? And I loved your approach of thinking about the customer, your customer, as defending themselves in context to threats, really leaning into it, being ready and able to defend. Horizon3 has a lot of that kind of military thinking for the good of the company. What's the motivation? Why this company? Why now? What's the value proposition? >> So there's two parts to why the company and why now. The first part was what my observation, when I left industry realm or my military background is watching "Jack Ryan" and "Tropic Thunder" and I didn't come from the military world. And so when I entered the special operations community, step one was to keep my mouth shut, learn, listen, and really observe and understand what made that community so impressive. And obviously the people and it's not about them being fast runners or great shooters or awesome swimmers, but rather there are learn-it-alls that can solve any problem as a team under pressure, which is the exact culture you want to have in any startup, early stage companies are learn-it-alls that can solve any problem under pressure as a team. So I had this immediate advantage when we started Horizon3, where a third of Horizon3 employees came from that special operations community. So one is this awesome talent. But the second part that, I remember this quote from a special operations commander that said we use live rounds in training because if we used fake rounds or rubber bullets, everyone would act like metal of honor winners. And the whole idea there is you train like you fight, you build that muscle memory for crisis and response and so on upfront. So when you're in the thick of it, you already know how to react. And this aligns to a pain I had in industry. I had no idea I was secure until the bad guy showed up. I had no idea if I was fixing the right vulnerabilities, logging the right data in Splunk, or if my CrowdStrike EDR platform was configured correctly, I had to wait for the bad guys to show up. I didn't know if my people knew how to respond to an incident. So what I wanted to do was proactively verify my security posture, proactively harden my systems. I needed to do that by continuously pen testing myself or continuously testing my security posture. And there just wasn't any way to do that where an IT admin or a network engineer could in three clicks have the power of a 20 year pen testing expert. And that was really what we set out to do, not build a autonomous pen testing platform for security people, build it so that anybody can quickly test their security posture and then use the output to fix problems that truly matter. >> So the value preposition, if I get this right is, there's a lot of companies out there doing pen tests. And I know I hate pen tests. They're like, cause you do DevOps, it changes you got to do another pen test. So it makes sense to do autonomous pen testing. So congratulations on seeing that that's obvious to that, but a lot of other have consulting tied to it. Which seems like you need to train someone and you guys taking a different approach. >> Yeah, we actually, as a company have zero consulting, zero professional services. And the whole idea is that build a true software as a service offering where an intern, in fact, we've got a video of a nine year old that in three clicks can run pen tests against themselves. And because of that, you can wire pen tests into your DevOps tool chain. You can run multiple pen tests today. In fact, I've got customers running 40, 50 pen tests a month against their organization. And that what that does is completely lowers the barrier of entry for being able to verify your posture. If you have consulting on average, when I was a CIO, it was at least a three month lead time to schedule consultants to show up and then they'd show up, they'd embarrass the security team, they'd make everyone look bad, 'cause they're going to get in, leave behind a report. And that report was almost identical to what they found last year because the older that report, the one the date itself gets stale, the context changes and so on. And then eventually you just don't even bother fixing it. Or if you fix a problem, you don't have the skills to verify that has been fixed. So I think that consulting led model was acceptable when you viewed security as a compliance checkbox, where once a year was sufficient to meet your like PCI requirements. But if you're really operating with a wartime mindset and you actually need to harden and secure your environment, you've got to be running pen test regularly against your organization from different perspectives, inside, outside, from the cloud, from work, from home environments and everything in between. >> So for the CISOs out there, for the CSOs and the CXOs, what's the pitch to them because I see your jacket that says Horizon3 AI, trust but verify. But this trust is, but is canceled out, just as verify. What's the product that you guys are offering the service. Describe what it is and why they should look at it. >> Yeah, sure. So one, when I back when I was the CIO, don't tell me we're secure in PowerPoint. Show me we're secure right now. Show me we're secure again tomorrow. And then show me we're secure again next week because my environment is constantly changing and the adversary always has a vote and they're always evolving. And this whole idea of show me we're secure. Don't trust that your security tools are working, verify that they can detect and respond and stifle an attack and then verify tomorrow, verify next week. That's the big mind shift. Now what we do is-- >> John: How do they respond to that by the way? Like they don't believe you at first or what's the story. >> I think, there's actually a very bifurcated response. There are still a decent chunk of CIOs and CSOs that have a security is a compliance checkbox mindset. So my attitude with them is I'm not going to convince you. You believe it's a checkbox. I'll just wait for you to get breached and sell to your replacement, 'cause you'll get fired. And in the meantime, I spend all my energy with those that actually care about proactively securing and hardening their environments. >> That's true. People do get fired. Can you give an example of what you're saying about this environment being ready, proving that you're secure today, tomorrow and a few weeks out. Give me an example. >> Of, yeah, I'll give you actually a customer example. There was a healthcare organization and they had about 5,000 hosts in their environment and they did everything right. They had Fortinet as their EDR platform. They had user behavior analytics in place that they had purchased and tuned. And when they ran a pen test self-service, our product node zero immediately started to discover every host on the network. It then fingerprinted all those hosts and found it was able to get code execution on three machines. So it got code execution, dumped credentials, laterally maneuvered, and became a domain administrator, which in IT, if an attacker becomes a domain admin, they've got keys to the kingdom. So at first the question was, how did the node zero pen test become domain admin? How'd they get code execution, Fortinet should have detected and stopped it. Well, it turned out Fortinet was misconfigured on three boxes out of 5,000. And these guys had no idea and it's just automation that went wrong and so on. And now they would've only known they had misconfigured their EDR platform on three hosts if the attacker had showed up. The second question though was, why didn't they catch the lateral movement? Which all their marketing brochures say they're supposed to catch. And it turned out that that customer purchased the wrong Fortinet modules. One again, they had no idea. They thought they were doing the right thing. So don't trust just installing your tools is good enough. You've got to exercise and verify them. We've got tons of stories from patches that didn't actually apply to being able to find the AWS admin credentials on a local file system. And then using that to log in and take over the cloud. In fact, I gave this talk at Black Hat on war stories from running 10,000 pen tests. And that's just the reality is, you don't know that these tools and processes are working for you until the bad guys have shown. >> The velocities there. You can accelerate through logs, you know from the days you've been there. This is now the threat. Being, I won't say lazy, but just not careful or just not thinking. >> Well, I'll do an example. We have a lot of customers that are Horizon3 customers and Splunk customers. And what you'll see their behavior is, is they'll have Horizon3 up on one screen. And every single attacker command executed with its timestamp is up on that screen. And then look at Splunk and say, hey, we were able to dump vCenter credentials from VMware products at this time on this host, what did Splunk see or what didn't they see? Why were no logs generated? And it turns out that they had some logging blind spots. So what they'll actually do is run us to almost like stimulate the defensive tools and then see what did the tools catch? What did they miss? What are those blind spots and how do they fix it. >> So your price called node zero. You mentioned that. Is that specifically a suite, a tool, a platform. How do people consume and engage with you guys? >> So the way that we work, the whole product is designed to be self-service. So once again, while we have a sales team, the whole intent is you don't need to have to talk to a sales rep to start using the product, you can log in right now, go to Horizon3.ai, you can run a trial log in with your Google ID, your LinkedIn ID, start running pen test against your home or against your network against this organization right now, without talking to anybody. The whole idea is self-service, run a pen test in three clicks and give you the power of that 20 year pen testing expert. And then what'll happen is node zero will execute and then it'll provide to you a full report of here are all of the different paths or attack paths or sequences where we are able to become an admin in your environment. And then for every attack path, here is the path or the kill chain, the proof of exploitation for every step along the way. Here's exactly what you've got to do to fix it. And then once you've fixed it, here's how you verify that you've truly fixed the problem. And this whole aha moment is run us to find problems. You fix them, rerun us to verify that the problem has been fixed. >> Talk about the company, how many people do you have and get some stats? >> Yeah, so we started writing code in January of 2020, right before the pandemic hit. And then about 10 months later at the end of 2020, we launched the first version of the product. We've been in the market for now about two and a half years total from start of the company till present. We've got 130 employees. We've got more customers than we do employees, which is really cool. And instead our customers shift from running one pen test a year to 40, 50 pen test. >> John: And it's full SaaS. >> The whole product is full SaaS. So no consulting, no pro serve. You run as often as you-- >> Who's downloading, who's buying the product. >> What's amazing is, we have customers in almost every section or sector now. So we're not overly rotated towards like healthcare or financial services. We've got state and local education or K through 12 education, state and local government, a number of healthcare companies, financial services, manufacturing. We've got organizations that large enterprises. >> John: Security's diverse. >> It's very diverse. >> I mean, ransomware must be a big driver. I mean, is that something that you're seeing a lot. >> It is. And the thing about ransomware is, if you peel back the outcome of ransomware, which is extortion, at the end of the day, what ransomware organizations or criminals or APTs will do is they'll find out who all your employees are online. They will then figure out if you've got 7,000 employees, all it takes is one of them to have a bad password. And then attackers are going to credential spray to find that one person with a bad password or whose Netflix password that's on the dark web is also their same password to log in here, 'cause most people reuse. And then from there they're going to most likely in your organization, the domain user, when you log in, like you probably have local admin on your laptop. If you're a windows machine and I've got local admin on your laptop, I'm going to be able to dump credentials, get the admin credentials and then start to laterally maneuver. Attackers don't have to hack in using zero days like you see in the movies, often they're logging in with valid user IDs and passwords that they've found and collected from somewhere else. And then they make that, they maneuver by making a low plus a low equal a high. And the other thing in financial services, we spend all of our time fixing critical vulnerabilities, attackers know that. So they've adapted to finding ways to chain together, low priority vulnerabilities and misconfigurations and dangerous defaults to become admin. So while we've over rotated towards just fixing the highs and the criticals attackers have adapted. And once again they have a vote, they're always evolving their tactics. >> And how do you prevent that from happening? >> So we actually apply those same tactics. Rarely do we actually need a CVE to compromise your environment. We will harvest credentials, just like an attacker. We will find misconfigurations and dangerous defaults, just like an attacker. We will combine those together. We'll make use of exploitable vulnerabilities as appropriate and use that to compromise your environment. So the tactics that, in many ways we've built a digital weapon and the tactics we apply are the exact same tactics that are applied by the adversary. >> So you guys basically simulate hacking. >> We actually do the hacking. Simulate means there's a fakeness to it. >> So you guys do hack. >> We actually compromise. >> Like sneakers the movie, those sneakers movie for the old folks like me. >> And in fact that was my inspiration. I've had this idea for over a decade now, which is I want to be able to look at anything that laptop, this Wi-Fi network, gear in hospital or a truck driving by and know, I can figure out how to gain initial access, rip that environment apart and be able to opponent. >> Okay, Chuck, he's not allowed in the studio anymore. (laughs) No, seriously. Some people are exposed. I mean, some companies don't have anything. But there's always passwords or so most people have that argument. Well, there's nothing to protect here. Not a lot of sensitive data. How do you respond to that? Do you see that being kind of putting the head in the sand or? >> Yeah, it's actually, it's less, there's not sensitive data, but more we've installed or applied multifactor authentication, attackers can't get in now. Well MFA only applies or does not apply to lower level protocols. So I can find a user ID password, log in through SMB, which isn't protected by multifactor authentication and still upon your environment. So unfortunately I think as a security industry, we've become very good at giving a false sense of security to organizations. >> John: Compliance drives that behavior. >> Compliance drives that. And what we need. Back to don't tell me we're secure, show me, we've got to, I think, change that to a trust but verify, but get rid of the trust piece of it, just to verify. >> Okay, we got a lot of CISOs and CSOs watching this showcase, looking at the hot startups, what's the message to the executives there. Do they want to become more leaning in more hawkish if you will, to use the military term on security? I mean, I heard one CISO say, security first then compliance 'cause compliance can make you complacent and then you're unsecure at that point. >> I actually say that. I agree. One definitely security is different and more important than being compliant. I think there's another emerging concept, which is I'd rather be defensible than secure. What I mean by that is security is a point in time state. I am secure right now. I may not be secure tomorrow 'cause something's changed. But if I'm defensible, then what I have is that muscle memory to detect, respondent and stifle an attack. And that's what's more important. Can I detect you? How long did it take me to detect you? Can I stifle you from achieving your objective? How long did it take me to stifle you? What did you use to get in to gain access? How long did that sit in my environment? How long did it take me to fix it? So on and so forth. But I think it's being defensible and being able to rapidly adapt to changing tactics by the adversary is more important. >> This is the evolution of how the red line never moved. You got the adversaries in our networks and our banks. Now they hang out and they wait. So everyone thinks they're secure. But when they start getting hacked, they're not really in a position to defend, the alarms go off. Where's the playbook. Team springs into action. I mean, you kind of get the visual there, but this is really the issue being defensible means having your own essentially military for your company. >> Being defensible, I think has two pieces. One is you've got to have this culture and process in place of training like you fight because you want to build that incident response muscle memory ahead of time. You don't want to have to learn how to respond to an incident in the middle of the incident. So that is that proactively verifying your posture and continuous pen testing is critical there. The second part is the actual fundamentals in place so you can detect and stifle as appropriate. And also being able to do that. When you are continuously verifying your posture, you need to verify your entire posture, not just your test systems, which is what most people do. But you have to be able to safely pen test your production systems, your cloud environments, your perimeter. You've got to assume that the bad guys are going to get in, once they're in, what can they do? So don't just say that my perimeter's secure and I'm good to go. It's the soft squishy center that attackers are going to get into. And from there, can you detect them and can you stop them? >> Snehal, take me through the use. You got to be sold on this, I love this topic. Alright, pen test. Is it, what am I buying? Just pen test as a service. You mentioned dark web. Are you actually buying credentials online on behalf of the customer? What is the product? What am I buying if I'm the CISO from Horizon3? What's the service? What's the product, be specific. >> So very specifically and one just principles. The first principle is when I was a buyer, I hated being nickled and dimed buyer vendors, which was, I had to buy 15 different modules in order to achieve an objective. Just give me one line item, make it super easy to buy and don't nickel and dime me. Because I've spent time as a buyer that very much has permeated throughout the company. So there is a single skew from Horizon3. It is an annual subscription based on how big your environment is. And it is inclusive of on-prem internal pen tests, external pen tests, cloud attacks, work from home attacks, our ability to harvest credentials from the dark web and from open source sources. Being able to crack those credentials, compromise. All of that is included as a singles skew. All you get as a CISO is a singles skew, annual subscription, and you can run as many pen tests as you want. Some customers still stick to, maybe one pen test a quarter, but most customers shift when they realize there's no limit, we don't nickel and dime. They can run 10, 20, 30, 40 a month. >> Well, it's not nickel and dime in the sense that, it's more like dollars and hundreds because they know what to expect if it's classic cloud consumption. They kind of know what their environment, can people try it. Let's just say I have a huge environment, I have a cloud, I have an on-premise private cloud. Can I dabble and set parameters around pricing? >> Yes you can. So one is you can dabble and set perimeter around scope, which is like manufacturing does this, do not touch the production line that's on at the moment. We've got a hospital that says every time they run a pen test, any machine that's actually connected to a patient must be excluded. So you can actually set the parameters for what's in scope and what's out of scope up front, most again we're designed to be safe to run against production so you can set the parameters for scope. You can set the parameters for cost if you want. But our recommendation is I'd rather figure out what you can afford and let you test everything in your environment than try to squeeze every penny from you by only making you buy what can afford as a smaller-- >> So the variable ratio, if you will is, how much they spend is the size of their environment and usage. >> Just size of the environment. >> So it could be a big ticket item for a CISO then. >> It could, if you're really large, but for the most part-- >> What's large? >> I mean, if you were Walmart, well, let me back up. What I heard is global 10 companies spend anywhere from 50 to a hundred million dollars a year on security testing. So they're already spending a ton of money, but they're spending it on consultants that show up maybe a couple of times a year. They don't have, humans can't scale to test a million hosts in your environment. And so you're already spending that money, spend a fraction of that and use us and run as much as you want. And that's really what it comes down to. >> John: All right. So what's the response from customers? >> What's really interesting is there are three use cases. The first is that SOC manager that is using us to verify that their security tools are actually working. So their Splunk environment is logging the right data. It's integrating properly with CrowdStrike, it's integrating properly with their active directory services and their password policies. So the SOC manager is using us to verify the effectiveness of their security controls. The second use case is the IT director that is using us to proactively harden their systems. Did they install VMware correctly? Did they install their Cisco gear correctly? Are they patching right? And then the third are for the companies that are lucky to have their own internal pen test and red teams where they use us like a force multiplier. So if you've got 10 people on your red team and you still have a million IPs or hosts in your environment, you still don't have enough people for that coverage. So they'll use us to do recon at scale and attack at scale and let the humans focus on the really juicy hard stuff that humans are successful at. >> Love the product. Again, I'm trying to think about how I engage on the test. Is there pilots? Is there a demo version? >> There's a free trials. So we do 30 day free trials. The output can actually be used to meet your SOC 2 requirements. So in many ways you can just use us to get a free SOC 2 pen test report right now, if you want. Go to the website, log in for a free trial, you can log into your Google ID or your LinkedIn ID, run a pen test against your organization and use that to answer your PCI segmentation test requirements, your SOC 2 requirements, but you will be hooked. You will want to run us more often. And you'll get a Horizon3 tattoo. >> The first hits free as they say in the drug business. >> Yeah. >> I mean, so you're seeing that kind of response then, trial converts. >> It's exactly. In fact, we have a very well defined aha moment, which is you run us to find, you fix, you run us to verify, we have 100% technical win rate when our customers hit a find, fix, verify cycle, then it's about budget and urgency. But 100% technical win rate because of that aha moment, 'cause people realize, holy crap, I don't have to wait six months to verify that my problems have actually been fixed. I can just come in, click, verify, rerun the entire pen test or rerun a very specific part of it on what I just patched my environment. >> Congratulations, great stuff. You're here part of the AWS Startup Showcase. So I have to ask, what's the relationship with AWS, you're on their cloud. What kind of actions going on there? Is there secret sauce on there? What's going on? >> So one is we are AWS customers ourselves, our brains command and control infrastructure. All of our analytics are all running on AWS. It's amazing, when we run a pen test, we are able to use AWS and we'll spin up a virtual private cloud just for that pen test. It's completely ephemeral, it's all Lambda functions and graph analytics and other techniques. When the pen test ends, you can delete, there's a single use Docker container that gets deleted from your environment so you have nothing on-prem to deal with and the entire virtual private cloud tears itself down. So at any given moment, if we're running 50 pen tests or a hundred pen tests, self-service, there's a hundred virtual private clouds being managed in AWS that are spinning up, running and tearing down. It's an absolutely amazing underlying platform for us to make use of. Two is that many customers that have hybrid environments. So they've got a cloud infrastructure, an Office 365 infrastructure and an on-prem infrastructure. We are a single attack platform that can test all of that together. No one else can do it. And so the AWS customers that are especially AWS hybrid customers are the ones that we do really well targeting. >> Got it. And that's awesome. And that's the benefit of cloud? >> Absolutely. And the AWS marketplace. What's absolutely amazing is the competitive advantage being part of the marketplace has for us, because the simple thing is my customers, if they already have dedicated cloud spend, they can use their approved cloud spend to pay for Horizon3 through the marketplace. So you don't have to, if you already have that budget dedicated, you can use that through the marketplace. The other is you've already got the vendor processes in place, you can purchase through your existing AWS account. So what I love about the AWS company is one, the infrastructure we use for our own pen test, two, the marketplace, and then three, the customers that span that hybrid cloud environment. That's right in our strike zone. >> Awesome. Well, congratulations. And thanks for being part of the showcase and I'm sure your product is going to do very, very well. It's very built for what people want. Self-service get in, get the value quickly. >> No agents to install, no consultants to hire. safe to run against production. It's what I wanted. >> Great to see you and congratulations and what a great story. And we're going to keep following you. Thanks for coming on. >> Snehal: Phenomenal. Thank you, John. >> This is the AWS Startup Showcase. I'm John John Furrier, your host. This is season two, episode four on cybersecurity. Thanks for watching. (upbeat music)
SUMMARY :
of the AWS Startup Showcase. I'm glad to see you again. to you doing the journey, and I became the CTO of Splunk. and the companies, they got over the next 18 to 24 months. And I loved your approach of and "Tropic Thunder" and I didn't come from the military world. So the value preposition, And the whole idea is that build a true What's the product that you and the adversary always has a vote Like they don't believe you and sell to your replacement, Can you give an example And that's just the reality is, This is now the threat. the defensive tools and engage with you guys? the whole intent is you We've been in the market for now about So no consulting, no pro serve. who's buying the product. So we're not overly rotated I mean, is that something and the criticals attackers have adapted. and the tactics we apply We actually do the hacking. Like sneakers the movie, and be able to opponent. kind of putting the head in the sand or? and still upon your environment. that to a trust but verify, looking at the hot startups, and being able to rapidly This is the evolution of and I'm good to go. What is the product? and you can run as many and dime in the sense that, So you can actually set the So the variable ratio, if you will is, So it could be a big and run as much as you want. So what's the response from customers? and let the humans focus on about how I engage on the test. So in many ways you can just use us they say in the drug business. I mean, so you're seeing I don't have to wait six months to verify So I have to ask, what's When the pen test ends, you can delete, And that's the benefit of cloud? And the AWS marketplace. And thanks for being part of the showcase no consultants to hire. Great to see you and congratulations This is the AWS Startup Showcase.
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Tim Jefferson & Sinan Eren, Barracuda | AWS re:Inforce 2022
>>And welcome back to the cubes coverage of a, of us. Reinforc here in Boston, Massachusetts. I'm John furrier. We're here for a great interview on the next generation topic of state of industrial security. We have two great guests, Tim Jefferson, senior vice president data network and application security at Barracuda. And Cenon Aron vice president of zero trust engineering at Barracuda. Gentlemen. Thanks for coming on the queue. Talk about industrial security. >>Yeah, thanks for having us. >>So one of the, one of the big things that's going on, obviously you got zero trust. You've got trusted, trusted software supply chain challenges. You've got hardware mattering more than ever. You've got software driving everything, and all this is talking about industrial, you know, critical infrastructure. We saw the oil pipeline had a hack and ransomware attack, and that's just constant barrage of threats in the industrial area. And all the data is pointing to that. This area is gonna be fast growth machine learning's kicking in automation is coming in. You see a huge topic, huge growth trend. What is the big story going on here? >>Yeah, I think at a high level, you know, we did a survey and saw that, you know, over 95% of the organizations are experiencing, you know, security challenges in this space. So, you know, the blast radius in the, of the, the interface that this creates so many different devices and things and objects that are getting network connected now create a huge challenge for security teams to kind of get their arms around that. >>Yeah. And I can add that, you know, majority of these incidents that, that these organizations suffer lead to significant downtime, right? And we're talking about operational technology here, you know, lives depend on, on these technologies, right? Our, our wellbeing everyday wellbeing depend on those. So, so that is a key driver of initiatives and projects to secure industrial IOT and operational technologies in, in these businesses. >>Well, it's great to have both of you guys on, you know, Tim, you know, you had a background at AWS and sit on your startup, founder, soldier, coming to Barracuda, both very experienced, seeing the ways before in this industry. And I'd like to, if you don't mind talk about three areas, remote access, which we've seen in huge demand with, with the pandemic and the out, coming out with the hybrid and certainly industrial, that's a big part of it. And then secondly, that the trend of clear commitment from enterprises to have in a public cloud component, and then finally the secure access edge, you know, with SAS business models, securing these things, these are the three hot areas let's go into the first one, remote access. Why is this important? It seems that this is the top priority for having immediate attention on what's the big challenge here? Is it the most unsecure? Is it the most important? What, why is this relevant? >>So now I'll let you jump in there. >>Yeah, sure. Happy to. I mean, if you think about it, especially now, we've been through a, a pandemic shelter in place cycle for almost two years. It, it becomes essentially a business continuity matter, right? You do need remote access. We also seen a tremendous shift in hiring the best talent, wherever they are, right. Onboarding them and bringing the talent into, into, into, into businesses that have maybe a lot more distributed environments than traditionally. So you have to account for remote access in every part of everyday life, including industrial technologies, you need remote support, right? You need vendors that might be overseas providing you, you know, guidance and support for these technologies. So remote support is every part of life. Whether you work from home, you work on your, on the go, or you are getting support from a vendor that happens to be in Germany, you know, teleporting into your environment in Hawaii. You know, all these things are essentially critical parts of everyday life. Now >>Talk about ZT and a zero trust network access is a, this is a major component for companies. Obviously, you know, it's a position taking trust and verifies. One other approach, zero trust is saying, Hey, I don't trust you. Take us through why that's important. Why is zero trust network access important in this area? >>Yeah. I mean, I could say that traditionally remote access, if you think about infancy of the internet in the nineties, right? It was all about encryption in, in transit, right? You were all about internet was vastly clear text, right? We didn't have even SSL TLS, widely distributed and, and available. So when VPNs first came out, it was more about preventing sniffing, clear tech clear text information from, from, from the network, right? It was more about securing the, the transport, but now that kind of created a, a big security control gap, which implicitly trusted user users, once they are teleported into a remote network, right? That's the essence of having a remote access session you're brought from wherever you are into an internal network. They implicitly trust you that simply breakdown over time because you are able to compromise end points relatively easily using browser exploits. >>You know, so, so for supply chain issues, water hole attacks, and leverage the existing VPN tunnels to laterally move into the organization from within the network, you literally move in further and further and further down, you know, down the network, right? So the VPN needed a, a significant innovation. It was meant to be securing packets and transit. It was all about an encryption layer, but it had an implicit trust problem with zero trust. We turn it into an explicit trust problem, right? Explicit trust concept, ideally. Right? So you are, who do you say you are? And you are authorized to access only to things that you need to access to get the work done. >>So you're talking about granular levels versus the one time database look up you're in >>That's right. >>Tim, talk about the OT it side of this equation of industrial, because it, you know, is IP based, networking, OT have been purpose built, you know, maybe some proprietary technology yeah. That connects to the internet internet, but it's mainly been secure. Those have come together over the years and now with no perimeter security, how is this world evolving? Because there's gonna be more cloud there, be more machine learning, more hybrid on premise, that's going on almost a reset if you will. I mean, is it a reset? What's the, what's the situation. >>Yeah. I think, you know, in typical human behavior, you know, there's a lot of over rotation going on. You know, historically a lot of security controls are all concentrated in a data center. You know, a lot of enterprises had very large sophisticated well-established security stacks in a data center. And as those applications kind of broke down and, and got rearchitected for the cloud, they got more modular, they got more distributed that centralized security stack became an anti pattern. So now this kind of over rotation, Hey, let's take this stack and, and put it up in the cloud. You know, so there's lots of names for this secure access, service edge, you know, secure service edge. But in the end, you know, you're taking your controls and, and migrating them into the cloud. And, you know, I think ultimately this creates a great opportunity to embrace some of security, best practices that were difficult to do in some of the legacy architectures, which is being able to push your controls as far out to the edge as possible. >>And the interesting thing about OT and OT now is just how far out the edge is, right? So instead of being, you know, historically it was the branch or user edge, remote access edge, you know, Syon mentioned that you, you have technologies that can VPN or bring those identities into those networks, but now you have all these things, you know, partners, devices. So it's the thing, edge device edge, the user edge. So a lot more fidelity and awareness around who users are. Cause in parallel, a lot of the IDP and I IBM's platforms have really matured. So marrying those concepts of this, this lot of maturity around identity management yeah. With device in and behavior management into a common security framework is really exciting. But of course it's very nascent. So people are, it's a difficult time getting your arms around >>That. It's funny. We were joking about the edge. We just watching the web telescope photos come in the deep space, the deep edge. So the edge is continuing to be pushed out. Totally see that. And in fact, you know, one of the things we're gonna, we're gonna talk about this survey that you guys had done by an independent firm has a lot of great data. I want to unpack that, but one of the things that was mentioned in there, and I'll get, I wanna get your both reaction to this is that virtually all organizations are committing to the public cloud. Okay. I think it was like 96% or so was the stat. And if you combine in that, the fact that the edge is expanding, the cloud model is evolving at the edge. So for instance, a building, there's a lot behind it. You know, how far does it go? So we don't and, and what is the topology because the topology seem to change too. So there's this growth and change where we need cloud operations, DevOps at, at the edge and the security, but it's changing. It's not pure cloud, but it's cloud. It has to be compatible. What's your reaction to that, Tim? I mean, this is, this is a big part of the growth of industrial. >>Yeah. I think, you know, if you think about, there's kind of two exciting developments that I would think of, you know, obviously there's this increase to the surface area, the tax surface areas, people realize, you know, it's not just laptops and devices and, and people that you're trying to secure, but now they're, you know, refrigerators and, you know, robots and manufacturing floors that, you know, could be compromised, have their firmware updated or, you know, be ransomware. So this a huge kind of increase in surface area. But a lot of those, you know, industrial devices, weren't built around the concept with network security. So kind of bolting on, on thinking through how can you secure who and what ultimately has access to those, to those devices and things. And where is the control framework? So to your point, the control framework now is typically migrated now into public cloud. >>These are custom applications, highly distributed, highly available, very modular. And then, you know, so how do you, you know, collect the telemetry or control information from these things. And then, you know, it creates secure connections back into these, these control applications, which again, are now migrated to public cloud. So you have this challenge, you know, how do you secure? We were talking about this last time we discussed, right. So how do you secure the infrastructure that I've, I've built in deploying now, this control application and in public cloud, and then connect in with this, this physical presence that I have with these, you know, industrial devices and taking telemetry and control information from those devices and bringing it back into the management. And this kind marries again, back into the remote axis that Sunan was mentioning now with this increase awareness around the efficacy of ransomware, we are, you know, we're definitely seeing attackers going after the management frameworks, which become very vulnerable, you know, and they're, they're typically just unprotected web applications. So once you get control of the management framework, regardless of where it's hosted, you can start moving laterally and, and causing some damage. >>Yeah. That seems to be the common thread. So no talk about, what's your reaction to that because, you know, zero trust, if it's evolving and changing, you, you gotta have zero trust you. I didn't even know it's out there and then it gets connected. How do you solve that problem? Cuz you know, there's a lot of surface area that's evolving all the OT stuff and the new, it, what's the, what's the perspective and posture that the clients your clients are having and customers. Well, >>I, I think they're having this conversation about further mobilizing identity, right? We did start with, you know, user identity that become kind of the first foundational building block for any kind of zero trust implementation. You work with, you know, some sort of SSO identity provider, you get your, you sync with your user directories, you have a single social truth for all your users. >>You authenticate them through an identity provider. However that didn't quite cut it for industrial OT and OT environments. So you see like we have the concept of hardware machines, machine identities now become an important construct, right? The, the legacy notion of being able to put controls and, and, and, and rules based on network constructs doesn't really scale anymore. Right? So you need to have this concept of another abstraction layer of identity that belongs to a service that belongs to an application that belongs to a user that belongs to a piece of hardware. Right. And then you can, yeah. And then you can build a lot more, of course, scalable controls that basically understand the, the trust relation between these identities and enforce that rather than trying to say this internal network can talk to this other internal network through a, through a network circuit. No, those things are really, are not scalable in this new distributed landscape that we live in today. So identity is basically going to operationalize zero trust and a lot more secure access going forward. >>And that's why we're seeing the sassy growth. Right. That's a main piece of it. Is that what you, what you're seeing too? I mean, that seems to be the, the approach >>I think like >>Go >>Ahead to, yeah. I think like, you know, sassy to me is really about, you know, migrating and moving your security infrastructure to the cloud edge, you know, as we talked to the cloud, you know, and then, you know, do you funnel all ingress and egress traffic through this, you know, which is potentially an anti pattern, right? You don't wanna create, you know, some brittle constraint around who and what has access. So again, a security best practices, instead of doing all your enforcement in one place, you can distribute and push your controls out as far to the edge. So a lot of SASI now is really around centralizing policy management, which is the big be one of the big benefits is instead of having all these separate management plans, which always difficult to be very federated policy, right? You can consolidate your policy and then decide mechanism wise how you're gonna instrument those controls at the edge. >>So I think that's the, the real promise of, of the, the sassy movement and the, I think the other big piece, which you kind of touched on earlier is around analytics, right? So it creates an opportunity to collect a whole bunch of telemetry from devices and things, behavior consumption, which is, which is a big, common, best practice around once you have SA based tools that you can instrument in a lot of visibility and how users and devices are behaving in being operated. And to Syon point, you can marry that in with their identity. Yeah. Right. And then you can start building models around what normal behavior is and, you know, with very fine grain control, you can, you know, these types of analytics can discover things that humans just can't discover, you know, anomalous behavior, any kind of indicators are compromised. And those can be, you know, dynamic policy blockers. >>And I think sun's point about what he was talking about, talks about the, the perimeters no longer secure. So you gotta go to the new way to do that. Totally, totally relevant. I love that point. Let me ask you guys a question on the, on the macro, if you don't mind, how concerned are you guys on the current threat landscape in the geopolitical situation in terms of the impact on industrial IOT in this area? >>So I'll let you go first. Yeah. >>I mean, it's, it's definitely significantly concerning, especially if now with the new sanctions, there's at least two more countries being, you know, let's say restricted to participate in the global economic, you know, Mar marketplace, right? So if you look at North Korea as a pattern, since they've been isolated, they've been sanctioned for a long time. They actually double down on rents somewhere to even fund state operations. Right? So now that you have, you know, BES be San Russia being heavily sanctioned due to due to their due, due to their activities, we can envision more increase in ransomware and, you know, sponsoring state activities through illegal gains, through compromising, you know, pipelines and, you know, industrial, you know, op operations and, and seeking large payouts. So, so I think the more they will, they're ized they're pushed out from the, from the global marketplace. There will be a lot more aggression towards critical infrastructure. >>Oh yeah. I think it's gonna ignite more action off the books, so to speak as we've seen. Yeah. We've >>Seen, you know, another point there is, you know, Barracuda also runs a, a backup, you know, product. We do a, a purpose built backup appliance and a cloud to cloud backup. And, you know, we've been running this service for over a decade. And historically the, the amount of ransomware escalations that we got were very slow, you know, is whenever we had a significant one, helping our customers recover from them, you know, you know, once a month, but over the last 18 months, this is routine now for us, this is something we deal with on a daily basis. And it's becoming very common. You know, it's, it's been a well established, you know, easily monetized route to market for the bad guys. And, and it's being very common now for people to compromise management planes, you know, they use account takeover. And the first thing they're doing is, is breaking into management planes, looking at control frameworks. And then first thing they'll do is delete, you know, of course the backups, which this sort of highlights the vulnerability that we try to talk to our customers about, you know, and this affects industrial too, is the first thing you have to do is among other things, is, is protect your management planes. Yeah. And putting really fine grain mechanisms like zero trust is, is a great, >>Yeah. How, how good is backup, Tim, if you gets deleted first is like no backup. There it is. So, yeah. Yeah. Air gaping. >>I mean, obviously that's kinda a best practice when you're bad guys, like go in and delete all the backups. So, >>And all the air gaps get in control of everything. Let me ask you about the, the survey pointed out that there's a lot of security incidents happening. You guys pointed that out and discussed a little bit of it. We also talked about in the survey, you know, the threat vectors and the threat landscape, the common ones, ransomware was one of them. The area that I liked, what that was interesting was the, the area that talked about how organizations are investing in security and particularly around this, can you guys share your thoughts on how you see the, the market, your customers and, and the industry investing? What are they investing in? What stage are they in when it comes to IOT and OT, industrial IOT and OT security, do they do audits? Are they too busy? I mean, what's the state of their investment thesis progress of, of, of how they're investing in industrial IOT? >>Yeah. Our, our view is, you know, we have a next generation product line. We call, you know, our next, our cloud chain firewalls. And we have a form factor that sports industrial use cases we call secure connectors. So it's interesting that if you, what we learned from that business is a tremendous amount of bespoke efforts at this point, which is sort of indicative of a, of a nascent market still, which is related to another piece of information I thought was really interested in the survey that I think it was 93% of the, the participants, the enterprises had a failed OT initiative, you know, that, you know, people tried to do these things and didn't get off the ground. And then once we see build, you know, strong momentum, you know, like we have a, a large luxury car manufacturer that uses our secure connectors on the, on the robots, on the floor. >>So well established manufacturing environments, you know, building very sophisticated control frameworks and, and security controls. And, but again, a very bespoke effort, you know, they have very specific set of controls and specific set of use cases around it. So it kind of reminds me of the late nineties, early two thousands of people trying to figure out, you know, networking and the blast radi and networking and, and customers, and now, and a lot of SI are, are invested in this building, you know, fast growing practices around helping their customers build more robust controls in, in helping them manage those environments. So, yeah, I, I think that the market is still fairly nascent >>From what we seeing, right. But there are some encouraging, you know, data that shows that at least helpful of the organizations are actively pursuing. There's an initiative in place for OT and a, you know, industrial IOT security projects in place, right. They're dedicating time and resources and budget for this. And, and in, in regards to industries, verticals and, and geographies oil and gas, you know, is, is ahead of the curve more than 50% responded to have the project completed, which I guess colonial pipeline was the, you know, the call to arms that, that, that was the big, big, you know, industrial, I guess, incident that triggered a lot of these projects to be accelerating and, and, you know, coming to the finish line as far as geographies go DACA, which is Germany, Austria, Switzerland, and of course, north America, which happens to be the industrial powerhouses of, of the world. Well, APAC, you know, also included, but they're a bit behind the curve, which is, you know, that part is a bit concerning, but encouragingly, you know, Western Europe and north America is ahead of these, you know, projects. A lot of them are near completion or, or they're in the middle of some sort of an, you know, industrial IOT security project right >>Now. I'm glad you brought the colonial pipeline one and, and oil and gas was the catalyst. Again, a lot of, Hey, scared that better than, than me kinda attitude, better invest. So I gotta ask you that, that supports Tim's point about the management plane. And I believe on that hack or ransomware, it wasn't actually control of the pipeline. It was control over the management billing, and then they shut down the pipeline cuz they were afraid it was gonna move over. So it wasn't actually the critical infrastructure itself to your point, Tim. >>Yeah. It's hardly over the critical infrastructure, by the way, you always go through the management plane, right. It's such an easier lying effort to compromise because it runs on an endpoint it's standard endpoint. Right? All this control software will, will be easier to get to rather than the industrial hardware itself. >>Yeah. It's it's, it's interesting. Just don't make a control software at the endpoint, put it zero trust. So down that was a great point. Oh guys. So really appreciate the time and the insight and, and the white paper's called NETEC it's on the Barracuda. Netex industrial security in 2022. It's on the barracuda.com website Barracuda network guys. So let's talk about the read force event hasn't been around for a while cuz of the pandemic we're back in person what's changed in 2019 a ton it's like security years is not dog years anymore. It's probably dog times too. Right. So, so a lot's gone on where are we right now as an industry relative to the security cybersecurity. Could you guys summarize kind of the, the high order bit on where we are today in 2022 versus 2019? >>Yeah, I think, you know, if you look at the awareness around how to secure infrastructure in applications that are built in public cloud in AWS, it's, you know, exponentially better than it was. I think I remember when you and I met in 2018 at one of these conferences, you know, there were still a lot of concerns, whether, you know, IAS was safe, you know, and I think the amount of innovation that's gone on and then the amount of education and awareness around how to consume, you know, public cloud resources is amazing. And you know, I think that's facilitated a lot of the fast growth we've seen, you know, the consistent, fast growth that we've seen across all these platforms >>Say that what's your reaction to the, >>I think the shared responsibility model is well understood, you know, and, and, and, and we can see a lot more implementation around, you know, CSBM, you know, continuously auditing the configurations in these cloud environments become a, a standard table stake, you know, investment from every stage of any business, right? Whether from early state startups, all the way to, you know, public companies. So I think it's very well understood and, and the, and the investment has been steady and robust when it comes to cloud security. We've been busy, you know, you know, helping our customers and AWS Azure environments and, and others. So I, I think it's well understood. And, and, and we are on a very optimistic note actually in a good place when it comes to public cloud. >>Yeah. A lot of great momentum, a lot of scale and data act out there. People sharing data, shared responsibility. Tim is in, thank you for sharing your insights here in this cube segment coverage of reinforce here in Boston. Appreciate it. >>All right. Thanks for having >>Us. Thank you. >>Okay, everyone. Thanks for watching the we're here at the reinforced conference. AWS, Amazon web services reinforced. It's a security focused conference. I'm John furier host of the cube. We'd right back with more coverage after the short break.
