(introductory riff) >> Hey everyone. Welcome to theCUBE's presentation of the "AWS Startup Showcase." This is Season 2, Episode 3 of our ongoing series that features great partners in the massive AWS partner ecosystem. This series is focused on, "MarTech, Emerging Cloud-Scale Customer Experiences." I'm Lisa Martin, and I've got two guests here with me to talk about this. Please welcome Daisy Urfer, Cloud Alliance Sales Director at Algolia, and Jason Lang, the Head of Product for Apply Digital. These folks are here to talk with us today about how Algolia's Search and Discovery enables customers to create dynamic realtime user experiences for those oh so demanding customers. Daisy and Jason, it's great to have you on the program. >> Great to be here. >> Thanks for having us. >> Daisy, we're going to go ahead and start with you. Give the audience an overview of Algolia, what you guys do, when you were founded, what some of the gaps were in the market that your founders saw and fixed? >> Sure. It's actually a really fun story. We were founded in 2012. We are an API first SaaS solution for Search and Discovery, but our founders actually started off with a search tool for mobile platforms, so just for your phone and it quickly expanded, we recognize the need across the market. It's been a really fun place to grow the business. And we have 11,000 customers today and growing every day, with 30 billion searches a week. So we do a lot of business, it's fun. >> Lisa: 30 billion searches a week and I saw some great customer brands, Locost, NBC Universal, you mentioned over 11,000. Talk to me a little bit about some of the technologies, I see that you have a search product, you have a recommendation product. What are some of those key capabilities that the products deliver? 'Cause as we know, as users, when we're searching for something, we expect it to be incredibly fast. >> Sure. Yeah. What's fun about Algolia is we are actually the second largest search engine on the internet today to Google. So we are right below the guy who's made search of their verb. So we really provide an overall search strategy. We provide a dashboard for our end users so they can provide the best results to their customers and what their customers see. Customers want to see everything from Recommend, which is our recommended engine. So when you search for that dress, it shows you the frequently bought together shoes that match, things like that, to things like promoted items and what's missing in the search results. So we do that with a different algorithm today. Most in the industry rank and they'll stack what you would want to see. We do kind of a pair for pair ranking system. So we really compare what you're looking for and it gives a much better result. >> And that's incredibly critical for users these days who want results in milliseconds. Jason, you, Apply Digital as a partner of Algolia, talk to us about Apply Digital, what it is that you guys do, and then give us a little bit of insight on that partnership. >> Sure. So Apply Digital was originally founded in 2016 in Vancouver, Canada. And we have offices in Vancouver, Toronto, New York, LA, San Francisco, Mexico city, Sao Paulo and Amsterdam. And we are a digital experiences agency. So brands and companies, and startups, and all the way from startups to major global conglomerates who have this desire to truly create these amazing digital experiences, it could be a website, it could be an app, it could be a full blown marketing platform, just whatever it is. And they lack either the experience or the internal resources, or what have you, then they come to us. And and we are end-to-end, we strategy, design, product, development, all the way through the execution side. And to help us out, we partner with organizations like Algolia to offer certain solutions, like an Algolia's case, like search recommendation, things like that, to our various clients and customers who are like, "Hey, I want to create this experience and it's going to require search, or it's going to require some sort of recommendation." And we're like, "Well, we highly recommend that you use Algolia. They're a partner of ours, they've been absolutely amazing over the time that we've had the partnership. And that's what we do." And honestly, for digital experiences, search is the essence of the internet, it just is. So, I cannot think of a single digital experience that doesn't require some sort of search or recommendation engine attached to it. So, and Algolia has just knocked it out of the park with their experience, not only from a customer experience, but also from a development experience. So that's why they're just an amazing, amazing partner to have. >> Sounds like a great partnership. Daisy, let's point it back over to you. Talk about some of those main challenges, Jason alluded to them, that businesses are facing, whether it's e-commerce, SaaS, a startup or whatnot, where search and recommendations are concerned. 'Cause we all, I think I've had that experience, where we're searching for something, and Daisy, you were describing how the recommendation engine works. And when we are searching for something, if I've already bought a tent, don't show me more tent, show me things that would go with it. What are some of those main challenges that Algolia solution just eliminates? >> Sure. So I think, one of the main challenges we have to focus on is, most of our customers are fighting against the big guides out there that have hundreds of engineers on staff, custom building a search solution. And our consumers expect that response. You expect the same search response that you get when you're streaming video content looking for a movie, from your big retailer shopping experiences. So what we want to provide is the ability to deliver that result with much less work and hassle and have it all show up. And we do that by really focusing on the results that the customers need and what that view needs to look like. We see a lot of our customers just experiencing a huge loss in revenue by only providing basic search. And because as Jason put it, search is so fundamental to the internet, we all think it's easy, we all think it's just basic. And when you provide basic, you don't get the shoes with the dress, you get just the text response results back. And so we want to make sure that we're providing that back to our customers. What we see average is even, and everybody's going mobile. A lot of times I know I do all my shopping on my phone a lot of the time, and 40%-50% better relevancy results for our customers for mobile users. That's a huge impact to their use case. >> That is huge. And when we talked about patients wearing quite thin the last couple of years. But we have this expectation in our consumer lives and in our business lives if we're looking for SaaS or software, or whatnot, that we're going to be able to find what we want that's relevant to what we're looking for. And you mentioned revenue impact, customer churn, brand reputation, those are all things that if search isn't done well, to your point, Daisy, if it's done in a basic fashion, those are some of the things that customers are going to experience. Jason, talk to us about why Algolia, what was it specifically about that technology that really led Apply Digital to say, "This is the right partner to help eliminate some of those challenges that our customers could face?" >> Sure. So I'm in the product world. So I have the wonderful advantage of not worrying about how something's built, that is left, unfortunately, to the poor, poor engineers that have to work with us, mad scientist, product people, who are like, "I want, make it do this. I don't know how, but make it do this." And one of the big things is, with Algolia is the lift to implement is really, really light. Working closely with our engineering team, and even with our customers/users and everything like that, you kind of alluded to it a little earlier, it's like, at the end of the day, if it's bad search, it's bad search. It just is. It's terrible. And people's attention span can now be measured in nanoseconds, but they don't care how it works, they just want it to work. I push a button, I want something to happen, period. There's an entire universe that is behind that button, and that's what Algolia has really focused on, that universe behind that button. So there's two ways that we use them, on a web experience, there's the embedded Search widget, which is really, really easy to implement, documentation, and I cannot speak high enough about documentation, is amazing. And then from the web aspect, I'm sorry, from the mobile aspect, it's very API fort. And any type of API implementation where you can customize the UI, which obviously you can imagine our clients are like, "No we want to have our own front end. We want to have our own custom experience." We use Algolia as that engine. Again, the documentation and the light lift of implementation is huge. That is a massive, massive bonus for why we partnered with them. Before product, I was an engineer a very long time ago. I've seen bad documentation. And it's like, (Lisa laughing) "I don't know how to imple-- I don't know what this is. I don't know how to implement this, I don't even know what I'm looking at." But with Algolia and everything, it's so simple. And I know I can just hear the Apply Digital technology team, just grinding sometimes, "Why is a product guy saying that (mumbles)? He should do it." But it is, it just the lift, it's the documentation, it's the support. And it's a full blown partnership. And that's why we went with it, and that's what we tell our clients. It's like, listen, this is why we chose Algolia, because eventually this experience we're creating for them is theirs, ultimately it's theirs. And then they are going to have to pick it up after a certain amount of time once it's theirs. And having that transition of, "Look this is how easy it is to implement, here is all the documentation, here's all the support that you get." It just makes that transition from us to them beautifully seamless. >> And that's huge. We often talk about hard metrics, but ease of use, ease of implementation, the documentation, the support, those are all absolutely business critical for the organization who's implementing the software, the fastest time to value they can get, can be table stakes, and it can be on also a massive competitive differentiator. Daisy, I want to go back to you in terms of hard numbers. Algolia has a recent force or Total Economic Impact, or TEI study that really has some compelling stats. Can you share some of those insights with us? >> Yeah. Absolutely. I think that this is the one of the most fun numbers to share. We have a recent report that came out, it shared that there's a 382% Return on Investment across three years by implementing Algolia. So that's increase to revenue, increased conversion rate, increased time on your site, 382% Return on Investment for the purchase. So we know our pricing's right, we know we're providing for our customers. We know that we're giving them the results that we need. I've been in the search industry for long enough to know that those are some amazing stats, and I'm really proud to work for them and be behind them. >> That can be transformative for a business. I think we've all had that experience of trying to search on a website and not finding anything of relevance. And sometimes I scratch my head, "Why is this experience still like this? If I could churn, I would." So having that ability to easily implement, have the documentation that makes sense, and get such high ROI in a short time period is hugely differentiated for businesses. And I think we all know, as Jason said, we measure response time in nanoseconds, that's how much patience and tolerance we all have on the business side, on the consumer side. So having that, not just this fast search, but the contextual search is table stakes for organizations these days. I'd love for you guys, and on either one of you can take this, to share a customer example or two, that really shows the value of the Algolia product, and then also maybe the partnership. >> So I'll go. We have a couple of partners in two vastly different industries, but both use Algolia as a solution for search. One of them is a, best way to put this, multinational biotech health company that has this-- We built for them this internal portal for all of their healthcare practitioners, their HCPs, so that they could access information, data, reports, wikis, the whole thing. And it's basically, almost their version of Wikipedia, but it's all internal, and you can imagine the level of of data security that it has to be, because this is biotech and healthcare. So we implemented Algolia as an internal search engine for them. And the three main reasons why we recommended Algolia, and we implemented Algolia was one, HIPAA compliance. That's the first one, it's like, if that's a no, we're not playing. So HIPAA compliance, again, the ease of search, the whole contextual search, and then the recommendations and things like that. It was a true, it didn't-- It wasn't just like a a halfhearted implementation of an internal search engine to look for files thing, it is a full blown search engine, specifically for the data that they want. And I think we're averaging, if I remember the numbers correctly, it's north of 200,000 searches a month, just on this internal portal specifically for their employees in their company. And it's amazing, it's absolutely amazing. And then conversely, we work with a pretty high level adventure clothing brand, standard, traditional e-commerce, stable mobile application, Lisa, what you were saying earlier. It's like, "I buy everything on my phone," thing. And so that's what we did. We built and we support their mobile application. And they wanted to use for search, they wanted to do a couple of things which was really interesting. They wanted do traditional search, search catalog, search skews, recommendations, so forth and so on, but they also wanted to do a store finder, which was kind of interesting. So, we'd said, all right, we're going to be implementing Algolia because the lift is going to be so much easier than trying to do everything like that. And we did, and they're using it, and massively successful. They are so happy with it, where it's like, they've got this really contextual experience where it's like, I'm looking for a store near me. "Hey, I've been looking for these items. You know, I've been looking for this puffy vest, and I'm looking for a store near me." It's like, "Well, there's a store near me but it doesn't have it, but there's a store closer to me and it does have it." And all of that wraps around what it is. And all of it was, again, using Algolia, because like I said earlier, it's like, if I'm searching for something, I want it to be correct. And I don't just want it to be correct, I want it to be relevant. >> Lisa: Yes. >> And I want it to feel personalized. >> Yes. >> I'm asking to find something, give me something that I am looking for. So yeah. >> Yeah. That personalization and that relevance is critical. I keep saying that word "critical," I'm overusing it, but it is, we have that expectation that whether it's an internal portal, as you talked about Jason, or it's an adventure clothing brand, or a grocery store, or an e-commerce site, that what they're going to be showing me is exactly what I'm looking for, that magic behind there that's almost border lines on creepy, but we want it. We want it to be able to make our lives easier whether we are on the consumer side, whether we on the business side. And I do wonder what the Go To Market is. Daisy, can you talk a little bit about, where do customers go that are saying, "Oh, I need to Algolia, and I want to be able to do that." Now, what's the GTM between both of these companies? >> So where to find us, you can find us on AWS Marketplace which another favorite place. You can quickly click through and find, but you can connect us through Apply Digital as well. I think, we try to be pretty available and meet our customers where they are. So we're open to any options, and we love exploring with them. I think, what is fun and I'd love to talk about as well, in the customer cases, is not just the e-commerce space, but also the content space. We have a lot of content customers, things about news, organizations, things like that. And since that's a struggle to deliver results on, it's really a challenge. And also you want it to be relevant, so up-to-date content. So it's not just about e-commerce, it's about all of your solution overall, but we hope that you'll find us on AWS Marketplace or anywhere else. >> Got it. And that's a great point, that it's not just e-commerce, it's content. And that's really critical for some industry, businesses across industries. Jason and Daisy, thank you so much for joining me talking about Algolia, Apply Digital, what you guys are doing together, and the huge impact that you're making to the customer user experience that we all appreciate and know, and come to expect these days is going to be awesome. We appreciate your insights. >> Thank you. >> Thank you >> For Daisy and Jason, I'm Lisa Martin. You're watching "theCUBE," our "AWS Startup Showcase, MarTech Emerging Cloud-Scale Customer Experiences." Keep it right here on "theCUBE" for more great content. We're the leader in live tech coverage. (ending riff)

>>Que presents HP Discover 2022. Brought to You by HP >>Good morning, everyone. It's the Cube live in Las Vegas. Day two of our coverage of HP Discover 2022 from the Venetian Expo Centre. Lisa Martin and David want a what a day we had yesterday and today. Unbelievable >>for today. Big Big day today, >>Big day Today we've got a lot. We got some big heavy hitters on talking with HP customers. Partners, leadership. We've a couple of guests up with us next. Going to be talking more about the ecosystem. He's welcome. Corey Dire, the chief revenue officer, Digital Realty and Cliff Evans, senior director. H P E Green like partner ecosystem Guys. Great to have you on the >>programme. Thank you. Great to be here. >>Thank you for having us excited to be here >>with. So that's so that's harness that excitement. Cory, talk to us about the partnership. The announcement? What's going on there with Digital Realty and Green like? >>Yeah, we're crazy excited about it. You know, we've got customers dealing with data, gravity and the opportunity around that and how they could make use of it. And then they're thinking through digital transformation. How how you doing? Multi cloud and they need a partnership. To do that in this partnership with Green Leg and digital is perfect solution for them. So I'm crazy excited to be here with Cliff absolute with all of you to talk about it and hopefully build out a great partnership in relationship with HP. >>Talk to us. Sure, you're crazy Excitement >>club? Absolutely no. I think it is absolutely fantastic Partnership. I think the term is coming together as organisations. Bringing the two platforms together isn't it is an amazing thing that we have for customers, customers we know they want. They want a cloud experience. But really, they want to do that without really the DC footprint that had previously. So how did they do that in a way that really works for them in a secure client secure, sustainable way. But with the cloud experience. Really, the combination of the two pieces coming together really makes that happen, and that is what that's exciting. So we >>dig in to the two things that you mentioned Cory digital transformation and multiply. When I go back to the early days of cloud, it was that girl, you know, nobody's going to do anything you know ever again in the data centre. You know Charles Phillips, the the CEO of in four, famously said, Friends don't let friends, Bill Data centres, right? Everything's going in the cloud. So a lot of people predicted, You know, guys like you were going to be in trouble. The exact opposite happened. The market took off. So you mentioned digital transformation of multi cloud. Can we peel the onion on that? What? What is it about those two items? Are there other trends? They're driving your business, >>you know, You tied right on to to where it started. All enterprises started going to the club and then they got to the cloud and there was more that they needed to make that rial. I talk about multi cloud. You're going to use different cloud providers for different opportunities and different applications. And so you have to start thinking about how does this work in a world where you're gonna go to multiple clouds, multiple locations and what it really drove? It is the need for Cole location to make this because you've got a distributed architecture in order to enable all of this and then having to have us help you out with it. And partners like HP. That's part of where it comes from. But if you think through going to the cloud, can you stay there? Is that the full solution? You need to secure sustainable solution for that. One of the opportunities for us around that is that if you're building data centres for yourself on Prem, you don't have all the cloud access we do. We've got more cloud access points than anybody. So that helps in this digital transformation. >>How How much home? I'm sorry, Didn't mean to you how much homogeneity is there are our clients or customers saying, Hey, I kind of want the same experience in the same infrastructure. Same same. Or they saying, Hey, I want to do stuff in Digital Realty that I can't get from, you know, a cloud provider, Oracle Rack. You know, something like that, >>I would tell you that they come to us from all the partners. So we are partner community. We are not going up the stack anywhere on that. We do are we do our part. We're really good at doing the data centres really good at building data. They descended sustainable. Our position in the market is sustainability around it. We were the first to sign up on the science based initiatives for zero kind of carbon neutrality and in the future in 2030. And so yeah, so I think there's the partner aspect that they need help with on it to drive that Yeah. >>And I think from that from the HP Green Lake perspective, I think customers they very much want that that cloud experience. But I want to do on their own terms. The partnership allows that to happen on Gapen simply the cloud experiencing with the green light cloud platform to really go and deliver that genuine cloud experience and then building cloud services. On top of that, they get all the benefits that they would have from a public cloud experience, but done in the way that they would prefer to do it. So it's bringing those pieces together on >>I think the other side of you asked if it was it was the same across the board and ubiquitous. It's very bespoke. Solutions weaken D'oh! Every customer we have has a different footprint. Most from the multinationals. So we think through where their data is, where it needs to be accessed where their customers are, where their employees are, what makes the most sense. And then the partnership we have with HP into a whole lot for making very bespoke solution for that customer and help them be successful. Journey >>s O on. That s o. So what we've done with destroy lt is we have a specific offer around how we go to market with this really going how customers So we call it Green Light with co location. It's all about really positioning on offer to customers that says, Look, we can go and do this with you and do it simply and really make it happen very quickly and efficiently. So the customer ends up with a single contract in a single invoice for Green Lake Cloud Services on the co location piece, all in one single contracts. That just makes it a lot easier in terms of organising on a really big part of that as well is that our involvement is also spans right from the design to the implementation to support. So we do the whole thing to really help organisations golf and do this. So that's the big for me. The big differentiator. So rather than just having Green Lake in Cloud Services, were saying, Look, we can now do the Coehlo piece and they can really take the whole thing to a whole new level in terms of that public cloud experience >>in the sari and that that that invoice comes from HPD or Digital Realty is bundled into that >>correct? Yes, directly through the channel. We can sell that in a number of different ways. Customers get that that single invoice on a big part of that as well, just going a little bit deeper on that. So what we do is we We use a part of the company called Data Centre Technology Services, which are a great kind of consulting organisation with tremendous experience and something like 3000 projects across 40 countries from the very smallest of the very largest of data centre implementation. So all of that really makes the whole thing a lot easier from a customer's perspective in terms of designing, implementing and then supporting. So you pull all of that together. It's fantastic >>and I think it's really changed to add on to that partner in prison. So customers, now we're thinking about it differently and data centres differently, and they see us as a strategic partner along with HP. To go after this used to be space, power and calling. Now it's How much connectivity do you have? What your sustainability profile? What's your security profile? How do you secure this data? Date is the lifeblood of all these companies and you have to have a really secure, sustainable solution for them, >>right? That's absolutely critical for every industry. Talk about the specific value prop at a bespoke co location solution delivers to customers. Maybe you got a favourite customer example that you think really articulates the value of this partnership. >>So I think a combination. So so I think we touched on a lot of it, actually. So there's obviously the data centre aspect itself in terms of with the footprint that realty have across the world, you