SUMMARY :
Thanks for coming on the queue. and all this is talking about industrial, you know, critical infrastructure. Yeah, I think at a high level, you know, we did a survey and saw that, you know, here, you know, lives depend on, on these technologies, right? Well, it's great to have both of you guys on, you know, Tim, you know, you had a background at AWS and sit on your startup, Germany, you know, teleporting into your environment in Hawaii. Obviously, you know, it's a position taking trust and verifies. breakdown over time because you are able to compromise end points relatively easily further and further down, you know, down the network, right? you know, maybe some proprietary technology yeah. But in the end, you know, you're taking your controls and, So instead of being, you know, historically it was the branch or user edge, And in fact, you know, one of the things we're gonna, we're gonna talk about this survey that you guys had done by But a lot of those, you know, industrial devices, And then, you know, it creates secure connections back into these, these control applications, Cuz you know, there's a lot of surface area that's evolving all the OT stuff and the you know, some sort of SSO identity provider, you get your, you sync with your user directories, So you need to have this concept of another abstraction layer of identity I mean, that seems to be the, the approach I think like, you know, sassy to me is really about, you know, behavior is and, you know, with very fine grain control, you can, you know, So you gotta go to the new way to do that. So I'll let you go first. the new sanctions, there's at least two more countries being, you know, I think it's gonna ignite more action off the books, so to speak as that we try to talk to our customers about, you know, and this affects industrial too, is the first thing you have Yeah. I mean, obviously that's kinda a best practice when you're bad guys, like go in and delete all the backups. We also talked about in the survey, you know, you know, that, you know, people tried to do these things and didn't get off the ground. So well established manufacturing environments, you know, the, you know, the call to arms that, that, that was the big, big, you know, industrial, So I gotta ask you that, that supports Tim's point about the management plane. It's such an easier lying effort to compromise because it runs on an endpoint it's standard endpoint. Could you guys summarize kind of the, at one of these conferences, you know, there were still a lot of concerns, whether, you know, Whether from early state startups, all the way to, you know, public companies. Tim is in, thank you for sharing your insights here in this Thanks for having I'm John furier host of the cube.
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Jay Bretzmann & Philip Bues, IDC | AWS re:Inforce 2022
(upbeat music) >> Okay, welcome back everyone. CUBE's coverage here in Boston, Massachusetts, AWS re:inforce 22, security conference. It's AWS' big security conference. Of course, theCUBE's here, all the reinvent, reese, remars, reinforced. We cover 'em all now and the summits. I'm John Furrier, my host Dave Vellante. We have IDC weighing in here with their analysts. We've got some great guests here, Jay Bretzmann research VP at IDC and Philip Bues research manager for Cloud security. Gentlemen, thanks for coming on. >> Thank you. >> Appreciate it. Great to be here. >> Appreciate coming. >> Got a full circle, right? (all laughing) Security's more interesting than storage, isn't it? (all laughing) >> Dave and Jay worked together. This is a great segment. I'm psyched that you guys are here. We had Crawford and Matt Eastwood on at HPE Discover a while back and really the data you guys are getting and the insights are fantastic. So congratulations to IDC. You guys doing great work. We appreciate your time. I want to get your reaction to the event and the keynotes. AWS has got some posture and they're very aggressive on some tones. Some things that we didn't hear. What's your reaction to the keynote? Share your assessment. >> So, you know, I manage two different research services at IDC right now. They are both Cloud security and identity and digital security, right? And what was really interesting is the intersection between the two this morning, because every one of those speakers that came on had something to say about identity or least privileged access, or enable MFA, or make sure that you control who gets access to what and deny explicitly. And it's always been a challenge a little bit in the identity world because a lot of people don't use MFA. And in RSA, that was another big theme at the RSA conference, MFA everywhere. Why don't they use it? Because it introduces friction and all of a sudden people can't get their jobs done. And the whole point of a network is letting people on to get that data they want to get to. So that was kind of interesting, but as we have in the industry, this shared responsibility model for Cloud computing, we've got shared responsibility for between Philip and I. (Philip laughing) I have done in the past more security of the Cloud and Philip is more security in the Cloud. >> So yeah. >> And now with Cloud operation Super Cloud, as we call it, you have on premises, private Cloud coming back, or hasn't really gone anywhere, all that on premises, Cloud operations, public Cloud, and now edge exploding with new requirements. It's really an ops challenge right now. Not so much dev. So the sec and op side is hot right now. >> Yeah, well, we've made this move from monolithic to microservices based applications. And so during the keynote this morning, the announcement around the GuardDuty Malware Protection component, and that being built into the pricing of current GuardDuty, I thought was really key. And there was also a lot of talk about partnering in security certifications, which is also so very important. So we're seeing this move towards filling in that talent gap, which I think we're all aware of in the security industry. >> So Jake, square the circle for me. So Kirk Coofell talked about Amazon AWS identity, where does AWS leave off, and companies like Okta or Ping identity or Cybertruck pickup, how are they working together? Does it just create more confusion and more tools for customers? We know the overused word of seamless. >> Yeah, yeah. >> It's never seamless, so how should we think about that? >> So, identity has been around for 35 years or something like that. Started with the mainframes and all that. And if you understand the history of it, you make more sense to the current market. You have to know where people came from and the baggage they're carrying, 'cause they're still carrying a lot of that baggage. Now, when it comes to the Cloud Service providers, they're more an accommodation from the identity standpoint. Let's make it easy inside of AWS to let you single sign on to anything in the Cloud that they have, right? Let's also introduce an additional MFA capability to keep people safer whenever we can and provide people with tools, to get into those applications somewhat easily, while leveraging identities that may live somewhere else. So there's a whole lot of the world that is still active, directory-centric, right? There's another portion of companies that were born in the Cloud that were able to jump on things like Okta and some of the other providers of these universal identities in the Cloud. So, like I said, if you understand where people came from in the beginning, you start to say, "Yeah, this makes sense." >> It's interesting you talk about mainframe. I always think about Rack F, you know. And I say, "Okay, who did what, when, where?" And you hear about a lot of those themes. So what's the best practice for MFA, that's non-SMS-based? Is it you got to wear something around your neck, is it to have sort of a third party authenticator? What are people doing that you guys would recommend? >> Yeah, one quick comment about adoption of MFA. If you ask different suppliers, what percent of your base that does SSO also does MFA, one of the biggest suppliers out there, Microsoft will tell you it's under 25%. That's pretty shocking. All the messaging that's come out about it. So another big player in the market was called Duo, Cisco bought them. >> Yep. >> And because they provide networks, a lot of people buy their MFA. They have probably the most prevalent type of MFA, it's called Push. And Push can be a red X and a green check mark to your phone, it can be a QR code, somewhere, it can be an email push as well. So that is the next easiest thing to adopt after SMS. And as you know, SMS has been denigrated by NIST and others saying, it's susceptible to man and middle attacks. It's built on a telephony protocol called SS7. Predates anything, there's no certification either side. The other real dynamic and identity is the whole adoption of PKI infrastructure. As you know, certificates are used for all kinds of things, network sessions, data encryption, well, identity increasingly. And a lot of the consumers and especially the work from anywhere, people these days have access through smart devices. And what you can do there, is you can have an agent on that smart device, generate your private key and then push out a public key and so the private key never leaves your device. That's one of the most secure ways to- >> So if our SIM card gets hacked, you're not going to be as vulnerable? >> Yeah, well, the SIM card is another challenge associated with the older ways, but yeah. >> So what do you guys think about the open source connection and they mentioned it up top. Don't bolt on security, implying shift left, which is embedding it in like sneak companies, like sneak do that. Very container oriented, a lot of Kubernetes kind of Cloud native services. So I want to get your reaction to that. And then also this reasoning angle they brought up. Kind of a higher level AI reasoning decisions. So open source, and this notion of AI reasoning. or AI reason. >> And you see more open source discussion happening, so you have your building maintaining and vetting of the upstream open source code, which is critical. And so I think AWS talking about that today, they're certainly hitting on a nerve, as you know, open source continues to proliferate. Around the automated reasoning, I think that makes sense. You want to provide guide rails and you want to provide roadmaps and you want to have sort of that guidance as to, okay, what's a correlation analysis of different tools and products? And so I think that's going to go over really well, yeah. >> One of the other key points about open source is, everybody's in a multi-cloud world, right? >> Yeah. >> And so they're worried about vendor lock in. They want an open source code base, so that they don't experience that. >> Yeah, and they can move the code around, and make sure it works well on each system. Dave and I were just talking about some of the dynamics around data control planes. So they mentioned encrypt everything which is great and I message by the way, I love that one. But oh, and he mentioned data at rest. I'm like, "What about data in flight? "Didn't hear that one." So one of the things we're seeing with SuperCloud, and now multi-cloud kind of as destinations of that, is that in digital transformation, customers are leaning into owning their data flows. >> Yeah. >> Independent of say the control plane aspects of what could come in. This is huge implications for security, where sharing data is huge, even Schmidt on stage said, we have billions and billions of things happening that we see things that no one else sees. So that implies, they're sharing- >> Quad trillion. >> Trillion, 15 zeros. (Jay laughs) >> 15 zeros. >> So that implies they're sharing that or using that pushing that into something. So sharing is huge with cyber security. So that implies open data, data flows. How do you guys see this evolving? I know it's kind of emerging, but it's becoming a nuanced point, that's critical to the architecture. >> Well, yeah, I think another way to look at that is the sharing of intelligence and some of the recent directives, from the executive branch, making it easier for private companies to share data and intelligence, which I think strengthens the cyber community overall. >> Depending upon the supplier, it's either an aggregate level of intelligence that has been anonymized or it's specific intelligence for your environment that everybody's got a threat feed, maybe two or three, right? (John laughs) But back to the encryption point, I mean, I was working for an encryption startup for a little while after I left IBM, and the thing is that people are scared of it. They're scared of key management and rotation. And so when you provide- >> Because they might lose the key. >> Exactly. >> Yeah. >> It's like shooting yourself in the foot, right? So that's when you have things like, KMS services from Amazon and stuff that really help out a lot. And help people understand, okay, I'm not alone in this. >> Yeah, crypto owners- >> They call that hybrid, the hybrid key, they don't know how they call the data, they call it the hybrid. What was that? >> Key management service? >> The hybrid- >> Oh, hybrid HSM, correct? >> Yeah, what is that? What is that? I didn't get that. I didn't understand what he meant by the hybrid post quantum key agreement. >> Hybrid post quantum key exchange. >> AWS never made a product name that didn't have four words in it. (John laughs) >> But he did reference the new NIST algos. And I think I inferred that they were quantum proof or they claim to be, and AWS was testing those. >> Correct, yeah. >> So that was kind of interesting, but I want to come back to identity for a second. So, this idea of bringing traditional IAM and Privileged Access Management together, is that a pipe dream, is that something that is actually going to happen? What's the timeframe, what's your take on that? >> So, there are aspects of privilege in every sort of identity. Back when it was only the back office that used computers for calculations, right? Then you were able to control how many people had access. There were two types of users, admins and users. These days, everybody has some aspect of- >> It's a real spectrum, really. >> Yeah. >> Granular. >> You got the C-suite, the finance people, the DevOps people, even partners and whatever. They all need some sort of privileged access, and the term you hear so much is least-privileged access, right? Shut it down, control it. So, in some of my research, I've been saying that vendors who are in the PAM space, Privilege Access Management space, will probably be growing their suites, playing a bigger role, building out a stack, because they have the expertise and the perspective that says, "We should control this better." How do we do that, right? And we've been seeing that recently. >> Is that a combination of old kind of antiquated systems meets for proprietary hyper scale, or kind of like build your own? 'Cause I mean, Amazon, these guys, Facebook, they all build their own stuff. >> Yes, they do. >> Then enterprises buy services from general purpose identity management systems. >> So as we were talking about knowing the past and whatever, Privileged Access Management used to be about compliance reporting. Just making sure that I knew who accessed what? And could prove it, so I didn't fail at all. >> It wasn't a critical infrastructure item. >> No, and now these days, what it's transitioning into, is much more risk management, okay. I know what our risk is, I'm ahead of it. And the other thing in the PAM space, was really session monitor. Everybody wanted to watch every keystroke, every screen's scrape, all that kind of stuff. A lot of the new Privileged Access Management, doesn't really require that. It's a nice to have feature. You kind of need it on the list, but is anybody really going to implement it? That's the question, right. And then if you do all that session monitoring, does anybody ever go back and look at it? There's only so many hours in the day. >> How about passwordless access? (Jay laughs) I've heard people talk about that. I mean, that's as a user, I can't wait but- >> Well, it's somewhere we want to all go. We all want identity security to just disappear and be recognized when we log in. So the thing with passwordless is, there's always a password somewhere. And it's usually part of a registration action. I'm going to register my device with a username password, and then beyond that I can use my biometrics, right? I want to register my device and get a private key, that I can put in my enclave, and I'll use that in the future. Maybe it's got to touch ID, maybe it doesn't, right? So even though there's been a lot of progress made, it's not quote, unquote, truly passwordless. There's a group, industry standards group called Fido. Which is Fast Identity Online. And what they realized was, these whole registration passwords, that's really a single point of failure. 'Cause if I can't recover my device, I'm in trouble. So they just did new extension to sort of what they were doing, which provides you with much more of like an iCloud vault that you can register that device in and other devices associated with that same identity. >> Get you to it if you have to. >> Exactly. >> I'm all over the place here, but I want to ask about ransomware. It may not be your wheelhouse. But back in the day, Jay, remember you used to cover tape. All the backup guys now are talking about ransomware. AWS mentioned it today and they showed a bunch of best practices and things you can do. Air gaps wasn't one of them. I was really surprised 'cause that's all every anybody ever talks about is air gaps and a lot of times that air gap could be a guess to the Cloud, I guess, I'm not sure. What are you guys seeing on ransomware apps? >> We've done a lot of great research around ransomware as a service and ransomware, and we just had some data come out recently, that I think in terms of spending and spend, and as a result of the Ukraine-Russia war, that ransomware assessments rate number one. And so it's something that we encourage, when we talk to vendors and in our services, in our publications that we write about taking advantage of those free strategic ransomware assessments, vulnerability assessments, as well and then security and training ranked very highly as well. So, we want to make sure that all of these areas are being funded well to try and stay ahead of the curve. >> Yeah, I was surprised to not see air gaps on the list, that's all everybody talks about. >> Well, the old model for air gaping in the land days, the novel days, you took your tapes home and put them in the sock drawer. (all laughing) >> Well, it's a form of air gap. (all laughing) >> Security and no one's going to go there and clean out. >> And then the internet came around and ruined it. >> Guys, final question we want to ask you, guys, we kind of zoom out, great commentary by the way. Appreciate it. We've seen this in many markets, a collection of tools emerge and then there's its tool sprawl. So cyber we're seeing the trend now where mon goes up on stage of all the ecosystems, probably other vendors doing the same thing where they're organizing a platform on top of AWS to be this super platform, for super Cloud capability by building a more platform thing. So we're saying there's a platform war going on, 'cause customers don't want the complexity. I got a tool but it's actually making it more complex if I buy the other tool. So the tool sprawl becomes a problem. How do you guys see this? Do you guys see this platform emerging? I mean tools won't go away, but they have to be easier. >> Yeah, we do see a consolidation of functionality and services. And we've been seeing that, I think through a 2020 Cloud security survey that we released that was definitely a trend. And that certainly happened for many companies over the last six to 24 months, I would say. And then platformization absolutely is something we talk and write about all the time so... >> Couple of years ago, I called the Amazon tool set an erector set because it really required assembly. And you see the emphasis on training here too, right? You definitely need to go to AWS University to be competent. >> It wasn't Lego blocks yet. >> No. >> It was erector set. >> Yeah. >> Very good distinction. >> Loose. >> And you lose a few. (chuckles) >> But still too many tools, right? You see, we need more consolidation. It's getting interesting because a lot of these companies have runway and you look at sale point at stock prices held up 'cause of the Thoma Bravo acquisition, but all the rest of the cyber stocks have been crushed especially the high flyers, like a Sentinel-1 one or a CrowdStrike, but just still M and A opportunity. >> So platform wars. Okay, final thoughts. What do you, think is happening next? What's your outlook for the next year or so? >> So, in the identity space, I'll talk about, Philip can cover Cloud for us. It really is more consolidation and more adoption of things that are beyond simple SSO. It was, just getting on the systems and now we really need to control what you're able to get to and who you are. And do it as transparently as we possibly can, because otherwise, people are going to lose productivity. They're not going to be able to get to what they want. And that's what causes the C-suite to say, "Wait a minute," DevOps, they want to update the product every day. Make it better. Can they do that or did security get in the way? People, every once in a while call security, the Department of No, right? >> They ditch it on stage. They want to be the Department of Yes. >> Exactly. >> Yeah. >> And the department that creates additional value. If you look at what's going on with B2C or CIAM, consumer oriented identity, that is all about opening up new direct channels and treating people like their old friends, not like you don't know them, you have to challenge them. >> We always say, you want to be in the boat together, it sinks or not. >> Yeah. Exactly. >> Philip I'm glad- >> Okay, what's your take? What's your outlook for the year? >> Yeah, I think, something that we've been seeing as consolidation and integration, and so companies looking at from built time to run time, investing in shift left infrastructure is code. And then also in the runtime detection, makes perfect sense to have both the agent and agent lists so that you're covering any of the gaps that might exist. >> Awesome, Jay Phillip, thanks for coming on "theCUBE" with IDC and sharing your- >> Oh, our pleasure- >> Perspective, commentary and insights and outlook. Appreciate it. >> You bet. >> Thank you. >> Okay, we've got the great direction here from IDC analyst here on the queue. I'm John Furrier, Dave Vellante. Be back more after this short break. (bright upbeat music)
SUMMARY :
We cover 'em all now and the summits. Great to be here. and the insights are fantastic. and Philip is more security in the Cloud. So the sec and op side is hot right now. and that being built into the So Jake, square the circle for me. and some of the other providers And you hear about a lot of those themes. the market was called Duo, And a lot of the consumers card is another challenge So what do you guys think of the upstream open source so that they don't experience that. and I message by the way, I love that one. the control plane aspects (Jay laughs) So that implies they're sharing that and some of the recent directives, and the thing is that and stuff that really help out a lot. the hybrid key, by the hybrid post quantum key agreement. that didn't have four words in it. the new NIST algos. So that was kind that used computers for and the term you hear so much Is that a combination of old identity management systems. about knowing the past and whatever, It wasn't a critical You kind of need it on the list, I mean, that's as a So the thing with passwordless is, But back in the day, Jay, and stay ahead of the curve. not see air gaps on the list, air gaping in the land days, Well, it's a form of air gap. Security and no one's going And then the internet of all the ecosystems, over the last six to I called the Amazon And you lose a few. 'cause of the Thoma Bravo acquisition, the next year or so? So, in the identity space, They ditch it on stage. And the department that We always say, you want of the gaps that might exist. and insights and outlook. analyst here on the queue.
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Phillip Bues & Jay Bretzmann, IDC | AWS re:Inforce 2022
>>Okay, welcome back everyone. Cube's coverage here in Boston, Massachusetts, AWS reinforced 22, the security conference. It's ADOS big security conference. Of course, the cubes here, all the reinvent res re Mars reinforce. We cover 'em all now and the summits. I'm John. Very my host, Dave ante have IDC weighing in here with their analysis. We've got some great guests here, Jay Brisbane, research VP at IDC and Philip who research managed for cloud security. Gentlemen, thanks for coming on. Thank you. Appreciate it. Great >>To, to be here. I appreciate the got the full >>Circle, right? Just, security's more interesting >>Than storage. Isn't it? >>Dave, Dave and Jay worked together. This is a, a great segment. I'm psyched that you guys are here. We had Crawford and Matt Eastwood on at HPE discover a while back and really the, the, the data you guys are getting and the insights are fantastic. So congratulations to IDC. You guys doing great work. We appreciate your time. I wanna get your reaction to the event and the keynotes. AWS has got some posture and they're very aggressive on some tones. Some things that they didn't, we didn't hear. What's your reaction to the keynote, share your, your assessment. >>So, you know, I managed two different research services at IDC right now. They are both cloud security and identity and, and digital security. Right. And what was really interesting is the intersection between the two this morning, because every one of those speakers that came on had something to say about identity or least privileged access, or, you know, enable MFA, or make sure that you, you know, control who gets access to what and deny explicitly. Right? And it's always been a challenge a little bit in the identity world because a lot of people don't use MFA. And in RSA, that was another big theme at the RSA conference, right? MFA everywhere. Why don't they use it because it introduces friction and all of a sudden people can't get their jobs done. Right. And the whole point of a network is letting people on to get that data they want to get to. So that was kind of interesting, but, you know, as we have in the industry, this shared responsibility model for cloud computing, we've got shared responsibility for between Philip and I, I have done in the ke past more security of the cloud and Philip is more security in the cloud, >>So yeah. And it's, and now with cloud operation, super cloud, as we call it, you have on premises, private cloud coming back, or hasn't really gone anywhere, all that on premises, cloud operations, public cloud, and now edge exploding with new requirements. Yeah. It's really an ops challenge right now. Not so much dev. So the sick and op side is hot right now. >>Yeah. Well, we've made this move from monolithic to microservices based applications. And so during the keynote this morning, the announcement around the guard duty malware protection component, and that being built into the pricing of current guard duty, I thought was, was really key. And there was also a lot of talk about partnering in security certifications. Yeah. Which is also so very important. So we're seeing this move towards filling in that talent gap, which I think we're all aware of in the security industry. >>So Jake square, the circle for me. So Kirk, Coel talked about Amazon AWS identity, where does AWS leave off and, and companies like Okta or ping identity or crock pickup, how are they working together? Does it just create more confusion and more tools for customers? We, we have, we know the over word overused word of seamless. Yeah. Yeah. It's never seamless. So how should we think about that? >>So, you know, identity has been around for 35 years or something like that started with the mainframes and all that. And if you understand the history of it, you make more sense to the current market. You have to know where people came from and the baggage they're carrying, cuz they're still carrying a lot of that baggage. Now, when it comes to the cloud service providers, they're more an accommodation from the identity standpoint, let's make it easy inside of AWS to let you single sign on to anything in the cloud that they have. Right. Let's also introduce an additional MFA capability to keep people safer whenever we can and, you know, provide people the tools to, to get into those applications somewhat easily, right. While leveraging identities that may live somewhere else. So, you know, there's a whole lot of the world that is still active directory centric, right? There's another portion of companies that were born in the cloud that were able to jump on things like Okta and some of the other providers of these universal identities in the cloud. So, you know, like I said, you, if you understand where people came from in the beginning, you start to, to say, yeah, this makes sense. >>It's, it's interesting. You talk about mainframe. I, I always think about rack F you know, and I say, okay, who did what, when, where, yeah. And you hear about a lot of those themes. What, so what's the best practice for MFA? That's, that's non SMS based. Is it, you gotta wear something around your neck, is it to have sort of a third party authenticator? What are people doing that is that, that, that you guys would recommend? >>Yeah. One quick comment about adoption of MFA. You know, if you ask different suppliers, what percent of your base that does SSO also does MFA one of the biggest suppliers out there Microsoft will tell you it's under 25%. That's pretty shocking. Right? All the messaging that's come out about it. So another big player in the market was called duo. Cisco bought them. Yep. Right. And because they provide networks, a lot of people buy their MFA. They have probably the most prevalent type of MFA it's called push. Right. And push can be, you know, a red X and a green check mark to your phone. It can be a QR code, you know, somewhere, it can be an email push as well. So that is the next easiest thing to adopt after SMS. And as you know, SMS has been denigrated by N and others saying, you know, it's susceptible to man and middle attacks. >>It's built on a telephony protocol called SS seven. Yep. You know, predates anything. There's no certification, either side. The other real dynamic and identity is the whole adoption of PKI infrastructure. As you know, certificates are used for all kinds of things, network sessions, data encryption, well identity increasingly, and a lot of the, you know, consumers and especially the work from anywhere, people these days have access through smart devices. Right. And what you can do there is you can have an agent on that smart device, generate your private key and then push out a public key. And so the private key never leaves your device. That's one of the most secure ways to, so if your >>SIM card gets hacked, you're not gonna be as at vulnerable >>Or as vulnerable. Well, the SIM card is another, you know, challenge associated with the, the older waste. But yeah. Yeah. >>So what do you guys think about the open source connection and, and they, they mentioned it up top don't bolt on security implying shift left, which is embedding it in like sneak companies, like sneak do that, right. Container oriented, a lot of Kubernetes kind of cloud native services. So I wanna get your reaction to that. And then also this reasoning angle, they brought up kind of a higher level AI reasoning decisions. So open source and this notion of AI reasoning >>Automation. Yeah. And, and you see more open source discussion happening, right. So you, you know, you have your building maintaining and vetting of the upstream open source code, which is critical. And so I think AWS talking about that today, they're certainly hitting on a nerve as, you know, open source continues to proliferate around the automated reasoning. I think that makes sense. You know, you want to provide guiderails and you want to provide roadmaps and you wanna have sort of that guidance as to okay. What's the, you know, a correlation analysis of different tools and products. And so I think that's gonna go over really well. >>Yeah. One of the other, you know, key points of what open source is, everybody's in a multi-cloud world, right? Yeah. And so they're worried about vendor lockin, they want an open source code base so that they don't experience that. >>Yeah. And they can move the code around and make sure it works well on each system. Dave and I were just talking about some of the dynamics around data control planes. So yeah. They mentioned encrypt everything, which is great. And I message, by the way, I love that one, but oh. And he mentioned data at rest. I'm like, what about data in flight? Didn't hear that one. So one of the things we're seeing with super cloud, and now multi-cloud kind of, as destinations of that, is that in digital transformation, customers are leaning into owning their data flows. >>Yeah. >>Independent of say the control plane aspects of what could come in. This is huge implications for security, where sharing data is huge. Even Schmidt on Steve said we have billions and billions of things happening that we see things that no one else else sees. So that implies, they're >>Sharing quad trillion, >>Trillion, 15 zeros trillion. Yeah. 15 >>Zeros, 15 zeros. Yeah. >>So that implies, they're sharing that or using that, pushing that into something. So sharing's huge with cyber security. So that implies open data, data flows. What do, how do you guys see this evolving? I know it's kind of emerging, but it's becoming a, a nuanced point that's critical to the architecture. >>Well, I, yeah, I think another way to look at that is the sharing of intelligence and some of the recent directives, you know, from the executive branch, making it easier for private companies to share data and intelligence, which I think strengthens the cyber community overall, >>Depending upon the supplier. Right? Yeah. It's either an aggregate level of intelligence that has been, you know, anonymized or it's specific intelligence for your environment that, you know, everybody's got a threat feed, maybe two or three, right. Yeah. But back to the encryption point, I mean, I was working for an encryption startup for a little while. Right after I left IBM. And the thing is that people are scared of it. Right. They're scared of key management and rotation. And so when you provide, >>Because they might lose the key. >>Exactly. Yeah. It's like shooting yourself in the foot. Right. So that's when you have things like, you know, KMS services from Amazon and stuff, they really help out a lot and help people understand, okay, I'm not alone in this. >>Yeah. Crypto >>Owners, they call that hybrid, the hybrid key, they call the, what they call the, today. They call it the hybrid. >>What was that? The management service. Yeah. The hybrid. So hybrid HSM, correct. >>Yeah. What is that? What is that? I didn't, I didn't get that. I didn't understand what he meant by the hybrid post hybrid, post quantum key agreement. Right. That still notes >>Hybrid, post quantum key exchange, >>You know, AWS never made a product name that didn't have four words in it, >>But he did, but he did reference the, the new N algos. And I think I inferred that they were quantum proof or the claim it be. Yeah. And AWS was testing those. Correct. >>Yeah. >>So that was kind of interesting, but I wanna come back to identity for a second. Okay. So, so this idea of bringing traditional IAM and, and privilege access management together, is that a pipe dream, is that something that is actually gonna happen? What's the timeframe, what's your take on that? >>So, you know, there are aspects of privilege in every sort of identity back when, you know, it was only the back office that used computers for calculations, right? Then you were able to control how many people had access. There were two types of users, admins, and users, right? These days, everybody has some aspect of, >>It's a real spectrum, really >>Granular. You got the, you know, the C suite, the finance people, the DevOps, people, you know, even partners and whatever, they all need some sort of privileged access. And the, the term you hear so much is least privileged access. Right? Shut it down, control it. So, you know, in some of my research, I've been saying that vendors who are in the Pam space privilege access management space will probably be growing their suites, playing a bigger role, building out a stack because they have, you know, the, the expertise and the, and the perspective that says we should control this better. How do we do that? Right. And we've been seeing that recently, >>Is that a combination of old kind of antiquated systems meets for proprietary hyperscale or kind of like build your own? Cause I mean, Amazon, these guys, they Facebook, they all build their own stuff. >>Yes. They >>Do enterprises buy services from general purpose identity management systems. >>So as we were talking about, you know, knowing the past and whatever privileged access management used to be about compliance reporting. Yeah. Right. Just making sure that I knew who accessed what and could prove it. So I didn't fail in art. It wasn't >>A critical infrastructure item. >>No. And now these days, what it's transitioning into is much more risk management. Okay. I know what our risk is. I'm ahead of it. And the other thing in the Pam space was really session monitor. Right. Everybody wanted to watch every keystroke, every screen's scrape, all that kind of stuff. A lot of the new privilege access Mon management doesn't really require that it's nice to have feature. You kind of need it on the list, but is anybody really gonna implement it? That's the question. Right. And then, you know, if, if you do all that session monitor, does anybody ever go back and look at it? There's only so many hours in the day. >>How about passwordless access? You know? Right. I've heard people talk about that. Yeah. I mean, that's as a user, I can't wait, but >>It's somewhere we want to all go. Yeah. Right. We all want identity security to just disappear and be recognized when we log in. So the, the thing with password list is there's always a password somewhere and it's usually part of a registration, you know, action. I'm gonna register my device with a username password. And then beyond that, I can use my biometrics. Right. I wanna register my device and get a private key that I can put in my enclave. And I'll use that in the future. Maybe it's gotta touch ID. Maybe it doesn't. Right. So even though there's been a lot of progress made, it's not quote unquote, truly passwordless, there's a group industry standards group called Fido. Right. Which is fast identity online. And what they realized was these whole registration passwords. That's really a single point of failure. Cuz if I can't recover my device, I'm in trouble. Yeah. So they just did a, a new extension to sort of what they were doing, which provides you with much more of a, like an iCloud vault, right. That you can register that device in and other devices associated with that same iPad that you can >>Get you to it. If you >>Have to. Exactly. I had >>Another have all over the place here, but I, I want to ask about ransomware. It may not be your wheelhouse. Yeah. But back in the day, Jay, remember you used to cover tape. All the, all the backup guys now are talking about ransomware. AWS mentioned it today and they showed a bunch of best practices and things you can do air gaps. Wasn't one, one of 'em. Right. I was really surprised cuz that's all, every anybody ever talks about is air gaps. And a lot of times that air gaps that air gap could be a guess to the cloud. I guess I'm not sure. What are you guys seeing on ransomware >>Apps? You know, we've done a lot of great research around ransomware as a service and ransomware and, and you know, we just had some data come out recently that I think in terms of spending and, and spend and in as a result of the Ukraine, Russia war, that ransomware assessments rate number one. And so it's something that we encourage, you know, when we talk to vendors and in our services, in our publications that we write about taking advantage of those free strategic ransomware assessments, vulnerability assessments, right. As well, and then security and training ranked very highly as well. So we wanna make sure that all of these areas are being funded well to try and stay ahead of the curve. >>Yeah. I was surprised that not the air gaps on the list, that's all everybody >>Talks about. Well, you know, the, the old model for air gaping in the, the land days, the Noel days, you took your tapes home and put 'em in the sock drawer. >>Well, it's a form of air gap security and no one's gonna go there >>Clean. And then the internet came around >>Guys. Final question. I want to ask you guys, we kind zoom out. Great, great commentary by the way. Appreciate it. As the, we've seen this in many markets, a collection of tools emerge and then there's it's tool sprawl. Oh yeah. Right? Yeah. So cyber we're seeing trend now where Mon goes up on stage of all the E probably other vendors doing the same thing where they're organizing a platform on top of AWS to be this super platform. If you super cloud ability by building more platform thing. So we're saying there's a platform war going on, cuz customers don't want the complexity. Yeah. I got a tool, but it's actually making it more complex if I buy the other tool. So the tool sprawl becomes a problem. How do you guys see this? Do you guys see this platform emerging? I mean, tools won't go away, but they have to be >>Easier. Yeah. We do see a, a consolidation of functionality and services. And we've been seeing that, I think through a 20, 20 flat security survey that we released, that that was definitely a trend. And you know, that certainly happened for many companies over the last six to 24 months, I would say. And then platformization absolutely is something we talk 'em right. About all the time. So >>More M and a couple of years ago, I called the, the Amazon tool set in rector set. Yeah. Because it really required assembly. Yeah. And you see the emphasis on training here too, right? Yeah. You definitely need to go to AWS university to be competent. It >>Wasn't Lego blocks yet. No, it was a rector set. Very good distinction rules, you know, and, and you lose a few. It's >>True. Still too many tools. Right. You see, we need more consolidation. That's getting interesting because a lot of these companies have runway and you look, you look at sale point, its stock prices held up cuz of the Toma Bravo acquisition, but all the rest of the cyber stocks have been crushed. Yeah. You know, especially the high flyers, like a Senti, a one or a crowd strike, but yeah, just still M and a opportunity >>Itself. So platform wars. Okay. Final thoughts. What do you thinks happening next? What's what's your outlook for the, the next year or so? >>So in the, in the identity space, I'll talk about Phillip can cover cloud force. You know, it really is more consolidation and more adoption of things that are beyond simple SSO, right. It was, you know, just getting on the systems and now we really need to control what you're able to get to and who you are and do it as transparently as we possibly can because otherwise, you know, people are gonna lose productivity, right. They're not gonna be able to get to what they want. And that's what causes the C-suite to say, wait a minute, you know, DevOps, they want to update the product every day. Right. Make it better. Can they do that? Or did security get in the way people every once in a while I'll call security, the department of no, right? Yeah. Well, >>Yeah. They did it on stage. Yeah. They wanna be the department of yes, >>Exactly. And the department that creates additional value. If you look at what's going on with B to C or C IAM, consumer identity, that is all about opening up new direct channels and treating people like, you know, they're old friends, right. Not like you don't know 'em you have to challenge >>'em we always say you wanna be in the boat together. It sinks or not. Yeah. Right. Exactly. >>Phillip, >>Okay. What's your take? What's your outlook for the year? >>Yeah. I think, you know, something that we've been seeing as consolidation and integration, and so, you know, companies looking at from built time to run time investing in shift left infrastructure is code. And then also in the runtime detection makes perfect sense to have both the agent and agentless so that you're covering any of the gaps that might exist. >>Awesome. Jerry, Phillip, thanks for coming on the queue with IDC and sharing >>Your oh our pleasure perspective. >>Commentary, have any insights and outlook. Appreciate it. You bet. Thank you. Okay. We've got the great direction here from IDC analyst here on the queue. I'm John for a Dave, we're back more after this shirt break.
SUMMARY :
We cover 'em all now and the summits. I appreciate the got the full I'm psyched that you guys are here. or, you know, enable MFA, or make sure that you, you know, And it's, and now with cloud operation, super cloud, as we call it, you have on premises, And so during the keynote this morning, the announcement around the guard duty malware protection So Jake square, the circle for me. to keep people safer whenever we can and, you know, provide people the tools to, I, I always think about rack F you know, And as you know, SMS has been denigrated by N and others saying, you know, and a lot of the, you know, consumers and especially the work from anywhere, Well, the SIM card is another, you know, challenge associated with the, So what do you guys think about the open source connection and, and they, they mentioned it up top don't you know, you have your building maintaining and vetting of the upstream open source code, And so they're worried about vendor lockin, they want an open source code base so And I message, by the way, I love that one, but oh. Independent of say the control plane aspects of what could come in. Yeah. 15 Yeah. What do, how do you guys see this evolving? been, you know, anonymized or it's specific intelligence for your environment So that's when you have They call it the hybrid. Yeah. I didn't understand what he meant by the hybrid post hybrid, And I think I inferred So that was kind of interesting, but I wanna come back to identity for a second. So, you know, there are aspects of privilege in every sort of identity back when, You got the, you know, the C suite, the finance people, the DevOps, people, you know, Cause I mean, Amazon, these guys, they Facebook, So as we were talking about, you know, knowing the past and whatever privileged access management used And then, you know, Yeah. somewhere and it's usually part of a registration, you know, action. Get you to it. I had But back in the day, Jay, remember you used to cover tape. And so it's something that we encourage, you know, the Noel days, you took your tapes home and put 'em in the sock drawer. And then the internet came around I want to ask you guys, we kind zoom out. And you know, that certainly happened for many companies over the And you see the emphasis on training here you know, and, and you lose a few. runway and you look, you look at sale point, its stock prices held up cuz of the Toma Bravo acquisition, What do you thinks happening next? the C-suite to say, wait a minute, you know, DevOps, they want to update the product every day. Yeah. direct channels and treating people like, you know, they're old friends, 'em we always say you wanna be in the boat together. What's your outlook for the year? and so, you know, companies looking at from built time to run time investing in shift analyst here on the queue.
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Anant Adya & Saju Sankarankutty, Infosys | HPE Discover 2022
>>the Cube presents H p E discover 2022. Brought to you by H P E. >>Okay, we're back at HPD. Discovered 2022 This is Day Three. We're kind of in the mid point of day three. John Furry and Dave Volonte Wall to wall coverage. I think there are 14th hp slash hp Discover we've sort of documented the history of the company over the last decade. Plus, I'm not a is here is executive vice president at Infosys and Cejudo. Sankaran Kutty is the CEO and vice president of Infosys. Infosys doing some amazing work in the field with clients. Guys, Thanks for coming on the Cube. Thank >>you for the opportunity. >>Yeah, absolutely so. Digital transformation. It's all the buzz word kind of pre pandemic. It was sort of Yeah, you know, we'll get there a lot of lip service to it. Some Some started the journey and then, of course, pandemic. If you weren't digital business, you are out of business. What are the trends that you're seeing now that we're exiting the isolation economy? >>Yeah, um, again, as you rightly called out pre pandemic, it was all about using sort of you know innovation at scale as one of the levers for digital transformation. But if you look at now, post Pandemic, one of the things that we see it's a big trend is at a broad level, right? Digital transformation is not about cost. Take out. Uh, it's all about growth, right? So essentially, uh, like, uh, what we hear from most of the CEO s and most of the customers and most of the executives in the tech company, Digital transformation should be used for business growth. And essentially, it means three things that we see three trends in that space. One is how can you build better products and solutions as part of your transformation strategy? How can you basically use digital transformation to expand into new markets and new new territories and new regions? And the third is, how can you better the experience for your customers? Right. So I think that is broadly what we see as, uh, some other things. And essentially, if you have better customer experience, they will buy more. If you expand into new markets, your revenue will increase. If you actually build better products and solutions, consumers will buy it right, so It's basically like a sort of an economy that goes hand in hand. So I would say the trend is clearly going towards business growth than anything else when it comes to the, >>you know, follow up on that. We had I d. C on yesterday and they were sharing with some of their high level numbers. We've looked at this and and and it seems like I t spending is pretty consistent despite the fact that, for example, you know, the to see the consumer businesses sort of tanking right now. Are you seeing any pullback or any evidence that people are pulling the reins back on the digital transformation Or they just going because if they don't keep keep moving fast, they're gonna fall behind. What are you seeing there? Absolutely. >>In fact, you know what? What we call them as the secular headwinds, right? I mean, if you look at the headwinds here, we see digital transformation is in the minds of everybody, every customer, right. So while there are budget constraints, where are all these macro tailwinds as we call with respect to inflation, with respect to what's happening with Russia and Ukraine with respect to everything that's happening with respect to supply chain right. I think we see some of those tail headwinds. But essentially, digital transformation is not stopping. Everybody is going after that because essentially they want to be relevant in the market. And if they want to be relevant in the market, they have to transform. And if they have to transform, they have to adopt digital transformation. >>Basically, there's no hiding anymore. You know, hiding and you can't hide the projects and give lip service because there's evidence of what the consequences are. And it can be quantified. Yes, you go out of business, you lose money. You mentioned some of the the cost takeouts growth is yes. So I got given the trends and the headwinds and the tail winds. What are you guys seeing as the pattern of companies that came out of the pandemic with growth? And what's going on with that growth driver? What are the elements that are powering companies to grow? Is that machine learning? Is that cloud scales and integration? What are some of the key areas that's given that extra up into the right? >>Yes, I I would say there are six technologies that are defining how growth is being enabled, right? So I think we call it as cloud ai edge five g, Iot and of course, everything to do with a And so these are six technologies that are powering digital transformation. And, uh, one of the things that we are saying is more and more customers are now coming and saying that we want to use these six technologies to drive business outcomes. Uh, for example, uh, we have a very large oil and gas customer of ours who says that, you know, we want to basically use cloud as a lever to Dr Decarbonization. E S G is such a big initiative for everybody in the SGS in the minds of everybody. So their outcome of using technology is to drive decarbonization. And they don't make sure that, you know, they achieve the goals of E. S G. Right There is another customer of ours in the retail space. They are saying we want to use cloud to drive experience for our employees. So I would say that you know, there is pretty much, you know, all these drivers which are helping not just growing their business, but also bettering the experience and meeting some of the organisation goals that they have set up with respect to cloud. So I would say Cloud is playing a big role in every digital transformation initiative of the company. >>How do you spend your time? What's the role of the CEO inside of a large organisation like Infosys? >>So, um, one is in terms of bringing in an outside in view of how technology is making an impact to our customers. And I'm looking at How do we actually start liberating some of these technologies in building solutions, you know, which can actually drive value for our customers? That's one of the focus areas. You know what I do? Um, And if you look at some of the trends, you know what we have seen in the past years as well as what we're seeing now? Uh, there's been a huge spend around cloud which is happening with our customers and predominantly around the cloud Native application development, leveraging some of the services. What's available from the cloud providers like eh? I am l in Hyoty. Um, and and there's also a new trend. You know what we are seeing off late now, which is, um, in terms of improving the experience overall experience liberating some of the technologies, like technologies like block, block, chain as well as we are, we are right, and and this is actually creating new set of solutions. Um, new demands, you know, for our customers in terms of leveraging technologies like matadors leveraging technologies like factory photo. Um, and these are all opportunities for us to build solutions, you know, which can, you know, improve the time to market for our customers in terms of adopting some of these things. Because there has been a huge focus on the improved end user experience or improve experience improved, uh, productivity of, uh, employees, you know, which is which has been a focus. Uh, post pandemic. Right? You know, it has been something which is happening pre pandemic, but it's been accelerated Post pandemic. So this is giving an opportunity for for my role right now in terms of liberating these technologies, building solutions, building value propositions, taking it to our customers, working with partners and then trying to see how we can have this tightly integrated with partners like HP E in this case, and then take it jointly to the market and and find out you know, what's what's the best we can actually give back to our customers? >>You know, you guys have been we've been following you guys for for a long, long time. You've seen many cycles, uh, in the industry. Um, and what's interesting to get your reaction to what we're seeing? A lot of acceleration points, whether it's cloud needed applications. But one is the software business is no longer there. It's open source now, but cloud scale integrations, new hybrid environment kind of brings and changes the game, so there's definitely software plentiful. You guys are doing a lot of stuff with the software. How are customers integrated? Because seeing more and more customers participating in the open source community uh, so what? Red hat's done. They're transforming the open shift. So as cloud native applications come in and get scale and open source software, cloud scale performance and integrations are big. You guys agree with that? >>Absolutely. Absolutely. So if you if you look at it, um, right from the way we can't socialise those solutions, um, open source is something What we have embedded big way right into the solution. Footprint. What we have one is, uh, the ability for us to scale the second is the ability for us to bring in a level of portability, right? And the third is, uh, ensuring that there is absolutely no locking into something. What we're building. We're seeing this this being resonated by our customers to because one is they want to build a child and scalable applications. Uh, it's something where the whole, I would say, the whole dependency on the large software stacks. Uh, you know, the large software providers is likely diminishing now, right? Uh, it's all about how can I simplify my application portfolio Liberating some of the open source technologies. Um, how can I deploy them on a multi cloud world liberating open standards so that I'm not locked into any of these providers? Um, how can I build cloud native applications, which can actually enable portability? And how can I work with providers who doesn't have a lock in, you know, into their solutions, >>And security is gonna be embedded in everything. Absolutely. >>So security is, uh, emperor, right from, uh, design phase. Right? You know, we call it a secure by design And that's something What? We drive for our customers right from our solutions as well as for developing their own solutions >>as opposed to secure by bolt on after the fact. What is the cobalt go to market strategy? How does that affect or how you do business within the HP ecosystem? Absolutely. >>I think you know what we did in, uh, in 2000 and 20. We were the first ones, uh, to come out with an integrated cloud brand called Cobalt. So essentially, our thought process was to make sure that, you know, we talk one consistent language with the customer. There is a consistent narrative. There is a consistent value proposition that we take right. So, essentially, if you look at the Cobalt gold market, it is based on three pillars. The first pillar is all about technology solutions. Getting out of data centres migrating were close to cloud E r. P on Cloud Cloud, Native Development, legacy modernisation. So we'll continue to do that because that's the most important pillar. And that's where our bread and butter businesses right. The second pillar is, uh, more and more customers are asking industry cloud. So what are you specifically doing for my industry. So, for example, if you look at banking, uh, they would say we are focused on Modernising our payment systems. We want to reduce the financial risk that we have because of anti money laundering and those kind of solutions that they're expecting. They want to better the security portion. And of course, they want to improve the experience, right? So they are asking for each of these imperatives that we have in banking. What are some of those specific industry solutions that you are bringing to the table? Right. So that's the second pillar of our global go to market. And the third pillar of our go to market as soon as I was saying is looking at what we call us Horizon three offerings, whether it is metal wars, whether it is 13.0, whether it is looking at something else that will come in the future. And how do we build those solutions which can become mainstream the next 18 to 24 months? So that's essentially the global >>market. That's interesting. Okay, so take the banking example where you've got a core app, it's probably on Prem, and it's not gonna have somebody shoved into the cloud necessarily. But they have to do things like anti money, money laundering and know your ky. See? How are they handling that? Are they building micro services? Are you building for them microservices layers around that that actually might be in the cloud or cloud Native on Prem and Greenway. How is that? How are customers Modernising? >>Absolutely brilliant question. In fact, what we have done is, uh, as part of cobalt, we have something called a reference. Architecture are basically a blueprint. So if you go to a bank and you're engaging a banking executive, uh, the language that we speak with them is not about, uh, private cloud or public cloud or AWS or HP or zero, right? I mean, we talk the language that they understand, which is the banking language. So we take this reference architecture, and we say here is what your core architecture should look like. And, as you rightly called out, there is K. I see there is retail banking. There is anti money laundering. There is security experience. Uh, there are some kpi s and those kind of things banking a PSR open banking as we call, How do we actually bring our solutions, which we have built on open source and something that are specific to cloud and something that our cloud neutral and that's what we take them. So we built this array of solutions around each of those reference architectures that we take to our customers. >>Final question for you guys. How are you guys leveraging the H, P E and new Green Lake and all the new stuff they got here to accelerate the customers journey to edge the cloud? >>So I would say it on three areas right now. This is one is Obviously we are working very closely with HP in terms of taking out solutions jointly to the market and, um, leveraging the whole green late model and providing what I call it as a hyper scale of like experience for our customers in a hybrid, multi cloud world. That's the first thing. The second thing is Onion talked about the cobalt, right? It's an important, I would say, an offering from, uh, you know and offering around cloud from our side. So what we've done is we've closely integrated the assets. You know what I was referring to what we have in our cobalt, uh, under other Kobold umbrella very closely with the HP ecosystem, right? You know, it can be tools like the Emphasis Polly Cloud Platform or the Emphasis pollinate platform very tightly integrated with the HP stack, so that we could actually offer the value proposition right across the value chain. The thought of you know we have actually taken the industry period, like what again mentioned right in terms of rather than talking about a public cloud or a private cloud solution or an edge computing solution. We actually talk about what exactly are the problem statements? What is there in manufacturing today? Or it's there in financial industries today? Or or it's in a bank today or whatever it's relevant to the industry. That's an industry people. So we talk right from an industry problem and and and and and and build that industry, industry people solutions, leveraging the assets, what we have in the and the framework that we have within the couple, plus the integrated solutions. What we bring along with HB. That's that's Those are the three things, what we do along with >>it and that that industry pieces do. There's a whole data layer emerging those industries learning cos they're building their own clouds. Look, working with companies like you because they want to monetise. That's a big part of their digital strategy, guys. Thanks so much for coming on the cue. Thank you. Appreciate your time. Thank >>you. Thank you very much. Really appreciate. >>Thank you. Thank you for watching John and I will be back. John Ferrier, Development at HPD Discovered 2022. You're watching the queue? >>Yeah. >>Mm.
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Breaking Analysis: Tech Spending Intentions are Holding Despite Macro Concerns
>> From theCUBE studios in Palo Alto in Boston bringing you data driven insights from theCUBE and ETR. This is breaking analysis with Dave Vellante. >> Despite fears of inflation, supply chain issues skyrocketing energy and home prices and global instability caused by the Ukraine crisis CIOs and IT buyers continue to expect overall spending to increase more than 6% in 2022. Now, while this is lower than our 8% prediction that we made earlier this year in January, it remains in line with last year's roughly six to 7% growth and is holding firm with the expectations reported by tech executives on the ETR surveys last quarter. Hello and welcome to this week's wiki bond cube insights powered by ETR in this breaking analysis, we'll update you on our latest look at tech spending with a preliminary take from ETR's latest macro drill down survey. We'll share some insights to which vendors have shown the biggest change in spending trajectory. And we'll tap our technical analysts to get a read on what they think it means for technology stocks going forward. The IT spending sentiment among IT buyers remains pretty solid. >> In the past two months, we've had conversations with dozens of CIOs, chief digital officers data executives, IT managers, and application developers, and across the board, they've indicated that for now at least their spending levels remain largely unchanged. The latest ETR drill down data which will share shortly, confirms these anecdotal checks. However, the interpretation of this data it's somewhat nuanced. Part of the reason for the spending levels being you know reasonably strong and holding up is inflation. Stuff costs more so spending levels are higher forcing IT managers to prioritize. Now security remains the number one priority and is less susceptible to cuts, cloud migration, productivity initiatives and other data projects remain top priorities. >> So where are CIO's robbing from Peter to pay Paul to focus on these priorities? Well, we've seen a slight uptick in certain speculative. IT projects being put on hold or frozen for a period of time. And according to ETR survey data we've seen some hiring freezes reported and this is especially notable in the healthcare sector. ETR also surveyed its buyer base to find out where they were adjusting their budgets and the strategies and tactics they were using to do so. Consolidating IT vendors was by far the most cited tactic. Now this makes sense as companies in an effort to negotiate better deals will often forego investments in newer so-called best of breed products and services, and negotiate bundles from larger suppliers. You know, even though they might not be as functional, the buyers >> can get a better deal if they bundle together from one of their larger suppliers. Think Microsoft or a Dell or other, you know, large companies. ETR survey respondents also cited cutting the cloud bill where discretionary spending was in play was another strategy or tactic that they were using. We certainly saw this with some of the largest snowflake customers this past quarter. Where even though they were still growing consumption rapidly certain snowflake customers dialed down their consumption and pushed spending off to future quarters. Now remember in the case of snowflake, anyway, customers negotiate consumption rates and their pricing based on a total commitment over a period of time. So while they may consume less in one quarter, over the lifetime of the contract, snowflake, as do many other cloud companies, have good visibility on the lifetime value of a deal. Now this next chart shows the latest ETR spending expectations among more than 900 respondents. The bars represent spending growth expectations from the periods of December, 2021 that's the gray bars, March of 2022 survey in the blue, and the most recent June data, That's the yellow bar. So you can see spending expectations for the quarter is down slightly in the mid 5% range. But overall for the year expectations remain in the mid 6% range. Now it's down from 8%, 8.3% in December where it looked like 2022 was going to really be a breakout year and have more momentum than even last year. Now, remember this was before Russia invaded Ukraine which occurred in mid-February of this year. So expectations were a little higher. So look, generally speaking CIOs have told us that their CFOs and CEOs have lowered their earnings outlooks and communicated that to Wall Street. They've told us that unless and until these revised forecasts appear at risk, they continue to expect their budget levels to remain pretty constant. Now there's still plenty of momentum and spending velocity on specific vendor platforms. Let's take a look at that. >> This chart shows the companies with the greatest spending momentum as measured by ETRs proprietary net score methodology. Net score essentially measures the net percent of customers spending more on a particular platform. That measurement is shown on the Y axis. The red line there that's inserted that red dotted line at 40%, we consider to be a highly elevated mark. And the green dots are companies in the ETR survey that are near or above that line. The X axis measures the presence in the data set, how much, you know sort of pervasiveness, if you will, is in the data. It's kind of a proxy for market presence. Now, of course we all know Kubernetes is not a company, but it remains an area where organizations are spending lots of resources and time particularly to modernize and mobilize applications. Snowflake remains the company which leads all firms in spending velocity, but as you'll see momentarily, despite its highest position relative to everybody else in the survey, it's still down from its previous levels in the high seventies and low 80% range. AWS is incredibly impressive because it has an elevated level but also a big presence in the data set in the survey. Same with Microsoft, same with ServiceNow which also stands out. And you can see the other smaller vendors like HashiCorp which is increasingly being seen as a strategic cross cloud enabler. They're showing, spending momentum. The RPA vendors you see in there automation anywhere and UI path are in the mix with numerous security companies, CrowdStrike, CyberArk, Netskope, Cloudflare, Tenable Okta, Zscaler Palo Alto networks, Sale Point Fortunate. A big number of cybersecurity firms hovering at or above that 40% mark you can see pure storage remains elevated as do PagerDuty and Coupa. So plenty of good news here, despite the recent tech crash. So that was the good, here's the not so good. So >> there is no 40% line on this chart because all these companies are well below that line. Now this doesn't mean these companies are bad companies. They just don't have the spending velocity of the ones we showed earlier. A good example here is Oracle. Look how they stand out on the X axis with a huge market presence. And Oracle remains an incredibly successful company selling to high end customers and really owning that mission critical data and application space. And remember ETR measures spending activity, but not actual spending dollars. So Oracle is skewed as a result because Oracle customers spend big bucks. But the fact is that Oracle has a large legacy install base that pulls down their growth rates. And that does show up in the ETR survey data. Broadcom is another example. They're one of the most successful companies in the industry, and they're not going after growth at all costs at all. They're going after EBITDA and of course ETR doesn't measure EBIT. So just keep that in mind, as you look at this data. Now another way to look at the data and the survey, is exploring the net score movement over the last period amongst companies. So how are they moving? What's happening to the net score over time. And this chart shows the year over year >> net score change for vendors that participate in at least three sectors within the ETR taxonomy. Remember ETR taxonomy has 12, 15 different segments. So the names above or below the gray dotted line are those companies where the net score has increased or decreased meaningfully. So to the earlier chart, it's all relative, right? Look at Oracle. While having lower net scores has also shown a more meaningful improvement in net score than some of the others, as have SAP and Teradata. Now what's impressive to me here is how AWS, Microsoft, and Google are actually holding that dotted line that gray line pretty well despite their size and the other ironically interesting two data points here are Broadcom and Nutanix. Now Broadcom, of course, as we've reported and dug into, is buying VMware and, and of, of course most customers are concerned about getting hit with higher prices. Once Broadcom takes over. Well Nutanix despite its change in net scores, in a good position potentially to capture some of that VMware business. Just yesterday, I talked to a customer who told me he migrated his entire portfolio off VMware using Nutanix AHV, the Acropolis hypervisor. And that was in an effort to avoid the VTEX specifically. Now this was a smaller customer granted and it's not representative of what I feel is Broadcom's ICP the ideal customer profile, but look, Nutanix should benefit from the Broadcom acquisition. If it can position itself to pick up the business that Broadcom really doesn't want. That kind of bottom of the pyramid. One person's trash is another's treasure as they say, okay. And here's that same chart for companies >> that participate in less than three segments. So, two or one of the segments in the ETR taxonomy. Only three names are seeing positive movement year over year in net score. SUSE under the leadership of amazing CEO, Melissa Di Donato. She's making moves. The company went public last year and acquired rancher labs in 2020. Look, we know that red hat is the big dog in Kubernetes but since the IBM acquisition people have looked to SUSE as a possible alternative and it's showing up in the numbers. It's a nice business. It's going to do more than 600 million this year in revenue, SUSE that is. It's got solid double digit growth in kind of the low teens. It's profitability is under pressure but they're definitely a player that is found a niche and is worth watching. The SolarWinds, What can I say there? I mean, maybe it's a dead cat bounce coming off the major breach that we saw a couple years ago. Some of its customers maybe just can't move off the platform. Constant contact we really don't follow and don't really, you know, focus on them. So, not much to say there. Now look at all the high priced earning stocks or infinite PE stocks that have no E and divide by zero or a negative number and boom, you have infinite PE and look at how their net scores have dropped. We've reported extensively on snowflake. They're still number one as we showed you earlier, net score, but big moves off their highs. Okta, Datadog, Zscaler, SentinelOne Dynatrace, big downward moves, and you can see the rest. So this chart really speaks to the change in expectations from the COVID bubble. Despite the fact that many of these companies CFOs would tell you that the pandemic wasn't necessarily a tailwind for them, but it certainly seemed to be the case when you look back in some of the ETR data. But a big question in the community is what's going to happen to these tech stocks, these tech companies in the market? We reached out to both Eric Bradley of ETR who used to be a technical analyst on Wall Street, and the long time trader and breaking analysis contributor, Chip Symington to get a read on what they thought. First, you know the market >> first point of the market has been off 11 out of the past 12 weeks. And bare market rallies like what we're seeing today and yesterday, they happen from time to time and it was kind of expected. Chair Powell's testimony was broadly viewed as a positive by the street because higher interest rates appear to be pushing commodity prices down. And a weaker consumer sentiment may point to a less onerous inflation outlook. That's good for the market. Chip Symington pointed out to breaking analysis a while ago that the NASDAQ has been on a trend line for the past six months where its highs are lower and the lows are lower and that's a bad sign. And we're bumping up against that trend line here. Meaning if it breaks through that trend it could be a buying signal. As he feels that tech stocks are oversold. He pointed to a recent bounce in semiconductors and cited the Qualcomm example. Here's a company trading at 12 times forward earnings with a sustained 14% growth rate over the next couple of years. And their cash flow is able to support their 2.4, 2% annual dividend. So overall Symington feels this rally was absolutely expected. He's cautious because we're still in a bear market but he's beginning to, to turn bullish. And Eric Bradley added that He feels the market is building a base here and he doesn't expect a 1970s or early 1980s year long sideways move because of all the money that's still in the system. You know, but it could bounce around for several months And remember with higher interest rates there are going to be more options other than equities which for many years has not been the case. Obviously inflation and recession. They are like two looming towers that we're all watching closely and will ultimately determine if, when, and how this market turns around. Okay, that's it for today. Thanks to my colleagues, Stephanie Chan, who helps research breaking analysis topics sometimes, and Alex Myerson who is on production in the podcast. Kristin Martin and Cheryl Knight they help get the word out and do all of our newsletters. And Rob Hof is our Editor in Chief over at siliconangle.com and does some wonderful editing for breaking analysis. Thank you. Remember, all these episodes are available as podcasts wherever you listen. All you got to do is search breaking analysis podcasts. I publish each week on wikibon.com and Siliconangle.com. And of course you can reach me by email at david.vellante@siliconangle.com or DM me at DVellante comment on my LinkedIn post and please do check out etr.ai for the best survey data in the enterprise tech business. This is Dave Vellante for the CUBE insights powered by ETR. Stay safe, be well. And we'll see you next time. (soft music)
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bringing you data driven by tech executives on the and across the board, they've and the strategies and tactics and the most recent June in the data set, how much, you know and the survey, is exploring That kind of bottom of the pyramid. in kind of the low teens. and the lows are lower
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Matthew Scullion, Matillion & Harveer Singh, Western Union | Snowflake Summit 2022
>>Hey everyone. Welcome back to Las Vegas. This is the Cube's live coverage of day. One of snowflake summit 22 fourth annual. We're very happy to be here. A lot of people here, Lisa Martin with Dave Valante, David's always great to be at these events with you, but me. This one is shot out of the cannon from day one, data, data, data, data. That's what you heard of here. First, we have two guests joining us next, please. Welcome Matthew Scalian. Who's an alumni of the cube CEO and founder of Matillion and Jer staying chief data architect and global head of data engineering from Western union. Welcome gentlemen. Thank >>You. Great to be here. >>We're gonna unpack the Western union story in a second. I love that, but Matthew, I wanted to start with you, give the audience who might not be familiar with Matillion an overview, your vision, your differentiators, your joint value statement with snowflake, >>Of course. Well, first of all, thank you for having me on the cube. Again, Matillion S mission is to make the world's data useful, and we do that by providing a technology platform that allows our customers to load transform, synchronize, and orchestrate data on the snowflake data cloud. And on, on the cloud in general, we've been doing that for a number of years. We're co headquartered in the UK and the us, hence my dat accents. And we work with all sorts of companies, commercial scale, large end enterprises, particularly including of course, I'm delighted to say our friends at Western union. So that's why we're here today. >>And we're gonna talk about that in a second, but I wanna understand what's new with the data integration platform from Matillion perspective, lots of stuff coming out, give us an overview. >>Yeah, of course, it's been a really busy year and it's great to be here at snowflake summit to be able to share some of what we've been working on. You know, the Matillion platform is all about making our customers as productive as possible in terms of time to value insight on that analytics, data science, AI projects, like get you to value faster. And so the more technology we can put in the platform and the easier we can make it to use, the better we can achieve that goal. So this year we've, we've shipped a product that we call MDL 2.0, that's enterprise focused, exquisitely, easy to use batch data pipelines. So customers can load data even more simply into the snowflake data cloud, very excitingly we've also launched Matillion CDC. And so this is an industry first cloud native writer, head log based change data capture. >>I haven't come up with a shorter way of saying that, but, and surprise customers need this technology and it's been around for years, but mostly pre-cloud technology. That's been repurposed for the cloud. And so Matillion has rebuilt that concept for the cloud. And we launched that earlier this year. And of course we've continued to build out the core Matillion ETL platform that today over a thousand joint snowflake Matillion customers use, including Western union, of course we've been adding features there such as universal connectivity. And so a challenge that all data integration vendors have is having the right connectors for their source systems. Universal connectivity allows you to connect to any source system without writing code point and click. We shape that as well. So it's been a busy year, >>Was really simple. Sorry. I love that. He said that and it also sounded great with your accent. I didn't wanna >>Thank you. Excellent. Javier, talk about your role at Western union in, in what you've seen in terms of the evolution of the, the data stack. >>So in the last few years, well, a little bit of Western union, a 70 or 170 year old company, pretty much everybody knows what Western union is, right? Driving an interesting synergy from what Matthew says, when data moves money moves, that's what we do when he moves the da, he moves the data. We move the money. That's the synergy between, you know, us and the organization that support us from data move perspective. So what I've seen in the last few years is obviously a shift towards the cloud, but, you know, within the cloud itself, obviously there's a lot of players as well. And we as customers have always been wishing to have a short, smaller footprint of data so that the movement becomes a little lesser. You know, interestingly enough, in this conference, I've heard some very interesting stuff, which kind of helping me to bring that footprint down to a manageable number, to be more governed, to be more, you know, effective in terms of delivering more end results for my customers as well. >>So Matillion has been a great partner for us from our cloud adoption perspective. During the COVID times, we were a re we are a, you know, multi-channel organization. We have retail stores as well, our digital presence, but people just couldn't go to the retail stores. So we had to find ways to accelerate our adoption, make sure our systems are scaling and making sure that we are delivering the same experience to our customers. And that's where, you know, tools like Matillion came in and really, really partnered up with us to kind of bring it up to the level. >>So talk specifically about the stack evolution. Cause I have this sort of theory that everybody talks about injecting data and, and machine intelligence and AI and machine learning into apps. But the application development stack is like totally separate from the, the data analytics and the data pipeline stack. And the database is somewhere over here as well. How is that evolving? Are those worlds coming together? >>Some part of those words are coming together, but where I still see the difference is your heavy lifting will still happen on the data stack. You cannot have that heavy lifting on the app because if once the apps becomes heavy, you'll have trouble communicating with, with, with the organizations. You know, you need to be as lean as possible in the front end and make sure things are curated. Things are available on demand as soon as possible. And that's why you see all these API driven applications are doing really, really well because they're delivering those results back to the, the leaner applications much faster. So I'm a big proponent of, yes, it can be hybrid, but the majority of the heavy lifting still needs to happen down at the data layer, which is where I think snowflake plays a really good role >>In APIs are the connective tissue >>APIs connections. Yes. >>Also I think, you know, in terms of the, the data stack, there's another parallel that you can draw from applications, right? So technology is when they're new, we tend to do things in a granular way. We write a lot of code. We do a lot of sticking of things together with plasters and sticky tape. And it's the purview of high end engineers and people enthusiastic about that to get started. Then the business starts to see the value in this stuff, and we need to move a lot faster. And technology solutions come in and this is what the, the data cloud is all about, right? The technology getting out of the way and allowing people to focus on higher order problems of innovating around analytics, data applications, AI, machine learning, you know, that's also where Matillion sit as well as other companies in this modern enterprise data stack is technology vendors are coming in allowing organizations to move faster and have high levels of productivity. So I think that's a good parallel to application development. >>And's just follow up on that. When you think about data prep and you know, all the focus on data quality, you've got a data team, you know, in the data pipeline, a very specialized, maybe even hyper specialized data engineers, quality engineers, data, quality engineers, data analysts, data scientist, but they, and they serve a lot of different business lines. They don't necessarily have the business, they don't have the business context typically. So it's kind of this back and forth. Do you see that changing in your organization or, or the are the lines of business taking more responsibility for the data and, and addressing that problem? It's, >>It's like you die by thousand paper cuts or you just die. Right? That's the kind >>Of, right, >>Because if I say it's, it's good to be federated, it comes with its own flaws. But if I say, if it's good to be decentralized, then I'm the, the guy to choke, right? And in my role, I'm the guy to choke. So I've selectively tried to be a pseudo federated organization, where do I do have folks reporting into our organization, but they sit close to the line of business because the business understands data better. We are working with them hand in glove. We have dedicated teams that support them. And our problem is we are also regional. We are 200 countries. So the regional needs are very different than our us needs. Majority of the organizations that you probably end up talking to have like very us focused, 50 per more than 50% of our revenue is international. So we do, we are dealing with people who are international, their needs for data, their needs for quality and their needs for the, the delivery of those analytics and the data is completely different. And so we have to be a little bit more closer to the business than traditionally. Some, some organizations feel that they need >>To, is there need for the underlying infrastructure and the operational details that as diverse, or is that something that you bring standardization to the, >>So the best part about this, the cloud that happened to us is exactly that, because at one point of time, I had infrastructure in one country. I had another infrastructure sitting in another country, regional teams, making different different decisions of bringing in different tools. Now I can standardize. I will say, Matillion is our standard for doing ETL work. If this is the use case, but then it gets deployed across the geographies because the cloud helps us or the cloud platform helps us to manage it. Sitting down here. I have three centers around the world, you know, Costa Rica, India, and the us. I can manage 24 7 sitting here. No >>Problem. So the underlying our infrastructure is, is global, but the data needs are dealt with locally. Yep. >>One of the pav question, I was just thinking JVE is super well positioned funds for you, which is around that business domain knowledge versus technical expertise. Cause again, early in technology journeys tend, things tend to be very technical and therefore only high end engineers can do it, but high end engineers are scar. Right? Right. And, and also, I mean, we survey our hundreds of large enterprise customers and they tell us they spend two thirds of their time doing stuff they don't really want to do like reinventing the wheel, basic data movement and the low order staff. And so if you can make those people more productive and allow them to focus on higher value problems, but also bring pseudo technical people into it. Overall, the business can go a lot faster. And the way you do that is by making it easier. That's why Matillion is a low code NOCO platform, but Jer and Western union are doing this right. I >>Mean, I can't compete with AWS and Google to hire people. So I need to find people who are smart to figure the products that we have to make them work. I don't want them to spend time on infrastructure, Adam, I don't want them to spend time on trying to manage platforms. I want them to deliver the data, deliver the results to the business so that they can build and serve their customers better. So it's a little bit of a different approach, different mindset. I used to be in consulting for 17 years. I thought I knew it all, but it changed overnight when I own all of these systems. And I'm like, I need to be a little bit more smarter than this. I need to be more proactive and figure out what my business needs rather than what just from a technology needs. It's more what the business needs and how I can deliver that needs to them. So simple analogy, you know, I can build the best architecture in the world. It's gonna cost me an arm and leg, but I can't drive it because the pipeline is not there. So I can have a Ferrari, but I can't drive it. It's still capped at 80, 80 miles an hour. So rather than spend, rather than building one Ferrari, let me have 10 Toyotas or 10 Fs, which will go further along and do better for my cus my, for my customers. >>So how do you see this whole, we hearing about the data cloud. We hear about the marketplace, data products now, application development inside the data cloud. How do you see that affecting not so much the productivity of the data teams. I don't wanna necessarily say, but the product, the value that, that customers like you can get out >>Data. So data is moving closer to the business. That's the value I see, because you are injecting the business and you're injecting the application much more closer to the data because it, in the past, it was days and days of, you know, churn the data to actually clear results. Now the data has moved much closer. So I have a much faster turnaround time. The business can adapt and actually react much, much faster. It took us like 16 to 30 days to deliver, you know, data for marketing. Now I can turn it down in four hours. If I see something happening, I'll give you an example. The war in Ukraine happened. Let is shut down operations in Russia. Ukraine is cash swamp. There's no cash in Ukraine. We have cash. We roll out campaign, $0 money, transferred to Ukraine within four hours of the world going on. That's the impact that we have >>Massive impact. That's huge, especially with such a macro challenge going on, on the, in, in the world. Thank you so much for sharing the Matillion snowflake partnership story, how it's helping Western union really transform into a data company. We love hearing stories of organizations that are 170 years old that have always really been technology focused, but to see it come to life so quickly is pretty powerful. Guys. Thank you so much for your time. Thanks >>Guys. Thank you, having it. Thank >>You >>For Dave Velante and our guests. I'm Lisa Martin. You're watching the cubes live coverage of snowflake summit 22 live from Las Vegas. Stick around. We'll be back after a short break.
SUMMARY :
Who's an alumni of the cube give the audience who might not be familiar with Matillion an overview, your vision, And on, on the cloud in general, we've been doing that for a number of And we're gonna talk about that in a second, but I wanna understand what's new with the data integration platform from Matillion And so the more technology we can put in the platform and the easier we can make it to use, And so Matillion has rebuilt that concept for the cloud. He said that and it also sounded great with your accent. in what you've seen in terms of the evolution of the, the data stack. That's the synergy between, you know, us and the organization that support us from data move perspective. are delivering the same experience to our customers. So talk specifically about the stack evolution. but the majority of the heavy lifting still needs to happen down at the data layer, Then the business starts to see the value or the are the lines of business taking more responsibility for the data and, That's the kind And in my role, I'm the guy to choke. So the best part about this, the cloud that happened to us is exactly that, So the underlying our infrastructure is, is global, And the way you do that is by making it easier. the data, deliver the results to the business so that they can build and serve their customers but the product, the value that, that customers like you can get out it, in the past, it was days and days of, you know, churn the data to actually clear in, in the world. Thank For Dave Velante and our guests.