can pick and choose the data centre in the class of data centre that you want in terms of your Leighton see and connectivity that you want. Then really, it's the green make peace in terms of the flexibility that you get with that really is that value. And as I touched on the Green Lake with Cole Oh, I think for me is from our perspective, I think the biggest piece of value that we provide there to really go make it happen. Yeah, >>there's about 70 applications right now that are part of Green Lake Polo that you can bespoke for what you need to. You can think around your specific solutions that you need, and we've got it all right there with HP Green like and follow for us. And because we have a 290 data centre footprint across 50 markets, it gives us the opportunity really be the data centre provider in the Partner for H P, pretty much anywhere but with connective ity everywhere. >>When you say 70 applications, these the 70 services are you talking about talking >>about? Okay, Category 70 services. There's a lot of stuff. >>Cory, when you talked about sustainability a couple of times, is a really important ingredient of the customer decision. Why is it because they're indirectly paying the power bill or is because that's the right thing to do? And they care. There's increased. People care about it more because you go back a while ago. People way always talked about green it, but it was all lip service. Is that changing or is that there? Is there an economics >>changing in a really big way? Almost every conversation I have with customers is how are you doing Sustainability. So if they're doing an on Prem, that's not their core capabilities. They don't know how to do that. On our end, I mentioned our SP R science based initiatives that we signed up for. But how do we enable that? Enable it for how do we build in designer data centres? How do we actually work them and operate them? And then how do we go after all the green sources of sustainable energy including, I think since 2015, we've issued six billion in green bonds around that same support of it. So yeah, >>and your customer can then I presume, report that on their sustainability report a >>good way to think about it. You no longer have your data centre at its sometimes less efficient way than way are we're really good at building sustainable data centres, and then you can actually get some credits back and forth, >>just from agreement. Perspective. So Green Lake. So there's a specific Forrester Impact report that looks a green lake on how it how it performs from sustainability. Perspective on Greenlee really is giving you their 30% reduction in your energy consumption. So there's a big kind of win there as well, I think. Which is then, >>why? Where does that come from? >>So it Zim part that kind of the avoidance of over provisioning such that you going right size things, Then you have you have you have a certain amount of reserve capacity that you're using them just using the extra consumption piece when you need it. So rather than having everything running at full speed, it really is kind of struggling as to how that work. So you get a combination of effects >>with consulting and the thoughtfulness around this bespoke solution that you have. You end up needing fewer servers, pure technology that drives less power consumption and therefore you get a lot of this same really base it down. You >>talked about the savings you talked about the simplification delivery perspective. Talk about the implementation. What's the time to value that Organisations can glean from this partnership >>superfast So So yeah this This does accelerate the whole process from from initial kind of opportunity if you like and customer inquiry through to actual implementation So previously this would take considerable amount of time in terms of to ing and froing between multiple organisations on Now what we do is coordinate that do it efficiently and effectively So D. C. T s Data Sentinel services team very closely. Just have those connections often do those things incredibly quickly and it does accelerate the whole time >>and they're tied in with our team is well around. Where's the leighton? See where the solutions Because we're really thinking about what is your stack looked like from an HP perspective, but then where you need to deploy it so that you have access to the clouds You have the right proper Leighton see across your environment and you really haven't distributed architecture that works the best for you and your company. >>So this is probably answer those questions Probably both, but I'm asking anyway, I've always been a repatriation sceptic, but I'm happy to be proven wrong. You guys have other data. And maybe this is part of what one of my blind spots question is, is what's driving your business in terms of the EU's case? Is it organisations saying Hey, we want to get out of the data centre business way Don't want to put everything into the cloud but we're going to go on a digital realty and being green leg and we're gonna move into that cola Or is it? People say, You know, while we over rotated into the cloud, you were going to come back. So it's >>both. It's both, >>Yeah, in the empire. The credit. >>I think there are a lot of customers with good intentions on going to the cloud, and then there's some cost with it that maybe they didn't fully factor in it at that time. And now you've got the ability around these bespoke solutions to really right size every bit of this. And when they originally did it, they didn't think through a distributor architecture. They thought my own prim, and then I'm just gonna burst everything that a cloud that's no longer the case, and it's not really the most efficient way to your point about repatriation. They start pulling their storage back in. Well, where do you want your data? Where do you want your storage? You wanted as close as you can to the clouds for that capability and in a solution that's wrapped around it makes it very simple for you. >>I think the repatriation is very real and is increasing, eh? So we're seeing a lot of it in terms of activity and customers really trying to understand the cost that they're incurring now from a public cloud perspective. And how can they do that differently? In fact, with combined offer that we have it, it makes it a lot easier to compare. So, yeah, that really is accelerating because you don't >>see it in the macro numbers. I mean, just to be honest, you see the cloud guys combined growing 35%. And is that because your business is in transition from traditional on prime model, too, and as a service model, and so you've got that imbalance and it gets hidden in >>all that, and I think it's I think it's a new wave of things that are happening. Yeah. I mean, there's a there's a lot of things, obviously, that makes complete sense to me in Public Cloud, but I do think there's been an over rotation towards it, so I think now that realisation and it's going to take time to kind of pick that. But it's absolutely happening. There are a lot of opportunities that we've gotten some very big ones I'd love to talk about. Can't quite talk about them just get but really, where there's big, big savings in terms of what they're paying from a public cloud perspective, Really, what they want is that full management cloud service to go make it happen. So the combination of the data centre piece to Green Lake piece and then some management services, whether they're from ourselves or from party community, from manage service providers that we also work with, that gives them the complete package. >>So I have another premise. A lot of it, of course, is traditionally been focused on internal, and I feel like there's a new era coming. It's talks of the ecosystem. Are you seeing customers not only running there it in digital realty and connecting to the cloud in a hybrid fashion, but also actually building new value and building businesses that are customer facing on that that air monetize herbal. Are you seeing that? Is that happening and having examples, even generic? >>Well, basic from our perspective, our partner community, that's what they do. We have a tonne of enterprise customers, but I'll need to connect and integrate the data that you have doesn't do anything for you, Fitz on its own. And it's not interacting with other data points. And it's not around interacting with other customers, other solutions in one night. So it does help build out a partner community, a solution community for our customers in our data centres and across the >>are their industry patterns emerging. In other words, is that data ecosystems emerging by industry or is a sort of or horizontal? >>There's a mix. So I think there's a lot of lot of financial sector stuff. Yes, certainly. And then certainly manufacturing s O. I think it's interesting that you're getting a bit of a combination, but not a lot of financial sector. >>Of course, the big bags early on that they could build their own cloud. Yeah, now they're probably rethinking that. Yeah, well, maybe >>they're also service providers. When you're that large a za bank on their end. They're doing a lot of work. E. I would also say the other part that a lot of people see as an opportunity is around all the HPC and AI applications as well, in addition to manufacturing distribution. So there's a lot of use cases, a lot of reasons, like us from sort of doing this >>wrap us up with value, perhaps that you're talking Torto Financial Services Organisation or a manufacturing company. What is that 32nd elevator pitch value problem? Why they should go HP Making Digital Realty together. >>So I would say green, like Rico location gives you a single contract. Singling voice, easy to go and design, implement support and go make happen. Sorry, that's very simple way say, very just make it easy >>on. And I would just say thank you on that. It's been great to speak with you guys. And yeah, when you think through that part of it also is a bespoke opportunity to put your data where it needs to be closer to your customers. Closer to the action you were thinking through the rape reiteration of it. A lot of it's being built out there on phones and whatnot. So you've got to think through where your data is and how you managed to >>write and enable every every company in every industry to be a data company. Because that's what, of course, the demanding consumers demanding that demand isn't it is not going to turn down right now. Absolutely. Just thanks so much for David. Very much. Thank you. Together in the ecosystem, there are guests. And Dave l want a I'm Lisa Martin. You're watching the key of live from the Venetian Expo Centre in Vegas, Baby. David, I will be back there next guest in a minute.

>> TheCUBE presents Dell Technologies World, brought to you by Dell. >> Hey, welcome back to theCUBE's coverage day three. From the show floor of Dell Technologies World 2022. We've been here with about seven to 8,000 people. It's been outstanding since Monday night, Lisa Martin with Dave Vellante, and we have two of the ladies from Dell digital with us, excited to welcome Jaynene Hapanowicz and Betsy Davis, leaders in Dell digital, which is Dell's IT organization. Ladies, thanks for joining Dave and me. >> Thanks for having us. Great to be here. >> Jaynene, let's start with you. We've heard a lot this week about the need for IT leaders to think very meaningfully on how to leave a lasting legacy. How in today's dynamic environment do IT leaders do that? >> Yeah. Well look, let's start with IT leaders have a pretty tough job. You're trying to stabilize an environment. You're trying to take care of anomalies, security incidents. Like that's the blocking and tackling, except you also have to transform your organization at the same time. And I think it's really important that you build a strategy that enables you to do both those things. So you have to do, you have to do the blocking and tackling or you don't get a seat at the table, but the other things that you have to prioritize are things like building the business relationships, putting your customer at the center of what you do, and building great teams that trust you and you trust them to develop capabilities that you need for the future. And your strategy has to support both of those things. >> We've heard a lot about trust this week, specifically from Mr. Dell himself, Betsy you've spoken in the past about the need for IT and the business to collaborate. There has to be trust there. How do you advise folks to accomplish that true collaboration? >> Yeah, it's look, trust is so important and it's funny because last time we were here live at a CUBE session, we were talking about the product model, which is how we do things in Dell Digital now. And it's all focused on jointly with the business, agreeing on human-centered outcomes, starting small, iterating and together you deliver extraordinary things. And so over the last few years, building collaboration through that product model has done tremendous things. I would say what we're learning more about more recently is how to extend that. Especially when you're taking multiple legacy regional tools and globalizing them, how do you extend it to policies and processes? But what we're finding that's interesting is, the same principles apply, agree on outcomes. What are you going for? And then work through it together. You don't assign it to one side or the other. It's truly a collaboration exercise. >> You know, I want to comment. So Dell has a culture, obviously. Founder led company, chairman's name is on the name of the company, Say:Do ratio, trust, et cetera. It seems like Dell Digital has its own little culture going on. And the reason I say that is, when Jen felt was up on stage yesterday, I heard a lot of yelling, screaming, hooping, people were standing up. That didn't seem like a typical IT department thing. You know, that was pretty cool. So what's the Dell Digital culture like, is it just an extension? Is it? What's it like? >> Yeah, yeah. Well, I think our leader who we admire very much, which you saw yesterday has built a great leadership team and a culture that her leaders trust each other and that cascades down. And I think our employees, like all of our folks, they love working in Dell Digital, and they love working at Dell digital because we empower them to do their jobs. We let them work where they need to work, and we have, I think, great leadership at every level to really help people propel the company forward. We have a single mission and that mission is to make Dell better. >> I like the, thank you for that. I like the way Betsy, you were talking about the, I called the product mindset. >> Yep. >> As opposed to commonly in IT, there's a project mindset. Ah, I got another project to do. >> Yeah. >> Explain the difference. >> So a project is, some people might say waterfall, it's a very old school way of doing things where you say, okay, business give me requirements. They take six months, They come up with a list of requirements. Your IT team goes off and deliver in those requirements. And two years later you come back together and go, oh, that's not what we were looking for, and it's delayed by now. So product model is really focused on, hey, let's do short sprints. Let's agree the outcome, let's attempt to deliver it, but if we deliver it and then find out, oh, that's actually not what we were looking for, then you just iterate and you haven't wasted two and a half years. And it's also quite frankly, as a leader, it's a lot more fun to lead teams in that environment, because you're constantly getting wins and they're getting that constant reinforcement of look at the impact you're making for the business. Which is a great motivator for all of us at Dell Digital. >> Quick follow up if I may, is the enabler there a mindset or is it technology? Why are you able to do that? >> It's both. So part of what makes that possible, is our modern environment. Jaynene has done an incredible job, really building a modern toolkit for our developers that makes it easier to collaborate and move quickly and iterate. But so much of it is that product model mindset of, okay, what outcomes are we delivering? What's the smallest unit of work we can break that into and let's just go and iterate. >> And you put the user in the center, like it's so much easier to develop what a customer needs, if the customer is at the center of what you're trying to do, and you iterate from there. That wasn't the way that it has historically worked. >> So how do you advise it leaders to become transformational like this rather than traditional? Because I imagine those traditional ones, those businesses may not survive the changing times that we're living in, but being transformational that's a challenging mindset, especially for organizations that are legacy or history, have been there a while. Can you advise? >> I mean, you have to fire on all cylinders, that old people process and technology is actually still true. Building a great culture and building a culture of trust, super important, but you got to pull your folks along with you on a journey. You have to have leadership that buys into doing both transformation and running the business. You have to, your technology has to support what you're trying to do. You can't expect great outcomes from things that are 20 years old, You're not going to get it. And your processes, they have to be adjusted to reflect a cloud operating model. A lot of companies even struggle with that, because they're using processes from a decade ago, and they need to update those policies to reflect what it is to operate like a cloud, in a cloud. And how have you guys accelerated this culture and this mindset during the last couple of years where things just went crazy overnight? What was that acceleration like? 'Cause we talked about digital transformation acceleration with your customers, but you guys have had to transform too. >> Yeah, and you know, I look at it from a leadership angle. I think these last couple years have really given us an opportunity to take what we took in the product model of human-centered experiences for our customers and business partner, and really focus on, hey, we need to be human centered leaders. So in some ways that was easier to do with Dell because we were always very flexible on where people work, when they work, et cetera. But I think we've had the opportunity these last couple years to demonstrate, hey, it really is about our people first, we set our people up for success. We help them take care of their immediate needs, whether those be personal or work and everything else works out. And I think companies that keep that in the forefront and always approach things from a human center perspective, whether that's leadership or experiences in the product model, always come out ahead. >> How are you faring in the talent war? My specific question is, if I were younger and a perspective employee, how would you recruit me in terms of how you would nurture my career? What's my future look like? What would you tell me? >> Yeah, I, well, first of all, let's start with the talent war. That, I mean, look, it's real. Our folks are getting recruited like crazy too. Except I think there is a cultural aspect that really causes folks to pause. I also think enabling people to work where they want to work or where they need to work, it's both, that has helped us in our recruitment because the advantage of people do not want to go back to the office. Like, I don't know, I'm speaking for like probably myself and everybody I talk to. I just don't think people want to go back to the office, but we're benefiting from that, because we are actually drawing in talent from companies that are sending folks back to the office. And we gave our employees remotely great tools to be able to work from home. And that has all been a win for us in terms of retaining our staff and drawing in new talent. And I think the other thing and it's a very important point that you raise, is that the future is working in modern tool sets. And one of the things that we did and Jen spoke about yesterday, was around developers want to develop and you've got to give them the tools that they need to perform their jobs as quickly as possible, because digital transformation is ultimately about creating applications that drive business value. >> I think I'm the only one that probably here that wants to go back to the office. If I do one more Zoom call from home, I might go puke. >> I go to the office, but I'm like 15 minutes away, so. >> Oh, I'm about 30 seconds away to really look at my commute. Let's talk about from that cultural perspective and the great resignation, all the things that are going on. You talked about folks getting recruited, that flexibility of meeting your, as you said Jaynene meeting the employees where they are is the same culture that Dell has about meeting its customers where they are. And that's really kind of the foundation of a lot of the announcements that we've heard over the last few days, is really that flexibility to be able to deliver what a great customer experience and a great employee experience. I think to me, they're inextricably linked. >> So I totally agree. >> So this notion of work remotely, et cetera, great. Most people, like you said right now are saying I'm not going back. And I think some kind of hybrid is probably going to be the norm. >> Agree. >> That's cool. But we have a tendency to work longer laps times from home. And so there's that even weekends, it's like everybody's always on we should never get emails on Saturday, now I'm like, I got to look, of course spend an hour or two hour, whatever it is. So how do you balance that with folks? What do you tell people in your organization? >> Yeah, I mean, we're very focused on our employees having quality of life, now we're in IT. Like, let's be real. We have always worked weekends. But I think what we're really really being very thoughtful about, is that balance for our employees that we're not creating more stress in their lives. Like we want them to have a great quality experience. A lot of that happens with the technology that we have built under the covers, because that has allowed our developers to work less weekends and has allowed our folks to release independently, which is kind of in the world of IT, that's the utopia, you want to get to let folks work independently. And that has actually freed up the time for developers to have to work as if we all work together, and now they can work independently. And that has actually helped with quality of life. So it's, it is still though a combination of all those things. It is also having leadership team that values that. And I think that's what we have. >> What's cool about this conversation. We're talking about IT, we haven't even, we haven't talked tech. Now are you guys techies? >> Yeah. >> You are? >> Yeah. >> Okay. So one of the things, I was in one of these private analyst meetings, a handful of analysts with (indistinct) and I was asking her about the cloud migration, that's a lot of CIOs top priority. It's obviously, her response essentially was, yeah, well, we are modernizing our infrastructure, That's essentially our cloud. We've got our own cloud. I wonder if you could like double click on that a little bit. 'Cause security number one for most IT organizations, cloud number two, she translated that into, way I interpret that data is modernization. I wonder if you could give us your perspective on that. >> I think the first thing as you map out, hey, what do we want our modern environment to be? And you make those technology decisions, just like with our people, we need to design optionality in and make sure that we stay as flexible and nimble as we can. The same is true for our technology environment. So that's why you see whether we're talking about what we offer to our customers or how we're modernizing our environment. We want to make sure we've got flexibility and optionality because what we do all know is we don't know what the future will bring. >> How did you guys get into tech? When did you fall in love with technology? >> How many years ago? >> No, like, like what was, was there something in your life that like appealed to you or? >> It's actually really funny story. My father was a mainframe programmer, so. >> Okay, So he was doing COBOL. >> I swear I wanted nothing to do with it. And then I found myself in those shoes. >> Yeah. Horrible. >> Yeah, horrible. >> It's in your DNA. >> I think so. I think so. >> Okay. So you just, when things started to get more modern. >> I just thought it was interesting. Like I'm almost 30 years in. Like I just thought it was really interesting. >> That's awesome. >> And I still think it is. >> How about you Betsy? >> I actually started on the business side, so I worked with IT through my 20 years at Dell. And when they started shifting to the product model, I was a business partner and I saw these incredible outcomes we were delivering to. And I'm like, oh, look at that cool technology. We were doing like optical character recognition to automate it. It was just, it was super cool. And you know, I'd known Jen for a long time and she said, well, why don't you come over to Dell Digital? And I did, it's been, it been a blast but I started as a business partner. >> But you, then you bring that understanding of the business the outcomes focused to the IT side. And that's probably why you guys make it sound like it's so simple to facilitate the IT business collaboration that so many businesses struggle with >> The magic is to make it simple. >> I agree. >> Yeah totally. >> It's not easy. >> No, it's not easy, but it's possible. >> Well, and that's what drives adoption. >> How have in our final minute or so here, how have the customers, we know what 15,000 customers globally, great customers on stage. We've had some customers on the show this week. How have they been influential in terms of the modernization of Dell Digital in especially the last two years, any interesting stories of customer influence you can share. >> In terms of our modernization efforts? >> Yeah. >> Yeah, I mean, look, we share all the time with customers on best practices in IT. And I would really say we have also moved an organization and solved many of the problems, the very problems our customers are trying to address through much of what we've developed within IT. And I think customers are very interested in learning from us and helping them on their own transformation journey. >> Excellent, ladies thank you so much for joining Dave and me talking about really what's under the covers of Dell Digital, but it's really about people, process and technologies and collaboration. >> That's right. >> Great use case (indistinct). We appreciate your time. >> We appreciate it back. >> Thanks for Dave Vellante. I'm Lisa Martin and you're watching theCube's coverage of Dell Technologies World, live from the show floor in Las Vegas. Stick around and be right back with our next guest. (gentle music)