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Daniel Fried, Veeam | VeeamON 2022
(digital music) >> Welcome back to VeeamON 2022. We're in the home stretch, actually, Dave Nicholson and Dave Vellante here. Daniel Fried is the general manager and senior vice president for EMEA and Worldwide Channel. Daniel, welcome to theCUBE. You got a big job. >> No, I don't have a big job. I have a job that I love. (chuckles) >> Yeah, a job you love. But seriously Veeam, all channel. I mean it has been. >> Yeah, I mean, it's something which just, just a few seconds on, on that piece here, the channel piece, it's something that I love because the ecosystem of partners, an ecosystem of partners, is something which is spending its time moving and developing and changing. You've got a lot of partners changing their roles, their missions, the type of services, type of product that they offer. They all adapt to what the market needs and all the markets around the world are very different because of all these different cultures, languages, and everything. So it's very interesting. In the middle of all that, you know, these tens of thousands of partners and you try to create and try to understand how you can organize, how you can make them happy. So this is fantastic. >> So you're a native of the continent in Europe, obviously. We heard Anton, today, who couldn't be here or chose not to be here, cause he's supporting family and friends in Ukraine. What's the climate like now? Can you share with us what's it like Europe? Just the overall climate and obviously the business climate. >> So the overall climate, the way I see it or I feel it, and obviously there may be some different opinions, that I will always appreciate as also very good opinions. My view is that it seems in Europe that there are a distinction between what people do for businesses, Their thinking for the business, which may be impacted by the situations that we know in Europe between, because of obviously the issues between Ukraine, because of Russia, let's put it this way. And then there is the personal view, which is okay. That happens from time to time, but life continues and we just continue pushing things and enjoying life, and getting the families together and so on and so forth. So, this is in most of the countries in Europe. Obviously, there are a number of countries, which are a little bit more sensitive, a little bit more impacted. All the ones who are next to Russia, or Belarus, so on and so forth. From an emotional standpoint, which is totally understandable. But overall, I'm pretty impressed by how the economy, how people, how the businesses are, you know, continue to thrive in Europe. >> Has Brexit had any...? What impact, if any, has it had? >> So for us Veeam, the impact is... So first there is an impact which is on the currencies. So all the European currencies are no, have slowed down and, and the US dollar is becoming much stronger. >> Despite its debt. >> Right. >> Shouldn't be, but yeah. >> But that doesn't impact on the business. I just... >> Yeah. Right. >> So everything which is economical, macroeconomical is impacted. We have the inflation also, which has an impact, which also has increased because of the oil, because of the gas of everything that they have been stuck, to be stuck. But people get used to it. As Veeam from a business standpoint, one of the big things is we stopped sales, selling into Russia and into Belarus and we are giving our technology, our product, our solutions for free to Ukraine. And that was a piece of the business that we were doing, within EMEA, which was non-neglectable. So it's, I would say a business hole, now that we need to try to fill with accelerating the business service in the other countries of Europe. >> I mean, okay. So thank you for that but we really didn't see it in last quarter's numbers that you guys shared with I mean, IBM. Similarly IBM said, it's noticeable, but it's not really a big impact on our business, but given the cultural ties that you had to Russia and the affinity, I mean you knew how to do business in Russia. It's quite remarkable that you're able to sort of power through that. How about privacy in, around data, in Europe, particularly versus the US? it seems like Europe is setting the trend on things like privacy, certainly on things like acquisitions, we saw the arm acquisition fail. >> Yeah. So there is a big difference. Effectively, there is a big difference between, I would say North America and the rest of the world. And I would say that EMEA, and within EMEA would say the EU is leading very much on what we call server sovereign cloud. So data privacy, which in other words, data is to as much as possible is to remain within either the EU or better within each of the countries, which means that there is again... It's I would say for in EMEA it's good, I would say for the business, for the partners, because then they have to develop around the cloud a number of functions to ensure that because of this data privacy, because of this GDPR or rules and things, all the data remains and resides in a given geographical environment. So it's, which is good because it creates a number of opportunities for the partners. It makes obviously the life of customers and their self a bit more difficult. But again, I think it's good. It's good. It's part of all the way we structure and we organize. And I think that it's going to expand because data is becoming so key, a key limit, a key asset of companies that we absolutely need to take care of it. And it is where Veeam plays a big role in that because we help paying companies managing their data and secure the data in sort of way. >> Yeah. Ransomware has been a big topic of conversation this week. Do you sense that the perception of that as a threat is universal? Are there, are there differences between North America and the EU and other parts of the world? Universal? >> Yeah, it is universal. We see that everywhere. And I think this is a good point, a good question too, is that it's very interesting because we need to get acquainted to the fact that we are going to ever. And so we are going to be attacked. No way out, no. There... Anybody the morning, is waking up, is going on emails and click clicking on an email. Too late. Was a run somewhere. What can you do against that? You know, all humans make mistakes. You can't so it'll happen, but where, where it's absolutely very important and where Veeam plays a big role and where our partners are going to play an even bigger role with our technology is that they can educate the customers to understand that, to have run somewhere is not an issue. What has, what happened is not a problem. What they have to do is to organize so that if they have run somewhere, their letter is safe. And this is where our place a big place. A couple hours back, I was, I was doing a kind of bar with something else. It's totally crazy, but that's okay. I'm going to say it. It's about the COVID. What, no, what do we do? Do we have, do we have something against COVID? No. People were going to get COVID, certainly many people still doing it, but what is important is to be capable of not being too sick. So it is the prevention, which is important. It's the same thing here. So there is this mindset we have psychologically with the partners and they have, they have to provide that services to their customers on how to organize their data using the technology of Veeam in order to be safe, if anything happens. >> So another related question, if I may. When Snowden blew the whistle on the NSA and divulged that the NSA was listening to all the phone calls, there was seemed to be at the time, as I recall, a backlash sentiment in Europe, particularly toward big tech and cloud providers and skepticism toward the cloud. Has the pandemic and the reliance on cloud and the rise of ransomware changed that sentiment? Had the sentiment changed before then? Obviously plenty of Cloud going on in Europe. But can you describe that dynamic? >> Yeah, no, I think that's... Yeah. I think that people were too... You know, as usual. It absolutely reminds me when I was at VMware, when we went from the physical boxes to the virtual machines. I remember the IT people in the company said, "No, I want to be capable of touching." Something here. When you talk about cloud, you talk about something which is virtual, but virtual outside, even outside somewhere. So there is a resistance, psychological resistance to where is my data? How do I control my data? And that is, I think that is very human. Then you need to, you know, it takes time. And again, depending on the cultures, you need to get acquainted to it. So that's what happened be before the pandemic, but then the pandemic took place. And then there was a big problem. There was nobody anymore in the data centers because they couldn't work there and then people were starting to, to work remotely. So the IT needed to be organized to compensate for all these different changes. And cloud was one of them where the data could be stored, where the data could reside, where things could happen. And that's how actually it has accelerated at least in a number of countries where people are a bit leg out to accept the adoption of cloud, cloud-based data. >> So is there a difference in terms of the level of domination by a small group of hyperscale clouds versus smaller service providers? You know, in theory, you have EU behaving in a unified way in sort of the same way that the United States behaves in sort of a federated way. Do you have that same level of domination or is there more, is there more market share available for smaller players in cloud? Any regional differences? >> Yeah. There are big differences. There are big differences again, because of this sovereignty, which is absolutely approved very much in Europe. I'm tell you, I'm going... I'm giving you an example that it was in, I think in October last year, somewhere. The French, the French administration said, "We don't want anymore. Any administration investing in Microsoft 365, because the data is in Azure. The data is out in the cloud." That's what they said. So now these last days, this last week that has changed because Microsoft, you know, introduced a number of technologies, data centers in France, and so on and so forth. So things are going to get better. But the sovereignty, the fact that the data, the privacy of data, everything has to remain in the countries is doing something like the technology of the hyperscalers is used locally wrapped by local companies like systematic writers, local systematic writers, to ensure that the sovereign is set and that the privacy of the data is for real and according to GDPR. So again, it's a value add. It makes things more complex. It doesn't mean that the Google, the Google cloud, the Azure, or the AWS are not going to exist in Europe, but there are going to be a number of layers between them and the customers in order to make sure that everything is totally brought up and that it complies with the EU regulations. >> Help us understand the numbers, Daniel. So the number of customers is mind-boggling it's over 400,000 now, is that right? >> Yeah. Correct. >> Yes. Comparable to VMware, which is again, pretty astounding and the partner ecosystem. Can you help us understand the scope of that? Part one. part two is how do you service and provide that partnership love to all those companies? >> The partners. So yeah, we have about 35,000 around the world, 35,000 partners, but again, it's 10 times less than Microsoft, by the way. So, and this is very interesting. I often have the questions, how do we manage? So first of all, we do tiering, like anybody does. >> Sure. >> We have an organization for that. And we have a two chair sales motion. That means that we use the distributors to take care of the mass, the volume of the smaller, smaller partners. We help the distributors, we help. So it's a leverage system. And we take care obviously more directly, of the large partners or the more complex partners or the ones of interest. But we don't want to forget any of those because even the small one is very important to us because he has these customers maybe in the middle of nowhere, but he's got a few of them. And again, to have a few of these customers, when you adapt, you know, it makes.. At the end, it makes a big business. You know, one plus one plus 1 million times makes, you know, makes huge things. And plus we are in the recurring business now, now that we've introduced three, four years ago, our subscription licenses, which means that it's only incremental. So it's just like the know the telephony, know the telephony business, where the number, the cell phone plans, you know, it's always grabbing as many as possible consumers in this case. So it was the same thing or I have the same, the same kind of, I do a parallel with the French, the French bakery, the French Boulangerie where I say they do their business with the baguette. And then from time to time, they sell the patisserie or they sell the cake, cookie or something, but the same of small things makes a big things. So it is important to have all these small partners everywhere that, that have their small customers or big customers, and that can serve them. So that's that's way. We segment by geography and what we do now is, it is something which is new. We segment by competencies. So it's what I call the soft segmentation. Because if not, we will have a lot of these partners competing to each other, just to sell Veeam. Veeam being number one in many countries, that is what is taking place. And we want them to be happy. We want, we don't want them to fight against each other. So what we do is we do soft segmentation and soft segmentation is this partner is competent in this field with that kind of use case doing this or this or this or this. It's just like you, when you go to the restaurant, you want the restaurant next to your place. So you click for the geography and then you want to, to go for Indian food. So you click restaurant Indian food, and then you want something. So we want to give that possibility to the customers to say, "Yeah, I think I know what I want." And then you can just click and get the partners or the list of partners, which are the most suited for, for his needs. So it's what I call the soft segmentation. The other thing which is important is the network. It's very interesting because when we look at a lot of companies, it's not the network. You've got VARs, you've got cloud and service providers. You've got SARs, you've got all the things. But if you take each of those individually, they don't have the competencies to answer all the request of the customer. So the networking is partnering with partner. That means to have the, the connection so that the partner A who has his customer, but these customer's are requests that this partner cannot fulfill because it's not its competency. That it's going to find the partners or the other partners that can feel this competency and work together. And then it's between them to have the model that they want so that together they can please the customer with their requests. >> Do you ever want to have VeeamON... I mean, I'm happy it's in the US and I like going to Europe, but you, have you ever want to have VeeamON in Europe? >> Yeah, we have VeeamON. We have many VeeamONs in Europe. >> Yeah. The mini ones. Okay. >> VeeamON tours. >> Globally. So where do you have them? >> Europe in APJ, that's what we do. Yes. >> Where do you do it in a APJ? In Japan, obviously in... >> Yeah. I don't know all the locations, tens and tens of them. >> A lot of them. Okay. >> The small ones. What we do, replicate what is done here on one day and then it goes. >> And you'll do that in UK. France, Germany. >> Yeah. Yeah. >> Local. >> And also small countries in Saudi, in South Africa, in Israel, in Bulgaria, in all these countries. Because, you know, we can be virtual. That's nice. >> Oh, right. >> But I love to be having a breakfast or a lunch or drink next to a partner or a customer because you learn so much more. The informal information is so important to understand how the business and how the market develops and what the needs are of customers and so on and so forth. >> How was the European attendance this year? It must have been down. It's hard to get into US. It's actually easier to go back to Europe. >> Virtually I, don't have the numbers, but I- >> No. Virtual. I'm sure it was huge. Yeah. But physical. >> Physical here, we've got about 300, 300 Europeans. >> Yeah. Okay. Out of, do we know? What are the numbers here? Do we know? Have we heard numbers? >> I know 45 was supposed to be around 45K combined. >> That's hybrid. >> So, yeah. >> It's hard to get into the US. We're still figuring that out. So I'm not surprised, but now you... >> But it's complimentary. Yeah. >> Do you go to 'em all? >> No >> You can't. >> No. That's not possible. I cannot. I actually, I would love... >> But some, yes. >> I would love to be capable of duplicate myself, but- >> You go to the one. >> I'm unique. >> You go to the one in France, obviously. Yeah? >> Yeah. Usually in France. Well... >> Depends if you're home. >> Yeah. You know, that is interesting is, the way we organize, the way we organize in Europe is I really want the local leaders to be the ones managing the countries. I'm there to support. I'm not there to be, you know? Yeah. The big boss is coming, he showing. No. It is not that. Again, if they request me to come, if they want me to pass a message to certain type of customer partners, I'll do that. But I don't want to run the show. It's not the way I manage that. >> Yeah. I get that. You want to respect that as if you show up in France and that's your home country, it's like rat man showing up here. It's like taking over the stage. You'll be like, you know, it's our turn. >> But it's just like, you know, I give you another example. So obviously we have... It's even the headquarters, the EMEA headquarters is in France. Right? But it is the French office. And I don't go there. I try not to be there because it is the place for the French people taking care of the French market. And for the French manager, if I go there, everybody's going to come and ask me questions and ask me to make decisions and things. No, they have to run their business. >> So where do you spend, where and how do you spend your time? >> In airports and in planes. (indistinct) What are you asking? >> Of course. >> Do you have another question? >> Actually, if we have time really quickly on just on that subject of sovereignty, we are here in Nevada just across the border, California. People in California have no problem at all, replicating things here for disaster recovery, because it's in the US. Now, is there sort of a cultural sense that tearing down those borders from a sovereignty perspective within Europe would fundamentally change the business climate and maybe tilt things in favor of the AWS and GCPs of the world instead of local regional business? The joke that I heard recently from someone, I thought it was funny. I don't know if it would offend either Germans or French, but it was that it was that AWS was confused and they were planning on putting a data center in Strasbourg, because they thought it was in Germany and it was- >> A joke. >> But the point is, the point is it's like, it's a gum bear. >> Is it true? >> No. But it was a dumb American joke. This was told by a French person basically saying... >> But this person was certainly not from- >> Yes. Right. >> Tell you, because I would've been a very bad way. >> But the point is this idea that you have these mega hyper clouds coming in and saying, "Okay, boom, we're putting one here and you're going to use us regardless of the country you're in." How does that, you know... Is there a push within the EU to tear those barriers down? Or are those sovereignty walls enjoyed by the majority because of the way that it changes the business climate? Any thoughts from that perspective? >> Oh yeah. Yeah. To me, it's very simple. It is a hybrid thing. That means that these big hyperscalers are there, not going to be used but what they do is they're going to partition themselves and work with these local people. So that their big thing appears as being independent, smaller data centers. That's the only thing, you know. You build a house and then you put walls between the different, between the different rooms. That's the only thing that happens. So it's not at all, no. At all to Azures or Google cloud. No, it's not that. It just means that there is a structure and organization that has to be put in place in order that the data resides in given geographical locations using their infrastructures, their technologies. That make, does it make sense? >> Yeah. Except that it puts them in the position of having to have a physical presence in each place, which is advantageous in one way and maybe less efficient in another. >> Yeah. But there are some big markets. >> Yeah. And they eventually got to get there. Right. I mean... >> Yeah. >> They started it. One patient in the world where they restarted was in ANZ. And that's what they did. You know, what, 5, 6, 7 years ago. They put their data centers over there because they wanted to gain the Australian market and the New Zealand market. >> So build it and they will come. Daniel, thanks so much for coming to the theCUBE. Very interesting conversation. >> Pleasure. >> Appreciate it. >> Thank you very much. >> All right, we're wrapping up. Day two at VeeamON 2022. Keep it right there. Dave and I will be back right after this break. (vibrant music)
SUMMARY :
We're in the home stretch, actually, I have a job that I love. Yeah, a job you love. and all the markets around obviously the business climate. because of obviously the What impact, if any, has it had? and the US dollar is on the business. because of the gas of everything and the affinity, and secure the data in sort of way. and the EU and other parts of the world? So it is the prevention, and divulged that the NSA was listening So the IT needed to be organized in sort of the same way that and that the privacy So the number of the partner ecosystem. I often have the questions, So it's just like the know the telephony, I mean, I'm happy it's in the Yeah, we have VeeamON. Okay. So where do you have them? Europe in APJ, that's what we do. Where do you do it in a APJ? tens and tens of them. A lot of them. and then it goes. And you'll do that in UK. Because, you know, we can be virtual. how the business and It's hard to get into US. I'm sure it was huge. Physical here, we've got about 300, What are the numbers here? to be around 45K combined. It's hard to get into the US. But it's complimentary. I actually, I would love... You go to the one in the local leaders to be the It's like taking over the stage. But it is the French office. In airports and in planes. and GCPs of the world But the point is, No. But it was a dumb American joke. Tell you, because I that it changes the business climate? in order that the data resides of having to have a physical presence eventually got to get there. and the New Zealand market. for coming to the theCUBE. Dave and I will be back
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Bill Andrews, ExaGrid | VeeamON 2022
(upbeat music) >> We're back at VeeamON 2022. We're here at the Aria in Las Vegas Dave Vellante with Dave Nicholson. Bill Andrews is here. He's the president and CEO of ExaGrid, mass boy. Bill, thanks for coming on theCUBE. >> Thanks for having me. >> So I hear a lot about obviously data protection, cyber resiliency, what's the big picture trends that you're seeing when you talk to customers? >> Well, I think clearly we were talking just a few minutes ago, data's growing like crazy, right This morning, I think they said it was 28% growth a year, right? So data's doubling almost just a little less than every three years. And then you get the attacks on the data which was the keynote speech this morning as well, right. All about the ransomware attacks. So we've got more and more data, and that data is more and more under attack. So I think those are the two big themes. >> So ExaGrid as a company been around for a long time. You've kind of been the steady kind of Eddy, if you will. Tell us about ExaGrid, maybe share with us some of the differentiators that you share with customers. >> Sure, so specifically, let's say in the Veeam world you're backing up your data, and you really only have two choices. You can back that up to disc. So some primary storage disc from a Dell, or a Hewlett Packard, or an NetApp or somebody, or you're going to back it up to what's called an inline deduplication appliance maybe a Dell Data Domain or an HPE StoreOnce, right? So what ExaGrid does is we've taken the best of both those but not the challenges of both those and put 'em together. So with disc, you're going to get fast backups and fast restores, but because in backup you keep weekly's, monthly's, yearly retention, the cost of this becomes exorbitant. If you go to a deduplication appliance, and let's say the Dell or the HPs, the data comes in, has to be deduplicated, compare one backup to the next to reduce that storage, which lowers the cost. So fixes that problem, but the fact that they do it inline slows the backups down dramatically. All the data is deduplicated so the restores are slow, and then the backup window keeps growing as the data grows 'cause they're all scale up technologies. >> And the restores are slow 'cause you got to rehydrate. >> You got to rehydrate every time. So what we did is we said, you got to have both. So our appliances have a front end disc cache landing zone. So you're right directed to the disc., Nothing else happens to it, whatever speed the backup app could write at that's the speed we take it in at. And then we keep the most recent backups in that landing zone ready to go. So you want to boot a VM, it's not an hour like a deduplication appliance it's a minute or two. Secondly, we then deduplicate the data into a second tier which is a repository tier, but we have all the deduplicated data for the long term retention, which gets the cost down. And on top of that, we're scale out. Every appliance has networking processor memory end disc. So if you double, triple, quadruple the data you double, triple, quadruple everything. And if the backup window is six hours at 100 terabyte it's six hours at 200 terabyte, 500 terabyte, a petabyte it doesn't matter. >> 'Cause you scale out. >> Right, and then lastly, our repository tier is non-network facing. We're the only ones in the industry with this. So that under a ransomware attack, if you get hold of a rogue server or you hack the media server, get to the backup storage whether it's disc or deduplication appliance, you can wipe out all the backup data. So you have nothing to recover from. In our case, you wipe it out, our landing zone will be wiped out. We're no different than anything else that's network facing. However, the only thing that talks to our repository tier is our object code. And we've set up security policies as to how long before you want us to delete data, let's say 10 days. So if you have an attack on Monday that data doesn't get deleted till like a week from Thursday, let's say. So you can freeze the system at any time and do restores. And then we have immutable data objects and all the other stuff. But the culmination of a non-network facing tier and the fact that we do the delayed deletes makes us the only one in the industry that can actually truly recover. And that's accelerating our growth, of course. >> Wow, great description. So that disc cache layer is a memory, it's a flash? >> It's disc, it's spinning disc. >> Spinning disc, okay. >> Yeah, no different than any other disc. >> And then the tiered is what, less expensive spinning disc? >> No, it's still the same. It's all SaaS disc 'cause you want the quality, right? So it's all SaaS, and so we use Western Digital or Seagate drives just like everybody else. The difference is that we're not doing any deduplication coming in or out of that landing zone to have fast backups and fast restores. So think of it like this, you've got disc and you say, boy it's too expensive. What I really want to do then is put maybe a deduplication appliance behind it to lower the cost or reverse it. I've got a deduplication appliance, ugh, it's too slow for backups and restores. I really want to throw this in front of it to have fast backups first. Basically, that's what we did. >> So where does the cost savings, Bill come in though, on the tier? >> The cost savings comes in the fact that we got deduplication in that repository. So only the most recent backup >> Ah okay, so I get it. >> are the duplicated data. But let's say you had 40 copies of retention. You know, 10 weekly's, 36 monthly's, a few yearly. All of that's deduplicated >> Okay, so you're deduping the stuff that's not as current. >> Right. >> Okay. >> And only a handful of us deduplicate at the layer we do. In other words, deduplication could be anywhere from two to one, up to 50 to one. I mean it's all over the place depending on the algorithm. Now it's what everybody's algorithms do. Some backup apps do two to one, some do five to one, we do 20 to one as well as much as 50 to one depending on the data types. >> Yeah, so the workload is going to largely determine the combination >> The content type, right. with the algos, right? >> Yeah, the content type. >> So the part of the environment that's behind the illogical air gap, if you will, is deduped data. >> Yes. >> So in this case, is it fair to say that you're trading a positive economic value for a little bit longer restore from that environment? >> No, because if you think about backup 95% of the customers restores are from the most recent data. >> From the disc cache. >> 95% of the time 'cause you think about why do you need fast restores? Somebody deleted a file, somebody overwrote a file. They can't go work, they can't open a file. It's encrypted, it's corrupted. That's what IT people are trying to keep users productive. When do you go for longer-term retention data? It's an SEC audit. It's a HIPAA audit. It's a legal discovery, you don't need that data right away. You have days and weeks to get that ready for that legal discovery or that audit. So we found that boundary where you keep users productive by keeping the most recent data in the disc cache landing zone, but anything that's long term. And by the way, everyone else is long term, at that point. >> Yeah, so the economics are comparable to the dedupe upfront. Are they better, obviously get the performance advance? >> So we would be a lot looped. The thing we replaced the most believe it or not is disc, we're a lot less expensive than the disc. I was meeting with some Veeam folks this morning and we were up against Cisco 3260 disc at a children's hospital. And on our quote was $500,000. The disc was 1.4 million. Just to give you an example of the savings. On a Data Domain we're typically about half the price of a Data Domain. >> Really now? >> The reason why is their front end control are so expensive. They need the fastest trip on the planet 'cause they're trying to do inline deduplication. >> Yeah, so they're chasing >> They need the fastest memory >> on the planet. >> this chips all the time. They need SSD on data to move in and out of the hash table. In order to keep up with inline, they've got to throw so much compute at it that it drives their cost up. >> But now in the case of ransomware attack, are you saying that the landing zone is still available for recovery in some circumstances? Or are you expecting that that disc landing zone would be encrypted by the attacker? >> Those are two different things. One is deletion, one is encryption. So let's do the first scenario. >> I'm talking about malicious encryption. >> Yeah, absolutely. So the first scenario is the threat actor encrypts all your primary data. What's does he go for next? The backup data. 'Cause he knows that's your belt and suspend is to not pay the ransom. If it's disc he's going to go in and put delete commands at the disc, wipe out the disc. If it's a data domain or HPE StoreOnce, it's all going to be gone 'cause it's one tier. He's going to go after our landing zone, it's going to be gone too. It's going to wipe out our landing zone. Except behind that we have the most recent backup deduplicate in the repository as well as all the other backups. So what'll happen is they'll freeze the system 'cause we weren't going to delete anything in the repository for X days 'cause you set up a policy, and then you restore the most recent backup into the landing zone or we can restore it directly to your primary storage area, right? >> Because that tier is not network facing. >> That's right. >> It's fenced off essentially. >> People call us every day of the week saying, you saved me, you saved me again. People are coming up to me here, you saved me, you saved me. >> Tell us a story about that, I mean don't give me the names but how so. >> I'll actually do a funnier story, 'cause these are the ones that our vendors like to tell. 'Cause I'm self-serving as the CEO that's good of course, a little humor. >> It's your 15 minutes of job. >> That is my 15 minutes of fame. So we had one international company who had one ExaGrid at one location, 19 Data Domains at the other locations. Ransomware attack guess what? 19 Data Domains wiped out. The one ExaGrid, the only place they could restore. So now all 20 locations of course are ExaGrids, China, Russia, Mexico, Germany, US, et cetera. They rolled us out worldwide. So it's very common for that to occur. And think about why that is, everyone who's network facing you can get to the storage. You can say all the media servers are buttoned up, but I can find a rogue server and snake my way over the storage, I can. Now, we also of course support the Veeam Data Mover. So let's talk about that since we're at a Veeam conference. We were the first company to ever integrate the Veeam Data Mover. So we were the first actually ever integration with Veeam. And so that Veeam Data Mover is a protocol that goes from Veeam to the ExaGrid, and we run it on both ends. So that's a more secure protocol 'cause it's not an open format protocol like SaaS. So with running the Veeam Data Mover we get about 30% more performance, but you do have a more secure protocol layer. So if you don't get through Veeam but you get through the protocol, boom, we've got a stronger protocol. If you make it through that somehow, or you get to it from a rogue server somewhere else we still have the repository. So we have all these layers so that you can't get at it. >> So you guys have been at this for a while, I mean decade and a half plus. And you've raised a fair amount of money but in today's terms, not really. So you've just had really strong growth, sequential growth. I understand it, and double digit growth year on year. >> Yeah, about 25% a year right now >> 25%, what's your global strategy? >> So we have sales offices in about 30 countries already. So we have three sales teams in Brazil, and three in Germany, and three in the UK, and two in France, and a lot of individual countries, Chile, Argentina, Columbia, Mexico, South Africa, Saudi, Czech Republic, Poland, Dubai, Hong Kong, Australia, Singapore, et cetera. We've just added two sales territories in Japan. We're adding two in India. And we're installed in over 50 countries. So we've been international all along the way. The goal of the company is we're growing nicely. We have not raised money in almost 10 years. >> So you're self-funding. You're cash positive. >> We are cash positive and self-funded and people say, how have you done that for 10 years? >> You know what's interesting is I remember, Dave Scott, Dave Scott was the CEO of 3PAR, and he told me when he came into that job, he told the VCs, they wanted to give him 30 million. He said, I need 80 million. I think he might have raised closer to a hundred which is right around what you guys have raised. But like you said, you haven't raised it in a long time. And in today's terms, that's nothing, right? >> 100 is 500 in today's terms. >> Yeah, right, exactly. And so the thing that really hurt 3PAR, they were public companies so you could see all this stuff is they couldn't expand internationally. It was just too damn expensive to set up the channels, and somehow you guys have figured that out. >> 40% of our business comes out of international. We're growing faster internationally than we are domestically. >> What was the formula there, Bill, was that just slow and steady or? >> It's a great question. >> No, so what we did, we said let's build ExaGrid like a McDonald's franchise, nobody's ever done that before in high tech. So what does that mean? That means you have to have the same product worldwide. You have to have the same spares model worldwide. You have to have the same support model worldwide. So we early on built the installation. So we do 100% of our installs remotely. 100% of our support remotely, yet we're in large enterprises. Customers racks and stacks the appliances we get on with them. We do the entire install on 30 minutes to about three hours. And we've been developing that into the product since day one. So we can remotely install anywhere in the world. We keep spares depots all over the world. We can bring 'em up really quick. Our support model is we have in theater support people. So they're in Europe, they're in APAC, they're in the US, et cetera. And we assign customers to the support people. So they deal with the same support person all the time. So everything is scalable. So right now we're going to open up India. It's the same way we've opened up every other country. Once you've got the McDonald's formula we just stamp it all over the world. >> That's amazing. >> Same pricing, same product same model, same everything. >> So what was the inspiration for that? I mean, you've done this since day one, which is what like 15, 16 years ago. Or just you do engineering or? >> No, so our whole thought was, first of all you can't survive anymore in this world without being an international company. 'Cause if you're going to go after large companies they have offices all over the world. We have companies now that have 17, 18, 20, 30 locations. And there were in every country in the world, you can't go into this business without being able to ship anywhere in the world and support it for a single customer. You're not going into Singapore because of that. You're going to Singapore because some company in Germany has offices in the U.S, Mexico Singapore and Australia. You have to be international. It's a must now. So that was the initial thing is that, our goal is to become a billion dollar company. And we're on path to do that, right. >> You can see a billion. >> Well, I can absolutely see a billion. And we're bigger than everybody thinks. Everybody guesses our revenue always guesses low. So we're bigger than you think. The reason why we don't talk about it is we don't need to. >> That's the headline for our writers, ExaGrid is a billion dollar company and nobody's know about it. >> Million dollar company. >> On its way to a billion. >> That's right. >> You're not disclosing. (Bill laughing) But that's awesome. I mean, that's a great story. I mean, you kind of are a well kept secret, aren't you? >> Well, I dunno if it's a well kept secret. You know, smaller companies never have their awareness of big companies, right? The Dells of the world are a hundred billion. IBM is 70 billion, Cisco is 60 billion. Easy to have awareness, right? If you're under a billion, I got to give a funny story then I think we got to close out here. >> Oh go ahead please. >> So there's one funny story. So I was talking to the CIO of a super large Fortune 500 company. And I said to him, "Just so who do you use?" "I use IBM Db2, and I use, Cisco routers, and I use EMC primary storage, et cetera. And I use all these big." And I said, "Would you ever switch from Db2?" "Oh no, the switching costs would kill me. I could never go to Oracle." So I said to him, "Look would you ever use like a Pure Storage, right. A couple billion dollar company." He says, "Who?" >> Huh, interesting. >> I said to him, all right so skip that. I said, "VMware, would you ever think about going with Nutanix?" "Who?" Those are billion dollar plus companies. And he was saying who? >> Public companies. >> And he was saying who? That's not uncommon when I talk to CIOs. They see the big 30 and that's it. >> Oh, that's interesting. What about your partnership with Veeam? Tell us more about that. >> Yeah, so I would actually, and I'm going to be bold when I say this 'cause I think you can ask anybody here at the conference. We're probably closer first of all, to the Veeam sales force than any company there is. You talk to any Veeam sales rep, they work closer with ExaGrid than any other. Yeah, we are very tight in the field and have been for a long time. We're integrated with the Veeam Data Boomer. We're integrated with SOBR. We're integrated with all the integrations or with the product as well. We have a lot of joint customers. We actually do a lot of selling together, where we go in as Veeam ExaGrid 'cause it's a great end to end story. Especially when we're replacing, let's say a Dell Avamar to Dell Data Domain or a Dell Network with a Dell Data Domain, very commonly Veeam ExaGrid go in together on those types of sales. So we do a lot of co-selling together. We constantly train their systems engineers around the world, every given week we're training either inside sales teams, and we've trained their customer support teams in Columbus and Prague. So we're very tight with 'em we've been tight for over a decade. >> Is your head count public? Can you share that with us? >> So we're just over 300 employees. >> Really, wow. >> We have 70 open positions, so. >> Yeah, what are you looking for? Yeah, everything, right? >> We are looking for engineers. We are looking for customer support people. We're looking for marketing people. We're looking for inside sales people, field people. And we've been hiring, as of late, major account reps that just focus on the Fortune 500. So we've separated that out now. >> When you hire engineers, I mean I think I saw you were long time ago, DG, right? Is that true? >> Yeah, way back in the '80s. >> But systems guy. >> That's how old I am. >> Right, systems guy. I mean, I remember them well Eddie Castro and company. >> Tom West. >> EMV series. >> Tom West was the hero of course. >> The EMV 4000, the EMV 20,000, right? >> When were kids, "The Soul of a New Machine" was the inspirational book but anyway, >> Yeah Tracy Kidder, it was great. >> Are you looking for systems people, what kind of talent are you looking for in engineering? >> So it's a lot of Linux programming type stuff in the product 'cause we run on a Linux space. So it's a lot of Linux programs so its people in those storage. >> Yeah, cool, Bill, hey, thanks for coming on to theCUBE. Well learned a lot, great story. >> It's a pleasure. >> That was fun. >> Congratulations. >> Thanks. >> And good luck. >> All right, thank you. >> All right, and thank you for watching theCUBE's coverage of VeeamON 2022, Dave Vellante for Dave Nicholson. We'll be right back right after this short break, stay with us. (soft beat music)
SUMMARY :
We're here at the Aria in Las Vegas And then you get the attacks on the data You've kind of been the steady and let's say the Dell or And the restores are slow that's the speed we take it in at. and the fact that we So that disc cache layer No, it's still the same. So only the most recent backup are the duplicated data. Okay, so you're deduping the deduplicate at the layer we do. with the algos, right? So the part of the environment 95% of the customers restores 95% of the time 'cause you think about Yeah, so the economics are comparable example of the savings. They need the fastest trip on the planet in and out of the hash table. So let's do the first scenario. So the first scenario is the threat actor Because that tier day of the week saying, I mean don't give me the names but how so. 'Cause I'm self-serving as the CEO So if you don't get through Veeam So you guys have been The goal of the company So you're self-funding. what you guys have raised. And so the thing that really hurt 3PAR, than we are domestically. It's the same way we've Same pricing, same product So what was the inspiration for that? country in the world, So we're bigger than you think. That's the headline for our writers, I mean, you kind of are a The Dells of the world So I said to him, "Look would you ever I said, "VMware, would you ever think They see the big 30 and that's it. Oh, that's interesting. So we do a lot of co-selling together. that just focus on the Fortune 500. Eddie Castro and company. in the product 'cause thanks for coming on to theCUBE. All right, and thank you for watching
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Breaking Analysis: Are Cyber Stocks Oversold or Still too Pricey?