(upbeat music) >> I'm Dave Nicholson and welcome to Dell Technologies World 2022. I'm delighted to be joined by Tony Bishop. Tony is senior vice president, enterprise strategy at Digital Realty. Tony, welcome to theCUBE. >> Thank you, Dave. Happy to be here. >> So Tony, tell me about your role at Digital Realty and give us a little background on Digital Realty and what you do. >> Absolutely, so my job is to figure out how to make our product and experience relevant for enterprises and partners alike. Digital Realty is probably one of the best kept secrets in the industry. It's the largest provider of multi-tenant data center capacity in the world, over 300 data centers, 50 submetros, 26 countries, six continents. So it's a substantial provider of data center infrastructure capacity to hyperscale clouds to the largest enterprise in the world and everywhere in between. >> So what's the connection with Dell? What are you guys doing with Dell? >> I think it's going to be a marriage made in heaven in terms of the partnership. You think of Dell as the largest leading provider of critical IT infrastructure for companies around the world. They bring expertise in building the most relevant performant efficient infrastructure, combine that with the largest most relevant full spectrum capability provider of data center capacity. And together you create this integrated pre-engineered kind of experience where infrastructure can be delivered on demand, secure and compliant, performant and efficient and really unlock the opportunity that's trapped in the world around data. >> So speaking of data, you have a unique view at Digital Realty because you're seeing things in aggregate, in a way that maybe a single client wouldn't be seeing them. What are some of the trends and important things we need to be aware of as we move forward from a data center, from an IT perspective, frankly. >> Yeah, it's an excellent question. The good part of the vantage point is we see emerging trends as they start to unfold 'cause you have the most unique diverse set of customers coming together and coming together, almost organized like in a community effect because you have them connecting and attaching to each other's infrastructure sharing data. And what we've seen is in explosion in data being created, data being processed, aggregated, stored, and then being enriched. And it's really around that, what we call the data creation life cycle, where what we're seeing is that data then needs to be shared across many different devices, applications, systems, companies, users, and that ends up creating this new type of workflow driven world that's very intelligent and is going to cause a radical explosion in all our eyes of needing more infrastructure and more infrastructure faster and more infrastructure as a service. >> Yeah, when you talk about data and you talk about all of these connectivity points and communication points, talk about how some of those are explained to us. Some of these are outside of your facilities and some of them are within your facilities. In this virtualized abstracted world we live in it's easy to think that everything lives in our endpoint mobile device but talk about how that gravity associated with data affects things moving forward. >> Absolutely, glad you brought up about the mobile device because I think it's probably the easiest thing to attach to, to think about how the mobile device has radically liberated and transformed end users and in versions of mobile devices, even being sensors, not just people on a mobile phone proliferating everywhere. So that proliferation of these endpoints that are accessing and coming over different networks mobile networks, wifi networks, corporate networks, all end up generating data that then needs to be brought together and processed. And what we found is that we've found a study that we've been spending multiple years and multiple millions of dollars building into an index in a tool called the Data Gravity Index where we've been able to quantify not only this data creation life cycle, but how big and how fast and how it creates a gravitational effect because as more data gets shared with more applications, it becomes very localized. And so we've now measured and predicted for 700 mentors around the world where that data gravity effect is occurring and it's affecting every industry, every enterprise, and it's going to fundamentally change how infrastructure needs to be architected because it needs to become data centric. It used to be connectivity centric but with these mobile phones and endpoints going everywhere you have to create a meeting place. And it has to be a meeting place where the data comes together and then systems and services are brought and user traffic comes in and out of. >> So in other words, despite your prowess in this space you guys have yet to solve the speed of light issue and the cost of bandwidth moving between sites. So is it fair to say that in an ideal world you could have dozens of actually different customers, separate entities that are physically living in data center locations that are built and posted and run by Digital Realty, communicating with one another. So when these services are communicating instead of communicating over a hundred miles or a thousand miles, it's like one side of the chicken wire fence to the other, not that you use chicken wire in your data center but you get the point, is that fair. >> It is, it's like the mall analogy, right? You're building these data malls and everybody's bringing their relevant infrastructure and then using private secure connections between each other and then enabling the ability for data to be exchanged, enriched and new business be conducted. So no, physics hasn't been solved, Dave, just to add to that. And what we're finding is it's not just physics. One of the other things that we're continuing to see and hear from customers and that we continue to study as a trend is regulations, compliance and security are becoming as big a factors as physics is. So it's not just physics and cost which I agree with what you're saying but there's also these other dimensions that's in effect in placement, connectivity in the management of data and infrastructure, basically, in all major metros around the world where companies do business and providers support them, or customers come to meet them both physically and digitally. It's an interesting trend, right? I think a number of the industrians call it a digital twin where there's a virtual version and of a digital version and a physical version and that's probably the best way to think of us, is that secure meeting place where each can have their own secure infrastructure of what's being digitized but actually being placed physically. >> Yeah, that's interesting. When you look at this from the Dell, Digital Realty partnership perspective we know here at theCUBE that Dell is trying to make consumption of what they build, very, very simple for end user customers. Removing the complexity of the underlying hardware. There's a saying that the hardware doesn't matter anymore. You hear things referred to as serverless or no code, low code, those sort of abstract away from the reality of what's going on under the covers. But APEX, as an example from Dell allows things to be consumed as operational expense, dramatically simplifying the process of consuming that hardware. Now, if you go down to almost the concrete layer where Digital Realty starts up, you're looking at things like density and square footage and power consumption, right? >> Yep. >> So tell me, you mentioned infrastructure. Tell me about the kind of optimization from a hardware standpoint that you expect to see from Dell. >> Yeah, in the data center, the subset of an industry, they call it digital or mission critical infrastructure, the space, the power, the secure housing, how do you create physical isolation? How do you deal with cooling and containment? How do you deal with different physical loads? 'Cause some of the more dense computers likely working with Dell and some of the various semiconductors that Dell takes and wraps into intelligent compute and storage blocks, the specialized processing for our use cases like artificial intelligence and machine learning, they run very fast, they generate a lot of heat and they consume a lot of power. So that means you have to be very smart about the critical infrastructure and the type of server infrastructure storage coming together where the heat can be quickly removed. The power is obviously distributed to it, so it can run as constant and as fast as possible to unlock insights and processing. And then you also need to be able to deal with things like, hey, the cabling between the server and the storage has to be that when you're running parallel calculations that there's an equal distance between the cabling. Well, if I don't think about how I'm physically bringing the server storage and all of that together and then having space that can accommodate and ensure the equal cabling in the layout, oh and then handle these very heavy physical computers. So that physical load into the floor, it becomes very problematic. So it's hidden, most people don't understand that engineering but that's the partnership that why we're excited about with Dell is you're bringing all that critical expertise of supporting all those various types of use cases of infrastructure combinations and then combining the engineering understanding of how do I build for the right performance, the right density, the right TCO and also do it where physical layout of having things in proximity and in a contiguous space can then be the way to unlock processing of data and connecting to others. >> Yeah, so from an end user perspective, I don't need to care about any of what you just said. All I heard was wawawawawa (chuckles). I will consume my APEX delivered Dell by the drink, as a service, as OPEX, however I want to consume it. But I can rest assured that Digital Realty and Dell are actually taking care of those meaningful things that are happening under the hood. Maybe I'm revealing my long term knuckle dragging hardware guy credentials when I just get that little mentioning. >> (indistinct) you got it, performance secure compliant and I don't need to worry about it. The two of you're taking care of it and you're taking care of it for me. And every major mentor around the world delivered in the experience it needs to be delivered in. >> So from the Digital Realty point of view, what are the things that not necessarily keep you up at night worrying, but sort of wake you up in the morning early with a sense of renewed opportunity when it comes to the data center space, a lot of people would think, well we're in the era of cloud, no one's building any data centers except for monster cloud players. But that's definitely not the case, is it? There's a demand for what you folks are building and delivering. So first, what's the opportunity look like and then what are the constraints that are out there? Is it dirt, is it power? What are the constraints you face? >> We have probably all the above, is the shortest answer, right? So we're not wawawa, right Dave? But what we are is the opportunity is huge because it's not one platform, there's many platforms there isn't one business that exists today that doesn't use many applications, doesn't consume many different services both internally and externally, and doesn't generate a ton of data that they may not even know where it is. So that's the exciting part. And that continues to force a requirement that says I need to be able to connect to all those clouds which you can do at our platform but I also need to be able to put infrastructure or the storage of data next to it and in between it. So it's like an integration approach that says if I think physical first think physical that's within logical proximity to where I have employees, customers, partners, I have business presence. That's what drives us, and in our industry continues to grow both. And we see it in our own business. It's a double digit growth rate for both commercial oriented enterprises and service providers in the telco cloud, or content kind of space. So it's kind of like a best of both worlds. I think that's what gets us excited. If I should take a second part of the question, what ends up boring is like all of us, it is a physical world, physical world start with, do we have enough power? Is it durable, sustainable and secure? Is it available? Do we have the right connectivity options. Keeping things available is a full-time job, making it so that you can accommodate local nuances when you start going in different regions and countries and metros there's a lot of regional policy compliance or market specific needs that have to be factored in. But you're still trying to deliver that consistent physical availability and experience. So it's a good problem to have but it's a critical infrastructure problem that I would put in the same kind of bucket as power companies, energy companies, telecommunication companies, because it's a meeting place for all of that. >> So you've been in this business, not just at Digital Realty but you you've been in this part of the IT world for a while. >> Yeah. >> How has the persona of a customer for a Digital Realty changed over time? Have we seen the kind of consolidation that people would expect in this space in terms of fewer but larger customers coming in and seeking floor space? >> Well, I think it's been the opposite of what probably people predict. And I pause there intentionally being very candid and open. And it's probably why that using data as the proxy to understand, is that it's a many to many world that's only getting bigger, not smaller. As much as companies consolidate, there's more that appear. Innovation is driving new businesses and new industries or the digitization of old industries which is then creating a whole multiplier effect. So what we're seeing is we're actually seeing a rapid uptake in the enterprise side of our business which is why I'm here in driving that. That really was much more nominal five years ago for being the provider of the space and capabilities for telcos and large hyperscalers continues to go because it's not like a once and done, it's I need to do this in many places. I need to continue to bring as there's a push towards the edge, I need to be able to create meeting places for all of it. And so to us, we're seeing a constant growth in more companies becoming customers on the enterprise side more enterprises deploying in more places solving more use cases. And more service providers figuring out new ways to monetize by bringing their infrastructure and making an accessibility to be connected to on our platform. >> So if I'm here hearing you right, you're saying that people who believe that we are maybe a few years away from everything being in a single cloud are completely off base. >> Mmh hmm. >> That is not the direction that we're heading, from your view, right? >> We love our cloud customers, they're going to continue to grow. But it's not all going to one cloud. I think what you would see is, that you would see where a great way to assess that and break it down is enterprise IT, Gartner's Forecast 4.2, four and a half trillion a year in spend, less than a third of that's hitting public cloud. So there's a long tail first of all, it's not going to one cloud of people. There's like seven or eight major players and then you go, okay, well, what do I do if it's not in seven or eight major players? Well, then I need to put it next to it. Oh, that's why we'll go to a Digital Realty. >> Makes a lot of sense. Tony Bishop, Digital Realty. Thanks for joining us on theCUBE. Have a great Dell Technologies World. For me, Dave Nicholson, stay tuned more live coverage from Dell Technologies World 2022 as we resume in just a moment. (soft music)

(upbeat music) >> Welcome to theCUBE. I'm Dave Nicholson, and this is part of the continuing conversation about Managing Risk in the Digital Supply Chain. I have with me today Vincent Danen, vice president of product security from Red Hat and Luke Hines security engineering lead from the office of the CTO at Red Hat. Gentlemen, welcome to theCUBE. >> Thank you. >> Great to be here. >> So let's just start out and dive right into this, Vincent, what is the software or digital supply chain? What are we talking about? Yeah, that's a good question. Software supply chain is basically the software that an end user would get from a vendor or in our case, we're talking about open source, so upstream. It is the software that comes in that is part of your package, operating system, applications. It could be something that you get from one vendor, multiple vendors. So we look at in the example of Red Hat, we are one part of the customer's software supply chain. >> So it's interesting that it's coming in from different areas. Do we have a sense for the ratio of kind of commercial software versus open source software that makes up an enterprise today? >> I think that's a really hard thing to answer and I think every enterprise or every company would have a little bit different. Depends if you have an open source vendor that you choose, you may get a significant amount of software from them. Certainly you're not going to get it all. As an example, Red Hat provides thousands of open source packages. We certainly can't provide all of them. There are millions that are out there. So when you're looking at a specific application that you're building, chances are, you could be running that on a managed platform or an enterprise supply platform, but there are going to be packages that you're going to be obtaining from other sources in other communities as well in order to power your applications. >> So, Luke, that sounds like a kind of a vague situation we're looking at in terms of where all of our software is coming from. So what do we need to know about our software supply chain in that context? What do we need to understand? Before we even get anywhere near the idea of securing it, what are some of the issues that arise from that? >> Yeah, so Vincent's touchpoint is a very wide range in ecosystem, multiple sources when we're talking about open source. So essentially awareness is key really. I think a lot of people are really not aware of the sources that they're drawing from to create their own supply chain. So there's multiple supply chains. You can be somebody like Red Hat that the provide software, and then people will leverage Red Hats for their own supply chain. And then you have the cloud provider and they have their own source of software. So I think that the key thing is the awareness of how much you rely upon that ecosystem before we look at the security of the supply chain. It's really understanding your supply chain. >> And just to follow up on that. So can you... I'm sort of checking my own level of understanding on this subject. When you talk about open source code, you're talking about a code base that is often maintained essentially by volunteers, isn't that correct? >> A mix of volunteers and paid professionals where a company has an interest in the open source project, but predominantly I would say it's... Well, I'm not entirely sure, but volunteers make up a substantial part of the ecosystem that is for sure. So it's a mix really. Some people do it because they enjoy writing software. They want to share software. Other people also enjoy working software, but they're in the position that a company pays for them to work on that software. So it's a mix of both. >> Vincent, give us a reminder of reminder of why this is important from a little bit of a higher level. Step back from the data center view of things, from the IT view of things, just from a societal perspective, Vincent, what happens when we don't secure our digital supply chain? What are the things that are put at risk? >> Okay, well, there's a significant number of things that are placed at risk, the security of the enterprise itself. So your own customer data, your own internal corporate data is place at risk if there were a supply chain breach. But further to that for a software provider, and I think that in a lot of cases, most companies today are software providers or software developers. You actually put your own customers at risk as well, not just their data, but their actual... The things that they're working on, any workloads that they may have, an order that they might place as an example. So there's a number of areas where you want to have the security of that supply chain and the software components that you have figured out. You want to be on top of that because there is that risk that trickles down when it comes to an event. I mean, we've seen that with breaches earlier this year, one company is breached multiple companies end up being breached as a result of that. So it's really important. I think we all have a part to play in that I always view it as it's not just about the company itself. So I mean, speaking from a Red Hat perspective, I don't look at it as we're just securing Red Hat, we're securing our customers, and then we're also doing that for their customers as well, because they're writing software that's running on the software that we're providing to them. So there is this trickle down effect that comes, and so I think that every link in that chain, I mean, it's wonderful that it's called a supply chain. It's only as strong as its weakest link. So our view is how do we strengthen every link in that chain? And we're one part of it, but we're kind of looking a little broader, what can we do upstream and how can we help our customers to ensure the security of their part in that supply chain? >> Yeah, I want to talk about that in a broad sense, but let's see if we can get a little bit more specific in terms of what some of the chains look like because it's not just really one chain when you think about it, there's the idea of inherent flaws that can be caught and then there are the things that bad actors might be doing to leverage those flaws. So you've got all of these different things that are converging. So first and Vincent, if you want to toss this to Luke back and forth, it's up to you guys. What about this issue of inherent flaws in code? We referenced this idea of the maintainer community. What are best practices for locking that down to make sure that there aren't inherent flaws or security risks? >> I'll take a stab at it, and then I'll let Luke follow up with maybe some of the technologies that Red Hat provides. And again, speaking to Red Hat as part of that chain. When we're talking about inherent risk, there's a vulnerability that's present upstream. We pull that software to Red Hat. We package it as a component of one of the pieces of software that we provide to our customers. It's our responsibility to pay attention to those upstream potential vulnerabilities, potential risks, and correct them in our code. So that might be taking a patch from upstream, applying it to our software, might be grabbing the latest version from upstream, whatever the case might be, but it's our responsibility to provide that protection for that software to actually remediate that risk, and then our customers can then install the update and apply the mitigation themselves. If we take a look at it from, when we're looking at multiple suppliers where you'd asked earlier about, what part of it is Red Hat and what part of it is self-service open source? When you look at that, the work that Red Hat's doing there as a commercial provider of open source and end user for that little bit that they're going to grab themselves, that Red Hat doesn't provide, it's going to have to do all of those things as well. They're going to have to pay attention to that risk from upstream. They're going to have to pay attention to any potential vulnerabilities and pull that in to figure out, do I need to patch? Where do I need to patch it? And that's something we didn't really touch on was an inventory of the software that you have in place. I mean, you don't know that you need to fix something. You don't even know that it's running. So, I mean, there's a lot of considerations there where you have to pay attention to a lot of sources. Certainly there's metadata, automation, all of these things that make it easier, but it doesn't absolve us of the responsibility across the board to pay attention to these things, whether you're grabbing it from upstream directly or from the vendor. And it's the vendor's responsibility to then be paying attention to things upstream. >> Yeah, so Luke, I want you to kind of riff on that from the perspective that let's just assume that Vincent was just primarily talking about the idea that, okay, we've established that this code is solid and we've got gold copy of it and we know it's okay. There aren't inherent problems in the code as far as we can tell. Well, that's fine. I'm a developer. I go out to pull code and to use. How do I know if it's not