>> From theCUBE Studios in Palo Alto in Boston, bringing you data driven insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. >> Cybersecurity stocks have been sending mixed signals as of late, mostly negative like much of tech, but some such as Palo Alto Networks, despite a tough go of it recently have held up better than most tech names. Others like CrowdStrike, had been out performing Broader Tech in March, but then flipped in May. Okta's performance was pretty much tracking along with CrowdStrike for most of the past several months, a little bit below, but then the Okta hack changed the trajectory of that name. Zscaler has crossed the critical billion dollar ARR revenue milestone, and now sees a path to five billion dollars in revenue, but the company stock fell sharply after its last earnings report and has been on a down trend since last November. Meanwhile, CyberArk's recent beat and raise, was encouraging and the stock acted well after its last report. Security remains the number one initiative priority amongst IT organizations and the spending momentum for many high flying cyber names remain strong. So what gives in cyber security? Hello, and welcome to this week's Wikibon CUBE insights powered by ETR. In this breaking analysis, we focus on security and will update you on the latest data from ETR to try to make sense out of the market and read into what this all means in both the near and long term, for some of our favorite names in cyber. First, the news. There's always something happening in security news cycles. The big recent news is new President Rodrigo Chavez declared a national emergency in Costa Rica due to the preponderance of Russian cyber attacks on the country's critical infrastructure. Such measures are normally reserved for natural disasters like earthquakes, but this move speaks to the nature of today's cyber threats. Of no surprise is modern superpower warfare even for a depleted power like Russia almost certainly involves cyber warfare as we continue to see in Ukraine. Privately held Arctic Wolf Networks hired Dustin Williams as its new CFO. Williams has taken three companies to IPO, including Nutanix in 2016, a very successful IPO for that company. Whether AWN chooses to pull the trigger this year or will wait until markets are less choppy or obviously remains to be seen. But it's a pretty clear sign the company is headed to IPO at some point. Now, big point of discussion this week at Red Hat Summit in Boston and the prior week at Dell technologies world was security. In the case of Red Hat, securing the digital supply chain was the main theme. And from Dell building, many security features into its storage arrays and cyber resilience services into its as a service offering called Apex. And we're seeing a trend where buyers want to reduce the number of bespoke tools they use if they, in fact can. Here's IDC's Jim Mercer, sharing data from a recent survey they conducted on the topic. Play the clip. >> Interestingly, we did a survey, I think around last August or something. And one of the questions was around where do you want your security, right? Where do you want to get your DevSecOps security from? Do you want to get it from individual vendors, right? Or do you want to get it from like your platforms that you're using and deploying changes in Kubernetes? >> Great question. What did they say? >> The majority of them, they're hoping they can get it built into the platform. That's really what they want-- >> Now, whether that's actually achievable is debatable because you have so much innovation and investment going on from the likes of startups and for instance, lace work or sneak and security companies that you see even trying to build platforms, you've got CrowdStrike, Okta, Zscaler and many others, trying to build security platforms and put it all under their umbrella. Now the last point will hit here is there was a lot of buzz in the news about Okta. The reaction to what was a relatively benign hack was pretty severe and probably overblown, but Okta's stock is paying the price of what is generally considered a blown communications plan versus a technical failure. Remember, identity is not an easy thing to rip and replace and Okta remains a best-of-breed player and leader in the space. So we're going to look at some ETR data later in this segment to try and make sense of the recent action in the market and certain names. Speaking of which let's take a look at how some of the names in cybersecurity have fared relative to some of the indices and relative indicators that we like to look at. Here's a Google finance comparison for a number of stocks and names in the bottom there you can see we plot the hack ETF which tracks security stocks. This is a year to date view. And so we don't show it here but the tech heavy NASDAQ is off around 26% year to date whereas the cyber ETF that we're showing is down 18%, okay. So cyber holding up a little bit better than broader tech as we've reported earlier, was actually much better and still seems to be a gap there, but the data are mixed. You can see Okta is way off relative to its peers. That's a combination of the breach that we talked about but also the run up in the stock since COVID. CrowdStrike was actually faring better but broke this month, we'll see how it's upcoming earnings announcements are received when it announces on June 2nd after the close. Palo Alto in the light blue has done better than most and until recently was holding up quite well. And of course, Sailpoint is another identity specialist, it is kind of off the charts here because it's going private with the acquisition by Thoma Bravo at nearly seven billion dollars. So you see some mixed signals in cyber these past several months and weeks. And so we're trying to understand what that all means. So let's take a look at the survey data and see how spending momentum is holding up. As we've reported IT spending forecast, at the macro level, they've come off their 8% highs from the end of the year, the ETRS December survey, but robust tech spending is still there. It's expected at nearly seven percent and this is amongst 1200 ETR respondents. Here's a picture from the ETR survey of the cybersecurity landscape. That y-axis that's net score or a measure of spending momentum and that horizontal access is overlap. We used to talk about it as a market share which is a measure of pervasiveness in the data set. That dotted red line at 40% indicates an elevated spending momentum level on the vertical axis and we filter the names and limited to only those with a hundred or more responses in the ETR survey. Then the pictures still pretty crowded as you can see. You got lots of companies above the red dotted line, including Microsoft which is up into the right, they're so far off the chart, it's just amazing. But also Palo Alto and Okta, Auth0, which of course is now owned by Okta, Zscaler, CyberArk is making moves. Sailpoint and Cloudflare, they're all above that magic 40% line. Now, you look at Cisco, it shows a very large presence in the horizontal axis in the data set. And it's got pretty respectable momentum and you see Splunk doing okay, no before and tenable just below that 40% line and a lot of names in the very respectable 20% zone. And we've included some legacy names just for context that fall below the zero percent line with a negative net score. And that means a larger proportion, that negative net score means a larger proportion of their customers in the survey are spending less than those that are spending more. Now, typically for these legacy names you're going to have a huge proportion of customers who have flat spending that kind of fat middle and that's why they sort of don't have that highly elevated score, but they're still viable as they get the recurring revenue each year. But the bottom line is that spending remains robust for some of the top names that we've talked about earlier despite their rocky stock performance. Now, let's filter this data a bit more to make it a little bit easier to read. So to do that, we take out Microsoft because they're just so dominant and we cherry pick some names to make the data more consumable and scannable. The other data point we've added is Okta's net score breakdown, the multicolored rows there, that row in the bottom right. Net score, it measures the percent of customers that are adding the platform new, that's the lime green, at 18% for Okta. The forest green is at 42%. That's the percent of customers in the survey that are spending six percent or more. The gray is flat spending. That's 32% for Okta, this past survey. The pink is customers that are spending less, that's three percent. They're spending six percent or worse in the survey, so only three percent for Okta. And the bright red at three percent is decommissioning the platform. You subtract the reds from the greens and you get a net score, well, into the 50s for Okta and you can see. We highlight Okta here because it's a name that we've been following for quite some time and customers have given us really solid feedback on the technology and up until the hack, they're affinity to Okta, but that seems to be continuing. We'll talk more about that. This recent breach to Okta has caused us to take a closer look. And you may recall, we reported with our ETR colleague, Eric Bradley. The breach was announced right in the middle of ETR collecting data in the last survey. And while we did see a noticeable downtick right after the announcement, the exposure of the hack and Okta's net score just after the breach was disclosed, you can see the combination of Okta and Auth0 remains very strong. I asked Eric Bradley this morning what he thought about Okta, and he pointed out that you can't evaluate this company on its price to earnings ratio. But it's forward sales multiple is now below 7X. And while attractive, these high flyers at some point, Eric says, they got to start making a profit. So you going to hold that thought, we'll come back to that. Now, another cut of the ETR data to look at our four star security names here. A while back we developed a methodology to try and cut through the noise of the crowded security sector using the ETR data to evaluate two key metrics; net score and shared N. Net score again is, spending momentum, the latter is an indicator of presence in the data set which is a proxy for market presence. Okay, we assigned those companies that cracked the top 10 in both net score and shared N, we give them four stars, okay, if they make the top 10. This chart here shows the April survey data for those companies with an N that's greater than, equal to a hundred responses. So again, we're filtering on those with a hundred or more responses. The table on the left that you see there, that's sorted by net score, okay. So we're sorting by spending momentum. And then the one on the right is sorted by shared N, so their presence in the data set. Seven companies hit the top 10 for both categories; Palo Alto Network, Splunk, CrowdStrike Okta, Proofpoint, Fortinet and Zscaler. Now, remember, take a look, Okta excludes Auth0, in this little methodology that we came up with. Auth0 didn't make the cuts but it hits the top 10 for net score. So if you add in Auth0's 112 N there that you see on the right. You add that into Okta, we put Okta in the number two spot in the survey on the right most table with the shared N of 354. Only Cisco has a higher presence in the data set. And you can see Cisco in the left lands just below that red dotted line. That's the top 10 in security. So if we were to combine Okta and Auth0 as one, Cisco would make the cut and earn four stars. Now, some other notables are CyberArk, which is just below the red line on the right most chart with an impressive 177 shared N. Again, if you combine Auth0 and Okta, CyberArk makes the four star grade because it's in the top 10 for net score on the left. And Sailpoint is another notable with a net score above 50% and it's got a shared N of 122, which is respectable. So despite the market's choppy waters, we're seeing some positive signs in the survey data for some of the more prominent names that we've been following for the last couple of years. So what does this mean for the markets going forward? As always, when we see these confusing signs we like to reach out to the network and one of the sharpest traders out there is Chip Simonton. We've quoted him before and we like to share some of his insights. And so we're going to highlight some of that here. So technically, almost every good tech stock is oversold. And as such, he suggested we might see a bounce here. We certainly are seeing that on this Friday, the 13th. But the right call tactically has been to sell into the rally these past several months, so we'll see what happens on Monday. The key issue with the name like Okta and some other momentum names like CrowdStrike and Zscaler is that when money comes back into tech, it's likely going to go to the FAANG stocks, the Facebook, Apple, Amazon, Netflix, Google, and of course, you put Microsoft in there as well. And we'll see about Amazon, by the way, it's kind of out of favor right now, as everyone's focused on the retail side of the business meanwhile it's cloud business is booming and that's where all the profit is. We think that should be the real focus for Amazon. But the point is, for these momentum names in cybersecurity that don't make money, they face real headwinds, as growth is slowing overall and interest rates rise, that makes the net present value of these investments much less attractive. We've talked about that before. But longer term, we agree with Chip Simonton that these are excellent companies and they will weather the storm and we think they're going to lead their respective markets. And in cyber, we would expect continued M&A activity, which could act as a booster shot in the arms of these names. Now in 2019, we saw the ETR data, it pointed to CrowdStrike, Zscaler, Okta and others in the security space. Some of those names that really looked to us like they were moving forward and the pandemic just created a surge in these names and admittedly they got out over their skis. But the data suggests that these leading companies have continued momentum and the potential for stay in power. Unlike the SolarWinds hack, it seems at this point anyway that Okta will recover in the market. For the reasons that we cited, investors, they might stay away for some time but longer term, there's a shift in CSO security strategies that appear to be permanent. They're really valuing cloud-based modern platforms, these platforms will likely continue to gain share and carry their momentum forward. Okay, that's it for now, thanks to Stephanie Chan, who helps with the background research and with social, Kristen Martin and Cheryl Knight help get the word out and do some great work as well. Alex Morrison is on production and handles all of our podcast. Alex, thank you. And Rob Hof is our Editor in Chief at SiliconANGLE. Remember, all these episodes, they're available as podcast, you can pop in the headphones and listen, just search "Breaking Analysis Podcast." I publish each week on wikibon.com and SiliconANGLE.com. Don't forget to check out etr.ai, best in the business for real customer data. It's an awesome platform. You can reach me at dave.vellante@siliconangle.com or @dvellante. You can comment on our LinkedIn posts. This is Dave Vellante for the CUBEinsights powered by ETR. Thanks for watching. And we'll see you next time. (bright upbeat music)
SUMMARY :
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Breaking Analysis: New Data Signals C Suite Taps the Brakes on Tech Spending
>> From theCUBE Studios in Palo Alto in Boston, bringing you data driven insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. >> New data from ETR's soon to be released April survey, shows a clear deceleration in spending and a more cautious posture from technology buyers. Just this week, we saw sell side downgrades in hardware companies like Dell and HP and revised guidance from high flyer UiPath, citing exposures to Russia, Europe and certain sales execution challenges, but these headlines, we think are a canary in the coal mine. According to ETR analysis and channel checks in theCUBE, the real story is these issues are not isolated. Rather we're seeing signs of caution from buyers across the board in enterprise tech. Hello and welcome to this week's Wikibon CUBE insights powered by ETR. In this Breaking Analysis, we are the bearers of bad news. Don't shoot the messenger. We'll share a first look at fresh data that suggests a tightening in tech spending calling for 6% growth this year which is below our January prediction of 8% for 2022. Now, unfortunately the party may be coming to an end at least for a while. You know, it's really not surprising, right? We've had a two year record run in tech spending and meteoric rises in high flying technology stocks. Hybrid work, equipping and securing remote workers. The forced march to digital that we talk about sometimes. These were all significant tailwinds for tech companies. The NASDAQ peaked late last year and then as you can see in this chart, bottomed in mid-March of 2022, and it made a nice run up through the 29th of last month, but the mini rally appears to be in jeopardy with FED rate hikes, Russia, supply chain challenges. There's a lot of uncertainty so we should expect the C-suite to be saying, hey, wait slow down. Now we don't think the concerns are confined to companies with exposure to Russia and Europe. We think it's more broad based than that and we're seeing caution from technology companies and tech buyers that we think is prudent, given the conditions. You know, looks like the two year party has ended and as my ETR colleague Erik Bradley said, a little hangover shouldn't be a surprise to anybody. So let's get right to the new spending data. I'm limited to what I can share with you today because ETR is in its quiet period and hasn't released full results yet outside of its client base. But, they did put out an alert today and I can share this slide. It shows the expectation on spending growth from more than a thousand CIOs and IT buyers who responded in the most recent survey. It measures their expectations for spending. The key focus areas that I want you to pay attention to in this data are the yellow bars. The most recent survey is the yellow compared to the blue and the gray bars, which are the December and September '21 surveys respectively. And you can see a steep drop from last year in Q1, lowered expectations for Q2 in the far right, a drop from nearly 9% last September to around 6% today. Now you may think a 200 basis point downgrade from our prediction in January of 8% seems somewhat benign, but in a $4 trillion IT market, that's 80 billion coming off the income statements of some tech companies. Now the good news is that 6% growth is still very healthy and higher than pre pandemic spending levels. And the buyers we've talked to this week are saying, look, we're still spending money. We just have to be more circumspect about where and how fast. Now, there were a few other callouts in the ETR data and in my discussions today with Erik Bradley on this. First, it looks like in response to expected supply chain constraints that buyers pulled forward their orders late last year and earlier this year. You remember when we couldn't buy toilet paper, people started the stockpile and it created this rubber banding effect. So we see clear signs of receding momentum in the PC and laptop market. But as we said, this is not isolated to PCs, UiPath's earning guidance confirm this but the story doesn't end there. This isn't isolated to UiPath in our view, rather it's a more based slowdown. The other big sign is spending in outsourced IT which is showing a meaningful deceleration in the last survey, showing a net score drop from 13% in January to 6% today. Net score remember is a measure of the net percentage of customers in the survey that on balance are spending more than last survey. It's derived by subtracting the percent of customers spending less from those spending more. And there's a, that's a 700 basis point drop in three months. This isn't a market where you can't hire enough people. The percent of companies hiring has gone from 10% during the pandemic to 50% today according to recent data from ETR. And we know there's still an acute skills shortage. So you would expect more IT outsourcing, but you don't see that in the data, it's down. And as this quote from Erik Bradley explains, historically, when outsourced IT drops like this, especially in a tight labor market, it's not good news for IT spending. All right, now, the other interesting callout from ETR were some specific company names that appear to be seeing the biggest change in spending momentum. Here's the list of those companies that all have meaningful exposure to Europe. That's really where the focus was. SAP has big exposure to on-premises installations and of course, Europe as well. ServiceNow has European exposure and also broad based exposure in IT in across the globe, especially in the US. Zoom didn't go to the moon, no surprise there given the quasi return to work and Zoom fatigue. McAfee is a bit of a concern because security seemed to be one of those areas, when you look at some of the other data, that is per actually insulated from all the spending caution. Of course we saw the Okta hack and we're going to cover that next week with hopefully some new data from ETR, but generally security's been holding up pretty well. You look at CrowdStrike, you look at Zscaler in particular. Adobe's another company that's had a nice bounce in the last couple of weeks. Accenture, again, speaks to that outsourcing headwinds that we mentioned earlier. And now the Google Cloud platform is a bit of a concern. It's still elevated overall, you know but down and well down in Europe. Under that magic, you know we often show that magic 40% dotted line, that red dotted line of net score anything above that we cite as elevated. Well, some important callouts to hear that you see companies that have Euro exposure. And again, we see this as just not confined to Europe and this is something we're going to pay close attention to and continue to report on in the next several weeks and months. All right, so what should we expect from here? The Ark investment stocks of Cathie Wood fame have been tracking in a downward trend since last November, meaning, you know, these high PE stocks are making lower lows and higher, sorry, lower highs and lower lows since then, right? The trend is not their friend. Investors I talk to are being much more cautious about buying the dip. They're raising cash and being a little bit more patient. You know, traders can trade in this environment but unless you can pay attention to in a minute by minute you're going to get whipsawed. Investors tell me that they're still eyeing big tech even though Apple has been on a recent tear and has some exposure with supply change challenges, they're looking for maybe entry points in, within that chop for Apple, Amazon, Microsoft, and Alphabet. And look, as I've been stressing, 6% spending growth is still very solid. It's a case of resetting the outlook relative to previous expectations. So when you zoom out and look at the growth in data, getting digital right, security investments, automation, cloud, AI containers, all the fundamentals are really strong and they have not changed. They're all powering this new digital economy and we believe it's just prudence versus a shift in the importance of IT. Now, one point of caution is there's a lot of discussion around a shift in global economies. Supply chain uncertainty, persistent semiconductor shortages especially in areas like, you know driver ICs and boring things like parts for displays and analog and micro controllers and power regulators. Stuff that's, you know, just not playing nice these days and wreaking havoc. And this creates uncertainty, which sometimes can pick up momentum in a snowballing effect. And that's something that we're watching closely and we're going to be vigilant reporting to you when we see changes in the data and in our forecast even when we think our forecast are wrong. Okay, that's it for today. Thanks to Alex Merson who does the production and podcasts for Breaking Analysis and Stephanie Chan who provides background research. Kristen Martin and Cheryl Knight, and all theCUBE writers they help get the word out, and thanks to Rob Hof, our EIC over at SiliconANGLE. Remember I publish weekly on wikibon.com and siliconangle.com. These episodes are all available as podcasts wherever you listen. All you got to do is search Breaking Analysis podcasts. etr.ai that's where you can get access to all this survey data and make your own cuts. It's awesome, check that out. Keep in touch with me. You can email me at dave.vellante@siliconangle.com. You can hit me up on LinkedIn. This is Dave Vellante for theCUBE insights powered by ETR. Be safe, stay well, and we'll see you next time. (gentle music)
SUMMARY :
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Breaking Analysis: Cyber Stocks Caught in the Storm While Private Firms Keep Rising
>> 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 pandemic precipitated what is shaping up to be a permanent shift in cybersecurity spending patterns. As a direct result of hybrid work, CSOs have vested heavily in endpoint security, identity access management, cloud security, and further hardening the network beyond the headquarters. We've reported on this extensively in this Breaking Analysis series. Moreover, the need to build security into applications from the start rather than bolting protection on as an afterthought has led to vastly high heightened awareness around DevSecOps. Finally, attacking security as a data problem with automation and AI is fueling new innovations in cyber products and services and startups. Hello and welcome to this week's Wikibon CUBE Insights powered by ETR. In this Breaking Analysis, we present our quarterly findings in the security industry, and share the latest ETR survey data on the spending momentum and market movers. Let's start with the most recent news in cybersecurity. Nary a week goes by without more concerning news. The latest focus in the headlines is, of course, Russia's relentless cyber attacks on critical infrastructure in the Ukraine, including banking, government websites, weaponizing information. The hacker group, BlackByte, put a double whammy on the San Francisco 49ers, meaning they exfiltrated data and they encrypted the organization's files as part of its ransomware attack. Then there's the best Super Bowl ad last Sunday, the Coinbase floating QR code. Did you catch that? As people rushed to scan the code and participate in the Coinbase Bitcoin giveaway, it highlights yet another exposure, meaning we're always told not to click on links that we don't trust or we've never seen, but so many people activated this random QR code on their smartphones that it crashed Coinbase's website. What does that tell you? In other news, Securonix raised a billion dollars. They did this raise on top of Lacework's massive $1.3 billion raise last November. Both of these companies are attacking security with data automation and APIs that can engage machine intelligence. Securonix, specifically in the announcement, mentioned the uptake from MSSPs, managed security service providers, something we've talked about in this series. And that's a trend that we see as increasingly gaining traction as customers are just drawing in and drowning in security incidents. Peter McKay's company, Snyk, acquired Fugue, a company focused on making sure security policies are consistent throughout the software development life cycle. It's a really an example of a developer-defined security approach where policy can be checked at the dev, deployment, and production phases to ensure the same policies are in place at all stages, including monitoring at runtime. Fugue, according to Crunchbase, had raised $85 million to date. In some other company news, Cisco was rumored to be acquiring Splunk for not much more than Splunk is worth today. And the talks reportedly broke down. This would be a major move in security by Cisco and underscores the pressure to consolidate. Cisco would get an extremely strong customer base and through efficiencies could improve Splunk's profitability, but it seems like the premium Cisco was willing to pay was not enough to entice board to act. Splunk board, that is. Datadog blew away its earnings, and the stock was up 12%. It's pulled back now, thanks to Putin, but it's one of those companies that is disrupting Splunk. Datadog is less than half the size of Splunk, revenue-wise, but its valuation is more than 2 1/2 times greater. Finally, Elastic, another Splunk disruptor, settled its trademark dispute with AWS, and now AWS will now stop using the name Elasticsearch. All right, let's take a high level look at how cyber companies have performed in the stock market over time. Here's a graph of the Cyber ETF, and you can see the March 1st crosshairs of 2020 signifying the start of the lockdown. The trajectory of cybersecurity stocks is shown by the orange and blue lines, and it surely has steepened post March of 2020. And, of course, it's been down with the market lately, but the run up, as you can see, was substantial and eclipsed the trajectory of the previous cycles over the last couple of years, owing much of the momentum to the spending dynamics that we talked about at our open. Let's now drill into some of the names that we've been following over the last few years and take a look at the firm level. This chart shows some data that we've been tracking since before the pandemic. The top rows show the S&P 500 and the NASDAQ prices, and the bottom rows show specific stocks. The first column is the index price or the market cap of the company just before the pandemic, then the same data one year later. Then the next column shows the peak value during the pandemic, and then the current value. Then it shows in the next column where it is today, in percentage terms, i.e., how far has it pulled back from the peak, then the delta from pre-pandemic, in other words, how much did the issue earn or lose during the pandemic for investors? We then compare the pre-pandemic revenue multiple using a trailing 12-month revenue metric. Sorry, that's what we used. It's easy to get. (laughs) And that's the revenue multiple compared to the August in 2020, when multiples were really high, and where they are today, and then a recent quarterly growth rate guide based on the last earnings report. That's the last column. Okay, so I'm throwing a lot of data at you here, but what does it tell us? First, the S&P and the NAS are well up from pre-pandemic levels, yet they're off 9% and 15%, respectively, from their peaks today. That was earlier on Friday morning. Now let's look at the names more closely. Splunk has been struggling. It definitely had a tailwind from the pandemic as all boats seem to rise, but its execution has been lacking. It's now 30% off from its pre-pandemic levels. (groans) And it's multiple is compressing, and perhaps Cisco thought it could pick up the company for a discount. Now let's talk about Palo Alto Networks. We had reported on some of the challenges the company faced moving into a cloud-friendly model. that was before the pandemic. And we talked about the divergence between Palo Alto's stock price and the valuations relative to Fortinet, and we said at the time, we fully expected Palo Alto to rebound, and that's exactly what happened. It rode the tailwinds of the last two years. It's up over 100% from its pre-COVID levels, and its revenue multiple is expanding, owing to the nice growth rates. Now Fortinet had been doing well coming into the pandemic. In fact, we said it was executing on a cloud strategy better than Palo Alto Networks, hence that divergence in valuations at the time. So it didn't get as much of a boost from the pandemic. Didn't get that momentum at first, but the company's been executing very well. And as you can see, with 155% increase in valuation since just before the pandemic, it's going more than okay for Fortinet. Now, Okta is a name that we've really followed closely, the identity access management specialist that rocketed. But since it's Auth0 acquisition, it's pulled back. Investors are concerned about its guidance and its profitability. And several analyst have downgraded their price targets on Okta. We still really like the company. The Auth0 acquisition gives Okta a developer vector, and we think the company is going hard after market presence and is willing to sacrifice short-term profitability. We actually like that posture. It's very Frank Slupin-like. This company spends a lot of money on R&D and go-to-market. The question is, does Okta have inherent profitability? The company, as they say, spends a ton in some really key areas but it looks to us like it's going to establish a footprint. It's guiding revenue CAGR in the mid-30s over the mid to long-term and near term should beat that benchmark handily. But you can see the red highlights on Okta. And even though Okta is up 59% from its pre-pandemic levels, it's far behind its peers shown in the chart, especially CrowdStrike and Zscaler, the latter being somewhat less impacted by the pullback in stocks recently, of course, due to the fears of inflation and interest rates, and, of course, Russian invasion escalation. But these high flyers, they were bound to pull back. The question is can they maintain their category leadership? And for the most part, we think they can. All right, let's get into some of the ETR data. Here's our favorite XY view with net score, or spending momentum on the Y-axis, and market share or pervasiveness in the data center on the horizontal axis. That red 40% line, that indicates a highly elevated spending level. And the chart inserts to the right, that shows how the data is plotted with net score and shared N in each of the columns by each company. Okay, so this is an eye chart, but there really are three main takeaways. One is that it's a crowded market. And this shows only the companies ETR captures in its survey. We filtered on those that had more than 50 mentions. So there's others in the ETR survey that we're not showing here, and there are many more out there which don't get reported in the spending data in the ETR survey. Secondly, there are a lot of companies above the 40% mark, and plenty with respectable net scores just below. Third, check out SentinelOne, Elastic, Tanium, Datadog, Netskope, and Darktrace. Each has under 100 N's but we're watching these companies closely. They're popping up in the survey, and they're catching our attention, especially SentinelOne, post-IPO. So we wanted to pare this back a bit and filter the data some more. So let's look at companies with more than 100 mentions in the same chart. It gets a little cleaner this picture, but it's still crowded. Auth0 leads everyone in net score. Okta is also up there, so that's very positive sign since they had just acquired Auth0. CrowdStrike SalePoint, Cyberark, CloudFlare, and Zscaler are all right up there as well. And then there's the bigger security companies. Palo Alto Network, very impressive because it's well above the 40% mark, and it has a big presence in the survey, and, of course, in the market. And Microsoft as well. They're such a big whale. They skew the data for everybody else to kind of mess up these charts. And the position of Cisco and Splunk make for an interesting combination. They get both decent net scores, not above the 40% line but they got a good presence in the survey as well. Thinking about the acquisition, Al Shugart was the CEO of of Seagate, and founder. Brilliant Silicon valley icon and engineer. Great business person. I was asking him one time, hey, you thinking about buying this company or that company? And of course, he's not going to tell me who he's thinking about buying or acquiring. He said, let me just tell you this. If you want to know what I'm thinking, ask yourself if it were free, would you take it? And he said the answer's not always obviously yes, because acquisitions can be messy and disruptive. In the case of Cisco and Splunk, I think the answer would be a definitive yes It would expand Cisco's portfolio and make it the leader in security, with an opportunity to bring greater operating leverage to Splunk. Cisco's just got to pay more if it wants that asset. It's got to pay more than the supposed $20 billion offer that it made. It's going to have to get kind of probably north of 23 billion. I pinged my ETR colleague, Erik Bradley, on this, and he generally agreed. He's very close to the security space. He said, Splunk isn't growing the customer base but the customers are sticky. I totally agree. Cisco could roll Splunk into its security suite. Splunk is the leader in that space, security information and event management, and Cisco really is missing that piece of the pie. All right, let's filter the data even more and look at some of the companies that have moved in the survey over the past year and a half. We'll go back here to July 2020. Same two-dimensional chart. And we're isolating here Auth0, Okta, SalePoint CrowdStrike, Zscaler, Cyberark, Fortinet, and Cisco. No Microsoft. That cleans up the chart. Okay, why these firms? Because they've made some major moves to the right, and some even up since last July. And that's what this next chart shows. Here's the data from the January 2022 survey. The arrow start points show the position that we just showed you earlier in July 2020, and all these players have made major moves to the right. How come? Well, it's likely a combination of strong execution, and the fact that security is on the radar of every CEO, CIO, of course, CSOs, business heads, boards of directors. Everyone is thinking about security. The market momentum is there, especially for the leaders. And it's quite tremendous. All right, let's now look at what's become a bit of a tradition with Breaking Analysis, and look at the firms that have earned four stars. Four-star firms are leaders in the ETR survey that demonstrate both a large presence, that's that X-axis that we showed you, and elevated spending momentum. Now in this chart, we filter the N's. Has to be greater than 100. And we isolate on those companies. So more than 100 responses in the survey. On the left-hand side of the chart, we sort by net score or spending velocity. On the right-hand side, we sort by shared N's or presence in the dataset. We show the top 20 for each of the categories. And the red line shows the top 10 cutoffs. Companies that show up in the top 10 for both spending momentum and presence in the data set earn four stars. If they show up in one, and make the top 10 in one, and make the top 20 in the other, they get two stars. And we've added a one-star category as honorable mention for those companies that make the top 20 in both categories. Microsoft, Palo Alto Networks, CrowdStrike, and Okta make the four-star grade. Okta makes it even without Auth0, which has the number one net score in this data set with 115 shared N to boot. So you can add that to Okta. The weighted average would pull Okta's net score to just above Cyberark's into fourth place. And its shared N would bump Okta up to third place on the right-hand side of the chart Cisco, Splunk, Proofpoint, KnowBe4, Zscaler, and Cyberark get two stars. And then you can see the honorable mentions with one star. Now thinking about a Cisco, Splunk combination. You'd get an entity with a net score in the mid-20s. Yeah, not too bad, definitely respectable. But they'd be number one on the right-hand side of this chart, with the largest market presence in the survey by far. Okay, let's wrap. The trends around hybrid work, cloud migration and the attacker escalation that continue to drive cybersecurity momentum and they're going to do so indefinitely. And we've got some bullet points here that you're seeing private companies, (laughs) they're picking up gobs of money, which really speaks to the fact that there's no silver bullet in this market. It's complex, chaotic, and cash-rich. This idea of MSSPs on the rise is going to continue, we think. About half the mid-size and large organization in the US don't have a SecOps, a security operation center, and outsourcing to one that can be tapped on a consumption basis, cloud-like, as a service just makes sense to us. We see the momentum that companies that we've highlighted over the many quarters of Breaking Analysis are forming. They're forming a strong base in the market. They're going for market share and footprint, and they're focusing on growth, at bringing in new talent. They have good balance sheets and strong management teams and we think they'll be leading companies in the future, Zscaler, CrowdStrike, Okta, SentinelOne, Cyberark, SalePoint, over time, joining the ranks of billion dollar cyber firms, when I say billion dollar, billion dollar revenue like Palo Alto Networks, Fortinet, and Splunk, if it doesn't get acquired. These independent firms that really focus on security. Which underscores the pressure and consolidation and M&A in the whole space. It's almost assured with the fragmentation of companies and so many new entrants fighting for escape velocity that this market is going to continue with robust M&A and consolidation. Okay, that's it for today. Thanks to my colleague, Stephanie Chan, who helped research this week's topics, and Alex Myerson on the production team. He also manages the Breaking Analysis podcast. Kristen Martin and Cheryl Knight, who get the word out. Thank you to all. Remember these episodes are all available as podcasts wherever you listen. All you do is search Breaking Analysis podcast. Check out ETR's website at etr.ai. We also publish a full report every week on wikibon.com and siliconangle.com. You can email me at david.vellante@siliconangle.com. @dvellante is my DM. Comment on our LinkedIn posts. This is Dave Vellante for theCUBE Insights powered by ETR. Have a great week. Be safe, be well, and we'll see you next time. (upbeat music)
SUMMARY :
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General Keith Alexander, IronNet Cybersecurity | AWS re:Invent 2021
(upbeat music) >> Welcome to theCube's continuous coverage of AWS re:Invent 2021. I'm Dave Nicholson, and we are running one of the industry's most important and largest hybrid tech events this year with AWS and its partners with two live sets on the scene. In addition to two remote studios. And we'll have somewhere in the neighborhood of a hundred guests on the program this year at re:Invent. I'm extremely delighted to welcome a very, very special guest. Right now. He served as the director of the NSA under two presidents, and was the first commander of the U.S Cyber Command. He's a Cube alumni, he's founder and co-CEO of IronNet Cybersecurity. General Keith Alexander. Thanks for joining us today General. >> Thanks, David. It's an honor to be here at re:Invent, you know, with AWS. All that they're doing and all they're making possible for us to defend sector states, companies and nations in cyber. So an honor to be here. >> Well, welcome back to theCube. Let's dive right in. I'd like to know how you would describe the current cyber threat landscape that we face. >> Well, I think it's growing. Well, let's start right out. You know, the good news or the bad news, the bad news is getting worse. We're seeing that. If you think about SolarWinds, you think about the Hafnium attacks on Microsoft. You think about this rapid growth in ransomware. We're seeing criminals and nation states engaging in ways that we've never seen in the past. It's more blatant. They're going after more quickly, they're using cyber as an element of national power. Let's break that down just a little bit. Do you go back to two, July. Xi Jinping, talked about breaking heads in bloodshed when he was referring to the United States and Taiwan. And this has gone hot and cold, that's a red line for him. They will do anything to keep Taiwan from breaking away. And this is a huge existential threat to us into the region. And when this comes up, they're going to use cyber to go after it. Perhaps even more important and closer right now is what's going on with Russia in the Donbas region of eastern Ukraine. We saw this in 2014, when Russia took over the Crimea. The way they did it, staging troops. They did that in 2008 against Georgia. And now there are, by some reports over a hundred thousand troops on the border of Eastern Ukraine. Some call it an exercise, but that's exactly what they did in Georgia. That's what they did in the Crimea. And in both those cases, they preceded those attacks, those physical attacks with cyber attacks. If you go to 2017, when Russia hit the Ukrainian government with the NotPetya attack that had global repercussions. Russia was responsible for SolarWinds, they have attacked our infrastructure to find out what our government is doing and they continue going. This is getting worse. You know, it's interesting when you think about, so what do you do about something like that? How do we stop that? And the answer is we've got to work together. You know, Its slam commissioner addressed it. The meeting with the president on August 25th. This is a great statement by the CEO and chairman of Southern Company, Tom Fanning. He said this, "the war is being waged on our nation's critical infrastructure in particular, our energy sector, our telecommunications sector and financial sector." The private sector owns and operates 87% of the critical infrastructure in the United States, making collaboration between industry and the federal government imperative too, for these attacks. SO >> General, I want to dig just a little bit on that point that you make for generations, people have understood that the term is 'kinetic war', right? Not everyone has heard that phrase, but for generations we've understood the concept of someone dropping a bomb on a building as being an attack. You've just mentioned that, that a lot of these attacks are directed towards the private sector. The private sector doesn't have an army to respond to those attacks. Number one, that's our government's responsibility. So the question I have is, how seriously are people taking these kinds of threats when compared to the threat of kinetic war? Because my gosh, you can take down the entire electrical grid now. That's not something you can do with a single bomb. What are your, what are your thoughts on that? >> So you're hitting on a key point, a theoretical and an operational point. If you look back, what's the intent of warfare? It's to get the mass of people to give up. The army protects the mass of people in that fight. In cyber, there's no protection. Our critical infrastructure is exposed to our adversaries. That's the problem that we face. And because it's exposed, we have a tremendous vulnerability. So those who wish us harm, imagine the Colonial Pipeline attack an order of magnitude or two orders of magnitude bigger. The impact on our country would paralyze much of what we do today. We are not ready for that. That's the issue that Tom Fanning and others have brought up. We don't practice between the public sector and the private sector working together to defend this country. We need to do that. That's the issue that we have to really get our hands around. And when we talk about practice, what do we mean? It means we have to let that federal government, the ones that are going to protect us, see what's going on. There is no radar picture. Now, since we're at re:Invent, the cloud, where AWS and others have done, is create an infrastructure that allows us to build that bridge between the public and private sector and scale it. It's amazing what we can now do. We couldn't do that when I was running Cyber Command. And running Cyber Command, we couldn't see threats on the government. And we couldn't see threats on critical infrastructure. We couldn't see threats on the private sector. And so it all went and all the government did was say, after the fact you've been attacked. That's not helpful. >> So >> It's like they dropped a bomb. We didn't know. >> Yeah, so what does IronNet doing to kind of create this radar capability? >> So, well, thanks. That's a great question because there's four things that you really got to do. First. You've got to be able to detect the SolarWinds type attacks, which we did. You've got to have a hunt platform that can see what it is. You've got to be able to use machine learning and AI to really cut down the number of events. And the most important you need to be able to anonymize and share that into the cloud and see where those attacks are going to create that radar picture. So behavioral analytics, then you use signature based as well, but you need those sets of analytics to really see what's going on. Machine learning, AI, a hunt platform, and cloud. And then analytics in the cloud to see what's going on, creates that air traffic control, picture radar, picture for cyber. That's what we're doing. You see, I think that's the important part. And that's why we really value the partnership with AWS. They've been a partner with us for six years, helping us build through that. You can see what we can do in the cloud. We could never do in hardware alone. Just imagine trying to push out equipment and then do that for hundreds of companies. It's not viable. So SaaS, what we are as a SaaS company, you can now do that at scale, and you can push this out and we can create, we can defend this nation in cyber if we work together. And that's the thing, you know, I really, had a great time in the military. One of the things I learned in the military, you need to train how you're going to fight. They're really good at that. We did that in the eighties, and you can see what happened in 1990 in the Gulf war. We need to now do that between the public and private sector. We have to have those training. We need to continuously uplift our capabilities. And that's where the cloud and all these other things make that possible. That's the future of cybersecurity. You know, it's interesting David, our country developed the internet. We're the ones that pioneered that. We ought to be the first to secure. >> Seems to make sense. And when you talk about collective defense in this private public partnership, that needs to happen, you get examples of some folks in private industry and what they're doing, but, but talk a little bit more about, maybe what isn't happening yet. What do we need to do? I don't want you to necessarily get political and start making budgetary suggestions, but unless you want to, but what, but where do you see, where do we really need to push forward from a public perspective in order to make these connections? And then how is that connection actually happen? This isn't someone from the IronNet security service desk, getting on a red phone and calling the White House, how are the actual connections made? >> So it has to be, the connections have to be just like we do radar. You know, when you think about radars across our nation or radar operator doesn't call up one of the towers and say, you've got an aircraft coming at you at such and such a speed. I hope you can distinguish between those two aircraft and make sure they don't bump into each other. They get a picture and they get a way of tracking it. And multiple people can see that radar picture at a speed. And that's how we do air traffic control safety. We need the same thing in cyber, where the government has a picture. The private sector has a picture and they can see what's going on. The private sector's role is I'm going to do everything I can, you know, and this is where the energy sector, I use that quote from Tom Fanning, because what they're saying is, "it's our job to keep the grid up." And they're putting the resources to do it. So they're actually jumping on that in a great way. And what they're saying is "we'll share that with the government", both the DHS and DOD. Now we have to have that same picture created for DHS and DOD. I think one of the things that we're doing is we're pioneering the building of that picture. So that's what we do. We build the picture to bring people together. So think of that is that's the capability. Everybody's going to own a piece of that, and everybody's going to be operating in it. But if you can share that picture, what you can begin to do is say, I've got an attack coming against company A. Company A now sees what it has to do. It can get fellow companies to help them defend, collective defense, knowledge sharing, crowdsourcing. At the same time, the government can see that attack going on and say, "my job is to stop that." If it's DHS, I could see what I have to do. Within the country, DOD can say, "my job is to shoot the archers." How do we go do what we're authorized to do under rules of engagement? So now you have a way of the government and the private sector working together to create that picture. Then we train them and we train them. We should never have had an event like SolarWinds happen in the future. We got to get out in front. And if we do that, think of the downstream consequences, not only can we detect who's doing it, we can hold them accountable and make them pay a price. Right now. It's pretty free. They get in, pap, that didn't work. They get away free. That didn't work, we get away free. Or we broke in, we got, what? 18,000 companies in 30,000 companies. No consequences. In the future there should be consequences. >> And in addition to the idea of consequences, you know, in the tech sector, we have this concept of a co-op petition, where we're often cooperating and competing. The adversaries from, U.S perspective are also great partners, trading partners. So in a sense, it sounds like what you're doing is also kind of adhering to the old adage that, that good fences make for great neighbors. If we all know that our respective infrastructures are secure, we can sort of get on with the honest business of being partners, because you want to make the cost of cyber war too expensive. Is that, is that a fair statement? >> Yes. And I would take that analogy and bend it slightly to the following. Today every company defends itself. So you take 90 companies with 10 people, each doing everything they can to defend themselves. Imagine in the world we trying to build, those 90 companies work together. You have now 900 people working together for the collective defense. If you're in the C-suite or the board of those companies, which would rather have? 900 help new security or 10? This isn't hard. And so what we say is, yes. That neighborhood watch program for cyber has tremendous value. And beyond neighborhood watch, I can also share collaboration because, I might not have the best people in every area of cyber, but in those 900, there will be, and we can share knowledge crowdsource. So it's actually let's work together. I would call it Americans working together to defend America. That's what we need to do. And the states we going to have a similar thing what they're doing, and that's how we'll work this together. >> Yeah. That makes a lot of sense. General Alexander it's been a pleasure. Thanks so much for coming on to theCube as part of our 2021 AWS re:Invent coverage. Are you going to get a chance to spend time during the conference in Las Vegas? So you just flying in, flying out. Any chance? >> Actually yeah. >> It's there, we're still negotiating working that. I've registered, but I just don't know I'm in New York city for two meetings and seeing if I can get to Las Vegas. A lot of friends, you know, Adam Solski >> Yes >> and the entire AWS team. They're amazing. And we really liked this partnership. I'd love to see you there. You're going to be there, David? Absolutely. Yes, absolutely. And I look forward to that, so I hope hopefully we get that chance again. Thank you so much, General Alexander, and also thank you to our title sponsor AMD for sponsoring this year's re:Invent. Keep it right here for more action on theCube, you're leader in hybrid tech event coverage, I'm Dave Nicholson for the Cube. Thanks. (upbeat music)
SUMMARY :
of a hundred guests on the So an honor to be here. I'd like to know how you would describe And the answer is we've got So the question I have is, the ones that are going to It's like they dropped a bomb. And that's the thing, you know, I really, partnership, that needs to happen, We build the picture to in the tech sector, we And the states we going to theCube as part of our 2021 and seeing if I can get to Las Vegas. I'd love to see you there.