been tampered with? How do I know if it's in fact the code that was validated during this process before? What do you do about that? >> So there's several methods there, but I just like to loop back to that point, because I think this is really interesting around, so if you look at a software supply chain, this is a mix of humans and machines, and both have flaws, probably humans a bit more. And a supply chain, you have developers. You have code reviewers, you have your systems administrators that set up the systems, and then you have your machine actors. So you've got your build systems, the various machines that are part of that supply chain. Now the humans, there's a as an attack factor there 'cause typically they will have some sort of identity, which they leverage for access to the supply chain. So quite often a developer's identity can be compromised. So a lot of the time people will have a corporate account that gives them some sort of single sign on access to multiple systems. So the developers are coming and this could be somebody in the community as well. Their account is compromised, then they're able to easily backdoor systems. So that's one aspect. And then there is machines as well. There's the whole premise of machines software not being up to date. So when the latest nasty vulnerability is released, machines are updated, then the machines have their flaws. They can be exploited. So I would say it's not just a technical problem. There is a humanistic element to this as well around protecting your supply chain. And I would say a really good perspective to carry when you're looking to, how do I secure my supply chain is treat it like you would a production system. So what do I mean by that? When we put something into production and we've got this very long legacy of treating it with a very strict security context around who can access that people, okay. How much it's upgraded and it's patched? And we seem to not have this same perception around our supply chain and our build systems, the integrity of those, the access of those, the policy around the access and so forth. So that's one giveaway that I would say is a real key focus that you should have is treat it like a production system. Be very mindful about what you're bringing in, who can access it because it is the keys to the kingdom, because if somebody compromises your supply chain, your build systems and so forth, they can compromise the whole chain because the chain is only as strong as the weakest link. So that's what I draw upon it. And around the verifications, there is multiple technologies that you can leverage. So Red Hat, we've got a very robust sign in system that we use so that you can be sure that the packages that we get you have non-repudiation that they've been produced by Red Hat. When you update your system, that's automatically looked after. And there are other systems as well, there's other new technologies that are starting to get a foothold around the provenance of aspects of your build system. So when you're pulling in from these multiple sources of open source communities, you can have some provenance around what you're putting in as well. And yeah, I don't want to bite share too much on the technologies, but there's some exciting stuff starting to happen there as well. >> So let's look at an example of something, because I think it's important to understand all of these different aspects. Recently, I think actually still in the news, we found that some logging software distributed by Apache that's widely used in people's websites to gather information about... To help from a security perspective and to help developers improve things that are going on in websites. A vulnerability was discovered. I guess, first Alibaba, some folks were reported it directly to some folks at Apache and the Apache Organization. And then of all people, some folks from Minecraft mentioned it in a blog. That seems like a crazy way to find out about something that's a critical flaw. Now we're looking at this right now with hindsight. So with hindsight, what could we have done to not be in the circumstances that we're in right now? Vincent, I'll toss that to you first, but again, if Luke is more appropriate, let us know. >> No, it's a great question, and it's a hard question. >> How did you let this happen, Vincent? How did you let this happen? >> It wasn't me, I promise. (Dave laughs) >> What I mean, it's a challenging question I mean, and there's a number of areas where we focused on a lot of what we perceived as critical software. So it comes to web server applications, DNS, a number of the kind of the critical infrastructure that powers the internet. Right or wrong. Do we look at logging software as a critical piece of that? Well, maybe, maybe we should, right? Logging is definitely important as part of an incident response or just an awareness of what's going on. So, I mean, yeah, it probably should have been considered critical software, but I mean, it's open source, right? So there's a number of different logging applications. I imagine now we're scrutinizing those a little bit more, but looking beforehand, how do you determine what's critical until an event like this happens, and it's unfortunate that it happens. And I like to think of these as learning opportunities, and certainly not just for Red Hat, but for this (talking over each other) >> Certainly this is not... Yeah, this is not an indictment of our entire industry. We are all in this together and learning every day. It just highlights how complex the situation is that we're dealing with, right? >> It really is. And I mean, a lot of what we're looking at now is how do we get tools into the hands of developers who can catch some of these things earlier. And there's a lot of commercial offerings, there's a lot of open source tools that are available and being produced that are going to help with these sorts of situations moving forward. But I mean, all the tools on the planet aren't going to help if they're not being used. So, I mean, there has to be an education and an incentive for these developers, particularly, maybe in some upstream communities where they are labors of love and they're passionate projects they're not sponsored or backed by a corporation who's paying for these tools, to be able to use some of them and move that forward. I think that looking at things now, there is work to be done. Obviously there's always going to be work to be done. Not all of these tools, and we have to recognize this, they're not all perfect. They're not going to catch everything. These tools could have been... I mean, I don't know if they were running these tools or not, they could have been, and the tool simply could not have picked them up. So part of it is the proactive part. We talk a lot about shift left and moving these things earlier into the development process and that's great, and we should do it. It certainly should never be seen as a silver bullet or a replacement for a good response. And I think the really important thing to highlight with respect to this, and I mean, this touches on the supply chain issue as well, companies, especially those who never maybe saw themselves as a software development company really have to figure out and understand how to do appropriate response. Part of that is awareness, what do you have installed? Part of it is sources of information. Like how do I find out about a new vulnerability or a potential vulnerability? And then it's just the speed to respond. We know that a number of companies they have, maybe it's a Patch Tuesday, maybe it's a patch 26th of the month, maybe it's patch day of the quarter, we have to learn how to respond to these things quickly so that we can apply these mitigations and these fixes as quickly as possible to them protect ourselves and protect the end users or customers that we have, or to keep the kids from using some backdoors in Minecraft is the word. >> (laughs) Yeah. Look, this is an immensely important subject. To wrap us up on this, Luke, I'd like you to pretend that you just got into an elevator in a moderately tall building, and you have 60 seconds to share with me someone who already trusts you, you don't have to convince me of your credentials or anything. I trust you. What tools specifically do you need me to be running, tools and processes. You've got 60 seconds to say, Dave, if you're not doing these things right now, you're unnecessarily vulnerable. So ready, and go, Luke. >> So automatically update all packages. Always stay up-to-date so that when an issue does hit, you're not having to go back 10 versions and work your way forward. That's the key thing. Ensure that everything you pull in, you're not going to have 100%, but have a very strict requirement that there is non-repudiation, is signed content, so you can verify that it's not being tampered with. For your developers that are producing code, run static, dynamic analysis, API fuzzes, all of these sorts of tools. They will find some vulnerabilities for you. Be part of communities. Be part of communities, help chop the wood and carry the water because the log for Jay, the thing is that was found because it was in the open. If it wasn't any open, it wouldn't have been found. And I've been in this business for a long time. Software developers will always write bugs. I do. Some of them will be security bugs. That's never going to change. So it's not about stopping something that's inevitable. It's about being prepared to react accordingly in our right and correct manner when it does happen so that you can mitigate against those risks. >> Well, we're here on the 35th floor. That was amazing. Thank you, Luke. Vincent, you were in the elevator also listening in on this conversation. Did we miss anything? >> No, I mean, the only thing I'll say is that it's really helpful to partner with an enterprise open source provider, be it Red Hat or anybody else. I don't want to toot our own horn. They do a lot of that work on your behalf that you don't have to do. A lot of the things that Luke was talking about, those providers do, so you don't have to. And that's where you.. I liked that you talked about, hey, you don't have to convince me that I'm trusted, or that I trust you. Trust those vendors. They're literally here to do a lot of that heavy lifting for you and trust the process. Yeah, it's a very, very good point. And I know that sometimes it's hard to get to that point where you are the trusted advisor. Both of you certainly are. And with that, I would like to thank you very much for an interesting conversation. Gentlemen, let's keep in touch. You're always welcome on theCUBE. Luke, second time, getting a chance to talk to you on theCUBE personally. Fantastic. With that, I would like to thank everyone for joining this very special series on theCUBE. Managing risk in the digital supply chain is a critical topic to keep on top of. Thanks for tuning into theCUBE. We'll be back soon. I'm Dave Nicholson saying, thanks again. (upbeat music)

(upbeat music) >> Okay, we're here talking about how you can better understand and manage the risks associated with the digital supply chain. How in this day and age where software comes from so many different places and sources throughout the ecosystem, how can organizations manage the risks associated with our dependence on software? And with me now are two great guests, Andrea Hall, who is a specialist solution architect and project manager for security and compliance at Red Hat. She's going to focus on public sector. And Andrew Block who's a distinguished architect at Red Hat Consulting, folks welcome. >> Welcome >> Thank you. Thanks for having us. >> You're very welcome. Andrea, let's start with you. Let's talk about regulations. What exists today that we should be aware of that organizations should be paying attention to? >> Oh sure, so the thing that comes to mind first being in the US is the presidential executive order on cybersecurity that came out a few months ago. Organizations are really paying attention to that. And in the US, it's having a ripple effect with policy, but we're also seeing policy considerations pop up in other countries, Australia and England. The supply chain is a big focus right now, of course, but we see these changes coming down the road as more and more government organizations are trying to secure their critical infrastructure. >> Is there kind of a leadership, or probably in other words, is somebody saying seeing what the UK does and say, okay, we're going to follow that template? Or is it just a variety and a mish mash with no sort of consolidation? How is that sort of playing out? >> I see a lot of organizations kind of basing their requirements on (indistinct) However, each organization has its own nuances. Each agency has its own nuances to how it wants them implemented. >> Andrew, maybe you could chime in here. What are you seeing when you talk to customers that are tuned into this issue? >> You know, as Andrea had just mentioned having that north star in terms of regulations is so fundamentally great for them because many of them especially in regulate industries, look to these regulations on how they apply their own policies. So at least it has some guidance on how to move forward because as we all know the secure software supply chain is getting news every day and how they react to it is something that I know all their leaders are asking themselves, especially those IT leaders. >> Andrea, when I talk to practitioners, sometimes they're frustrated. They understand they have to comply. They know new regulations are coming out, but sometimes it's hard for them to keep up. It would be helpful if you're sitting across the table from somebody who's frustrated and they ask you, what are your expectations? What are the trends in regulations? How do you see the current regulations evolving to specifically accommodate the digital supply chain and the security exposures and corollary requirements there? >> We see a lot of organizations struggling in the sense of trying to understand what the policy actually wants. Definitions are still a little bit vague, but implementation is also difficult because sometimes organizations will add more tools to their toolkit, adding a layer of complexity there. Really automation has to be pulled in. That's key to implementing this instead of adding more workload and more burden to your folks. It's really important for these organizations to pull stakeholders in the organization together. So the IT leaders bring together the developers, the security operations sit at the same table, talk about whether or not what needs to be implemented or what's proposed to be implemented, will affect the mission or in any way or disrupt operations. It's important for everybody to be on the same page so it doesn't slow anything down as you're trying to roll it out. >> And one of the things here is that we're seeing a lot of change with these new regulations and with a lot of organizations, any type of change is scary. And that is one area that they're looking for guidance not only in the tooling, but also how they apply it in the organization. >> I'll add on. >> Please. >> I'll add onto that and say, organizations really need to take into account the people side of things too. People need to understand what the impact is to the organization, so that they don't try to find the loopholes, they're buying into what needs to be done. They understand the why behind it. You for example, if you walk into your house, you normally close the door behind you. Security needs to be seen as that, as well, that's the culture and it's the habit. And it's ingrained in the fabric of the organization to live this way, not just implement the tools to do it. >> Right, and the number of doors you have in your infrastructure are a lot more than just a couple. Andrew mentioned sort of guidance and governments are obviously taking a more active role. I mean, sometimes I'm a cynic. I mean, the president Biden signs an executive order, but swipe of a pen doesn't really give us enough to go on. Do you think Andrea, that we're going to see new guidance from governments in the very near future? What are you expecting? >> I expect to see more conversations happening. I know that agencies who developed the policies are pulling together stakeholders and getting input. But I do see in the not too distant future, that mandates will be rolling out, yes. >> Well, so Andrew of course, Andrea, if you have a thought on this as well, but how do you see organizations dealing with adopting these new policies. >> Slowly, don't boil the ocean is one thing I tell a lot to every one of them, because a lot of these tooling, a lot of these concepts are foreign to them, brand new. How they adopt those and how they implement them, needs to be done in a very agile fashion, very slow and prescriptive. Go ahead and try to find one area of improvement and go ahead and work upon it and build upon it. Because not only does that normally make your organization more successful and secure, but also helps your organization just from a more out standpoint. One thing that you need to emphasize is that don't blame anyone. 'Cause a lot of times when you're going through this, you're reassessing your own supply chain. You might find where you could see improvements that need to be done. Don't blame things that may have occurred in the past. See how you can benefit from these lessons learned in the future. >> It's interesting you say that the blame game, I mean it used to be that failure meant you get fired and that's obviously has changed. As many have said, you know you're going to have incidents. It's how you respond to those incidents. What you learn from them. Do you have Andrew, any insights from specifically working with customers on securing their software supply chain? What can you tell us about what leading practitioners are doing today? >> They're going in and not only assessing what their software components consist of. Using tools like an SBOM, a software bill of materials, understand where all the components of their ecosystem and their lineage comes from. We're hearing almost every single day, new vulnerabilities that are being introduced in various software packages. By having that understanding of what is in your ecosystem, you can then better understand how to mitigate those concerns moving forward. >> Andrea, Andrew was just saying, one of the things is you don't just dive in. You've got to be careful. There's going to be ripple effects is what I'm inferring, but at the same time, there's a mandate to move quickly. Are there things that could accelerate the adoption of regulation or even the creation of regulations and that guidance in your view? What could accelerate this? >> As far as accelerating it goes, I think it's having those conversations proactively with the stakeholders in your organization and understanding the environment like Andrew said. Go ahead and get that baseline. And just know that whatever changes you make are maybe going to be audited down the road, because as we were moving towards this kind of third-party verification, that you're actually implementing things in order to do business with another organization. The importance of that, if organizations see that gravity to this, I think they will try to speed things up. I think that if organizations and the people in those organizations understand that why, that I talked about earlier and they understand how things like solar winds or things like the oil disruption that happened earlier this year. The personal effect to cyber events will help your organization move forward. Again, everybody's bought into the concept, everybody's working towards the same goals and they understand that why behind it. >> In addition to that, having tooling available, that makes it easy for them. You have a lot of individuals who this is all foreign, providing that base level tooling that aligns to a lot of the regulations that might be applicable within their real realm and their domain, makes it easier for them to start to complying and taking less burden off of them to be able to be successful. >> So it's a hard problem because Andrew, how do you deal with sort of the comment more tools, okay. But I look at that the Optiv map, if you've seen that. It makes your eyes cross. You've got so many tools, so much fragmentation, you're introducing new tools. Can automation help that? Is there hope for consolidation of that tools portfolio? >> Right now, this space is very emerging. It's very emerging, it's very fluid to be honest, 'cause there is actually mandates only a year or two old. But as they come over the course of time, however, I do see these types of tooling starting to consolidate where right now it seems like every vendor has a tool that tries to address this. It's being able to have the people work together, have more regulations that will come out that will allow us to start to redefine and solidify on certain tools like ISO standards. There are certain ones that I mentioned on as balance previously, there's now a ISO standard on SBOM there wasn't previously. So as more and more of these regulations come out, it makes it easier to provide that recommended set of tooling that organizations can start leveraging instead of vendor A, vendor B. >> Andrea, I said this before I was a cynic, but will give you the last word, give us some hope. I mean, obviously public policy is very important. A partnership between governments and industry, both the practitioners, the organizations that are buying these tools, as well as the technology industry got to work together in an ecosystem. Give us some hope. >> The hope I think will come from realizing that as you're doing this, as you are implementing these changes, you're in a sense trying to prevent those future incidents from happening. There's some assurance that you're doing everything that you can do here. It's a situation, it can be daunting, I'll put it that way. It can be really daunting for organizations, but just know that organizations like Red Hat are doing what we can to help you down the road. >> And really it's just continuing this whole shifting left mentality. The top of supply chain is just one component, but the introducing dev sec ops security at the beginning, that really will make the organizations become successful because this is not just a technology problem, It's a people issue as well. And being able to kind of package them all up together will help organizations as a whole. >> Yeah, so that's a really important point. You hear that term shift left. For years, people say, hey, you can't just bolt security on, as an afterthought, that's problematic. And that's the answer to that problem, right? Is shifting left meaning designing it in at the point of code, infrastructure as code, dev sec ops. That's where it starts, right? >> Exactly, being able to have security at the forefront and then have everything afterwards. Propagate from your security mindset. >> Excellent, okay, Andrea, Andrew, thanks so much for coming to the program today. >> Thank you for having us. >> Very welcome, thanks for watching. This is Dave Vellante for The Cube. Your a global leader in enterprise tech coverage. (soft music)