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Suni Potti & Lior Div | CUBE Conversation, October 2021
hello and welcome to this special cube conversation i'm dave nicholson and this is part of our continuing coverage of google cloud next 2021 i have two very special guests with me and we are going to talk about the topic of security uh i have sunil potti who is vice president and general manager of google cloud security uh who in a previous life had senior leadership roles at nutanix and citrix along with lior div who is the ceo and co-founder of cyber reason lior was formerly a commander in the much famed unit 8200 uh part of the israeli defense forces uh where he was actually a medal of honor recipient uh very uh honored to have him here this morning sunil and lior welcome to the cube sunil welcome back to the cube yeah great to be here david and and to be in the presence of a medal of honor recipient by the way a good friend of mine leor so be here well good to have both of you here so uh i'm the kind of person who likes my dessert before my uh before my entree so why don't we just get right to it you're the two of you are here to announce something very very significant uh in the field of security uh sunil do you want to start us out what are we here to talk about yeah i mean i think maybe uh you know just to set this context um as as many of you know about a decade ago a nation's sponsored attack you know actually got into google plus a whole bunch of tech companies you know the project aurora was quite uh you know infamous for a certain period of time and actually google realized almost a decade ago that look you know security can't just be a side thing it has to be the primary thing including one of the co-founders becoming for lack of a better word the chief security officer for a while but one of the key takeaways from that whole incident was that look you have to be able to detect everything and trust nothing and and the underpinning for at least one of them led to this whole zero trust architectures that everybody now knows about but the other part which is not as popular at least in industry vernacular but in many ways equally important and some ways more important is the fact that you need to be able to detect everything so that you can actually respond and that led to the formation of you know a project internal to google to actually say that look let's democratize uh storage and make sure that nobody has to pay for capturing security events and that led to the formation of this uh new industry concept called a security data lake in chronicle was born and then as we started evolving that over into the enterprise segment partnering with you know cyber reason on one hand created a one plus one equals three synergy between say the presence around what do you detect from the end point but also generally just so happens that as lior will tell you the cyber reason technology happens to start with endpoint but it's actually the core tech is around detecting events but doing it in a smart way to actually respond to them in much more of a contextual manner but beyond just that you know synergy between uh you know a world-class planet scale you know security data like forming the foundation and integrating you know in a much more cohesive way with uh cyber reasons detection response offering the spirit was actually that this is the first step of a long journey to really hit the reset button in terms of going from reactive mode of security to a proactive mode of security especially in a nation-state-sponsored attack vector so maybe leo you can speak a few minutes on that as well absolutely so um as you said i'm coming from a background of uh nation state hacking so for us at cyberism it's uh not is foreign uh what the chinese are doing uh on a daily basis and the growing uh ransomware cartel that's happening right now in russia um when we looked at it we said then uh cyberism is very famous by our endpoint detection and response capability but when we establish cyber reason we establish the cyberism on a core or almost fundamental idea of finding malicious operation we call it the male idea so basically instead of looking for alerts or instead of looking for just pieces of data we want to find the hackers we want to find the attack we want to be able to tell basically the full story of what's going on uh in order to do that we build the inside cyberism basically from day one the ability to analyze any data in real time in order to stitch it into the story of the male the malicious operation but what we realize very quickly that while our solution can process more than 27 trillion events a week we cannot feed it fast enough just from end point and we are kind of blind when it comes to the rest of the attack surface so we were looking uh to be honest quite a while for the best technology that can feed this engine and to as sunil said the one plus one equal three or four or five to be able to fight against those hackers so in this journey uh we we found basically chronicle and the combination of the scale that chronicle bringing the ability to feed the engine and together basically to be able to find those hackers in real time and real time is very very important and then to response to those type of attack so basically what is uh exciting here we created a solution that is five times faster than any solution that exists right now in the market and most importantly it enables us to reverse the atmospheric advantage and basically to find them and to push them out so we're moving from hey just to tell you a story to actually prevent hackers to being in your environment so leor can you i want to double click on that just just a little bit um can you give give us a kind of a concrete example of this difference between simply receiving alerts and uh and actually um you know taking taking uh uh correlating creating correlations and uh and actually creating actionable proactive intelligence can you give us an example of that working in in the real world yeah absolutely we can start from a simple example of ransomware by the time that i will tell you that there is a ransomware your environment and i will send an alert uh it will be five computers that are encrypted and by the time that you gonna look at the alert it's gonna be five thousand uh basically machines that are encrypted and by the time that you will do something it's going to be already too little too late and this is just a simple example so preventing that thing from happening this is critical and very timely manner in order to prevent the damage of ransomware but if you go aside from ransomware and you look for example of the attack like solarwind basically the purpose of this attack was not to create damage it was espionage the russian wanted to collect data on our government and this is kind of uh the main purpose that they did this attack so the ability to be able to say hey right now there is a penetration this is the step that they are doing and there is five ways to push them out of the environment and actually doing it this is something that today it's done manually and with the power of chronicle and cyberism we can do it automatically and that's the massive difference sunil are there specific industries that should be really interested in this or is this a is this a broad set of folks that should be impacted no you know in some ways uh you know the the the saying these days to learn's point on ransomware is that you know if if a customer or an enterprise has a reasonable top-line revenue you're a target you know you're a target to some extent so in that sense especially given that this has moved from pure espionage or you know whether it be you know government oriented or industrial espionage to a financial fraud then at that point in time it applies to pretty much a wide gamut of industries not just financial services or you know critical infrastructure companies like oil and gas pipeline or whatever it could be like any company that has any sort of ip that they feel drives their top line business is now a target for such attacks so when you talk about the idea of partnership and creating something out of a collaboration what's the meat behind this what what what do you what are you guys doing beyond saying you know hey sunil lior these guys really like each other and they respect what the other is doing what's going on behind the scenes what are you actually implementing here moving forward so every partnership is starting with love so it's good [Laughter] but then it need to translate to to really kind of pure value to our customers and pure value coming from a deep integration when it's come to the product so basically uh what will happen is every piece of data that we can collect at cyber is in uh from endpoint any piece of data that the chronicle can collect from any log that exists in the world so basically this is kind of covering the whole attack surface so first we have access to every piece of information across the full attack surface then the main question is okay once you collect all this data what you're gonna do with it and most of companies or all the companies today they don't have an answer they're saying oh we're gonna issue an alert and we hope that there is a smart person behind the keyboard that can understand what just happened and make a decision and with this partnership and with this integration basically we're not asking and outsourcing the question what to do to the user we're giving them the answer we're telling them hey this is the story of the attack this is all the pieces that's going on right now and in most cases we're gonna say hey and by the way we just stopped it so you can prevent it from the future when will people be able to leverage this capability in an integrated way and and and by the way restate how this is going to market as an integrated solution what is what is the what is what are we going to call this moving forward so basically this is the cyber reason xdr uh powered by chronicle and we are very very um uh happy about it yeah and i think just to add to that i would say look the the meta strategy here and the way it'll manifest is in this offering that comes out in early 2022 um is that if you think about it today you know a classical quote-unquote security pipeline is to detect you know analyze and then respond obviously you know just just doing those three in a good way is hard doing it in real time at scale is even harder so just that itself was where cyber reason and chronicle would add real value where we are able to collect a lot of events react in real time but a couple of things that i think that you know to your original point of why this is probably going to be a little for game changer in the years to come is we're trying to change that from detect analyze respond to detect understand and anticipate so because ultimately that's really how we can change you know the profile from being reactive in a world of ransomware or anything else to being proactive against a nation sponsored or nation's influenced attacks because they're not going to stop right so the only way to do this is to rather than just go back up the hatches is just really you know change change the profile of how you'll actually anticipate what they were probably going to do in 6 months or 12 months and so the the graph technology that powers the heart of you know cyber reason is going to be intricately woven in with the contextual information that chronicle can get so that the intermediate step is not just about analysis but it's about truly understanding the overall strategy that has been employed in the past to predict what could happen in the future so therefore then actions could be taken downstream that you can now say hey most likely this these five buckets have this kind of personal information data there's a reasonable chance that you know if they're exposed to the internet then as you create more such buckets in that project you're going to be susceptible to more ransomware attacks or some other attacks right and that's the the the kind of thinking or the transformation that we're trying to bring out with this joint office so lior uh this this concept of uh of mallops and uh cyber reason itself you weren't just born yesterday you've been you've been uh you have thousands of customers around the globe he does look like he was born i i know i know i know well you you know it used to be that the ideal candidate for ceo of a startup company was someone who dropped out of stanford i think it's getting to the point where it's people who refused admission to stanford so uh the the dawn of the 14 year old ceo it's just it's just around the corner but uh but lior do you get frustrated when you see um you know when you become aware of circumstances that would not have happened had they implemented your technology as it exists today yeah we have a for this year it was a really frustrating year that starting with solarwind if you analyze the code of solarwind and we did it but other did it as well basically the russians were checking if cyberism is installed on the machine and if we were installed on the machine they decided to stop the attack this is something that first it was a great compliment for us from you know our not friend from the other side that decided to stop the attack but on a serious note it's like we were pissed because if people were using this technology we know that they are not going to be attacked when we analyze it we realize that we have three different ways to find the solar wind hackers in a three different way so this is just one example and then the next example in the colonial pipeline hack we were the one that found darkseid as a group that we were hacking we were the first one that released a research on them and we showed how we can prevent the basically what they are doing with our technology so when you see kind of those type of just two examples and we have many of them on a daily basis we just know that we have the technology in order to do that now when we're combining uh the chronicle technology into the the technology that we already have we basically can reverse the adversary advantage this is something that you're not doing in a single day but this is something that really give power to the defenders to the communities of siso that exist kind of across the us um and i believe that if we're going to join forces and lean into this community and and basically push the solution out the ability for us to fight against those cartels specifically the ransomware cartels is going to be massive sunil this time next year when we are in uh google cloud next 2022 um are you guys going to come back on and offer up the we told you so awards because once this is actually out there and readily available the combination of chronicle and cyber reasons technology um it's going to be hard for some csos to have an excuse uh it may be it may be a uncomfortable to know that uh they could have kept the door secure uh but didn't yeah where's that bad business is that bad business to uh hand out awards for doing dumb things i don't know about uh you know a version of darwin awards probably don't make sense but but but generally speaking so i do think uh you know we're all like as citizens in this right because you know we talk about customers i mean you know alphabet and google is a customer in some ways cyber reason is a customer the cube is a customer right so i think i think the robot hitting the road a year from now will be we should we should do this where i don't know if the cube does more than two folks at the same time david but we should i mean i'm sure we'll have enough to have at least a half a dozen in in the room to kind of talk about the solution because i think the the you know as you can imagine this thing didn't materialize i mean it's been being cooked for a while between your team and our team and in fact it was inspired by feedback from some joint customers out in the market and all that good stuff so so a year from now i think the best thing would be not just having customers to talk about the solution but to really talk about that transformation from respond to anticipate and do they feel better on their security posture in a world that they know like and leo should probably spend a few minutes on this is i think we're on the tip of the sphere of this nation-state era and what we've just seen in the last few years is what maybe the nation-states have seen over two decades ago and they're going to run those playbooks on the enterprise for the next decade or so yeah leor talk about that for a minute yeah it's it's really you know just to continue the sunil thought it's it's really about finding the unknown because what's happening on the other side it's like specifically china and russia and lately we saw iran starting to gain uh power um basically their job is to become better and better and to basically innovate and create a new type of attack on a daily basis as technology has evolved so basically there is a very simple equation as we're using more technology and relying more on technology the other side is going to exploit it in order to gain more power espionage and create financial damage but it's important to say that this evolution it's not going to stop this is just the beginning and a lot of the data that was belong just to government against government fight basically linked in the past few years now criminals starting to use it as well so in a sense if you think about it what's happening right now there is basically a cold war that nobody is talking about it between kind of the giant that everybody is hacking everybody and in the crossfire we see all of those enterprises across the world it was not a surprise that um you know after the biden and putin uh meeting suddenly it was a quiet it was no ransomware for six weeks and after something changing the politics suddenly we can see a a groin kind of attack when it's come to ransomware that we know that was directed from russia in order to create pressure on the u.s economy sunil wrap us up what are your f what are what are your final thoughts and uh what's what's the what's the big takeaway here no i think you know i i think the key thing for everyone to know is look i think we are going into an era of state-sponsored uh not espionage as much as threat vectors that affect every business and so in many ways the chiefs the chief information security officer the chief risk officer in many ways the ceo and the board now have to pay attention to this topic much like they paid attention to mobile 15 years ago as a transformation thing or maybe cloud 10 years ago i think cyber has been one of those it's sort of like the wireless error david like it existed in the 90s but didn't really break around until iphone hit or the world of consumerization really took off right and i think we're at the tip of the spear of that cyber really becoming like the era of mobile for 15 years ago and so i think that's the if there's like a big takeaway i think yes there's lots of solutions the good news is great innovations are coming through companies like cyber reason working with you know proven providers like google and so forth and so there's a lot of like support in the ecosystem but i think if there was one takeaway that was that everybody should just be ready internalized we don't have to be paranoid about it but we anticipate that this is going to be a long game that we'll have to play together well with that uh taking off my journalist hat for a moment and putting on my citizen hat uh it's reassuring to know that we have really smart people working on this uh because when we talk about critical infrastructure control systems and things like that being under threat um that's more significant than simply having your social security number stolen in a in a data breach so um with that uh i'd like to thank you sunil leor thank you so much for joining us on this special cube conversation this is dave nicholson signing off from our continuing coverage of google cloud next 2021 [Music] you
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Zak Brown, McLaren Racing | Splunk .conf1
>>Hello, and welcome back to the cubes coverage of splunk.com here in the virtual studios in Silicon valley broadcasting around the world's a virtual event. Um, John four-year host of the queue. We've got a great guest, Zach brown, chief executive officer of McLaren racing, really looking forward to this interview, Zach, welcome to the queue. Well, thanks for coming on. Thanks for having me. So we have a huge fan base in the tech community. A lot of geeks love the neurons. They love the tech behind the sport. Uh, and Netflix is driving to survive. Series has absolutely catapulted the popularity of F1 in the tech community. So congratulations on all the success in that program and on, and then on the >>Thank you very much, it's been a, it's been a good run. We've won our first race in a while, but we still have a ways to go to get in that, uh, world championship that, uh, >>So for the techies out there and the folks in our audience that aren't familiar with, the specifics of the racing team and the dynamics, take a minute to explain what you guys do. >>Uh, so McLaren racing, uh, which has a variety of, uh, racing teams, uh, a formula one team in indie car team and extremely team and an e-sports team. Uh, we're the second most successful form of the one team in the history of sport. Now 183 wins 182, uh, when I joined 20 world championships and, uh, we're, we're close to a thousand people to, to run a couple of racing cars and, uh, currently third in the championship, uh, with Lando Norris and, uh, Daniel, Ricardo. >>So talk about the, um, the, the dynamics of the spore. Obviously data is big part of it. Uh, we see the, a lot of the coverage. You can see anything can happen overnight. It's very quick. Um, technology has been being, uh, playing a big role in sport. What's your vision on how that's evolving? Are you happy with where things are, uh, and where do you see it going? >>Yeah, it does some interesting stats. So, um, the car that qualifies first at the beginning of the year, if you didn't touch, it would be last by the end of the year. So that's the pace of a development of a, of a formula one car. We change a, uh, and develop a new part on the car every 14 minutes, 365 days, days a year. Um, and technology plays a huge role. Uh, it's, it's probably the most technical, um, evolved sport in the world. Uh, both safety data, uh, the innovation it's it's awesome. And what a lot of people don't know is a lot of what we develop in a formula. One car ends up in other parts of the world, whether it was a ventilators that we helped develop for the UK government, uh, to working with our, uh, various partners or safety and innovation in the automotive industry. >>You know, I love it. I always loved the IOT internet of things, story around cars, because sensors or instrumentation is a big part of it. Um, and it all comes together. So it's pretty, it's not simple. No, give it feel, give it a taste a little bit about what's it. How complicated is it, how you guys pay attention to the details? What's important. Take us through some of the, some of the inside the ropes around the IOT of the sensors and all the data. >>Yeah. So we have over 300 sensors on our race car. We collect the one and a half terabytes of data. Every race weekend, we have a thousand people, um, and the strong majority of those are working around data and technology, as opposed to physically touching the car out of those thousand people, you probably only have about 60 or 70. They're actually touch the race card at a race weekend. We've been doing connected cars for about 25 years. So that's kind of a new thing here to, to most people, but we've been communicating back and forth with our race car for, for decades all around the world. And what a lot of people don't realize is it all starts in our mission control back in our factory in Woking, England. So wherever we are around the world, the racing team actually starts in England. >>So I want to ask you about the personalities on the team. How big is the staff? What's the makeup of the personnel has to get the drivers. They're critical. They're a very dynamic personalities. We'll come to the side question on that later, but what's the staff look like on when you guys put this together. So you get, you get race day and you got back office support. >>What's the team look like? Yeah. So you've got about a thousand people that, that make up the collective team. You'll have about a hundred in marketing. Uh, you'll have about a hundred in finance, HR, and then you kind of get to the, the racing team. If you'd like 800 people, you have about a hundred people traveling to each race, uh, about 50 people back at the factory, working with data and communications that are grand Prix weekend. And then everybody else is designing manufacturing, production laminating. So we run 24, 7 shifts, uh, three shifts, uh, in certain parts. Uh, we develop, uh, 85% of the car changes of what's allowed to be changed start of the year to the, the end of the year. So the development is, is unbelievable. >>I know you're here in the U S for the U S grand Prix in Austin. Um, coming up, I'm just curious how cars get transported. >>Uh, w when we're traveling around the world, uh, they, they travel on 7 47 and are flown around the world. And then when we're in Europe, we have about 18 trucks that were communing around when we're kind of in the European part of the circuit is usually in the middle of the year. But when we're going to Australia or Singapore, Bahrain, those are, those are on planes form of the one actually does that. They give us an allocation of, of space, and then we have to write a check if we need more space than where >>Yeah. We're allowed. Yeah. And that brings up the security question, because honestly, there's a lot of fans, a lot of people are into it. Also, this potentially security risks. Have you guys thought about that obviously like physical moving the supply chain around from event event, but also technology risk. Um, how do you guys think about security? >>Yeah, it's, it's critically important. We've had, uh, fortunately we've not had any breach of our technology. We have had a breach in the late nineties of our radio communications and, uh, it was in Australia, Mika Hakkinen and a fan, uh, who I think was probably having some fun and were able to break into our radio channel and actually asked Mika to pit. He pitted team wasn't ready. And fortunately, we will run in one, two, but we actually had to reverse the drivers. So security is >>Critically important, probably Katie Scrivener, and they all look, I just hack the radio, was talking to the driver. That is a funny story, but it could be serious. I mean, now you have all kinds of >>The stuff going on and, and, you know, there's a lot of money at stake, you know, so, you know, we're fortunate in this particular instance, it didn't hurt us cause we were running one, two, so we could reverse the drivers and the right guide one. Um, but you know, that could decide, uh, a world championship and you have, you know, tens of millions of dollars online, but even besides the economics, we want to win races. >>You know, what's funny is that you guys have a lot of serious on the line stakes with these races, but you're known for having a lot of fun, the team team dynamic. I have to ask you, when you finish on the podium one and two, there's a Shui with the drivers. How'd that go down. It was pretty, pretty a big spectacle online and >>Yeah, it was, it was good, fun. That's something, obviously Daniel Ricardo is kind of developed as his thing when he, uh, when he wins. And, uh, when we were, uh, before we went on the podium, he said to me, you're going to do the shoe. Yes, of course. In the car show you got to do, we have to like a bunch of 12 year old kids, uh, on the podium, but that's where we're just big kids going, motor racing and >>The end of the day. Well, I gotta say you guys come across really strong as a team, and I love the fun and, you know, competitive side. So congratulations on that, I think is good on the competitive side, take me through the advantage, driving the advantage with data, because that's really the theme here at.com, which is Splunk, which they're a big partner, as well as your other sponsors. Data's big, you know, and it's striving an advantage. Where do you see that coming from? Take us through where you guys see the advantages. Yes. >>So, you know, everything we do is, is precision and, you know, every second, every 10th counts and, um, you know, you can get all this data in, but what do you do with this data? And the humans can, uh, real, uh, react as quickly as is, you know, people like Splunk who can help us, uh, not only collect data, but help us understand data. And, um, you know, typically there's one pit stop, which can be the difference between winning and losing. Um, you have all these different scenarios playing out with weather with tire wear competition. And so, you know, we live by data. We didn't, uh, when, in, in Russia, when we, uh, could have, and it was because we got a bit emotionally caught up in the excitement of trying to win the race instead of staying disciplined and focused on, on data. And so it's a very data-driven sport when I'm on the pit wall, there's a thing called racer instinct, which is my 30 years in the sport. And, uh, your experience and your kind of your gut to make decisions. And every time our team makes a decision that I'm sitting there going, I'm not sure that was the right decision. They're staring at data. I'm not, I'm trusting my 30 years of experience. They'd beat me nine out of 10. >>Yeah. I mean, you know, this is a huge topic too, in the industry, explainable AI is one of the hottest trends in computer science where there's so much algorithms involved. The gut instinct is now coming back. What algorithms are available, knowing when to deploy what algorithms or what data to pay attention to is a huge new gut factor. Yep. Can you explain how the young drivers and the experience folks in the industry are dealing with this new instinct full data-driven? >>Yeah. That's, you know, that's what we have 50 people back at the factory doing, and they're looking at all sorts of information coming in, and then they're taking that information and they're feeding it to our head of strategy. Who's then feeding it to our racing director. Who's getting all these data points in from tire to performance, to reliability, and then the human data from both drivers coming through their engineers. And then he gets all that information in. He has to process it immediately and make decisions, but it's, it's a data-driven sport. >>I saw Lando walking around, got a selfie with them. It's great. Everyone's loving it on Twitter. My family, like get an autograph, the future of the sport. He's a young young driver. So that instincts coming in the future sport comes up all the time. The tires are a big discussion point, but also you've got a lot of presets going on, a lot of data, a lot of going on and you see the future where there's remote, you know, kind of video game you're in the pit wall and you can make decisions and deploy on behalf of the drivers. Is that something that >>Well, that technology is there and we used to do that, but now it's been outlawed because there's a real push to make sure the drivers are driving the car. So that technology is here. It has been deployed in the past. We could do it, but we're trying to find as a sport, the balance between, you know, letting the driver do it. So he, or she might make a mistake and a little bit of excitement to it. So, um, we now there are certain protocols on what we communicate. Um, we can't, um, everything has to be driver fed into the car. So we can now you'll hear all sorts of codes that we're talking through, which there are, um, about 300 different adjustments the driver can make on the steering wheel, which is unbelievable. And so that's us seeing information, getting data in coming to conclusions that we're giving him or her information that we think will help make the car >>A lot of new dimensions for drivers to think about when they're being successful with the gut, that the track data everything's kind of coming together. >>Yeah. It's amazing. Um, when you listen to these drivers on the radio, you forget that they're going 200 plus miles an hour. Cause they sound quite relaxed in this very, you know, open and easy communication of here's what I'm feeling with. Again, we're talking all these codes and then we all, because we can hear each other, there's a lot of trickery that goes on. So for a driver to be going to turn a miles an hour, taking this information and then know what code we're talking, are we kind of throwing a code out there to put the competition off is pretty amazing that they can take this all in. >>You know, I wish I was younger again, like we're old school and the younger generation, I was having a few conversations with a lot of the young audience. They wanted me to ask you, when are you guys going to metaverse the tracks? When can I get involved and participate and maybe even make the team, or how do I become more active, engaged with the McLaren racing team? >>And that technology is almost, we're actually, um, that's in development. So I, I think it won't be long before, you know, Sunday you can log on, uh, and, and race Lando around Monaco and be in the race. So that, that technology is around the corner. >>That's the shadow thing to developing. I see that. E-sports just quick. I know you've got to go on, but last minute we have here, e-sports, what's the future of e-sports with the team, >>But e-sports been great for the sport. You know, it's gone from, you know, when I was growing up, it was video games and now it's real simulation. And, uh, so we've held, I think we're going four years into it. Now we were the first team to really develop any sports platform and we've had competitors go on to help us with our simulation. So it's, it's real racially developed the race car before it goes on the racetrack it's in simulation. And that's where e-sports, >>And this is the new advantage. This is a new normal, this is where you guys see the data driving. The >>Definitely. And I think the other thing it is, you know, somewhat stick and ball sports, you can play in school. And motor racing has historically been partying, which can cost hundreds of thousands of dollars. Now with e-sports you have a less expensive platform to let young men and women around the world, but a steering wheel in their hand and go motor racing. So I think it's also going to kind of bring that younger generation of fan and >>There's so much collective intelligence, potentially competitive advantage data. Again, data coming up final word to end the segment, Splunk, big partner on the data side, obviously helping you guys financially, as well as you do need some sponsorship support to make the team run. Um, what's the relationship with Splunk? Take a minute to talk about the plug. >>It's been a, it's been great, you know, they're, they're two big contributors. We need a lot of money to run the racing team. So they're a great partner in that respect, but more importantly, they're helping us with our whole data journey, making smarter, quicker decisions. So their contribution to being part of the race team. And, uh, we used our technology. Um, it has been great. And I think, um, you know, if I look at our technology partners, uh, we have many that all contribute to making a >>Yeah. I mean, it really is nice. It's data inaction, it's teamwork, it's competitive, it's fun. That's kind of a good, good, >>I think fun is the center of everything that we do. It's the center of everything spunk does. Cause I think if you have fun, people enjoy going to working a little bit harder. We're seven days a week. And uh, you know, a lot of teammates you've got to work well together. So I think if you're having fun, you enjoy what you're doing and it doesn't feel like work. >>Congratulations on climbing up in the rankings and everything on your team. Two great drivers. Thanks for coming on the cube. We appreciate it. Thank you. All right. We're here. The key. We like to have fun here and get all the action on the tech side. Honestly, F1 is technology enabled data, driving the advantage and driving to is a great Netflix series. Check it out. McLaren's featured heavily in there and got a great team. Zach brown Siegel. Thanks for coming on. Appreciate it. I'm sure for your host. Thank you for watching.
SUMMARY :
So congratulations on all the success in that program and on, and then on the Thank you very much, it's been a, it's been a good run. take a minute to explain what you guys do. Uh, so McLaren racing, uh, which has a variety of, uh, racing teams, Are you happy with where things are, uh, and where do you see it going? So that's the pace of a development of a, how you guys pay attention to the details? as opposed to physically touching the car out of those thousand people, you probably only have about 60 or 70. So you get, you get race day and you got HR, and then you kind of get to the, the racing team. I know you're here in the U S for the U S grand Prix in Austin. of the year. how do you guys think about security? We have had a breach in the late nineties of our radio communications and, I mean, now you have all kinds of Um, but you know, that could decide, uh, a world championship and you have, you know, tens of millions of dollars online, You know, what's funny is that you guys have a lot of serious on the line stakes with these races, In the car show you got to do, we have to like a bunch Take us through where you guys see the advantages. uh, real, uh, react as quickly as is, you know, people like Splunk who can help us, experience folks in the industry are dealing with this new instinct full data-driven? of information coming in, and then they're taking that information and they're feeding it to our head of strategy. a lot of going on and you see the future where there's remote, you know, kind of video game you're in the pit wall and the balance between, you know, letting the driver do it. A lot of new dimensions for drivers to think about when they're being successful with the gut, that the track data everything's Um, when you listen to these drivers on the radio, you forget that they're going 200 plus When can I get involved and participate and maybe even make the team, or how do I become more active, So I, I think it won't be long before, you know, That's the shadow thing to developing. So it's, it's real racially developed the race car before it goes on the racetrack it's in simulation. This is a new normal, this is where you guys see the data driving. Now with e-sports you have a less expensive platform to let young to end the segment, Splunk, big partner on the data side, obviously helping you guys financially, And I think, um, you know, if I look at our technology partners, That's kind of a good, good, And uh, you know, a lot of teammates you've got to work well together. Honestly, F1 is technology enabled data, driving the advantage and driving to is
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HelloFresh v2
>>Hello. And we're here at the cube startup showcase made possible by a Ws. Thanks so much for joining us today. You know when Jim McDaid Ghani was formulating her ideas around data mesh, She wasn't the only one thinking about decentralized data architecture. Hello, Fresh was going into hyper growth mode and realized that in order to support its scale, it needed to rethink how it thought about data. Like many companies that started in the early part of last decade, Hello Fresh relied on a monolithic data architecture and the internal team. It had concerns about its ability to support continued innovation at high velocity. The company's data team began to think about the future and work backwards from a target architecture which possessed many principles of so called data mesh even though they didn't use that term. Specifically, the company is a strong example of an early but practical pioneer of data mission. Now there are many practitioners and stakeholders involved in evolving the company's data architecture, many of whom are listed here on this on the slide to are highlighted in red are joining us today, we're really excited to welcome into the cube Clements cheese, the Global Senior Director for Data at Hello Fresh and christoph Nevada who's the Global Senior Director of data also, of course. Hello Fresh folks. Welcome. Thanks so much for making some time today and sharing your story. >>Thank you very much. Hey >>steve. All right, let's start with Hello Fresh. You guys are number one in the world in your field, you deliver hundreds of millions of meals each year to many, many millions of people around the globe. You're scaling christoph. Tell us a little bit more about your company and its vision. >>Yeah. Should I start or Clements maybe maybe take over the first piece because Clements has actually been a longer trajectory yet have a fresh. >>Yeah go ahead. Climate change. I mean yes about approximately six years ago I joined handle fresh and I didn't think about the startup I was joining would eventually I. P. O. And just two years later and the freshman public and approximately three years and 10 months after. Hello fresh was listed on the German stock exchange which was just last week. Hello Fresh was included in the Ducks Germany's leading stock market index and debt to mind a great great milestone and I'm really looking forward and I'm very excited for the future for the future for head of fashion. All our data. Um the vision that we have is to become the world's leading food solution group and there's a lot of attractive opportunities. So recently we did lounge and expand Norway. This was in july and earlier this year we launched the U. S. Brand green >>chef in the U. K. As >>well. We're committed to launch continuously different geographies in the next coming years and have a strong pipe ahead of us with the acquisition of ready to eat companies like factor in the U. S. And the planned acquisition of you foods in Australia. We're diversifying our offer now reaching even more and more untapped customer segments and increase our total addressable market. So by offering customers and growing range of different alternatives to shop food and consumer meals. We are charging towards this vision and the school to become the world's leading integrated food solutions group. >>Love it. You guys are on a rocket ship, you're really transforming the industry and as you expand your tam it brings us to sort of the data as a as a core part of that strategy. So maybe you guys could talk a little bit about your journey as a company specifically as it relates to your data journey. You began as a start up. You had a basic architecture like everyone. You made extensive use of spreadsheets. You built a Hadoop based system that started to grow and when the company I. P. O. You really started to explode. So maybe describe that journey from a data perspective. >>Yes they saw Hello fresh by 2015 approximately had evolved what amount of classical centralized management set up. So we grew very organically over the years and there were a lot of very smart people around the globe. Really building the company and building our infrastructure. Um This also means that there were a small number of internal and external sources. Data sources and a centralized the I team with a number of people producing different reports, different dashboards and products for our executives for example of our different operations teams, christian company's performance and knowledge was transferred um just via talking to each other face to face conversations and the people in the data where's team were considered as the data wizard or as the E. T. L. Wizard. Very classical challenges. And those et al. Reserves indicated the kind of like a silent knowledge of data management. Right? Um so a central data whereas team then was responsible for different type of verticals and different domains, different geographies and all this setup gave us to the beginning the flexibility to grow fast as a company in 2015 >>christoph anything that might add to that. >>Yes. Um Not expected to that one but as as clement says it right, this was kind of set up that actually work for us quite a while. And then in 2017 when L. A. Freshman public, the company also grew rapidly and just to give you an idea how that looked like. As was that the tech department self actually increased from about 40 people to almost 300 engineers And the same way as a business units as Clemens has described, also grew sustainable, sustainably. So we continue to launch hello fresh and new countries launching brands like every plate and also acquired other brands like much of a factor and with that grows also from a data perspective the number of data requests that centrally we're getting become more and more and more and also more and more complex. So that for the team meant that they had a fairly high mental load. So they had to achieve a very or basically get a very deep understanding about the business. And also suffered a lot from this context switching back and forth, essentially there to prioritize across our product request from our physical product, digital product from the physical from sorry, from the marketing perspective and also from the central reporting uh teams. And in a nutshell this was very hard for these people. And this that also to a situation that, let's say the solution that we have became not really optimal. So in a nutshell, the central function became a bottleneck and slowdown of all the innovation of the company. >>It's a classic case, isn't it? I mean Clements, you see you see the central team becomes a bottleneck and so the lines of business, the marketing team salesman's okay, we're going to take things into our own hands. And then of course I I. T. And the technical team is called in later to clean up the mess. Uh maybe, I mean was that maybe I'm overstating it, but that's a common situation, isn't it? >>Yeah. Uh This is what exactly happened. Right. So um we had a bottleneck, we have the central teams, there was always a little of tension um analytics teams then started in this business domains like marketing, trade chain, finance, HR and so on. Started really to build their own data solutions at some point you have to get the ball rolling right and then continue the trajectory um which means then that the data pipelines didn't meet the engineering standards. And um there was an increased need for maintenance and support from central teams. Hence over time the knowledge about those pipelines and how to maintain a particular uh infrastructure for example left the company such that most of those data assets and data sets are turned into a huge step with decreasing data quality um also decrease the lack of trust, decreasing transparency. And this was increasing challenge where majority of time was spent in meeting rooms to align on on data quality for example. >>Yeah. And and the point you were making christoph about context switching and this is this is a point that Jemaah makes quite often is we've we've we've contextualized are operational systems like our sales systems, our marketing system but not our our data system. So you're asking the data team, Okay. Be an expert in sales, be an expert in marketing, be an expert in logistics, be an expert in supply chain and it start stop, start, stop, it's a paper cut environment and it's just not as productive. But but on the flip side of that is when you think about a centralized organization you think, hey this is going to be a very efficient way, a cross functional team to support the organization but it's not necessarily the highest velocity, most effective organizational structure. >>Yeah, so so I agree with that. Is that up to a certain scale, a centralized function has a lot of advantages, right? That's clear for everyone which would go to some kind of expert team. However, if you see that you actually would like to accelerate that and specific and this hyper growth, right, you wanna actually have autonomy and certain teams and move the teams or let's say the data to the experts in these teams and this, as you have mentioned, right, that increases mental load and you can either internally start splitting your team into a different kind of sub teams focusing on different areas. However, that is then again, just adding another peace where actually collaboration needs to happen busy external sees, so why not bridging that gap immediately and actually move these teams and to end into into the function themselves. So maybe just to continue what, what was Clements was saying and this is actually where over. So Clements, my journey started to become one joint journey. So Clements was coming actually from one of these teams to build their own solutions. I was basically having the platform team called database housed in these days and in 2019 where basically the situation become more and more serious, I would say so more and more people have recognized that this model doesn't really scale In 2019, basically the leadership of the company came together and I identified data as a key strategic asset and what we mean by that, that if we leverage data in a proper way, it gives us a unique competitive advantage which could help us to, to support and actually fully automated our decision making process across the entire value chain. So what we're, what we're trying to do now or what we should be aiming for is that Hello, Fresh is able to build data products that have a purpose. We're moving away from the idea. Data is just a by problem products, we have a purpose why we would like to collect this data. There's a clear business need behind that. And because it's so important to for the company as a business, we also want to provide them as a trust versi asset to the rest of the organization. We say there's the best customer experience, but at least in a way that users can easily discover, understand and security access high quality data. >>Yeah, so and and and Clements, when you c J Maxx writing, you see, you know, she has the four pillars and and the principles as practitioners you look at that say, okay, hey, that's pretty good thinking and then now we have to apply it and that's and that's where the devil meets the details. So it's the four, you know, the decentralized data ownership data as a product, which we'll talk about a little bit self serve, which you guys have spent a lot of time on inclement your wheelhouse which is which is governance and a Federated governance model. And it's almost like if you if you achieve the first two then you have to solve for the second to it almost creates a new challenges but maybe you could talk about that a little bit as to how it relates to Hello fresh. >>Yes. So christophe mentioned that we identified economic challenge beforehand and for how can we actually decentralized and actually empower the different colleagues of ours. This was more a we realized that it was more an organizational or a cultural change and this is something that somebody also mentioned I think thought words mentioned one of the white papers, it's more of a organizational or cultural impact and we kicked off a um faced reorganization or different phases we're currently and um in the middle of still but we kicked off different phases of organizational reconstruct oring reorganization, try unlock this data at scale. And the idea was really moving away from um ever growing complex matrix organizations or matrix setups and split between two different things. One is the value creation. So basically when people ask the question, what can we actually do, what shall we do? This is value creation and how, which is capability building and both are equal in authority. This actually then creates a high urge and collaboration and this collaboration breaks up the different silos that were built and of course this also includes different needs of stuffing forward teams stuffing with more, let's say data scientists or data engineers, data professionals into those business domains and hence also more capability building. Um Okay, >>go ahead. Sorry. >>So back to Tzemach did johnny. So we the idea also Then crossed over when she published her papers in May 2019 and we thought well The four colors that she described um we're around decentralized data ownership, product data as a product mindset, we have a self service infrastructure and as you mentioned, Federated confidential governance. And this suited very much with our thinking at that point of time to reorganize the different teams and this then leads to a not only organisational restructure but also in completely new approach of how we need to manage data, show data. >>Got it. Okay, so your business is is exploding. Your data team will have to become domain experts in too many areas, constantly contact switching as we said, people started to take things into their own hands. So again we said classic story but but you didn't let it get out of control and that's important. So we actually have a picture of kind of where you're going today and it's evolved into this Pat, if you could bring up the picture with the the elephant here we go. So I would talk a little bit about the architecture, doesn't show it here, the spreadsheet era but christoph maybe you can talk about that. It does show the Hadoop monolith which exists today. I think that's in a managed managed hosting service, but but you you preserve that piece of it, but if I understand it correctly, everything is evolving to the cloud, I think you're running a lot of this or all of it in A W. S. Uh you've got everybody's got their own data sources, uh you've got a data hub which I think is enabled by a master catalog for discovery and all this underlying technical infrastructure. That is really not the focus of this conversation today. But the key here, if I understand it correctly is these domains are autonomous and not only that this required technical thinking, but really supportive organizational mindset, which we're gonna talk about today. But christoph maybe you could address, you know, at a high level some of the architectural evolution that you guys went through. >>Yeah, sure. Yeah, maybe it's also a good summary about the entire history. So as you have mentioned, right, we started in the very beginning with the model is on the operation of playing right? Actually, it wasn't just one model is both to one for the back end and one for the for the front and and or analytical plane was essentially a couple of spreadsheets and I think there's nothing wrong with spreadsheets, right, allows you to store information, it allows you to transform data allows you to share this information. It allows you to visualize this data, but all the kind of that's not actually separating concern right? Everything in one tool. And this means that obviously not scalable, right? You reach the point where this kind of management set up in or data management of isn't one tool reached elements. So what we have started is we've created our data lake as we have seen here on Youtube. And this at the very beginning actually reflected very much our operational populace on top of that. We used impala is a data warehouse, but there was not really a distinction between borders, our data warehouse and borders our data like the impala was used as a kind of those as the kind of engine to create a warehouse and data like construct itself and this organic growth actually led to a situation as I think it's it's clear now that we had to centralized model is for all the domains that will really lose kimball modeling standards. There was no uniformity used actually build in house uh ways of building materialized use abuse that we have used for the presentation layer, there was a lot of duplication of effort and in the end essentially they were missing feedbacks, food, which helped us to to improve of what we are filled. So in the end, in the natural, as we have said, the lack of trust and that's basically what the starting point for us to understand. Okay, how can we move away and there are a lot of different things that you can discuss of apart from this organizational structure that we have said, okay, we have these three or four pillars from from Denmark. However, there's also the next extra question around how do we implement our talking about actual right, what are the implications on that level? And I think that is there's something that we are that we are currently still in progress. >>Got it. Okay, so I wonder if we could talk about switch gears a little bit and talk about the organizational and cultural challenges that you faced. What were those conversations like? Uh let's dig into that a little bit. I want to get into governance as well. >>The conversations on the cultural change. I mean yes, we went through a hyper growth for the last year since obviously there were a lot of new joiners, a lot of different, very, very smart people joining the company which then results that collaboration uh >>got a bit more difficult. Of course >>there are times and changes, you have different different artifacts that you were created um and documentation that were flying around. Um so we were we had to build the company from scratch right? Um Of course this then resulted always this tension which I described before, but the most important part here is that data has always been a very important factor at l a fresh and we collected >>more of this >>data and continued to improve use data to improve the different key areas of our business. >>Um even >>when organizational struggles, the central organizational struggles data somehow always helped us to go through this this kind of change. Right? Um in the end those decentralized teams in our local geography ease started with solutions that serve the business which was very very important otherwise wouldn't be at the place where we are today but they did by all late best practices and standards and I always used sport analogy Dave So like any sport, there are different rules and regulations that need to be followed. These rules are defined by calling the sports association and this is what you can think about data governance and compliance team. Now we add the players to it who need to follow those rules and bite by them. This is what we then called data management. Now we have the different players and professionals, they need to be trained and understand the strategy and it rules before they can play. And this is what I then called data literacy. So we realized that we need to focus on helping our teams to develop those capabilities and teach the standards for how work is being done to truly drive functional excellence in a different domains. And one of our mission of our data literacy program for example is to really empower >>every employee at hello >>fresh everyone to make the right data informs decisions by providing data education that scaled by royal Entry team. Then this can be different things, different things like including data capabilities, um, with the learning paths for example. Right? So help them to create and deploy data products connecting data producers and data consumers and create a common sense and more understanding of each other's dependencies, which is important, for example, S. S. L. O. State of contracts and etcetera. Um, people getting more of a sense of ownership and responsibility. Of course, we have to define what it means, what does ownership means? But the responsibility means. But we're teaching this to our colleagues via individual learning patterns and help them up skill to use. Also, there's shared infrastructure and those self self service applications and overall to summarize, we're still in this progress of of, of learning, we are still learning as well. So learning never stops the tele fish, but we are really trying this um, to make it as much fun as possible. And in the end we all know user behavior has changed through positive experience. Uh, so instead of having massive training programs over endless courses of workshops, um, leaving our new journalists and colleagues confused and overwhelmed. >>We're applying um, >>game ification, right? So split different levels of certification where our colleagues can access, have had access points, they can earn badges along the way, which then simplifies the process of learning and engagement of the users and this is what we see in surveys, for example, where our employees that your justification approach a lot and are even competing to collect Those learning path batteries to become the # one on the leader board. >>I love the game ification, we've seen it work so well and so many different industries, not the least of which is crypto so you've identified some of the process gaps uh that you, you saw it is gloss over them. Sometimes I say paved the cow path. You didn't try to force, in other words, a new architecture into the legacy processes. You really have to rethink your approach to data management. So what what did that entail? >>Um, to rethink the way of data management. 100%. So if I take the example of Revolution, Industrial Revolution or classical supply chain revolution, but just imagine that you have been riding a horse, for example, your whole life and suddenly you can operate a car or you suddenly receive just a complete new way of transporting assets from A to B. Um, so we needed to establish a new set of cross functional business processes to run faster, dry faster, um, more robustly and deliver data products which can be trusted and used by downstream processes and systems. Hence we had a subset of new standards and new procedures that would fall into the internal data governance and compliance sector with internal, I'm always referring to the data operations around new things like data catalog, how to identify >>ownership, >>how to change ownership, how to certify data assets, everything around classical software development, which we know apply to data. This this is similar to a new thinking, right? Um deployment, versioning, QA all the different things, ingestion policies, policing procedures, all the things that suffer. Development has been doing. We do it now with data as well. And in simple terms, it's a whole redesign of the supply chain of our data with new procedures and new processes and as a creation as management and as a consumption. >>So data has become kind of the new development kit. If you will um I want to shift gears and talk about the notion of data product and, and we have a slide uh that we pulled from your deck and I'd like to unpack it a little bit. Uh I'll just, if you can bring that up, I'll read it. A data product is a product whose primary objective is to leverage on data to solve customer problems where customers, both internal and external. So pretty straightforward. I know you've gone much deeper and you're thinking and into your organization, but how do you think about that And how do you determine for instance who owns what? How did you get everybody to agree? >>I can take that one. Um, maybe let me start with the data product. So I think um that's an ongoing debate. Right? And I think the debate itself is an important piece here, right? That visit the debate, you clarify what we actually mean by that product and what is actually the mindset. So I think just from a definition perspective, right? I think we find the common denominator that we say okay that our product is something which is important for the company has come to its value what you mean by that. Okay, it's it's a solution to a customer problem that delivers ideally maximum value to the business. And yes, it leverages the power of data and we have a couple of examples but it had a fresh year, the historical and classical ones around dashboards for example, to monitor or error rates but also more sophisticated ways for example to incorporate machine learning algorithms in our recipe recommendations. However, I think the important aspects of the data product is a there is an owner, right? There's someone accountable for making sure that the product that we are providing is actually served and is maintained and there are, there is someone who is making sure that this actually keeps the value of that problem thing combined with the idea of the proper documentation, like a product description, right that people understand how to use their bodies is about and related to that peace is the idea of it is a purpose. Right? You need to understand or ask ourselves, Okay, why does this thing exist does it provide the value that you think it does. That leads into a good understanding about the life cycle of the data product and life cycle what we mean? Okay from the beginning from the creation you need to have a good understanding, we need to collect feedback, we need to learn about that. We need to rework and actually finally also to think about okay benefits time to decommission piece. So overall, I think the core of the data product is product thinking 11 right that we start the point is the starting point needs to be the problem and not the solution and this is essentially what we have seen what was missing but brought us to this kind of data spaghetti that we have built there in in Russia, essentially we built at certain data assets, develop in isolation and continuously patch the solution just to fulfill these articles that we got and actually these aren't really understanding of the stakeholder needs and the interesting piece as a result in duplication of work and this is not just frustrating and probably not the most efficient way how the company should work. But also if I build the same that assets but slightly different assumption across the company and multiple teams that leads to data inconsistency and imagine the following too narrow you as a management for management perspective, you're asking basically a specific question and you get essentially from a couple of different teams, different kind of grass, different kind of data and numbers and in the end you do not know which ones to trust. So there's actually much more ambiguity and you do not know actually is a noise for times of observing or is it just actually is there actually a signal that I'm looking for? And the same is if I'm running in a B test right, I have a new future, I would like to understand what has it been the business impact of this feature. I run that specific source in an unfortunate scenario. Your production system is actually running on a different source. You see different numbers. What you've seen in a B test is actually not what you see then in production typical thing then is you're asking some analytics tend to actually do a deep dive to understand where the discrepancies are coming from. The worst case scenario. Again, there's a different kind of source. So in the end it's a pretty frustrating scenario and that's actually based of time of people that have to identify the root cause of this divergence. So in a nutshell, the highest degree of consistency is actually achieved that people are just reusing Dallas assets and also in the media talk that we have given right, we we start trying to establish this approach for a B testing. So we have a team but just providing or is kind of owning their target metric associated business teams and they're providing that as a product also to other services including the A B testing team, they'll be testing team can use this information defines an interface is okay I'm joining this information that the metadata of an experiment and in the end after the assignment after this data collection face, they can easily add a graph to the dashboard. Just group by the >>Beatles Hungarian. >>And we have seen that also in other companies. So it's not just a nice dream that we have right. I have actually worked in other companies where we worked on search and we established a complete KPI pipeline that was computing all this information. And this information was hosted by the team and it was used for everything A B test and deep dives and and regular reporting. So uh just one of the second the important piece now, why I'm coming back to that is that requires that we are treating this data as a product right? If you want to have multiple people using the things that I am owning and building, we have to provide this as a trust mercy asset and in a way that it's easy for people to discover and actually work with. >>Yeah. And coming back to that. So this is to me this is why I get so excited about data mesh because I really do think it's the right direction for organizations. When people hear data product they say well, what does that mean? Uh but then when you start to sort of define it as you did, it's it's using data to add value, that could be cutting costs, that could be generating revenue, it could be actually directly you're creating a product that you monetize, So it's sort of in the eyes of the beholder. But I think the other point that we've made is you made it earlier on to and again, context. So when you have a centralized data team and you have all these P NL managers a lot of times they'll question the data because they don't own it. They're like wait a minute. If they don't, if it doesn't agree with their agenda, they'll attack the data. But if they own the data then they're responsible for defending that and that is a mindset change, that's really important. Um And I'm curious uh is how you got to, you know, that ownership? Was it a was it a top down with somebody providing leadership? Was it more organic bottom up? Was it a sort of a combination? How do you decide who owned what in other words, you know, did you get, how did you get the business to take ownership of the data and what is owning? You know, the data actually mean? >>That's a very good question. Dave I think this is one of the pieces where I think we have a lot of learnings and basically if you ask me how we could start the feeling. I think that would be the first piece. Maybe we need to start to really think about how that should be approached if it stopped his ownership. Right? It means somehow that the team has a responsibility to host and self the data efforts to minimum acceptable standards. This minimum dependencies up and down string. The interesting piece has been looking backwards. What what's happening is that under that definition has actually process that we have to go through is not actually transferring ownership from the central team to the distributor teams. But actually most cases to establish ownership, I make this difference because saying we have to transfer ownership actually would erroneously suggests that the data set was owned before. But this platform team, yes, they had the capability to make the changes on data pipelines, but actually the analytics team, they're always the ones who had the business understands, you use cases and but no one actually, but it's actually expensive expected. So we had to go through this very lengthy process and establishing ownership. We have done that, as in the beginning, very naively. They have started, here's a document here, all the data assets, what is probably the nearest neighbor who can actually take care of that and then we we moved it over. But the problem here is that all these things is kind of technical debt, right? It's not really properly documented, pretty unstable. It was built in a very inconsistent over years and these people who have built this thing have already left the company. So there's actually not a nice thing that is that you want to see and people build up a certain resistance, e even if they have actually bought into this idea of domain ownership. So if you ask me these learnings, but what needs to happen as first, the company needs to really understand what our core business concept that they have, they need to have this mapping from. These are the core business concept that we have. These are the domain teams who are owning this concept and then actually link that to the to the assets and integrated better with both understanding how we can evolve actually, the data assets and new data build things new in the in this piece in the domain. But also how can we address reduction of technical death and stabilizing what we have already. >>Thank you for that christoph. So I want to turn a direction here and talk about governance and I know that's an area that's passionate, you're passionate about. Uh I pulled this slide from your deck, which I kind of messed up a little bit sorry for that, but but by the way, we're going to publish a link to the full video that you guys did. So we'll share that with folks. But it's one of the most challenging aspects of data mesh, if you're going to decentralize you, you quickly realize this could be the Wild West as we talked about all over again. So how are you approaching governance? There's a lot of items on this slide that are, you know, underscore the complexity, whether it's privacy, compliance etcetera. So, so how did you approach this? >>It's yeah, it's about connecting those dots. Right. So the aim of the data governance program is about the autonomy of every team was still ensuring that everybody has the right interoperability. So when we want to move from the Wild West riding horses to a civilised way of transport, um you can take the example of modern street traffic, like when all participants can manoeuvre independently and as long as they follow the same rules and standards, everybody can remain compatible with each other and understand and learn from each other so we can avoid car crashes. So when I go from country to country, I do understand what the street infrastructure means. How do I drive my car? I can also read the traffic lights in the different signals. Um, so likewise as a business and Hello Fresh, we do operate autonomously and consequently need to follow those external and internal rules and standards to set forth by the redistribution in which we operate so in order to prevent a car crash, we need to at least ensure compliance with regulations to account for society's and our customers increasing concern with data protection and privacy. So teaching and advocating this advantage, realizing this to everyone in the company um was a key community communication strategy and of course, I mean I mentioned data privacy external factors, the same goes for internal regulations and processes to help our colleagues to adapt to this very new environment. So when I mentioned before the new way of thinking the new way of um dealing and managing data, this of course implies that we need new processes and regulations for our colleagues as well. Um in a nutshell then this means the data governance provides a framework for managing our people the processes and technology and culture around our data traffic. And those components must come together in order to have this effective program providing at least a common denominator, especially critical for shared dataset, which we have across our different geographies managed and shared applications on shared infrastructure and applications and is then consumed by centralized processes um for example, master data, everything and all the metrics and KPI s which are also used for a central steering. Um it's a big change day. Right. And our ultimate goal is to have this noninvasive, Federated um ultimatum and computational governance and for that we can't just talk about it. We actually have to go deep and use case by use case and Qc buy PVC and generate learnings and learnings with the different teams. And this would be a classical approach of identifying the target structure, the target status, match it with the current status by identifying together with the business teams with the different domains have a risk assessment for example, to increase transparency because a lot of teams, they might not even know what kind of situation they might be. And this is where this training and this piece of illiteracy comes into place where we go in and trade based on the findings based on the most valuable use case um and based on that help our teams to do this change to increase um their capability just a little bit more and once they hand holding. But a lot of guidance >>can I kind of kind of trying to quickly David will allow me I mean there's there's a lot of governance piece but I think um that is important. And if you're talking about documentation for example, yes, we can go from team to team and tell these people how you have to document your data and data catalog or you have to establish data contracts and so on the force. But if you would like to build data products at scale following actual governance, we need to think about automation right. We need to think about a lot of things that we can learn from engineering before. And that starts with simple things like if we would like to build up trust in our data products, right, and actually want to apply the same rigor and the best practices that we know from engineering. There are things that we can do and we should probably think about what we can copy and one example might be. So the level of service level agreements, service level objectives. So that level indicators right, that represent on on an engineering level, right? If we're providing services there representing the promises we made to our customers or consumers, these are the internal objectives that help us to keep those promises. And actually these are the way of how we are tracking ourselves, how we are doing. And this is just one example of that thing. The Federated Governor governance comes into play right. In an ideal world, we should not just talk about data as a product but also data product. That's code that we say, okay, as most as much as possible. Right? Give the engineers the tool that they are familiar basis and actually not ask the product managers for example to document their data assets in the data catalog but make it part of the configuration. Have this as a, as a C D C I, a continuous delivery pipeline as we typically see another engineering task through and services we say, okay, there is configuration, we can think about pr I can think about data quality monitoring, we can think about um the ingestion data catalog and so on and forest, I think ideally in the data product will become of a certain templates that can be deployed and are actually rejected or verified at build time before we actually make them deploy them to production. >>Yeah, So it's like devoPS for data product um so I'm envisioning almost a three phase approach to governance and you kind of, it sounds like you're in early phases called phase zero where there's there's learning, there's literacy, there's training, education, there's kind of self governance and then there's some kind of oversight, some a lot of manual stuff going on and then you you're trying to process builders at this phase and then you codify it and then you can automate it. Is that fair? >>Yeah, I would rather think think about automation as early as possible in the way and yes, there needs to be certain rules but then actually start actually use case by use case. Is there anything that small piece that we can already automate? It's as possible. Roll that out and then actually extended step by step, >>is there a role though that adjudicates that? Is there a central Chief state officer who is responsible for making sure people are complying or is it how do you handle that? >>I mean from a from a from a platform perspective, yes, we have a centralized team to uh implement certain pieces they'll be saying are important and actually would like to implement. However, that is actually working very closely with the governance department. So it's Clements piece to understand and defy the policies that needs to be implemented. >>So Clements essentially it's it's your responsibility to make sure that the policy is being followed. And then as you were saying, christoph trying to compress the time to automation as fast as possible percent. >>So >>it's really it's uh >>what needs to be really clear that it's always a split effort, Right? So you can't just do one thing or the other thing, but everything really goes hand in hand because for the right automation for the right engineering tooling, we need to have the transparency first. Uh I mean code needs to be coded so we kind of need to operate on the same level with the right understanding. So there's actually two things that are important which is one its policies and guidelines, but not only that because more importantly or even well equally important to align with the end user and tech teams and engineering and really bridge between business value business teams and the engineering teams. >>Got it. So just a couple more questions because we gotta wrap I want to talk a little bit about the business outcome. I know it's hard to quantify and I'll talk about that in a moment but but major learnings, we've got some of the challenges that you cited. I'll just put them up here. We don't have to go detailed into this, but I just wanted to share with some folks. But my question, I mean this is the advice for your peers question if you had to do it differently if you had a do over or a Mulligan as we like to say for you golfers, what would you do differently? Yeah, >>I mean can we start with from a from the transformational challenge that understanding that it's also high load of cultural change. I think this is this is important that a particular communication strategy needs to be put into place and people really need to be um supported. Right? So it's not that we go in and say well we have to change towards data mesh but naturally it's in human nature, you know, we're kind of resistance to to change right? Her speech uncomfortable. So we need to take that away by training and by communicating um chris we're gonna add something to that >>and definitely I think the point that I have also made before right we need to acknowledge that data mesh is an architecture of scale, right? You're looking for something which is necessary by huge companies who are vulnerable, data productive scale. I mean Dave you mentioned it right, there are a lot of advantages to have a centralized team but at some point it may make sense to actually decentralized here and at this point right? If you think about data Mash, you have to recognize that you're not building something on a green field. And I think there's a big learning which is also reflected here on the slide is don't underestimate your baggage. It's typically you come to a point where the old model doesn't doesn't broke anymore and has had a fresh right? We lost our trust in our data and actually we have seen certain risks that we're slowing down our innovation so we triggered that this was triggering the need to actually change something. So this transition implies that you typically have a lot of technical debt accumulated over years and I think what we have learned is that potentially we have decentralized some assets to earlier, this is not actually taking into account the maturity of the team where we are actually distributed to and now we actually in the face of correcting pieces of that one. Right? But I think if you if you if you start from scratch you have to understand, okay, is are my team is actually ready for taking on this new uh, this news capabilities and you have to make sure that business decentralization, you build up these >>capabilities and the >>teams and as Clements has mentioned, right, make sure that you take the people on your journey. I think these are the pieces that also here, it comes with this knowledge gap, right? That we need to think about hiring and literacy the technical depth I just talked about and I think the last piece that I would add now which is not here on the flight deck is also from our perspective, we started on the analytical layer because that's kind of where things are exploding, right, this is the thing that people feel the pain but I think a lot of the efforts that we have started to actually modernize the current state uh, towards data product towards data Mash. We've understood that it always comes down basically to a proper shape of our operational plane and I think what needs to happen is is I think we got through a lot of pains but the learning here is this need to really be a commitment from the company that needs to happen and to act. >>I think that point that last point you made it so critical because I I hear a lot from the vendor community about how they're gonna make analytics better and that's that's not unimportant, but but through data product thinking and decentralized data organizations really have to operationalize in order to scale. So these decisions around data architecture an organization, their fundamental and lasting, it's not necessarily about an individual project are why they're gonna be project sub projects within this architecture. But the architectural decision itself is an organizational, its cultural and what's the best approach to support your business at scale. It really speaks to to to what you are, who you are as a company, how you operate and getting that right, as we've seen in the success of data driven driven companies is yields tremendous results. So I'll ask each of you to give give us your final thoughts and then we'll wrap maybe >>maybe it quickly, please. Yeah, maybe just just jumping on this piece that you have mentioned, right, the target architecture. If we talk about these pieces right, people often have this picture of mind like OK, there are different kind of stages, we have sources, we have actually ingestion layer, we have historical transformation presentation layer and then we're basically putting a lot of technology on top of that kind of our target architecture. However, I think what we really need to make sure is that we have these different kind of viewers, right? We need to understand what are actually the capabilities that we need in our new goals. How does it look and feel from the different kind of personas and experience view? And then finally, that should actually go to the to the target architecture from a technical perspective um maybe just to give an outlook but what we're what we're planning to do, how we want to move that forward. We have actually based on our strategy in the in the sense of we would like to increase that to maturity as a whole across the entire company and this is kind of a framework around the business strategy and it's breaking down into four pillars as well. People meaning the data, cultural, data literacy, data organizational structure and so on that. We're talking about governance as Clements has actually mentioned that, right, compliance, governance, data management and so on. You talk about technology and I think we could talk for hours for that one. It's around data platform, better science platform and then finally also about enablement through data, meaning we need to understand that a quality data accessibility and the science and data monetization. >>Great, thank you christophe clement. Once you bring us home give us your final thoughts. >>Can't can just agree with christoph that uh important is to understand what kind of maturity people have to understand what the maturity level, where the company where where people organization is and really understand what does kind of some kind of a change replies to that those four pillars for example, um what needs to be taken first and this is not very clear from the very first beginning of course them it's kind of like Greenfield you come up with must wins to come up with things that we really want to do out of theory and out of different white papers. Um only if you really start conducting the first initiatives you do understand. Okay, where we have to put the starts together and where do I missed out on one of those four different pillars? People, process technology and governance. Right? And then that kind of an integration. Doing step by step, small steps by small steps not boiling the ocean where you're capable ready to identify the gaps and see where either you can fill um the gaps are where you have to increase maturity first and train people or increase your text text, >>you know Hello Fresh is an excellent example of a company that is innovating. It was not born in Silicon Valley which I love. It's a global company. Uh and I gotta ask you guys, it seems like this is an amazing place to work you guys hiring? >>Yes, >>definitely. We do >>uh as many rights as was one of these aspects distributing. And actually we are hiring as an entire company specifically for data. I think there are a lot of open roles serious. Please visit or our page from better engineering, data, product management and Clemens has a lot of rules that you can speak about. But yes >>guys, thanks so much for sharing with the cube audience, your, your pioneers and we look forward to collaborations in the future to track progress and really want to thank you for your time. >>Thank you very much. Thank you very much. Dave >>thank you for watching the cubes startup showcase made possible by A W. S. This is Dave Volonte. We'll see you next time. >>Yeah.
SUMMARY :
and realized that in order to support its scale, it needed to rethink how it thought Thank you very much. You guys are number one in the world in your field, Clements has actually been a longer trajectory yet have a fresh. So recently we did lounge and expand Norway. ready to eat companies like factor in the U. S. And the planned acquisition of you foods in Australia. So maybe you guys could talk a little bit about your journey as a company specifically as So we grew very organically So that for the team becomes a bottleneck and so the lines of business, the marketing team salesman's okay, we're going to take things into our own Started really to build their own data solutions at some point you have to get the ball rolling But but on the flip side of that is when you think about a centralized organization say the data to the experts in these teams and this, as you have mentioned, right, that increases mental load look at that say, okay, hey, that's pretty good thinking and then now we have to apply it and that's And the idea was really moving away from um ever growing complex go ahead. we have a self service infrastructure and as you mentioned, the spreadsheet era but christoph maybe you can talk about that. So in the end, in the natural, as we have said, the lack of trust and that's and cultural challenges that you faced. The conversations on the cultural change. got a bit more difficult. there are times and changes, you have different different artifacts that you were created These rules are defined by calling the sports association and this is what you can think about So learning never stops the tele fish, but we are really trying this and this is what we see in surveys, for example, where our employees that your justification not the least of which is crypto so you've identified some of the process gaps uh So if I take the example of This this is similar to a new thinking, right? gears and talk about the notion of data product and, and we have a slide uh that we There's someone accountable for making sure that the product that we are providing is actually So it's not just a nice dream that we have right. So this is to me this is why I get so excited about data mesh because I really do the company needs to really understand what our core business concept that they have, they need to have this mapping from. to the full video that you guys did. in order to prevent a car crash, we need to at least ensure the promises we made to our customers or consumers, these are the internal objectives that help us to keep a three phase approach to governance and you kind of, it sounds like you're in early phases called phase zero where Is there anything that small piece that we can already automate? and defy the policies that needs to be implemented. that the policy is being followed. so we kind of need to operate on the same level with the right understanding. or a Mulligan as we like to say for you golfers, what would you do differently? So it's not that we go in and say So this transition implies that you typically have a lot of the company that needs to happen and to act. It really speaks to to to what you are, who you are as a company, how you operate and in the in the sense of we would like to increase that to maturity as a whole across the entire company and this is kind Once you bring us home give us your final thoughts. and see where either you can fill um the gaps are where you Uh and I gotta ask you guys, it seems like this is an amazing place to work you guys hiring? We do you can speak about. really want to thank you for your time. Thank you very much. thank you for watching the cubes startup showcase made possible by A W. S.