(upbeat music) >> Hello everyone, my name is Dave Vellante, and we're digging into the many facets of the software supply chain and how to better manage digital risk. I'd like to introduce Kirsten Newcomer, who is the Director of Cloud and DevSecOps Strategy at Red Hat. Hello Kirsten, welcome. >> Hello Dave, great to be here with you today. >> Let's dive right in. What technologies and practices should we be thinking about that can help improve the security posture within the software supply chain? >> So I think the most important thing for folks to think about really is adopting DevSecOps. And while organizations talk about DevSecOps, and many folks have adopted DevOps, they tend to forget the security part of DevSecOps. And so for me, DevSecOps is both DevSec, how do I shift security left into my supply chain, and SecOps which is a better understood and more common piece of the puzzle, but then closing that loop between what issues are discovered in production and feeding that back to the development team to ensure that we're really addressing that supply chain. >> Yeah I heard a stat. I don't know what the source is, I don't know if it's true, but it probably is that around 50% of the organizations in North America, don't even have a SecOps team. Now of course that probably includes a lot of smaller organizations, but the SecOps team, they're not doing DevSecOps, but so what are organizations doing for supply chain security today? >> Yeah, I think the most common practice, that people have adopted is vulnerability scanning. And so they will do that as part of their development process. They might do it at one particular point, they might do it at more than one point. But one of the challenges that, we see first of all, is that, that's the only security gate that they've integrated into their supply chain, into their pipeline. So they may be scanning code that they get externally, they may be scanning their own code. But the second challenge is that the results take so much work to triage. This is static vulnerability scanning. You get information that is not in full context, because you don't know whether a vulnerability is truly exploitable, unless you know how exposed that particular part of the code is to the internet, for example, or to other aspects. And so it's just a real challenge for organizations, who are only looking at static vulnerability data, to figure out what the right steps to take are to manage those. And there's no way we're going to wind up with zero vulnerabilities, in the code that we're all working with today. Things just move too quickly. >> Is that idea of vulnerability scanning, is it almost like sampling where you may or may not find the weakest link? >> I would say that it's more comprehensive than that. The vulnerability scanners that are available, are generally pretty strong, but they are, again, if it's a static environment, a lot of them rely on NVD database, which typically it's going to give you the worst case scenario, and by nature can't account for things like, was the software that you're scanning built with controls, mitigations built in. It's just going to tell you, this is the package, and this is the known vulnerabilities associated with that package. It's not going to tell you whether there were compiler time flags, that may be mitigated that vulnerability. And so it's almost overwhelming for organizations, to prioritize that information, and really understand it in context. And so when I think about the closed loop feedback, you really want not just that static scan, but also analysis that takes into account, the configuration of the application, and the runtime environment and any mitigations that might be present there. >> I see, thank you for that. So, given that this digital risk and software supply chains are now front and center, we read about them all the time now, how do you think organizations are responding? What's the future of software supply chain going to look like? >> That's a great one. So I think organizations are scrambling. We've certainly at Red Hat, We've seen an increase in questions, about Red Hat's own supply chain security, and we've got lots of information that we can share and make available. But I think also we're starting to see, this strong increased interest, in security bill of materials. So I actually started working with, automation and standards around security bill of materials, a number of years ago. I participated in The Linux Foundation, SPDX project. There are other projects like CycloneDX. But I think all organizations are going to need to, those of us who deliver software, we're going to need to provide S-bombs and consumers of our software should be looking for S-bombs, to help them understand, to build transparency across the projects. And to facilitate that automation, you can leverage the data, in a software package list, to get a quick view of vulnerabilities. Again, you don't have that runtime context yet, but it saves you that step, perhaps of having to do the initial scanning. And then there are additional things that folks are looking at. Attested pipelines is going to be key, for building your custom software. As you pull the code in and your developers build their solutions, their applications, being able to vet the steps in your pipeline, and attest that nothing has happened in that pipeline, is really going to be key. >> So the software bill of materials is going to give you, a granular picture of your software, and then what the chain of, providence if you will or? >> Well, an S-bomb depending on the format, an S-bomb absolutely can provide a chain of providence. But another thing when we think about it, from the security angles, so there's the providence, where did this come from? Who provided it to me? But also with that bill of materials, that list of packages, you can leverage tooling, that will give you information about vulnerability information about those packages. At Red Hat we don't think that vulnerability info should be included in the S-bomb, because vulnerability data changes everyday. But, it saves you a step potentially. Then you don't necessarily have to be so concerned about doing the scan, you can pull data about known vulnerabilities for those packages without a scan. Similarly the attestation in the pipeline, that's about things like ensuring that, the code that you pull into your pipeline is signed. Signatures are in many ways of more important piece for defining providence and getting trust. >> Got it. So I was talking to Asiso the other day, and was asking her okay, what are your main challenges, kind of the standard analyst questions, if you will. She said look, I got great people, but I just don't have enough depth of talent, to handle, the challenges I'm always sort of playing catch up. That leads one to the conclusion, okay, automation is potentially an answer to address that problem, but the same time, people have said to me, sometimes we put too much faith in automation. some say okay, hey Kirsten help me square the circle. I want to automate because I lack the talent, but it's not, it's not sufficient. What are your thoughts on automation? >> So I think in the world we're in today, especially with cloud native applications, you can't manage without automation, because things are moving too quickly. So I think the way that you assess whether automation is meeting your goals becomes critical. And so looking for external guidance, such as the NIST's Secure Software Development Framework, that can help. But again, when we come back, I think, look for an opinionated position from the vendors, from the folks you're working with, from your advisors, on what are the appropriate set of gates. And we've talked about vulnerability scanning, but analyzing the configed data for your apps it's just as important. And so I think we have to work together as an industry, to figure out what are the key security gates, how do we audit the automation, so that I can validate that automation and be comfortable, that it is actually meeting the needs. But I don't see how we move forward without automation. >> Excellent. Thank you. We were forced into digital, without a lot of thought. Some folks, it's a spectrum, some organizations are better shape than others, but many had to just dive right in without a lot of strategy. And now people have sat back and said, okay, let's be more planful, more thoughtful. So as you, and then of course, you've got, the supply chain hacks, et cetera. How do you think the whole narrative and the strategy is going to change? How should it change the way in which we create, maintain, consume softwares as both organizations and individuals? >> Yeah. So again, I think there's going to be, and there's already, need request for more transparency, from software vendors. This is a place where S-bombs play a role, but there's also a lot of conversation out there about zero trust. So what does that mean in, you have to have a relationship with your vendor, that provides transparency, so that you can assess the level of trust. You also have to, in your organization, determine to your point earlier about people with skills and automation. How do you trust, but verify? This is not just with your vendor, but also with your internal supply chain. So trust and verify remains key. That's been a concept that's been around for a while. Cloud native doesn't change that, but it may change the tools that we use. And we may also decide what are our trust boundaries. Are they where are we comfortable trusting? Where do we think that zero trust is more applicable place, a more applicable frame to apply? But I do think back to the automation piece, and again, it is hard for everybody to keep up. I think we have to break down silos, we have to ensure that teams are talking across those silos, so that we can leverage each other's skills. And we need to think about managing everything as code. What I like about the everything is code including security, is it does create auditability in new ways. If you're managing your infrastructure, and get Ops like approach your security policies, with a get Ops like approach, it provides visibility and auditability, and it enables your dev team to participate in new ways. >> So when you're talking about zero trust I think, okay, I can't trust users, I got to trust the verified users, machines, employees, my software, my partners. >> Yap >> Every possible connection point. >> Absolutely. And this is where both attestation and identity become key. So being able to, I mean, the SolarWinds team has done a really interesting set of things with their supply chain, after they were, in response to the hack they were dealing with. They're now using Tekton CD chains, to ensure that they have, attested every step in their supply chain process, and that they can replicate that with automation. So they're doing a combination of, yep. We've got humans who need to interact with the chain, and then we can validate every step in that chain. And then workload identity, is a key thing for us to think about too. So how do we assert identity for the workloads that are being deployed to the cloud and verify whether that's with SPIFFE SPIRE, or related projects verify, that the workload is the one that we meant to deploy and also runtime behavioral analysis. I know we've been talking about supply chain, but again, I think we have to do this closed loop. You can't just think about shifting security left. And I know you mentioned earlier, a lot of teams don't have SecOps, but there are solutions available, that help assess the behavior and runtime, and that information can be fed back to the app dev team, to help them adjust and verify and validate. Where do I need to tighten my security? >> Am glad you brought up the SolarWinds to Kirsten what they're doing. And as I remember after 911, everyone was afraid to fly, but it was probably the safest time in history to fly. And so same analogy here. SolarWinds probably has learned more about this and its reputation took a huge hit. But if you had to compare, what SolarWinds has learned and applied, at the speed at which they've done it with maybe, some other software suppliers, you might find that they've actually done a better job. It's just, unfortunately, that something hit that we never saw before. To me it was Stuxnet, like we'd never seen anything like this before, and then boom, we've entered a whole new era. I'll give you the last word Kirsten. >> No just to agree with you. And I think, again, as an industry, it's pushed us all to think harder and more carefully about where do we need to improve? What tools do we need to build to help ourselves? Again, S-bombs have been around, for a good 10 years or so, but they are enjoying a resurgence of importance signing, image signing, manifest signing. That's been around for ages, but we haven't made it easy to integrate that into the supply chain, and that's work that's happening today. Similarly that attestation of a supply chain, of a pipeline that's happening. So I think as a industry, we've all recognized, that we need to step up, and there's a lot of creative energy going into improving in this space. >> Excellent Kirsten Newcomer, thanks so much for your perspectives. Excellent conversation. >> My pleasure, thanks so much. >> You're welcome. And you're watching theCUBE, the leader in tech coverage. (soft music)

(upbeat music) >> Dave Vellante: Okay. We're back with Mark Hill. who's the Director of IT Operations at Digital River. Mark. Welcome to the cube. Good to see you. Thanks for having me. I really appreciate it. >> Hey, tell us a little bit more about Digital River, people know you as a, a payment platform, you've got marketing expertise. How do you differentiate from other e-commerce platforms? >> Well, I don't think people realize it, but Digital River was founded about 27 years ago. Primarily as a one-stop shop for e-commerce right? And so we offered site development, hosting, order management, fraud, expert controls, tax, um, physical and digital fulfillment, as well as multilingual customer service, advanced reporting and email marketing campaigns, right? So it was really just kind of a broad base for e-commerce. People could just go there. Didn't have to worry about anything. What we found over time as e-commerce has matured, we've really pivoted to a more focused API offering, specializing in just our global seller services. And to us that means payment, fraud, tax, and compliance management. So our, our global footprint allows companies to outsource that risk management and expand their markets internationally, um very quickly. And with low cost of entry. >> Yeah. It's an awesome business. And, you know, to your point, you were founded way before there was such a thing as the modern cloud, and yet you're a cloud native business. >> Yeah. >> Which I think talks to the fact that, that incumbents can evolve. They can reinvent themselves from a technology perspective. I wonder if you could first paint a picture of, of how you use the cloud, you use AWS, you know, I'm sure you got S3 in there. Maybe we could talk about that a little bit. >> Yeah, exactly. So when I think of a cloud native business, you kind of go back to the history. Well, 27 years ago, there wasn't a cloud, right? There wasn't any public infrastructure. It was, we basically stood our own data center up in a warehouse. And so over our history, we've managed our own infrastructure and collocated data centers over time through acquisitions and just how things worked. You know those over 10 data centers globally. for us it was expensive, well from a software hardware perspective, as well as, you know, getting the operational teams and expertise up to up to speed too. So, and it was really difficult to maintain and ultimately not core to our business, right? Nowhere in our mission statement, does it say that we're our goal is to manage data centers? So, so about five years ago, we started the journey from our hosted into AWS. It was a hundred percent lift it and shift plan, and we were able to bleed that migration a little over two years, right. Amazon really just fit for us. It was a natural, a natural place for us to land and they made it really easy here for us to not to say it wasn't difficult, but, but once in the public cloud, we really adopted a cloud first vision. Meaning that we'll not only consume their infrastructure as the service, but we'll also purposely evaluate and migrate to software as a service. So I come from a database background. So an example would be migrating from self deployed and managed relational databases over to AWS RDS, relational database service. You know, you're able to utilize the backups, the standby and the patching tools. Automagically, you know, with a click of the button. And that's pretty cool. And so we moved away from the time consuming operational tasks and, and really put our resources into revenue and generate new products, you know, like pivoting to an API offering. I always like to say that we stopped being busy and started being productive. >> Ha ha. I love that. >> That's really what the cloud has done for us. >> Is that you mean by cloud native? I mean, being able to take advantage of those primitives and native API. So what does that mean for your business? >> Yeah, exactly. I think, well, the first step for us was just to consume the infrastructure right, in that, but now we're looking at targeted services that they have in there too. So, you know, we have our, our, our data stream of services. So log analytics, for example, we used to put it locally on the machine. Now we're just dumping into an S3 bucket and we're using Kinesis to consume that data, put it in Eastic and go from there. And none of the services are managed by Digital River. We're just utilizing the capabilities that AWS has there too. So. >> And as an e-commerce player, retail company, we were ever concerned about moving to AWS as a possible competitor, or did you look at other clouds? What can you tell us about that? >> Yeah. And, and so I think e-commerce has really matured, right? And so we, we got squeezed out by the Amazons of the world. It's just not something that we were doing, but we had really a good area of expertise with our global seller services. But so we evaluated Microsoft. We evaluated AWS as well as Google. And, you know, back when we did that, Microsoft was Windows-based. Google was just coming into the picture, really didn't fit for what we were doing, but Amazon was just a natural fit. So we made a business decision, right? It was financially really the best decision for us. And so we didn't really put our feelings into it, right? We just had to move forward and it's better than where we're at. And we've been delighted actually. >> Yeah. It makes sense. Best cloud, best, best tech. >> Yeah. >> Yeah. I want to talk about ChaosSearch. A lot of people describe it as a data lake for log analytics. Do you agree with that? You know, what does that, what does that even mean? >> Well, from, from our perspective, because they're self-managed solutions were costly and difficult to maintain, you know, we had older versions of self deployed using Splunk, other things like that, too. So over time, we made a conscious decision to limit our data retention in generally seven days. But in a lot of cases, it was zero. We just couldn't consume that, that log data because of the cost, intimidating in itself, because of this limit, you know, we've lost important data points use for incident triage, problem management, problem management, trending, and other things too. So ChaosSearch has offered us a manageable and cost-effective opportunity to store months, or even years of data that we can use for operations, as well as trending automation. And really the big thing that we're pushing into is an event driven architecture so that we can proactively manage our services. >> Yeah. You mentioned Elastic, I know I've talked to people who use the ELK Stack. They say you there's these exponential growth in the amount of data. So you have to cut it off at whatever. I think you said seven days or, or less you're saying, you're not finding that with, with ChaosSearch? >> Yeah. Yeah, exactly. And that was one of the huge benefits here too. So, you know, we were losing out if there was a lower priority incident, for example, and people didn't get to it until eight, nine days later. Well, all the breadcrumbs are gone. So it was really just kind of a best guess or the incident really wasn't resolved. We didn't find a root cause. >> Yeah. Like my video camera down there. My, you know, my other house, somebody breaks in and I don't find out for, for two weeks and then the video's gone. That kind of same thing. >> Yep So, so, so how do you, can you give us some more detail on how you use your data lake and ChaosSearch specifically? >> Yeah, yeah. Yep. And, and so there's, there's many different areas, but what we found is we were able to easily consolidate data from multiple regions, into a single pane of glass to our customers. So internally and externally, you know, it relieves us of that operational support for the data extract transformation load process, right? It offered us also a seamless transition for the users, who were familiar with ElasticSearch, right? It wasn't, it wasn't difficult to move over. And so all these are a lot of selling points, benefits. And, and so now that we have all this data that we're able to, to capture and utilize, it gives us an opportunity to use machine learning, predictive analysis. And like I said, you know, driving to an event driven architecture. >> Okay. >> So that's, that's really what it's offered. And it's, it's been a huge benefit. >> So you're saying that you can speak the language of Elastic. You don't have to move the data out of an S3 bucket and you can scale more easily. Is that right? >> Yeah, yeah, absolutely. And, so for us, just because we're running in multiple regions to drive more high availability, having that data available from multiple regions in a single pane of glass or a single way to utilize it, is a huge benefit as well. Just, you know, not to mention actually having the data. >> What was the initial catalyst to sort of rethink what you were doing with log analytics? Was it cost? Was it flexibility? Scale? >> There was, I think all of those went into it. One of the main drivers. So, so last year we had a huge project, so we have our ELK Stack and it's probably from a decade ago, right? And, you know, a version point oh two or something, you know, anyways, it's a very old, and we went through a whole project to get that upgraded and migrated over. And it was just, we found it impossible internally to do, right? And so this was a method for us to get out of that business, to get rid of the security risks, the support risk, and have a way for people to easily migrate over. And it was just a nightmare here, consolidating the data across regions. And so that was, that was a huge thing, but yeah, it was also been the cost, right? It was, we were finding it cheaper to use ChaosSearch and have more data available versus what we're doing currently in AWS. >> Got it. I wonder if you could, you could share maybe any stories that you have or examples that, that underscore the impact that this approach to analytics is having on your business, maybe your team's everyday activities, any, any metrics you can provide or even just anecdotal information. >> Yeah. Yeah. And, and I think, you know, one coming from an Oracle background here, so Digital River historically has been an Oracle shop, right? And we've been developing a reporting and analytics environment on Oracle and that's complicated and expensive, right? We had to use advance features in Oracle, like partitioning materialized views, and bring in other supporting software like Informatica, Hyperion, Sbase, right? And all of these required our large team with a wide set of expertise into these separate focus areas, right? And the amount of data that we were pushing at the ChaosSearch would simply have overwhelmed this legacy method for data analysis than a relational database, right? In that dimension, the human toll of, of the stress of supporting that Oracle environment, meant that a 24 by seven by 365 environment, you know, which requires little or no downtime. So, just that alone, it's a huge thing. So it's allowed us to break away from Oracle, it's allowed us to use new technologies that make sense to solve business solutions. >> I, you know, ChaosSearch is really interesting company to me. I'm sure like me, you see a lot of startups, I'm sure they're knocking on your door every day. And I always like to say, okay, where are they going after? Are they going after a big market? How are they getting product market fit? And it seems like ChaosSearch has really looked at, hard at log analytics and kind of maybe disrupting the ELK Stack. But I see, you know, other potential use cases, you know, beyond analyzing logs. I wonder if you agree, are there other use cases that you see in your future? >> Yeah, exactly. So I think there's, one area would be Splunk, for example, we have that here too. So we use Splunk versus, you know, flat file analysis or other ways to, to capture that data just because from a PCI perspective, it needs to be secured for our compliance and certification, right? So ChaosSearch allows us to do that. There's different types of authentication. Um, really a hodgepodge of authentication that we used in our old environment, but ChaosSearch has a more easily usable one, One that we could set up, one that can really segregate the data and allow us to satisfy our PCR requirements too. So, but Splunk, but I think really deprecating all of our ElasticSearch environments are homegrown ones, but then also taking a hard look at what we're doing with relational databases, right? 27 years ago, there was only relational databases; Oracle and Sequel Server. So we we've been logging into those types of databases and that's not, cost-effective, it's not supportable. And so really getting away from that and putting the data where it belongs and that was easily accessible in a secure environment and allowing us to, to push our business forward. >> Yep. When you say, where the data belongs, right? It sounds like you're putting it in the bit bucket, S3, leaving it there, because it's the the most cost-effective way to do it and then sort of adding value on top of it. That's, what's interesting about ChaosSearch to me. >> Yeah, exactly. Yup. Yup. Versus the high priced storage, you know, that you have to use for a relational database, you know, and not to mention that the standbys, the backups. So, you know, you're duplicating, triplicating all this data too in an expensive manner, so yeah. Yeah. >> Yeah. Copy. Create. Moving data around and it gets expensive. It's funny when you say about databases, it's true. But database used to be such a boring market. Now it's exploded. Then you had the whole no Sequel movement and Sequel, Sequel became the killer app. You know, it's like full circle, right? >> Yeah, exactly. >> Well, anyway, good stuff, Mark, really, really appreciate you coming on the Cube and, and sharing your perspectives. We'd love to have you back in the future. >> Oh yeah, no problem. Thanks for having me. I really appreciate it. (upbeat music) >> Okay. So that's a wrap. You know, we're seeing a new era in data and analytics. For example, we're moving from a world where data lives in a cloud object store and needs to be extracted, moved into a new data store, transformed, cleansed, structured into a schema, and then analyzed. This cumbersome and expensive process is being revolutionized by companies like ChaosSearch that leave the data in place and then interact with it in a multi-lingual fashion with tooling, that's familiar to analytic pros. You know, I see a lot of potential for this technology beyond just login analytics use cases, but that's a good place to start. You know, really, if I project out into the future, we see a trend of the global data mesh, really taking hold where a data warehouse or data hub or a data lake or an S3 bucket is just a discoverable node on that mesh. And that's governed by an automated computational processes. And I do see ChaosSearch as an enabler of this vision, you know, but for now, if you're struggling to scale with existing tools or you're forced to limit your attention because data is exploding at too rapid a pace, you might want to check these guys out. You can schedule a demo just by clicking the button on the site to do that. Or stop by the ChaosSearch booth at AWS Reinvent. The Cube is going to also be there. We'll have two sets, a hundred guests. I'm Dave Volante. You're watching the Cube, your leader in high-tech coverage.

(gentle music) >> Okay, we're back with Mark Hill who's the director of IT operations at Digital River. Mark, Welcome to "The Cube." Good to see you. >> Thanks for having me. I really appreciate it. >> Hey, tell us a little bit more about Digital River, people know you as a payment platform. >> You've got marketing expertise. >> Yeah. >> How do you differentiate from other e-commerce platforms? >> Well, I don't think people realize it, but Digital River was founded about 27 years ago primarily as a one-stop shop for e-commerce, right? And so we offered site development, hosting, order management, fraud, expert controls, tax, physical and digital fulfillment as well as multilingual customer service, advanced reporting and email marketing campaigns, right? So it was really just kind of a broad base for e-commerce. People could just go there. Didn't have to worry about anything. What we found over time as e-commerce has matured, we've really pivoted to a more focused API offering specializing in just a global seller services. And to us that means payment, fraud, tax and compliance management. So our global footprint allows companies to outsource that risk management and expand their markets internationally very quickly and with the low cost of entry. >> Yeah, it's an awesome business. And, you know, to your point, you were founded way before there was such a thing as the modern cloud, and yet you're a cloud native business. >> Yeah. >> Which I think talks to the fact that incumbents can evolve, they can reinvent themselves from a technology perspective. I wonder if you could first paint a picture of how you use the cloud, you use AWS, you know, I'm sure you got S3 in there. Maybe we could talk about that a little bit. >> Yeah, exactly. So when I think of a cloud native business, you kind of go back to the history. Well, 27 years ago, there wasn't a cloud, right? There wasn't any public infrastructure. We basically started our own data center up in a warehouse. And so over our history, we've managed our own infrastructure and co-located data centers over time through acquisitions and just how things works, you know, those are over 10 data centers globally for us. For us it was expensive, well from a software, hardware perspective, as well as, you know, getting the operational teams and expertise up to speed too. And it was really difficult to maintain and ultimately not core to our business, right? Nowhere in our mission statement does it say that our goal is to manage data centers. (laughing) So, about five years ago we started the journey from our host into AWS. It was a hundred percent lift and shift plan and we were able to complete that migration a little over two years, right? Amazon really just fit for us, it was a natural, a natural place for us to land in and they made it really easy here for us to, not to say it wasn't difficult, but once in the public cloud, we really adopted a cloud first vision, meaning that we'll not only consume their infrastructure as the service, but we'll also purposely evaluate and migrate to software as a service. So, I come from a database background. So an example would be migrating from self deployed and manage relational databases over to AWS RDS, relational database service. You know, you're able to utilize the backups, the standby and the patching tools auto magically, you know, with a click of a button. And that's pretty cool. And so we moved away from the time consuming operational task and really put our resources into revenue and generating the products, you know, like pivoting to an API offering. I always like to say that we stopped being busy and started being productive. (laughing) >> I love that. >> And that's really what the cloud has done for us. >> Is that what you mean by cloud native? I mean, being able to take advantage of those primitives and native API. So what does that mean for your business? >> Yeah, exactly. I think, well, the first step for us was just to consume the infrastructure, right? But now we're looking at targeted services that they have in there too. So, you know, we have our data stream of services. So log analytics, for example, we used to put it locally on the machine. Now we're just dumping into an S3 bucket the way you're using Kinesis to consume that data and put it in elastic and go from there. And none of the services are managed by Digital River. We're just realizing the capabilities that AWS has there too. >> And as an e-commerce player, retail company, were you ever concerned about moving to AWS as a possible competitor, or did you look at other clouds? What can you tell us about that? >> Yeah, and so, I think e-commerce is really mature, right? And so we got squeezed out by the Amazons of the world. It's just not something that we were doing, but we had really a good area of expertise with our global seller services. So we evaluated Microsoft, we evaluated AWS as well as Google and, you know, back when we did that, Microsoft was Windows-based. Google was just coming into the picture, really didn't fit for what we're doing, but Amazon was just a natural fit. So, we made a business decision, right? It was financially really the best decision for us. And so we didn't really put our feelings into it, right? We just had to move forward and it's better than where we're at and we've been delighted actually. >> Yeah, makes sense, best cloud, the best tech. >> Yeah. >> You know, I want to talk about Chaos Search. A lot of people describe it as a data lake for log analytics. Do you agree with that? You know, what does that even mean? >> Yeah, well, from our perspective because the self-managed solutions are costly and difficult to maintain. You know, we had older versions of self deployed using Splunk, other things like that too. So over time, we made a conscious decision to limit our data retention in generally seven days. But in a lot of cases, it was zero. We just couldn't consume that log data because of the cost, intimidating in itself, because of this limit, you know, we've lost important data points, use for incident triage problem management, trending and other things too. So, Chaos Search has offered us a manageable and cost-effective opportunity to store months or even years of data that we can use for operations as well as trending automation. And really the big thing that we're pushing into is in the event of an architecture so that we can proactively manage our services. >> Yeah, you mentioned elastic. So I know I've talked to people who use the Elk Stack. They say, yes, this is exponential growth in the amount of data. So you have to cut it off at whatever. I think you said seven days, >> Yeah. >> Or less, you're saying you're not finding that with Chaos Search? >> Yeah, yeah, exactly. And that was one of the huge benefits here too. So, you know, we we're losing out if there was, you know, a lower priority incident for example and people didn't get to it until eight, nine days later. Well, all the bread crumbs are gone. So it was really just kind of a best guess or the incident really wasn't resolved. We didn't find a root cause. >> Yeah, like my video camera's down you know, by your other house, is that when somebody breaks in, I don't find out for two weeks and then the video's gone, kind of like same thing. >> Yeah. >> So, how do you, can you give us some more detail on how you use your data lake and Chaos Search specifically? >> Yeah, yeah. Yep and so there's many different areas, but what we found is we were able to easily consolidate data from multiple regions into a single pane of glass to our customers. So internal and externally, you know, it really does serve that operational support for the data extract transformation load process, right? It offered us also a seamless transition for the users who were familiar with elastic search, right? It wasn't difficult to move over. And so all these are a lot of selling points benefits. And so now that we have all this data that we're able to capture and utilize, it gives us an opportunity to use machine learning, predictive analysis. And like I said, you know, driving to an event driven architecture. >> Okay. >> So that's really what is offered and it's been a huge benefit. >> So you're saying you can speak the language of elastic. You don't have to move the data out of an S3 bucket and you can scale more easily. Is that right? >> Yeah, yeah, absolutely. And it is so for us just because running in multiple regions to drive more high availability, having that data available from multiple regions in a single pane of glass or a single way to utilize it is a huge benefit as well, just to, you know, not to mention actually having the data. >> What was the initial catalyst to sort of rethink what you were doing with log analytics? Was it cost, was it flexibility scale? >> There was, I think all of those went into it. One of the main drivers, so last year we had a huge project, so we have our Elk Stack and it's probably from a decade ago, right? And, you know, a version point or two or something, you know, anyways, it's very old and we went through a whole project to get that upgraded and migrated over. And it was just, we found it impossible internally to do, right? And so this was a method for us to get out of that business, to get rid of the security risks and support risk and have a way for people to easily migrate over. And it was just a nightmare here consolidating the data across regions. And so that was a huge thing. But yeah, it has also been the cost, right? We're finding that cheaper to use Chaos Search and have more data available versus what we were doing currently in AWS. >> Got it, I wonder if you could share maybe any stories that you have or examples that underscore the impact that this approach to analytics, >> Yeah >> Is having on your business, maybe your team's everyday activities, any metrics you can provide, >> Yeah. >> Or even just anecdotal information? >> Yeah, yeah. And and I think, you know, one, coming from an Oracle background here, so Digital River historically has been an Oracle shop, right? And we've been developing a reporting and analytics environment on Oracle and that's complicated and expensive, right? We had to use advanced features in Oracle like partitioning materialized views and bringing other supporting software like Informatic, Hyperion, Essbase, right? And all of these require a large team with a wide set of expertise into the separate focus areas, right? And the amount of data that we were pushing at the KF search would simply have overwhelmed this legacy method for data analysis than a relational database, right? In that dimension, the human toll of the stress of supporting that Oracle environment than a 24 by seven by 365 environment, you know, which requires literal or no downtime. So just that alone, it was a huge thing. So, it's allowed us to break away from Oracle, it's allowed us to use new technologies that make sense to solve business solutions. >> You know, Chaos Search is just a really interesting company to me, I'm sure like me, you see a lot of startups. I'm sure they're knocking on your door every day. And I always like to say, "Okay, where are they going after? "Are they going after a big market? "How are they getting product market fit?" And it seems like Chaos Search has really looked that hard at log analytics and sort of maybe disrupting the Elk Stack. But I see, you know, other potential use cases, you know, beyond analyzing logs. I wonder if you agree, are there other use cases that you see in your future? >> Yeah, exactly. So, I think there's one area would be Splunk for example. We have that here too. So we use Splunk versus, you know, flat file analysis or other ways to capture that data just because from a PCI perspective, it needs to be secured for our compliance and certification, right? So Chaos Search allows us to do that. There's different types of authentication, really a hodgepodge of authentication that we used in our old environment, but Chaos Search has a more easily usable one, one that we could set up, one that can really segregate the data and allows to satisfy our PCR requirements too. But Splunk, I think really, deprecating all of our elastic search environments are homegrown ones, but then also taking a hard look at what we're doing with relational databases, right? 27 years ago, there was only relational databases, Oracle and SQL server. So we've been logging into those types of databases and that's not cost-effective, it's not supportable. And so really getting away from that and putting the data where it belongs and that is easily accessible in a secure environment and allowing us to push our business forward. >> And when you say where the data belongs, it sounds like you're putting it in the bit bucket S3, leaving it there, >> Yeah. >> And this is the most cost-effective way to do it and then sort of adding value on top of it. That's what's interesting about Chaos Search to me. >> Yeah, exactly, yup, yup versus the high price storage, you know, that you have to use for a relational database, you know, and not to mention the standbys, the backups. So, you know, you're duplicating, triplicating all this data in here too in expensive manner. So yeah. >> Yeah, copy creating, moving data around and it gets expensive. It's funny when you say about databases, it's true. But database used to be such a boring market now it's exploded. Then you had the whole no SQL movement and SQL became the killer app, you know, it's like full circle. (laughing) >> Yeah, yeah, exactly. >> Well, anyway, good stuff Mark, really, I really appreciate you coming on "The Cube" and sharing your perspectives. We'd love to have you back in the future. >> Oh yeah, yeah, no problem. Thanks for having me. I really appreciate it. >> Yeah, our pleasure. Okay, in a moment, I'll have some closing thoughts on getting more value out of your growing data lakes. You're watching "The Cube," you're leader in high-tech coverage. (gentle music)

from the cube studios in palo alto in boston bringing you data driven insights from the cube and etr this is breaking analysis with dave vellante recent survey data from etr shows that enterprise tech spending is tracking with projected u.s gdp growth at six to seven percent this year many markers continue to point the way to a strong recovery including hiring trends and the loosening of frozen it project budgets however skills shortages are blocking progress at some companies which bodes well for an increased reliance on external i.t services moreover while there's much to talk about well there's much talk about the rotation out of work from home plays and stocks such as video conferencing vdi and other remote worker tech we see organizations still trying to figure out the ideal balance between funding headquarter investments that have been neglected and getting hybrid work right in particular the talent gap combined with a digital mandate means companies face some tough decisions as to how to fund the future while serving existing customers and transforming culturally hello everyone and welcome to this week's wikibon cube insights powered by etr in this breaking analysis we welcome back eric porter bradley of etr who will share fresh data perspectives and insights from the latest survey data eric great to see you welcome thank you very much dave always good to see you and happy to be on the show again okay we're going to share some macro data and then we're going to dig into some highlights from etr's most recent march covid survey and also the latest april data so eric the first chart that we want to show it shows cio and it buyer responses to expected i.t spend for each quarter of 2021 versus 2020. and you can see here a steady quarterly improvement eric what are the key takeaways from your perspective sure well first of all for everyone out there this particular survey had a record-setting number of uh participation we had uh 1 500 i.t decision makers participate and we had over half of the fortune 500 and over a fifth of the global 1000. so it was a really good survey this is the seventh iteration of the covet impact survey specifically and this is going to transition to an over large macro survey going forward so we could continue it and you're 100 right what we've been tracking here since uh march of last year was how is spending being impacted because of covid where is it shifting and what we're seeing now finally is that there is a real re-acceleration in spend i know we've been a little bit more cautious than some of the other peers out there that just early on slapped an eight or a nine percent number but what we're seeing is right now it's at a midpoint of over six uh about six point seven percent and that is accelerating so uh we are still hopeful that that will continue uh really that spending is going to be in the second half of the year as you can see on the left part of this chart that we're looking at uh it was about 1.7 versus 3 for q1 spending year over year so that is starting to accelerate through the back half you know i think it's prudent to be be cautious relative because normally you'd say okay tech is going to grow a couple of points higher than gdp but it's it's really so hard to predict this year okay the next chart is here that we want to show you is we ask respondents to indicate what strategies they're employing in the short term as a result of coronavirus and you can see a few things that i'll call out and then i'll ask eric to chime in first there's been no meaningful change of course no surprise in tactics like remote work and halting travel however we're seeing very positive trends in other areas trending downward like hiring freezes and freezing i.t deployments downward trend in layoffs and we also see an increase in the acceleration of new i.t deployments and in hiring eric what are your key takeaways well first of all i think it's important to point out here that uh we're also capturing that people believe remote work productivity is still increasing now the trajectory might be coming down a little bit but that is really key i think to the backdrop of what's happening here so people have a perception that productivity of remote work is better than hybrid work and that's from the i.t decision makers themselves um but what we're seeing here is that uh most importantly these organizations are citing plans to increase hiring and that's something that i think is really important to point out it's showing a real thawing and to your point in right in the beginning of the intro uh we are seeing deployments stabilize versus prior survey levels which means early on they had no plans to launch new tech deployments then they said nope we're going to start and now that's stalling and i think it's exactly right what you said is there's an i.t skills shortage so people want to continue to do i.t deployments because they have to support work from home and a hybrid back return to the office but they just don't have the skills to do so and i think that's really probably the most important takeaway from this chart um is that stalling and to really ask why it's stalling yeah so we're going to get into that for sure and and i think that's a really key point is that that that accelerating it deployments is some it looks like it's hit a wall in the survey and so but before before we get deep into the skills let's let's take a look at this next chart and we're asking people here how a return to the new normal if you will and back to offices is going to change spending with on-prem architectures and applications and so the first two bars they're cloud-friendly if you add them up at 63 percent of the respondents say that either they'll stay in the cloud for the most part or they're going to lower the on-prem spend when they go back to the office the next three bars are on-prem friendly if you add those up as 29 percent of the respondents say their on-prem spend is going to bounce back to pre-covert levels or actually increase and of course 12 percent of that number by the way say they they've never altered their on-prem spend so eric no surprise but this bodes well for cloud but but it it isn't it also a positive for on-prem this we've had this dual funding premise meaning cloud continues to grow but neglected data center spend also gets a boost what's your thoughts you know really it's interesting it's people are spending on all fronts you and i were talking in a prep it's like you know we're we're in battle and i've got naval i've got you know air i've got land uh i've got to spend on cloud and digital transformation but i also have to spend for on-prem uh the hybrid work is here and it needs to be supported so this spending is going to increase you know when you look at this chart you're going to see though that roughly 36 percent of all respondents say that their spending is going to remain mostly on cloud so this you know that is still the clear direction uh digital transformation is still happening covid accelerated it greatly um you know you and i as journalists and researchers already know this is where the puck is going uh but spend has always lagged a little bit behind because it just takes some time to get there you know inversely 27 said that their on-prem spending will decrease so when you look at those two i still think that the trend is the friend for cloud spending uh even though yes they do have to continue spending on hybrid some of it's been neglected there are refresh cycles coming up so overall it just points to more and more spending right now it really does seem to be a very strong backdrop for it growth so i want to talk a little bit about the etr taxonomy before we bring up the next chart we get a lot of questions about this and of course when you do a massive survey like you're doing you have to have consistency for time series so you have to really think through what that what the buckets look like if you will so this next chart takes a look at the etr taxonomy and it breaks it down into simple to understand terms so the green is the portion of spending on a vendor's tech within a category that is accelerating and the red is the portion that is decelerating so eric what are the key messages in this data well first of all dave thank you so much for pointing that out we used to do uh just what we call a next a net score it's a proprietary formula that we use to determine the overall velocity of spending some people found it confusing um our data scientists decided to break this sector breakdown into what you said which is really more of a mode analysis in that sector how many of the vendors are increasing versus decreasing so again i just appreciate you bringing that up and allowing us to explain the the the reasoning behind our analysis there but what we're seeing here uh goes back to something you and i did last year when we did our predictions and that was that it services and consulting was going to have a true rebound in 2021 and that's what this is showing right here so in this chart you're going to see that consulting and services are really continuing their recovery uh 2020 had a lot of declines and they have the biggest sector over year-over-year acceleration sector-wise the other thing to point out in this which we'll get to again later is that the inverse analysis is true for video conferencing uh we will get to that so i'm going to leave a little bit of ammunition behind for that one but what we're seeing here is it consulting services being the real favorable and video conferencing uh having a little bit more trouble great okay and then let's let's take a look at that services piece and this next chart really is a drill down into that