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MANUFACTURING V1b | CLOUDERA
>>Welcome to our industry. Drill-downs from manufacturing. I'm here with Michael Gerber, who is the managing director for automotive and manufacturing solutions at cloud era. And in this first session, we're going to discuss how to drive transportation efficiencies and improve sustainability with data connected trucks are fundamental to optimizing fleet performance costs and delivering new services to fleet operators. And what's going to happen here is Michael's going to present some data and information, and we're gonna come back and have a little conversation about what we just heard. Michael, great to see you over to you. >>Oh, thank you, Dave. And I appreciate having this conversation today. Hey, um, you know, this is actually an area connected trucks. You know, this is an area that we have seen a lot of action here at Cloudera. And I think the reason is kind of important, right? Because, you know, first of all, you can see that, you know, this change is happening very, very quickly, right? 150% growth is forecast by 2022. Um, and the reasons, and I think this is why we're seeing a lot of action and a lot of growth is that there are a lot of benefits, right? We're talking about a B2B type of situation here. So this is truck made truck makers providing benefits to fleet operators. And if you look at the F the top fleet operator, uh, the top benefits that fleet operators expect, you see this in the graph over here. >>Now almost 80% of them expect improved productivity, things like improved routing rates. So route efficiencies and improve customer service decrease in fuel consumption, but better technology. This isn't technology for technology sake, these connected trucks are coming onto the marketplace because Hey, it can provide for Mendez value to the business. And in this case, we're talking about fleet operators and fleet efficiencies. So, you know, one of the things that's really important to be able to enable this right, um, trucks are becoming connected because at the end of the day, um, we want to be able to provide fleet deficiencies through connected truck, um, analytics and machine learning. Let me explain to you a little bit about what we mean by that, because what, you know, how this happens is by creating a connected vehicle analytics machine learning life cycle, and to do that, you need to do a few different things, right? >>You start off of course, with connected trucks in the field. And, you know, you can have many of these trucks cause typically you're dealing at a truck level and at a fleet level, right? You want to be able to do analytics and machine learning to improve performance. So you start off with these trucks. And the first you need to be able to do is connect to those products, right? You have to have an intelligent edge where you can collect that information from the trucks. And by the way, once you conducted the, um, this information from the trucks, you want to be able to analyze that data in real-time and take real-time actions. Now what I'm going to show you the ability to take this real-time action is actually the result of your machine learning license. Let me explain to you what I mean by that. >>So we have this trucks, we start to collect data from it right at the end of the day. Well we'd like to be able to do is pull that data into either your data center or into the cloud where we can start to do more advanced analytics. And we start with being able to ingest that data into the cloud, into that enterprise data lake. We store that data. We want to enrich it with other data sources. So for example, if you're doing truck predictive maintenance, you want to take that sensor data that you've connected collected from those trucks. And you want to augment that with your dealership, say service information. Now you have, you know, you have sensor data and there was salting repair orders. You're now equipped to do things like predict one day maintenance will work correctly for all the data sets that you need to be able to do that. >>So what do you do here? Like I said, you adjusted your storage, you're enriching it with data, right? You're processing that data. You're aligning say the sensor data to that transactional system data from your, uh, from your, your pair maintenance systems, you know, you're bringing it together so that you can do two things you can do. First of all, you could do self-service BI on that date, right? You can do things like fleet analytics, but more importantly, what I was talking to you about before is you now have the data sets to be able to do create machine learning models. So if you have the sensor right values and the need, for example, for, for a dealership repair, or as you could start to correlate, which sensor values predicted the need for maintenance, and you could build out those machine learning models. And then as I mentioned to you, you could push those machine learning models back out to the edge, which is how you would then take those real-time action. >>I mentioned earlier as that data that then comes through in real-time, you're running it against that model, and you can take some real time actions. This is what we are, this, this, this, this analytics and machine learning model, um, machine learning life cycle is exactly what Cloudera enables this end-to-end ability to ingest, um, stroke, you know, store it, um, put a query, lay over it, um, machine learning models, and then run those machine learning models. Real-time now that's what we, that's what we do as a business. Now when such customer, and I just wanted to give you one example, um, a customer that we have worked with to provide these types of results is Navistar and Navistar was kind of an early, early adopter of connected truck analytics. And they provided these capabilities to their fleet operators, right? And they started off, uh, by, um, by, you know, connecting 475,000 trucks to up to well over a million now. >>And you know, the point here is with that, they were centralizing data from their telematics service providers, from their trucks, from telematics service providers. They're bringing in things like weather data and all those types of things. Um, and what they started to do was to build out machine learning models, aimed at predictive maintenance. And what's really interesting is that you see that Navistar, um, made tremendous strides in reducing the need or the expense associated with maintenance, right? So rather than waiting for a truck to break and then fixing it, they would predict when that truck needs service, condition-based monitoring and service it before it broke down so that you could do that in a much more cost-effective manner. And if you see the benefits, right, they, they reduced maintenance costs 3 cents a mile, um, from the, you know, down from the industry average of 15 cents a mile down to 12 cents cents a mile. >>So this was a tremendous success for Navistar. And we're seeing this across many of our, um, um, you know, um, uh, truck manufacturers. We were working with many of the truck OEMs and they are all working to achieve, um, you know, very, very similar types of, um, benefits to their customers. So just a little bit about Navistar. Um, now we're gonna turn to Q and a, Dave's got some questions for me in a second, but before we do that, if you want to learn more about our, how we work with connected vehicles and autonomous vehicles, please go to our lives or to our website, what you see up, uh, up on the screen, there's the URLs cloudera.com for slash solutions for slash manufacturing. And you'll see a whole slew of, um, um, lateral and information, uh, in much more detail in terms of how we connect, um, trucks to fleet operators who provide analytics, use cases that drive dramatically improved performance. So with that being said, I'm going to turn it over to Dave for questions. >>Thank you. Uh, Michael, that's a great example. You've got, I love the life cycle. You can visualize that very well. You've got an edge use case you do in both real time inference, really at the edge. And then you're blending that sensor data with other data sources to enrich your models. And you can push that back to the edge. That's that lifecycle. So really appreciate that, that info. Let me ask you, what are you seeing as the most common connected vehicle when you think about analytics and machine learning, the use cases that you see customers really leaning into. >>Yeah, that's really, that's a great question. They, you know, cause you know, everybody always thinks about machine learning. Like this is the first thing you go, well, actually it's not right for the first thing you really want to be able to go around. Many of our customers are doing slow. Let's simply connect our trucks or our vehicles or whatever our IOT asset is. And then you can do very simple things like just performance monitoring of the, of the piece of equipment in the truck industry, a lot of performance monitoring of the truck, but also performance monitoring of the driver. So how has the, how has the driver performing? Is there a lot of idle time spent, um, you know, what's, what's route efficiencies looking like, you know, by connecting the vehicles, right? You get insights, as I said into the truck and into the driver and that's not machine learning. >>Right. But that, that, that monitoring piece is really, really important. The first thing that we see is monitoring types of use cases. Then you start to see companies move towards more of the, uh, what I call the machine learning and AI models, where you're using inference on the edge. And then you start to see things like, uh, predictive maintenance happening, um, kind of route real-time, route optimization and things like that. And you start to see that evolution again, to those smarter, more intelligent dynamic types of decision-making, but let's not, let's not minimize the value of good old fashioned monitoring that site to give you that kind of visibility first, then moving to smarter use cases as you, as you go forward. >>You know, it's interesting. I'm, I'm envisioning when you talked about the monitoring, I'm envisioning a, you see the bumper sticker, you know, how am I driving this all the time? If somebody ever probably causes when they get cut off it's snow and you know, many people might think, oh, it's about big brother, but it's not. I mean, that's yeah. Okay, fine. But it's really about improvement and training and continuous improvement. And then of course the, the route optimization, I mean, that's, that's bottom line business value. So, so that's, I love those, uh, those examples. Um, I wonder, I mean, one of the big hurdles that people should think about when they want to jump into those use cases that you just talked about, what are they going to run into, uh, you know, the blind spots they're, they're going to, they're going to get hit with, >>There's a few different things, right? So first of all, a lot of times your it folks aren't familiar with the kind of the more operational IOT types of data. So just connecting to that type of data can be a new skill set, right? That's very specialized hardware in the car and things like that. And protocols that's number one, that that's the classic, it OT kind of conundrum that, um, you know, uh, many of our customers struggle with, but then more fundamentally is, you know, if you look at the way these types of connected truck or IOT solutions started, you know, oftentimes they were, the first generation were very custom built, right? So they were brittle, right? They were kind of hardwired. And as you move towards, um, more commercial solutions, you had what I call the silo, right? You had fragmentation in terms of this capability from this vendor, this capability from another vendor, you get the idea, you know, one of the things that we really think that we need with that, that needs to be brought to the table is first of all, having an end to end data management platform, that's kind of integrated, it's all tested together. >>You have the data lineage across the entire stack, but then also importantly, to be realistic, we have to be able to integrate to, um, industry kind of best practices as well in terms of, um, solution components in the car, how the hardware and all those types things. So I think there's, you know, it's just stepping back for a second. I think that there is, has been fragmentation and complexity in the past. We're moving towards more standards and more standard types of art, um, offerings. Um, our job as a software maker is to make that easier and connect those dots. So customers don't have to do it all on all on their own. >>And you mentioned specialized hardware. One of the things we heard earlier in the main stage was your partnership with Nvidia. We're talking about, you know, new types of hardware coming in, you guys are optimizing for that. We see the it and the OT worlds blending together, no question. And then that end to end management piece, you know, this is different from your right, from it, normally everything's controlled or the data center, and this is a metadata, you know, rethinking kind of how you manage metadata. Um, so in the spirit of, of what we talked about earlier today, uh, uh, other technology partners, are you working with other partners to sort of accelerate these solutions, move them forward faster? >>Yeah, I'm really glad you're asking that because we actually embarked on a product on a project called project fusion, which really was about integrating with, you know, when you look at that connected vehicle life cycle, there are some core vendors out there that are providing some very important capabilities. So what we did is we joined forces with them to build an end-to-end demonstration and reference architecture to enable the complete data management life cycle. Cloudera is Peter piece of this was ingesting data and all the things I talked about being storing and the machine learning, right? And so we provide that end to end. But what we wanted to do is we wanted to partner with some key partners and the partners that we did with, um, integrate with or NXP NXP provides the service oriented gateways in the car. So that's a hardware in the car when river provides an in-car operating system, that's Linux, right? >>That's hardened and tested. We then ran ours, our, uh, Apache magnify, which is part of flood era data flow in the vehicle, right on that operating system. On that hardware, we pump the data over into the cloud where we did them, all the data analytics and machine learning and, and builds out these very specialized models. And then we used a company called Arabic equity. Once we both those models to do, you know, they specialize in automotive over the air updates, right? So they can then take those models and update those models back to the vehicle very rapidly. So what we said is, look, there's, there's an established, um, you know, uh, ecosystem, if you will, of leaders in this space, what we wanted to do is make sure that our, there was part and parcel of this ecosystem. And by the way, you mentioned Nvidia as well. We're working closely with Nvidia now. So when we're doing the machine learning, we can leverage some of their hardware to get some further acceleration in the machine learning side of things. So, uh, yeah, you know, one of the things I always say about this types of use cases, it does take a village. And what we've really tried to do is build out that, that, uh, an ecosystem that provides that village so that we can speed that analytics and machine learning, um, lifecycle just as fast as it can be. This >>Is again another great example of, of data intensive workloads. It's not your, it's not your grandfather's ERP. That's running on, you know, traditional, you know, systems it's, these are really purpose-built, maybe they're customizable for certain edge use cases. They're low cost, low, low power. They can't be bloated, uh, ended you're right. It does take an ecosystem. You've got to have, you know, API APIs that connect and, and that's that, that takes a lot of work and a lot of thoughts. So that, that leads me to the technologies that are sort of underpinning this we've talked we've we talked a lot in the cube about semiconductor technology, and now that's changing and the advancements we're seeing there, what do you see as the, some of the key technical technology areas that are advancing this connected vehicle machine learning? >>You know, it's interesting, I'm seeing it in a few places, just a few notable ones. I think, first of all, you know, we see that the vehicle itself is getting smarter, right? So when you look at, we look at that NXP type of gateway that we talked about that used to be kind of a, a dumb gateway. That was really all it was doing was pushing data up and down and provided isolation, um, as a gateway down to the, uh, down from the lower level subsistence. So it was really security and just basic, um, you know, basic communication that gateway now is becoming what they call a service oriented gate. So it can run. It's not that it's bad desk. It's got memories that always, so now you could run serious compute in the car, right? So now all of these things like running machine learning, inference models, you have a lot more power in the corner at the same time. >>5g is making it so that you can push data fast enough, making low latency computing available, even on the cloud. So now you now you've got credible compute both at the edge in the vehicle and on the cloud. Right. And, um, you know, and then on the, you know, on the cloud, you've got partners like Nvidia who are accelerating, it's still further through better GPU based compute. So I mean the whole stack, if you look at it, that that machine learning life cycle we talked about, no, David seems like there's improvements and EV every step along the way, we're starting to see technology, um, optimum optimization, um, just pervasive throughout the cycle. >>And then real quick, it's not a quick topic, but you mentioned security. If it was seeing a whole new security model emerge, there is no perimeter anymore in this use case like this is there. >>No there isn't. And one of the things that we're, you know, remember where the data management platform platform and the thing we have to provide is provide end-to-end link, you know, end end-to-end lineage of where that data came from, who can see it, you know, how it changed, right? And that's something that we have integrated into from the beginning of when that data is ingested through, when it's stored through, when it's kind of processed and people are doing machine learning, we provide, we will provide that lineage so that, um, you know, that security and governance is a short throughout the, throughout the data learning life cycle, it >>Federated across in this example, across the fleet. So, all right, Michael, that's all the time we have right now. Thank you so much for that great information. Really appreciate it, >>Dave. Thank you. And thank you. Thanks for the audience for listening in today. Yes. Thank you for watching. >>Okay. We're here in the second manufacturing drill down session with Michael Gerber. He was the managing director for automotive and manufacturing solutions at Cloudera. And we're going to continue the discussion with a look at how to lower costs and drive quality in IOT analytics with better uptime. And look, when you do the math, that's really quite obvious when the system is down, productivity is lost and it hits revenue and the bottom line improve quality drives, better service levels and reduces loss opportunities. Michael. Great to see you >>Take it away. All right. Thank you so much. So I'd say we're going to talk a little bit about connected manufacturing, right. And how those IOT IOT around connected manufacturing can do as Dave talked about improved quality outcomes for manufacturing improve and improve your plant uptime. So just a little bit quick, quick, little indulgent, quick history lesson. I promise to be quick. We've all heard about industry 4.0, right? That is the fourth industrial revolution. And that's really what we're here to talk about today. First industrial revolution, real simple, right? You had steam power, right? You would reduce backbreaking work. Second industrial revolution, massive assembly line. Right. So think about Henry Ford and motorized conveyor belts, mass automation, third industrial revolution. Things got interesting, right? You started to see automation, but that automation was done, essentially programmed a robot to do something. It did the same thing over and over and over irrespective about it, of how your outside operations, your outside conditions change fourth industrial revolution, very different breakfast. >>Now we're connecting, um, equipment and processes and getting feedback from it. And through machine learning, we can make those, um, those processes adaptive right through machine learning. That's really what we're talking about in the fourth industrial revolution. And it is intrinsically connected to data and a data life cycle. And by the way, it's important, not just for a little bit of a slight issue. There we'll issue that, but it's important, not for technology sake, right? It's important because it actually drives and very important business outcomes. First of all, quality, right? If you look at the cost of quality, even despite decades of, of, of, of, uh, companies, um, and manufacturers moving to improve while its quality promise still accounted to 20% of sales, right? So every fifth of what you meant or manufactured from a revenue perspective, you've got quality issues that are costing you a lot. >>Plant downtime, cost companies, $50 billion a year. So when we're talking about using data and these industry 4.0 types of use cases, connected data types of use cases, we're not doing it just merely to implement technology. We're doing it to move these from drivers, improving quality, reducing downtime. So let's talk about how a connected manufacturing data life cycle, what like, right, because this is actually the business that cloud era is, is in. Let's talk a little bit about that. So we call this manufacturing edge to AI, this, this analytics life cycle, and it starts with having your plants, right? Those plants are increasingly connected. As I said, sensor prices have come down two thirds over the last decade, right? And those sensors have connected over the internet. So suddenly we can collect all this data from your, um, ma manufacturing plants. What do we want to be able to do? >>You know, we want to be able to collect it. We want to be able to analyze that data as it's coming across. Right? So, uh, in scream, right, we want to be able to analyze it and take intelligent real-time actions. Right? We might do some simple processing and filtering at the edge, but we really want to take real-time actions on that data. But, and this is the inference part of things, right? Taking the time. But this, the ability to take these real-time actions, um, is actually the result of a machine learning life cycle. I want to walk you through this, right? And it starts with, um, ingesting this data for the first time, putting it into our enterprise data lake, right in that data lake enterprise data lake can be either within your data center or it could be in the cloud. You've got, you're going to ingest that data. >>You're going to store it. You're going to enrich it with enterprise data sources. So now you'll have say sensor data and you'll have maintenance repair orders from your maintenance management systems. Right now you can start to think about do you're getting really nice data sets. You can start to say, Hey, which sensor values correlate to the need for machine maintenance, right? You start to see the data sets. They're becoming very compatible with machine learning, but so you, you bring these data sets together. You process that you align your time series data from your sensors to your timestamp data from your, um, you know, from your enterprise systems that your maintenance management system, as I mentioned, you know, once you've done that, we could put a query layer on top. So now we can start to do advanced analytics query across all these different types of data sets. >>But as I mentioned, you, and what's really important here is the fact that once you've stored long histories that say that you can build out those machine learning models I talked to you about earlier. So like I said, you can start to say, which sensor values drove the need, a correlated to the need for equipment maintenance for my maintenance management systems, right? And you can build out those models and say, Hey, here are the sensor values of the conditions that predict the need for Maples. Once you understand that you can actually then build out those models for deploy the models out the edge, where they will then work in that inference mode that we talked about, I will continuously sniff that data as it's coming and say, Hey, which are the, are we experiencing those conditions that PR that predicted the need for maintenance? If so, let's take real-time action, right? >>Let's schedule a work order or an equipment maintenance work order in the past, let's in the future, let's order the parts ahead of time before that piece of equipment fails and allows us to be very, very proactive. So, you know, we have, this is a, one of the Mo the most popular use cases we're seeing in terms of connecting connected manufacturing. And we're working with many different manufacturers around the world. I want to just highlight. One of them is I thought it's really interesting. This company is bought for Russia, for SIA, for ACA is the, um, is the, was, is the, um, the, uh, a supplier associated with Peugeot central line out of France. They are huge, right? This is a multi-national automotive parts and systems supplier. And as you can see, they operate in 300 sites in 35 countries. So very global, they connected 2000 machines, right. >>Um, and then once be able to take data from that. They started off with learning how to ingest the data. They started off very well with, um, you know, with, uh, manufacturing control towers, right? To be able to just monitor data firms coming in, you know, monitor the process. That was the first step, right. Uh, and, you know, 2000 machines, 300 different variables, things like, um, vibration pressure temperature, right? So first let's do performance monitoring. Then they said, okay, let's start doing machine learning on some of these things to start to build out things like equipment, um, predictive maintenance models or compute. And what they really focused on is computer vision while the inspection. So let's take pictures of, um, parts as they go through a process and then classify what that was this picture associated with the good or bad Bali outcome. Then you teach the machine to make that decision on its own. >>So now, now the machine, the camera is doing the inspections. And so they both had those machine learning models. They took that data, all this data was on-prem, but they pushed that data up to the cloud to do the machine learning models, develop those machine learning models. Then they push the machine learning models back into the plants where they, where they could take real-time actions through these computer vision, quality inspections. So great use case. Um, great example of how you can start with monitoring, moved to machine learning, but at the end of the day, or improving quality and improving, um, uh, equipment uptime. And that is the goal of most manufacturers. So with that being said, um, I would like to say, if you want to learn some more, um, we've got a wealth of information on our website. You see the URL in front of you, please go there and you'll learn. There's a lot of information there in terms of the use cases that we're seeing in manufacturing, a lot more detail, and a lot more talk about a lot more customers we'll work with. If you need that information, please do find it. Um, with that, I'm going to turn it over to Dave, to Steve. I think you had some questions you want to run by. >>I do, Michael, thank you very much for that. And before I get into the questions, I just wanted to sort of make some observations that was, you know, struck by what you're saying about the phases of industry. We talk about industry 4.0, and my observation is that, you know, traditionally, you know, machines have always replaced humans, but it's been around labor and, and the difference with 4.0, and what you talked about with connecting equipment is you're injecting machine intelligence. Now the camera inspection example, and then the machines are taking action, right? That's, that's different and, and is a really new kind of paradigm here. I think the, the second thing that struck me is, you know, the cost, you know, 20% of, of sales and plant downtime costing, you know, many tens of billions of dollars a year. Um, so that was huge. I mean, the business case for this is I'm going to reduce my expected loss quite dramatically. >>And then I think the third point, which we turned in the morning sessions, and the main stage is really this, the world is hybrid. Everybody's trying to figure out hybrid, get hybrid, right. And it certainly applies here. Uh, this is, this is a hybrid world you've got to accommodate, you know, regardless of, of where the data is. You've gotta be able to get to it, blend it, enrich it, and then act on it. So anyway, those are my big, big takeaways. Um, so first question. So in thinking about implementing connected manufacturing initiatives, what are people going to run into? What are the big challenges that they're going to, they're going to hit, >>You know, there's, there's, there, there's a few of the, but I think, you know, one of the ones, uh, w one of the key ones is bridging what we'll call the it and OT data divide, right. And what we mean by the it, you know, your, it systems are the ones, your ERP systems, your MES systems, right? Those are your transactional systems that run on relational databases and your it departments are brilliant, are running on that, right? The difficulty becomes an implementing these use cases that you also have to deal with operational technology, right? And those are, um, all of the, that's all the equipment in your manufacturing plant that runs on its proprietary network with proprietorial pro protocols. That information can be very, very difficult to get to. Right. So, and it's, it's a much more unstructured than from your OT. So th the key challenge is being able to bring these data sets together in a single place where you can start to do advanced analytics and leverage that diverse data to do machine learning. Right? So that is one of the, if I boil it down to the single hardest thing in this, uh, in this, in this type of environment, nectar manufacturing is that that operational technology has kind of run on its own in its own world. And for a long time, the silos, um, uh, the silos a, uh, bound, but at the end of the day, this is incredibly valuable data that now can be tapped, um, um, to, to, to, to move those, those metrics we talked about right around quality and uptime. So a huge, >>Well, and again, this is a hybrid team and you, you've kind of got this world, that's going toward an equilibrium. You've got the OT side and, you know, pretty hardcore engineers. And we know, we know it. A lot of that data historically has been analog data. Now it's getting, you know, instrumented and captured. Uh, so you've got that, that cultural challenge. And, you know, you got to blend those two worlds. That's critical. Okay. So, Michael, let's talk about some of the use cases you touched on, on some, but let's peel the onion a bit when you're thinking about this world of connected manufacturing and analytics in that space, when you talk to customers, you know, what are the most common use cases that you see? >>Yeah, that's a good, that's a great question. And you're right. I did allude to a little bit earlier, but there really is. I want people to think about, there's a spectrum of use cases ranging from simple to complex, but you can get value even in the simple phases. And when I talk about the simple use cases, the simplest use cases really is really around monitoring, right? So in this, you monitor your equipment or monitor your processes, right? And you just make sure that you're staying within the bounds of your control plan, right. And this is much easier to do now. Right? Cause some of these sensors are a more sensors and those sensors are moving more and more towards internet types of technology. So, Hey, you've got the opportunity now to be able to do some monitoring. Okay. No machine learning, but just talking about simple monitoring next level down, and we're seeing is something we would call quality event forensic analysis. >>And now on this one, you say, imagine I've got warranty plans in the, in the field, right? So I'm starting to see warranty claims kick up. And what you simply want to be able to do is do the forensic analysis back to what was the root cause of within the manufacturing process that caused it. So this is about connecting the dots. What about warranty issues? What were the manufacturing conditions of the day that caused it? Then you could also say which other tech, which other products were impacted by those same conditions. And we call those proactively rather than, and, and selectively rather than say, um, recalling an entire year's fleet of the car. So, and that, again, also not machine learning, we're simply connecting the dots from a warranty claims in the field to the manufacturing conditions of the day, so that you could take corrective actions, but then you get into a whole slew of machine learning, use dates, you know, and that ranges from things like Wally or say yield optimization. >>We start to collect sensor values and, um, manufacturing yield, uh, values from your ERP system. And you're certain start to say, which, um, you know, which on a sensor values or factors drove good or bad yield outcomes, and you can identify those factors that are the most important. So you, um, you, you measure those, you monitor those and you optimize those, right. That's how you optimize your, and then you go down to the more traditional machine learning use cases around predictive maintenance. So the key point here, Dave is, look, there's a huge, you know, depending on a customer's maturity around big data, you could start simply with, with monitoring, get a lot of value, start then bringing together more diverse data sets to do things like connect the.analytics then and all the way then to, to, to the more advanced machine learning use cases, there's this value to be had throughout. >>I remember when the, you know, the it industry really started to think about, or in the early days, you know, IOT and IOT. Um, it reminds me of when, you know, there was, uh, the, the old days of football field, we were grass and, and the new player would come in and he'd be perfectly white uniform, and you had it. We had to get dirty as an industry, you know, it'll learn. And so, so I question it relates to other technology partners that you might be working with that are maybe new in this space that, that to accelerate some of these solutions that we've been talking about. >>Yeah. That's a great question. And it kind of goes back to one of the things I alluded to alluded upon earlier. We've had some great partners, a partner, for example, litmus automation, whose whole world is the OT world. And what they've done is for example, they built some adapters to be able to catch it practically every industrial protocol. And they've said, Hey, we can do that. And then give a single interface of that data to the Idera data platform. So now, you know, we're really good at ingesting it data and things like that. We can leverage say a company like litmus that can open the flood gates of that OT data, making it much easier to get that data into our platform. And suddenly you've got all the data you need to, to, to implement those types of, um, industry for porno, our analytics use cases. And it really boils down to, can I get to that? Can I break down that it OT, um, you know, uh, a barrier that we've always had and, and bring together those data sets that we can really move the needle in terms of improving manufacturing performance. >>Okay. Thank you for that last question. Speaking to moving the needle, I want to li lead this discussion on the technology advances. I'd love to talk tech here. Uh, what are the key technology enablers and advancers, if you will, that are going to move connected manufacturing and machine learning forward in this transportation space. Sorry, manufacturing. Yeah. >>Yeah. I know in the manufacturing space, there's a few things, first of all, I think the fact that obviously I know we touched upon this, the fact that sensor prices have come down and have become ubiquitous that number one, we can, we've finally been able to get to the OT data, right? That's that's number one, you know, numb number two, I think, you know, um, we, we have the ability that now to be able to store that data a whole lot more efficiently, you know, we've got, we've got great capabilities to be able to do that, to put it over into the cloud, to do the machine learning types of workloads. You've got things like if you're doing computer vision, while in analyst respect GPU's to make those machine learning models much more, uh, much more effective, if that 5g technology that starts to blur at least from a latency perspective where you do your computer, whether it be on the edge or in the cloud, you've, you've got more, the super business critical stuff. >>You probably don't want to rely on, uh, any type of network connection, but from a latency perspective, you're starting to see, uh, you know, the ability to do compute where it's the most effective now. And that's really important. And again, the machine learning capabilities, and they believed a book to build a GP, you know, GPU level machine learning, build out those models and then deployed by over the air updates to, to your equipment. All of those things are making this, um, there's, you know, the advanced analytics and machine learning, uh, data life cycle just faster and better. And at the end of the day, to your point, Dave, that equipment and processor getting much smarter, uh, very much more quickly. Yeah, we got >>A lot of data and we have way lower cost, uh, processing platforms I'll throw in NP use as well. Watch that space neural processing units. Okay. Michael, we're going to leave it there. Thank you so much. Really appreciate your time, >>Dave. I really appreciate it. And thanks. Thanks for, uh, for everybody who joined us. Thanks. Thanks for joining today. Yes. Thank you for watching. Keep it right there.
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Michael, great to see you over to you. And if you look at the F the top fleet operator, uh, the top benefits that So, you know, one of the things that's really important to be able to enable this right, And by the way, once you conducted the, um, this information from the trucks, you want to be able to analyze And you want to augment that with your dealership, say service information. So what do you do here? And they started off, uh, by, um, by, you know, connecting 475,000 And you know, the point here is with that, they were centralizing data from their telematics service providers, many of our, um, um, you know, um, uh, truck manufacturers. And you can push that back to the edge. And then you can do very simple things like just performance monitoring And then you start to see things like, uh, predictive maintenance happening, uh, you know, the blind spots they're, they're going to, they're going to get hit with, it OT kind of conundrum that, um, you know, So I think there's, you know, it's just stepping back for a second. the data center, and this is a metadata, you know, rethinking kind of how you manage metadata. with, you know, when you look at that connected vehicle life cycle, there are some core vendors And by the way, you mentioned Nvidia as well. and now that's changing and the advancements we're seeing there, what do you see as the, um, you know, basic communication that gateway now is becoming um, you know, and then on the, you know, on the cloud, you've got partners like Nvidia who are accelerating, And then real quick, it's not a quick topic, but you mentioned security. And one of the things that we're, you know, remember where the data management Thank you so much for that great information. Thank you for watching. And look, when you do the math, that's really quite obvious when the system is down, productivity is lost and it hits Thank you so much. So every fifth of what you meant or manufactured from a revenue So we call this manufacturing edge to AI, I want to walk you through this, um, you know, from your enterprise systems that your maintenance management system, And you can build out those models and say, Hey, here are the sensor values of the conditions And as you can see, they operate in 300 sites in They started off very well with, um, you know, great example of how you can start with monitoring, moved to machine learning, I think the, the second thing that struck me is, you know, the cost, you know, 20% of, And then I think the third point, which we turned in the morning sessions, and the main stage is really this, And what we mean by the it, you know, your, it systems are the ones, You've got the OT side and, you know, pretty hardcore engineers. And you just make sure that you're staying within the bounds of your control plan, And now on this one, you say, imagine I've got warranty plans in the, in the field, look, there's a huge, you know, depending on a customer's maturity around big data, I remember when the, you know, the it industry really started to think about, or in the early days, you know, uh, a barrier that we've always had and, if you will, that are going to move connected manufacturing and machine learning forward that starts to blur at least from a latency perspective where you do your computer, and they believed a book to build a GP, you know, GPU level machine learning, Thank you so much. Thank you for watching.
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Manufacturing Reduce Costs and Improve Quality with IoT Analytics
>>Okay. We're here in the second manufacturing drill down session with Michael Gerber. He was the managing director for automotive and manufacturing solutions at Cloudera. And we're going to continue the discussion with a look at how to lower costs and drive quality in IOT analytics with better uptime and hook. When you do the math, that's really quite obvious when the system is down, productivity is lost and it hits revenue and the bottom line improve quality drives, better service levels and reduces lost opportunities. Michael. Great to see you, >>Dave. All right, guys. Thank you so much. So I'll tell you, we're going to talk a little bit about connected manufacturing, right? And how those IOT IOT around connected manufacturing can do as Dave talked about improved quality outcomes for manufacturing improve and improve your plant uptime. So just a little bit quick, quick, little indulgent, quick history lesson. I promise to be quick. We've all heard about industry 4.0, right? That is the fourth industrial revolution. And that's really what we're here to talk about today. First industrial revolution, real simple, right? You had steam power, right? You would reduce backbreaking work. Second industrial revolution, mass assembly line. Right. So think about Henry Ford and motorized conveyor belts, mass automation, third industrial revolution. Things got interesting, right? You started to see automation, but that automation was done essentially programmed a robot to do something. It did the same thing over and over and over irrespective about of how your outside operations, your outside conditions change fourth industrial revolution, very different breakfasts. >>Now we're connecting, um, equipment and processes and getting feedback from it. And through machine learning, we can make those, um, those processes adapted right through machine learning. That's really what we're talking about in the fourth industrial revolution. And it is intrinsically connected to data and a data life cycle. And by the way, it's important, not just for a little bit of a slight issue. There we'll issue that, but it's important, not for technology sake, right? It's important because it actually drives very important business outcomes. First of all, falling, right? If you look at the cost of quality, even despite decades of, of, uh, companies and manufacturers moving to improve while its quality prompts still account to 20% of sales, right? So every fifth of what you meant or manufactured from a revenue perspective, you've got quality issues that are costing you a lot. Plant downtime, cost companies, $50 billion a year. >>So when we're talking about using data and these industry 4.0 types of use cases, connected data types of use cases, we're not doing it just narrowly to implement technology. We're doing it to move these from adverse, improving quality, reducing downtime. So let's talk about how a connected manufacturing data life cycle with what like, right. But so this is actually the business that cloud areas is in. Let's talk a little bit about that. So we call this manufacturing edge to AI. This is analytics, life something, and it starts with having your plants, right? Those plants are increasingly connected. As I said, sensor prices have come down two thirds over the last decade, right? And those sensors are connected over the internet. So suddenly we can collect all this data from your, um, manufacturing plants, and what do we want to be able to do? You know, we want to be able to collect it. >>We want to be able to analyze that data as it's coming across. Right? So, uh, in scream, right, we want to be able to analyze it and take intelligent real-time actions. Right? We might do some simple processing and filtering at the edge, but we really want to take real-time actions on that data. But, and this is the inference part of things, right? Taking that time. But this, the ability to take these real-time actions, um, is actually the result of a machine learning life cycle. I want to walk you through this, right? And it starts with, um, ingesting this data for the first time, putting it into our enterprise data lake, right? And that data lake enterprise data lake can be either within your data center or it could be in the cloud. You're going to, you're going to ingest that data. You're going to store it. >>You're going to enrich it with enterprise data sources. So now you'll have say sensor data and you'll have maintenance repair orders from your maintenance management systems. Right now you can start to think about do you're getting really nice data sets. You can start to say, Hey, which sensor values correlate to the need for machine maintenance, right? You start to see the data sets. They're becoming very compatible with machine learning, but so you bring these datasets together. You process that you align your time series data from your sensors to your timestamp data from your, um, you know, from your enterprise systems that your maintenance management system, as I mentioned, you know, once you've done that, we could put a query layer on top. So now we can start to do advanced analytics query across all these different types of data sets. But as I mentioned to you, and what's really important here is the fact that once you've stored one histories that say that you can build out those machine learning models I talked to you about earlier. >>So like I said, you can start to say, which sensor values drove the need of correlated to the need for equipment maintenance for my maintenance management systems, right? And then you can build out those models and say, Hey, here are the sensor values of the conditions that predict the need for maintenance. And once you understand that you can actually then build out those models, you deploy the models out to the edge where they will then work in that inference mode, that photographer, I will continuously sniff that data as it's coming and say, Hey, which are the, are we experiencing those conditions that, that predicted the need for maintenance? If so, let's take real-time action, right? Let's schedule a work order and equipment maintenance work order in the past, let's in the future, let's order the parts ahead of time before that a piece of equipment fails and allows us to be very, very proactive. >>So, you know, we have, this is a, one of the Mo the most popular use cases we're seeing in terms of connected, connected manufacturing. And we're working with many different, um, manufacturers around the world. I want to just highlight one of them. Cause I thought it's really interesting. This company is bought for Russia. And for SIA for ACA is the, um, is the, is the, um, the, uh, a supplier associated with out of France. They are huge, right? This is a multi-national automotive, um, parts and systems supplier. And as you can see, they operate in 300 sites in 35 countries. So very global, they connected 2000 machines, right. Um, I mean at once be able to take data from that. They started off with learning how to ingest the data. They started off very well with, um, you know, with, uh, manufacturing control towers, right? >>To be able to just monitor the data from coming in, you know, monitor the process. That was the first step, right. Uh, and you know, 2000 machines, 300 different variables, things like, um, vibration pressure temperature, right? So first let's do performance monitoring. Then they said, okay, let's start doing machine learning on some of these things, just start to build out things like equipment, um, predictive maintenance models, or compute. What they really focused on is computer vision while the inspection. So let's take pictures of, um, parts as they go through a process and then classify what that was this picture associated with the good or bad quality outcome. Then you teach the machine to make that decision on its own. So now, now the machine, the camera is doing the inspections for you. And so they both had those machine learning models. They took that data, all this data was on-prem, but they pushed that data up to the cloud to do the machine learning models, develop those machine learning models. >>Then they push the machine learning models back into the plants where they, where they could take real-time actions through these computer vision, quality inspections. So great use case. Um, great example of how you start with monitoring, move to machine learning, but at the end of the day, or improving quality and improving, um, uh, equipment uptime. And that is the goal of most manufacturers. So with that being said, um, I would like to say, if you want to learn some more, um, we've got a wealth of information on our website. You see the URL in front of you, please go, then you'll learn. There's a lot of information there in terms of the use cases that we're seeing in manufacturing and a lot more detail and a lot more talk about a lot more customers we'll work with. If you need that information, please do find it. Um, with that, I'm going to turn it over to Dave, to Steve. I think you had some questions you want to run by. >>I do, Michael, thank you very much for that. And before I get into the questions, I just wanted to sort of make some observations that was, you know, struck by what you're saying about the phases of industry. We talk about industry 4.0, and my observation is that, you know, traditionally, you know, machines have always replaced humans, but it's been around labor and, and the difference with 4.0, and what you talked about with connecting equipment is you're injecting machine intelligence. Now the camera inspection example, and then the machines are taking action, right? That's, that's different and, and is a really new kind of paradigm here. I think the, the second thing that struck me is, you know, the costs, you know, 20% of, of sales and plant downtime costing, you know, many tens of billions of dollars a year. Um, so that was huge. I mean, the business case for this is I'm going to reduce my expected loss quite dramatically. >>And then I think the third point, which we turned in the morning sessions, and the main stage is really this, the world is hybrid. Everybody's trying to figure out hybrid, get hybrid, right. And it certainly applies here. Uh, this is, this is a hybrid world you've got to accommodate, you know, regardless of where the data is, you've got to be able to get to it, blend it, enrich it, and then act on it. So anyway, those are my big, big takeaways. Um, so first question. So in thinking about implementing connected manufacturing initiatives, what are people going to run into? What are the big challenges that they're going to, they're going to hit? >>No, there's, there's there, there's a few of the, but I think, you know, one of the, uh, one of the key ones is bridging what we'll call the it and OT data divide, right. And what we mean by the it, you know, your, it systems are the ones, your ERP systems, your MES system, Freightos your transactional systems that run on relational databases and your it departments are brilliant at running on that, right? The difficulty becomes an implementing these use cases that you also have to deal with operational technology, right? And those are all of the, that's all the equipment in your manufacturing plant that runs on its proprietary network with proprietary pro protocols. That information can be very, very difficult to get to. Right? So, and it's uncertain, it's a much more unstructured than from your OT. So the key challenge is being able to bring these data sets together in a single place where you can start to do advanced analytics and leverage that diverse data to do machine learning. Right? So that is one of the, if I had to boil it down to the single hardest thing in this, uh, in this, in this type of environment, nectar manufacturing is that that operational technology has kind of run on its own in its own. And for a long time, the silos, the silos, a bound, but at the end of the day, this is incredibly valuable data that now can be tapped, um, um, to, to, to, to move those, those metrics we talked about right around quality and uptime. So a huge opportunity. >>Well, and again, this is a hybrid team and you, you've kind of got this world, that's going toward an equilibrium. You've got the OT side and, you know, pretty hardcore engineers. And we know, we know it. A lot of that data historically has been analog data. This is Chris now is getting, you know, instrumented and captured. Uh, and so you've got that, that cultural challenge and, you know, you got to blend those two worlds. That's critical. Okay. So Michael, let's talk about some of the use cases you touched on, on some, but let's peel the onion a bit when you're thinking about this world of connected manufacturing and analytics in that space, when you talk to customers, you know, what are the most common use cases that you see? >>Yeah, that's a great, that's a great question. And you're right. I did allude to a little bit earlier, but there really is. I want people to think about this, a spectrum of use cases ranging from simple to complex, but you can get value even in the simple phases. And when I talk about the simple use cases, the simplest use cases really is really around monitoring, right? So in this, you monitor your equipment or monitor your processes, right? And you just make sure that you're staying within the bounds of your control plan, right? And this is much easier to do now. Right? Cause some of these sensors are a more sensors and those sensors are moving more and more towards the internet types of technology. So, Hey, you've got the opportunity now to be able to do some monitoring. Okay. No machine learning, we're just talking about simple monitoring next level down. >>And we're seeing is something we would call quality event forensic announces. And now on this one, you say, imagine I'm got warranty plans in the, in the field, right? So I'm starting to see warranty claims kicked off on them. And what you simply want to be able to do is do the forensic analysis back to what was the root cause of within the manufacturing process that caused it. So this is about connecting the dots I've got, I've got warranty issues. What were the manufacturing conditions of the day that caused it? Then you could also say which other, which other products were impacted by those same conditions. And we call those proactively rather than, and, and selectively rather than say, um, recalling an entire year's fleet of a car. So, and that, again, also not machine learning is simply connecting the dots from a warranty claims in the field to the manufacturing conditions of the day so that you could take corrective actions, but then you get into a whole slew of machine learning use case, you know, and, and that ranges from things like quality or say yield optimization, where you start to collect sensor values and, um, manufacturing yield, uh, values from your ERP system. >>And you're certain start to say, which, um, you know, which map a sensor values or factors drove good or bad yield outcomes. And you can identify those factors that are the most important. So you, um, you, you measure those, you monitor those and you optimize those, right. That's how you optimize your, and then you go down to the more traditional machine learning use cases around predictive maintenance. So the key point here, Dave is, look, there's a huge, you know, depending on a customer's maturity around big data, you could start simply with monitoring, get a lot of value, start, then bring together more diverse datasets to do things like connect the.analytics then all and all the way then to, to, to the more advanced machine learning use cases this value to be had throughout. >>I remember when the, you know, the it industry really started to think about, or in the early days, you know, IOT and IOT. Um, it reminds me of when, you know, there was, uh, the, the old days of football field, we were grass and, and a new player would come in and he'd be perfectly white uniform and you had it. We had to get dirty as an industry, you know, it'll learn. And so, so my question relates to other technology partners that you might be working with that are maybe new in this space that, that to accelerate some of these solutions that we've been talking about. >>Yeah. That's a great question. I kind of, um, goes back to one of the things I alluded a little bit about earlier. We've got some great partners, a partner, for example, litmus automation, whose whole world is the OT world. And what they've done is for example, they built some adapters to be able to get to practically every industrial protocol. And they've said, Hey, we can do that. And then give a single interface of that data to the Idera data platform. So now, you know, we're really good at ingesting it data and things like that. We can leverage say a company like litmus that can open the flood gates of that OT data, making it much easier to get that data into our platform. And suddenly you've got all the data you need to, to implement those types of, um, industry 4.0, uh, analytics use cases. And it really boils down to, can I get to that? Can I break down that it OT, um, you know, uh, uh, barrier that we've always had and, and bring together those data sets that really move the needle in terms of improving manufacturing performance. >>Okay. Thank you for that last question. Speaking to moving the needle, I want to Lee lead this discussion on the technology advances. I'd love to talk tech here. Uh, what are the key technology enablers and advancers, if you will, that are going to move connected manufacturing and machine learning forward in this transportation space. Sorry. Manufacturing in >>Factor space. Yeah, I know in the manufacturing space, there's a few things, first of all, I think the fact that obviously I know we touched upon this, the fact that sensor prices have come down and it had become ubiquitous that number one, we can w we're finally been able to get to the OT data, right? That's that's number one, number, number two, I think, you know, um, we, we have the ability that now to be able to store that data a whole lot more efficiently, you know, we've got, we've got great capabilities to be able to do that, to put it over into the cloud, to do the machine learning types of workloads. You've got things like if you're doing computer vision, while in analyst respect GPU's to make those machine learning models much more, um, much more effective, if that 5g technology that starts to blur at least from a latency perspective where you do your computer, whether it be on the edge or in the cloud, you've, you've got more, you know, super business critical stuff. >>You probably don't want to rely on, uh, any type of network connection, but from a latency perspective, you're starting to see, uh, you know, the ability to do compute where it's the most effective now. And that's really important. And again, the machine learning capabilities, and they believed the book, bullet, uh, GP, you know, GPU level, machine learning, all that, those models, and then deployed by over the air updates to your equipment. All of those things are making this, um, there's, you know, there's the advanced analytics and machine learning, uh, data life cycle just faster and better. And at the end of the day, to your point, Dave, that equipment and processes are getting much smarter, uh, very much more quickly. >>Yep. We've got a lot of data and we have way lower costs, uh, processing platforms I'll throw in NP use as well. Watch that space neural processing units. Okay. Michael, we're going to leave it there. Thank you so much. Really appreciate your time, >>Dave. I really appreciate it. And thanks. Thanks for, uh, for everybody who joined. Uh, thanks. Thanks for joining today. Yes. Thank you for watching. Keep it right there.
SUMMARY :
When you do the math, that's really quite obvious when the system is down, productivity is lost and it hits revenue and the bottom Thank you so much. So every fifth of what you meant or manufactured from a revenue perspective, And those sensors are connected over the internet. I want to walk you through those machine learning models I talked to you about earlier. And then you can build out those models and say, Hey, here are the sensor values of the conditions And as you can see, they operate in 300 sites To be able to just monitor the data from coming in, you know, monitor the process. And that is the goal of most manufacturers. I think the, the second thing that struck me is, you know, the costs, you know, 20% of, And then I think the third point, which we turned in the morning sessions, and the main stage is really this, And what we mean by the it, you know, your, it systems are the ones, So Michael, let's talk about some of the use cases you touched on, on some, And you just make sure that you're staying within the bounds of your control plan, And now on this one, you say, imagine I'm got warranty plans in the, in the field, And you can identify those factors that I remember when the, you know, the it industry really started to think about, or in the early days, litmus that can open the flood gates of that OT data, making it much easier to if you will, that are going to move connected manufacturing and machine learning forward that data a whole lot more efficiently, you know, we've got, we've got great capabilities to be able to do that, And at the end of the day, to your point, Dave, that equipment and processes are getting much smarter, Thank you so much. Thank you for watching.
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