space and emphasizes eric what you were just talking about and we saw this in ibm's earnings where still more than 60 percent of ibm's business comes from services and the company beat earnings you know in part due to services outperforming expectations i think it had a somewhat easier compare and some of this pen-up demand that we've been talking about bodes well for ibm and in other services companies it's not just ibm right eric no it's not but again i'm going to point out that you and i did point out ibm in our in our predictions one we did in late december so it is nice to see one of the reasons we don't have a more favorable rating on ibm at the moment is because they are in the the process of spinning out uh this large unit and so there's a little bit of you know corporate action there that keeps us off on the sideline but i would also want to point out here uh tata infosys and cognizant because they're seeing year-over-year acceleration in both it consulting and outsourced i t services so we break those down separately and those are the three names that are seeing acceleration in both of those so again a tata emphasis and cognizant are all looking pretty well positioned as well so we've been talking a little bit about this skill shortage and this is what's i think so hard for for forecasters um is that you know on the one hand there's a lot of pent up demand you know it's like scott gottlieb said it's like woodstock coming out of the covid uh but on the other hand if you have a talent gap you've got to rely on external services so there's a learning curve there's a ramp up it's an external company and so it takes time to put those together so so this data that we're going to show you next uh is is really important in my view and ties what we're saying we're saying at the top it asks respondents to comment on their staffing plans the light blue is we're increasing staff the gray is no change in the magenta or whatever whatever color that is that sort of purplish color anyway that color is is decreasing and the picture is very positive across the board full-time staff offshoring contract employees outsourced professional services all up trending upwards and this eric is more evidence of the services bounce back yeah it certainly is david and what happened is when we caught this trend we decided to go one level deeper and say all right we're seeing this but we need to know why and that's what we always try to do here data will tell you what's happening it doesn't always tell you why and that's one of the things that etr really tries to dig in with through the insights interviews panels and also going direct with these more custom survey questions uh so in this instance i think the real takeaway is that 30 of the respondents said that their outsourced and managed services are going to increase over the next three months that's really powerful that's a large portion of organizations in a very short time period so we're capturing that this acceleration is happening right now and it will be happening in real time and i don't see it slowing down you and i are speaking about we have to you know increase cloud spend we have to increase hybrid spend there are refresh cycles coming up and there's just a real skill shortage so this is a long-term setup that bodes very well for it services and consulting you know eric when i came out of college i somebody told me read read read read as much as you can and and so i would and they said read the wall street journal every day and i so i did it and i would read the tech magazines and back then it was all paper and what happens is you begin to connect the dots and so the reason i bring that up is because i've now been had taken a bath in the etr data for the better part of two years and i'm beginning to be able to connect the dots you know the data is not always predictive but many many times it is and so this next data gets into the fun stuff where we name names a lot of times people don't like it because the marketing people and organizations say well the data's wrong of course that's the first thing they do is attack the data but you and i know we've made some really great calls work from home for sure you're talking about the services bounce back uh we certainly saw the rise of crowdstrike octa zscaler well before people were talking about that same thing with video conferencing and so so anyway this is the fun stuff and it looks at positive versus negative sentiment on on companies so first how does etr derive this data and how should we interpret it and what are some of your takeaways [Music] sure first of all how we derive the data or systematic um survey responses that we do on a quarterly basis and we standardize those responses to allow for time series analysis so we can do trend analysis as well we do find that our data because it's talking about forward-looking spending intentions is really more predictive because we're talking about things that might be happening six months three months in the future not things that a lot of other competitors and research peers are looking at things that already happened uh they're looking in the past etr really likes to look into the future and our surveys are set up to do so so thank you for that question it's an enjoyable lead-in but to get to the fun stuff like you said uh what we do here is we put ratings on the data sets i do want to put the caveat out there that our spending intentions really only captures top-line revenue it is not indicative of profit margin or any other line items so this is only going to be viewed as what we are rating the data set itself not the company um you know that's not what we're in the game of doing so i think that's very important for the marketing and the vendors out there themselves when they when they take a look at this we're just talking about what we can control which is our data we're going to talk about a few of the names here on this highlighted vendors list one we're going to go back to that you and i spoke about i guess about six months ago or maybe even earlier which was the observability space um you and i were noticing that it was getting very crowded a lot of new entrants um there was a lot of acquisition from more of the legacy or standard entrance players in the space and that is continuing so i think in a minute we're going to move into that observability space but what we're seeing there is that it's becoming incredibly crowded and we're possibly seeing signs of them cannibalizing each other uh we're also going to move on a little bit into video conferencing where we're capturing some spend deceleration and then ultimately we're going to get into a little bit of a storage refresh cycle and talk about that but yeah these are the highlighted vendors for april um we usually do this once a quarter and they do change based on the data but they're not usually whipsawed around the data doesn't move that quickly yeah so you can see the some of the big names on the left-hand side some of the sas companies that have momentum obviously servicenow has been doing very very well we've talked a lot about snowflake octa crowdstrike z scalar in all very positive as well as you know several others i i guess i'd add some some things i mean i think if thinking about the next decade it's it's cloud which is not going to be like the same cloud as last decade a lot of machine learning and deep learning and ai and the cloud is extending to the edge in the data center data obviously very important data is decentralized and distributed so data architectures are changing a lot of opportunities to connect across clouds and actually create abstraction layers and then something that we've been covering a lot is processor performance is actually accelerating relative to moore's law it's probably instead of doubling every two years it's quadrupling every two years and so that is a huge factor especially as it relates to powering ai and ai inferencing at the edge this is a whole new territory custom silicon is is really becoming in vogue uh and so we're something that we're watching very very closely yeah i completely completely agree on that and i do think that the the next version of cloud will be very different another thing to point out on that too is you can't do anything that you're talking about without collecting the data and and organizations are extremely serious about that now it seems it doesn't matter what industry they're in every company is a data company and that also bodes well for the storage call we do believe that there is going to just be a huge increase in the need for storage um and yes hopefully that'll become portable across multi-cloud and hybrid as well now as eric said the the etr data's it's it's really focused on that top line spend so if you look at the uh on on the right side of that chart you saw you know netapp was kind of negative was very negative right but there's a company that's in in transformation now they've lowered expectations and they've recently beat expectations that's why the stock has been doing better but but at the macro from a spending standpoint it's still challenged so you have big footprint companies like netapp and oracle is another one oracle's stock is at an all-time high but the spending relative to sort of previous cycles or relative to you know like for instance snowflake much much smaller not as high growth but they're managing expectations they're managing their transition they're managing profitability zoom is another one zoom looking looking negative but you know zoom's got to use its market cap now to to transform and increase its tam uh and then splunk is another one we're going to talk about splunk is in transition it acquired signal fx it just brought on this week teresa carlson who was the head of aws public sector she's the president and head of sales so they've got a go to market challenge and they brought in teresa carlson to really solve that but but splunk has been trending downward we called that you know several quarters ago eric and so i want to bring up the data on splunk and this is splunk eric in analytics and it's not trending in the right direction the green is accelerating span the red is and the bars is decelerating spend the top blue line is spending velocity or net score and the yellow line is market share or pervasiveness in the data set your thoughts yeah first i want to go back is a great point dave about our data versus a disconnect from an equity analysis perspective i used to be an equity analyst that is not what we do here and you you may the main word you said is expectations right stocks will trade on how they do compared to the expectations that are set uh whether that's buy side expectations sell side expectations or management's guidance themselves we have no business in tracking any of that what we are talking about is top line acceleration or deceleration so uh that was a great point to make and i do think it's an important one for all of our listeners out there now uh to move to splunk yes i've been capturing a lot of negative commentary on splunk even before the data turned so this has been about a year-long uh you know our analysis and review on this name and i'm dating myself here but i know you and i are both rock and roll fans so i'm gonna point out a led zeppelin song and movie and say that the song remains the same for splunk we are just seeing uh you know recent spending intentions are taking yet another step down both from prior survey levels from year ago levels uh this we're looking at in the analytics sector and spending intentions are decelerating across every single customer group if we went to one of our other slide analysis um on the etr plus platform and you do by customer sub sample in analytics it's dropping in every single vertical it doesn't matter which one uh it's really not looking good unfortunately and you had mentioned this as an analytics and i do believe the next slide is an information security yeah let's bring that up and it's unfortunately it's not doing much better so this is specifically fortune 500 accounts and information security uh you know there's deep pockets in the fortune 500 but from what we're hearing in all the insights and interviews and panels that i personally moderate for etr people are upset they didn't like the the strong tactics that splunk has used on them in the past they didn't like the ingestion model pricing the inflexibility and when alternatives came along people are willing to look at the alternatives and that's what we're seeing in both analytics and big data and also for their sim in security yeah so i think again i i point to teresa carlson she's got a big job but she's very capable she's gonna she's gonna meet with a lot of customers she's a go to market pro she's gonna have to listen hard and i think you're gonna you're gonna see some changes there um okay so there's more sorry there's more bad news on splunk so bring this up is is is net score for splunk in elastic accounts uh this is for analytics so there's 106 elastic accounts that uh in the data set that also have splunk and it's trending downward for splunk that's why it's green for elastic and eric the important call out from etr here is how splunk's performance in elastic accounts compares with its performance overall the elk stack which obviously elastic is a big part of that is causing pain for splunk as is data dog and you mentioned the pricing issue uh is it is it just well is it pricing in your assessment or is it more fundamental you know it's multi-level based on the commentary we get from our itdms that take the survey so yes you did a great job with this analysis what we're looking at is uh the spending within shared accounts so if i have splunk already how am i spending i'm sorry if i have elastic already how is my spending on splunk and what you're seeing here is it's down to about a 12 net score whereas splunk overall has a 32 net score among all of its customers so what you're seeing there is there is definitely a drain that's happening where elastic is draining spend from splunk and usage from them uh the reason we used elastic here is because all observabilities the whole sector seems to be decelerating splunk is decelerating the most but elastic is the only one that's actually showing resiliency so that's why we decided to choose these two but you pointed out yes it's also datadog datadog is cloud native uh they're more devops oriented they tend to be viewed as having technological lead as compared to splunk so that's a really good point a dynatrace also is expanding their abilities and splunk has been making a lot of acquisitions to push their cloud services they are also changing their pricing model right they're they're trying to make things a little bit more flexible moving off ingestion um and moving towards uh you know consumption so they are trying and the new hires you know i'm not gonna bet against them because the one thing that splunk has going for them is their market share in our survey they're still very well entrenched so they do have a lot of accounts they have their foothold so if they can find a way to make these changes then they you know will be able to change themselves but the one thing i got to say across the whole sector is competition is increasing and it does appear based on commentary and data that they're starting to cannibalize themselves it really seems pretty hard to get away from that and you know there are startups in the observability space too that are going to be you know even more disruptive i think i think i want to key on the pricing for a moment and i've been pretty vocal about this i think the the old sas pricing model where essentially you essentially lock in for a year or two years or three years pay up front or maybe pay quarterly if you're lucky that's a one-way street and i think it's it's a flawed model i like what snowflake's doing i like what datadog's doing look at what stripe is doing look what twilio is doing these are cons you mentioned it because it's consumption based pricing and if you've got a great product put it out there and you know damn the torpedoes and i think that is a game changer i i look at for instance hpe with green lake i look at dell with apex they're trying to mimic that model you know they're there and apply it to to infrastructure it's much harder with infrastructure because you got to deploy physical infrastructure but but that is a model that i think is going to change and i think all of the traditional sas pricing is going to is going to come under disruption over the next you know better part of the decades but anyway uh let's move on we've we've been covering the the apm space uh pretty extensively application performance management and this chart lines up some of the big players here comparing net score or spending momentum from the april 20th survey the gray is is um is sorry the the the gray is the april 20th survey the blue is jan 21 and the yellow is april 21. and not only are elastic and data dog doing well relative to splunk eric but everything is down from last year so this space as you point out is undergoing a transformation yeah the pressures are real and it's you know it's sort of that perfect storm where it's not only the data that's telling us that but also the direct feedback we get from the community uh pretty much all the interviews i do i've done a few panels specifically on this topic for anyone who wants to you know dive a little bit deeper we've had some experts talk about this space and there really is no denying that there is a deceleration in spend and it's happening because that spend is getting spread out among different vendors people are using you know a data dog for certain aspects they're using elastic where they can because it's cheaper they're using splunk because they have to but because it's so expensive they're cutting some of the things that they're putting into splunk which is dangerous particularly on the security side if i have to decide what to put in and whatnot that's not really the right way to have security hygiene um so you know this space is just getting crowded there's disruptive vendors coming from the emerging space as well and what you're seeing here is the only bit of positivity is elastic on a survey over survey basis with a slight slight uptick everywhere else year over year and survey over survey it's showing declines it's just hard to ignore and then you've got dynatrace who based on the the interviews you do in the venn you're you know one on one or one on five you know the private interviews that i've been invited to dynatrace gets very high scores uh for their road map you've got new relic which has been struggling you know financially but they've got a purpose built they've got a really good product and a purpose-built database just for this apm space and then of course you've got cisco with appd which is a strong business for them and then as you mentioned you've got startups coming in you've got chaos search which ed walsh is now running you know leave the data in place in aws and really interesting model honeycomb it's going to be really disruptive jeremy burton's company observed so this space is it's becoming jump ball yeah there's a great line that came out of one of them and that was that the lines are blurring it used to be that you knew exactly that app dynamics what they were doing it was apm only or it was logging and monitoring only and a lot of what i'm hearing from the itdm experts is that the lines are blurring amongst all of these names they all have functionality that kind of crosses over each other and the other interesting thing is it used to be application versus infrastructure monitoring but as you know infrastructure is becoming code more and more and more and as infrastructure becomes code there's really no difference between application and infrastructure monitoring so we're seeing a convergence and a blurring of the lines in this space which really doesn't bode well and a great point about new relic their tech gets good remarks uh i just don't know if their enterprise level service and sales is up to snuff right now um as one of my experts said a cto of a very large public online hospitality company essentially said that he would be shocked that within 18 months if all of these players are still uh standalone that there needs to be some m a or convergence in this space okay now we're going to call out some of the data that that really has jumped out to etr in the latest survey and some of the names that are getting the most queries from etr clients which are many of which are investor clients so let's start by having a look at one of the most important and prominent work from home names zoom uh let's let's look at this eric is the ride over for zoom oh i've been saying it for a little bit of a time now actually i do believe it is um i will get into it but again pointing out great dave uh the reason we're presenting today splunk elastic and zoom are they are the most viewed on the etr plus platform uh trailing behind that only slightly is f5 i decided not to bring f5 to the table today because we don't have a rating on the data set um so then i went one deep one below that and it's pure so the reason we're presenting these to you today is that these are the ones that our clients and our community are most interested in which is hopefully going to gain interest to your viewers as well so to get to zoom um yeah i call zoom the pandec pandemic bull market baby uh this was really just one that had a meteoric ride you look back january in 2020 the stock was at 60 and 10 months later it was like like 580. that's in 10 months um that's cooled down a little bit uh into the mid 300s and i believe that cooling down should continue and the reason why is because we are seeing a huge deceleration in our spending intentions uh they're hitting all-time lows it's really just a very ugly data set um more importantly than the spending intentions for the first time we're seeing customer growth in our survey flattened in the past we could we knew that the the deceleration and spend was happening but meanwhile their new customer growth was accelerating so it was kind of hard to really make any call based on that this is the first time we're seeing flattening customer growth trajectory and that uh in tandem with just dominance from microsoft in every sector they're involved in i don't care if it's ip telephony productivity apps or the core video conferencing microsoft is just dominating so there's really just no way to ignore this anymore the data and the commentary state that zoom is facing some headwinds well plus you've pointed out to me that a lot of your private conversations with buyers says that hey we're we're using the freebie version of zoom you know we're not paying them and so in that combined with teams i mean it's it's uh it's i think you know look zoom has to figure it out they they've got to they've got to figure out how to use their elevated market cap to transform and expand their tan um but let's let's move on here's the data on pure storage and we've highlighted a number of times this company is showing elevated spending intentions um pure announces earnings in in may ibm uh just announced storage what uh it was way down actually so sort of still pure more positive but i'll comment on a moment but what does this data tell you eric yeah you know right now we started seeing this data last survey in january and that was the first time we really went positive on the data set itself and it's just really uh continuing so we're seeing the strongest year-over-year acceleration in the entire survey um which is a really good spot to be pure is also a leading position in among its sector peers and the other thing that was pretty interesting from the data set is among all storage players pure has the highest positive public cloud correlation so what we can do is we can see which respondents are accelerating their public cloud spend and then cross-reference that with their storage spend and pure is best positioned so as you and i both know uh you know digital transformation cloud spending is increasing you need to be aligned with that and among all storage uh sector peers uh pure is best positioned in all of those in spending intentions and uh adoptions and also public cloud correlation so yet again just another really strong data set and i have an anecdote about why this might be happening because when i saw the date i started asking in my interviews what's going on here and there was one particular person he was a director of cloud operations for a very large public tech company now they have hybrid um but their data center is in colo so they don't own and build their own physical building he pointed out that doran kovid his company wanted to increase storage but he couldn't get into his colo center due to covert restrictions they weren't allowed you had so 250 000 square feet right but you're only allowed to have six people in there so it's pretty hard to get to your rack and get work done he said he would buy storage but then the cola would say hey you got to get it out of here it's not even allowed to sit here we don't want it in our facility so he has all this pent up demand in tandem with pent up demand we have a refresh cycle the ssd you know depreciation uh you know cycle is ending uh you know ssds are moving on and we're starting to see uh new technology in that space nvme sorry for technology increasing in that space so we have pent up demand and we have new technology and that's really leading to a refresh cycle and this particular itdm that i spoke to and many of his peers think this has a long tailwind that uh storage could be a good sector for some time to come that's really interesting thank you for that that extra metadata and i want to do a little deeper dive on on storage so here's a look at storage in the the industry in context and some of the competitive i mean it's been a tough market for the reasons that we've highlighted cloud has been eating away that flash headroom it used to be you'd buy storage to get you know more spindles and more performance and you were sort of forced to buy more flash gave more headroom but it's interesting what you're saying about the depreciation cycle so that's good news so etr combines just for people's benefit here combines primary and secondary storage into a single category so you have companies like pure and netapp which are really pure play you know primary storage companies largely in the sector along with veeam cohesity and rubric which are kind of secondary data or data protection so my my quick thoughts here are that pure is elevated and remains what i call the one-eyed man in the land of the blind but that's positive tailwinds there so that's good news rubric is very elevated but down it's a big it's big competitor cohesity is way off its highs and i have to say to me veeam is like the steady eddy consistent player here they just really continue to do well in the data protection business and and the highs are steady the lows are steady dell is also notable they've been struggling in storage their isg business which comprises service and storage it's been soft during covid and and during even you know this new product rollout so it's notable with this new mid-range they have in particular the uptick in dell this survey because dell so large a small uptick can be very good for dell hpe has a big announcement next month in storage so that might improve based on a product cycle of course the nimble brand continues to do well ibm as i said just announced a very soft quarter you know down double digits again uh and there in a product cycle shift and netapp is that looks bad in the etr data from a spending momentum standpoint but their management team is transforming the company into a cloud play which eric is why it was interesting that pure has the greatest momentum in in cloud accounts so that is sort of striking to me i would have thought it would be netapp so that's something that we want to pay attention to but i do like a lot of what netapp is doing uh and other than pure they're the only big kind of pure play in primary storage so long winded uh uh intro there eric but anything you'd add no actually i appreciate it was long winded i i'm going to be honest with you storage is not my uh my best sector as far as a researcher and analyst goes uh but i actually think a lot of what you said is spot on um you know we do capture a lot of large organizations spend uh we don't capture much mid and small so i think when you're talking about these large large players like netapp and um you know not looking so good all i would state is that we are capturing really big organizations spending attention so these are names that should be doing better to be quite honest uh in those accounts and you know at least according to our data we're not seeing it and it's long-term depression as you can see uh you know netapp now has a negative spending velocity in this analysis so you know i can go dig around a little bit more but right now the names that i'm hearing are pure cohesity uh um i'm hearing a little bit about hitachi trying to reinvent themselves in the space but you know i'll take a wait-and-see approach on that one but uh pure and cohesity are the ones i'm hearing a lot from our community so storage is transforming to cloud as a service you're seeing things like apex and in green lake from dell and hpe and container storage little so not really a lot of people paying attention to it but pure about a company called portworx which really specializes in container storage and there's many startups there they're trying to really change the way david flynn has a startup in that space he's the guy who started fusion i o so a lot a lot of transformations happening here okay i know it's been a long segment we have to summarize and then let me go through a summary and then i'll give you the last word eric so tech spending appears to be tracking us gdp at six to seven percent this talent shortage could be a blocker to accelerating i.t deployments and that's kind of good news actually for for services companies digital transformation you know it's it remains a priority and that bodes well not only for services but automation uipath went public this week we we profiled that you know extensively that went public last wednesday um organizations they've i said at the top face some tough decisions on how to allocate resources you know running the business growing the business transforming the business and we're seeing a bifurcation of spending and some residual effects on vendors and that remains a theme that we're watching eric your final thoughts yeah i'm going to go back quickly to just the overall macro spending because there's one thing i think is interesting to point out and we're seeing a real acceleration among mid and small so it seems like early on in the covid recovery or kovitz spending it was the deep pockets that moved first right fortune 500 knew they had to support remote work they started spending first round that in the fortune 500 we're only seeing about five percent spent but when you get into mid and small organizations that's creeping up to eight nine so i just think it's important to point out that they're playing catch-up right now uh also would point out that this is heavily skewed to north america spending we're seeing laggards in emea they just don't seem to be spending as much they're in a very different place in their recovery and uh you know i do think that it's important to point that out um lastly i also want to mention i know you do such a great job on following a lot of the disruptive vendors that you just pointed out pure doing container storage we also have another bi-annual survey that we do called emerging technology and that's for the private names that's going to be launching in may for everyone out there who's interested in not only the disruptive vendors but also private equity players uh keep an eye out for that we do that twice a year and that's growing in its respondents as well and then lastly one comment because you mentioned the uipath ipo it was really hard for us to sit on the sidelines and not put some sort of rating on their data set but ultimately um the data was muted unfortunately and when you're seeing this kind of hype into an ipo like we saw with snowflake the data was resoundingly strong we had no choice but to listen to what the data said for snowflake despite the hype um we didn't see that for uipath and we wanted to and i'm not making a large call there but i do think it's interesting to juxtapose the two that when snowflake was heading to its ipo the data was resoundingly positive and for uipath we just didn't see that thank you for that and eric thanks for coming on today it's really a pleasure to have you and uh so really appreciate the the uh collaboration and look forward to doing more of these we enjoy the partnership greatly dave we're very very happy to have you in the etr family and looking forward to doing a lot lot more with you in the future ditto okay that's it for today remember these episodes are all available as podcasts wherever you listen all you got to do is search breaking analysis podcast and please subscribe to the series check out etr's website it's etr dot plus we also publish a full report every week on wikibon.com at siliconangle.com you can email me david.velante at siliconangle.com you can dm me on twitter at dvalante or comment on our linkedin post i could see you in clubhouse this is dave vellante for eric porter bradley for the cube insights powered by etr have a great week stay safe be well and we'll see you next time

>>from around the globe. It's the Cube presenting enterprise. Digital resilience on hybrid and multi cloud Brought to You by Iota Ho. Hello, everyone, and welcome to our continuing Siri's covering data automation brought to you by Io Tahoe. Today we're gonna look at how to ensure enterprise resilience for hybrid and multi cloud. Let's welcome in age. Eva Hora, who is the CEO of Iota A J. Always good to see you again. Thanks for coming on. >>Great to be back. David Pleasure. >>And he's joined by Fozzy Coons, who is a global principal architect for financial services. The vertical of financial services. That red hat. He's got deep experiences in that sector. Welcome, Fozzie. Good to see you. >>Thank you very much. Happy to be here. >>Fancy. Let's start with you. Look, there are a lot of views on cloud and what it is. I wonder if you could explain to us how you think about what is a hybrid cloud and and how it works. >>Sure, yes. So the hybrid cloud is a 90 architecture that incorporates some degree off workload, possibility, orchestration and management across multiple clouds. Those clouds could be private cloud or public cloud or even your own data centers. And how does it all work? It's all about secure interconnectivity and on demand. Allocation of resources across clouds and separate clouds can become hydrate when they're similarly >>interconnected. And >>it is that interconnectivity that allows the workloads workers to be moved and how management can be unified in off the street. You can work and how well you have. These interconnections has a direct impact on how well your hybrid cloud will work. >>Okay, so we'll fancy staying with you for a minute. So in the early days of Cloud that turned private Cloud was thrown a lot around a lot, but often just meant virtualization of an on PREM system and a network connection to the public cloud. Let's bring it forward. What, in your view, does a modern hybrid cloud architecture look like? >>Sure. So for modern public clouds, we see that, um, teams organizations need to focus on the portability off applications across clouds. That's very important, right? And when organizations build applications, they need to build and deploy these applications as small collections off independently, loosely coupled services, and then have those things run on the same operating system which means, in other words, running it on Lenox everywhere and building cloud native applications and being able to manage and orchestrate thes applications with platforms like KUBERNETES or read it open shit, for example. >>Okay, so that Z, that's definitely different from building a monolithic application that's fossilized and and doesn't move. So what are the challenges for customers, you know, to get to that modern cloud? Aziz, you've just described it. Is it skill sets? Is that the ability to leverage things like containers? What's your view there? >>So, I mean, from what we've seen around around the industry, especially around financial services, where I spent most of my time, we see that the first thing that we see is management right now because you have all these clouds and all these applications, you have a massive array off connections off interconnections. You also have massive array off integrations, possibility and resource allocations as well, and then orchestrating all those different moving pieces. Things like storage networks and things like those are really difficult to manage, right? That's one. What s O Management is the first challenge. The second one is workload, placement, placement. Where do you place this? How do you place this cloud? Native applications. Do you or do you keep on site on Prem? And what do you put in the cloud? That is the the the other challenge. The major one. The third one is security. Security now becomes the key challenge and concern for most customers. And we could talk about how hundreds? Yeah, >>we're definitely gonna dig into that. Let's bring a J into the conversation. A J. You know, you and I have talked about this in the past. One of the big problems that virtually every companies face is data fragmentation. Um, talk a little bit about how I owe Tahoe unifies data across both traditional systems legacy systems. And it connects to these modern I t environments. >>Yeah, sure, Dave. I mean, fancy just nailed it. There used to be about data of the volume of data on the different types of data. But as applications become or connected and interconnected at the location of that data really matters how we serve that data up to those those app. So working with red hat in our partnership with Red Hat being able Thio, inject our data Discovery machine learning into these multiple different locations. Would it be in AWS on IBM Cloud or A D. C p R. On Prem being able thio Automate that discovery? I'm pulling that. That single view of where is all my data then allows the CEO to manage cast that can do things like one. I keep the data where it is on premise or in my Oracle Cloud or in my IBM cloud on Connect. The application that needs to feed off that data on the way in which you do that is machine learning. That learns over time is it recognizes different types of data, applies policies to declassify that data. Andi and brings it all together with automation. >>Right? And that's one of the big themes and we've talked about this on earlier episodes. Is really simplification really abstracting a lot of that heavy lifting away so we can focus on things A. J A. Z. You just mentioned e nifaz e. One of the big challenges that, of course, we all talk about his governance across thes disparity data sets. I'm curious as your thoughts. How does Red Hat really think about helping customers adhere to corporate edicts and compliance regulations, which, of course, are are particularly acute within financial services. >>Oh, yeah, Yes. So for banks and the payment providers, like you've just mentioned their insurers and many other financial services firms, Um, you know, they have to adhere Thio standards such as a PC. I. D. S s in Europe. You've got the G g d p g d p r, which requires strange and tracking, reporting documentation. And you know, for them to to remain in compliance and the way we recommend our customers to address these challenges is by having an automation strategy. Right. And that type of strategy can help you to improve the security on compliance off the organization and reduce the risk after the business. Right. And we help organizations build security and compliance from the start without consulting services residencies. We also offer courses that help customers to understand how to address some of these challenges. And that's also we help organizations build security into their applications without open sources. Mueller, where, um, middle offerings and even using a platform like open shift because it allows you to run legacy applications and also continue rights applications in a unified platform right And also that provides you with, you know, with the automation and the truly that you need to continuously monitor, manage and automate the systems for security and compliance >>purposes. Hey, >>Jay, anything. Any color you could add to this conversation? >>Yeah, I'm pleased. Badly brought up Open shift. I mean, we're using open shift to be able. Thio, take that security application of controls to to the data level. It's all about context. So, understanding what data is there being able to assess it to say who should have access to it. Which application permission should be applied to it. Um, that za great combination of Red Hat tonight. Tahoe. >>But what about multi Cloud? Doesn't that complicate the situation even even further? Maybe you could talk about some of the best practices to apply automation across not only hybrid cloud, but multi >>cloud a swell. Yeah, sure. >>Yeah. So the right automation solution, you know, can be the difference between, you know, cultivating an automated enterprise or automation caress. And some of the recommendations we give our clients is to look for an automation platform that can offer the first thing is complete support. So that means have an automation solution that provides that provides, um, you know, promotes I t availability and reliability with your platform so that you can provide, you know, enterprise great support, including security and testing, integration and clear roadmaps. The second thing is vendor interoperability interoperability in that you are going to be integrating multiple clouds. So you're going to need a solution that can connect to multiple clouds. Simples lee, right? And with that comes the challenge off maintain ability. So you you you're going to need to look into a automation Ah, solution that that is easy to learn or has an easy learning curve. And then the fourth idea that we tell our customers is scalability in the in the hybrid cloud space scale is >>is >>a big, big deal here, and you need a to deploy an automation solution that can span across the whole enterprise in a constituent, consistent manner, right? And then also, that allows you finally to, uh, integrate the multiple data centers that you have, >>So A J I mean, this is a complicated situation, for if a customer has toe, make sure things work on AWS or azure or Google. Uh, they're gonna spend all their time doing that, huh? What can you add really? To simplify that that multi cloud and hybrid cloud equation? >>Yeah. I could give a few customer examples here Warming a manufacturer that we've worked with to drive that simplification Onda riel bonuses for them is has been a reduction cost. We worked with them late last year to bring the cost bend down by $10 million in 2021 so they could hit that reduced budget. Andre, What we brought to that was the ability thio deploy using open shift templates into their different environments. Where there is on premise on bond or in as you mentioned, a W s. They had G cps well, for their marketing team on a cross, those different platforms being out Thio use a template, use pre built scripts to get up and running in catalog and discover that data within minutes. It takes away the legacy of having teams of people having Thio to jump on workshop cause and I know we're all on a lot of teens. The zoom cause, um, in these current times, they just sent me is in in of hours in the day Thio manually perform all of this. So yeah, working with red hat applying machine learning into those templates those little recipes that we can put that automation toe work, regardless of which location the data is in allows us thio pull that unified view together. Right? >>Thank you, Fozzie. I wanna come back to you. So the early days of cloud, you're in the big apple, you know, financial services. Really well. Cloud was like an evil word within financial services, and obviously that's changed. It's evolved. We talked about the pandemic, has even accelerated that, Um And when you really, you know, dug into it when you talk to customers about their experiences with security in the cloud it was it was not that it wasn't good. It was great, whatever. But it was different. And there's always this issue of skill, lack of skills and multiple tools suck up teams, they're really overburdened. But in the cloud requires new thinking. You've got the shared responsibility model you've got obviously have specific corporate requirements and compliance. So this is even more complicated when you introduce multiple clouds. So what are the differences that you can share from your experience is running on a sort of either on Prem or on a mono cloud, um, or, you know, and versus across clouds. What? What? What do you suggest there? >>Yeah, you know, because of these complexities that you have explained here, Miss Configurations and the inadequate change control the top security threats. So human error is what we want to avoid because is, you know, as your clouds grow with complexity and you put humans in the mix, then the rate off eras is going to increase, and that is going to exposure to security threat. So this is where automation comes in because automation will streamline and increase the consistency off your infrastructure management. Also application development and even security operations to improve in your protection, compliance and change control. So you want to consistently configure resources according to a pre approved um, you know, pre approved policies and you want to proactively maintain a to them in a repeatable fashion over the whole life cycle. And then you also want to rapid the identified system that require patches and and reconfiguration and automate that process off patching and reconfiguring so that you don't have humans doing this type of thing, right? And you want to be able to easily apply patches and change assistant settings. According Thio, Pre defined, based on like explained before, you know, with the pre approved policies and also you want is off auditing and troubleshooting, right? And from a rate of perspective, we provide tools that enable you to do this. We have, for example, a tool called danceable that enables you to automate data center operations and security and also deployment of applications and also obvious shit yourself, you know, automates most of these things and obstruct the human beings from putting their fingers on, causing, uh, potentially introducing errors right now in looking into the new world off multiple clouds and so forth. The difference is that we're seeing here between running a single cloud or on prem is three main areas which is control security and compliance. Right control here it means if your on premise or you have one cloud, um, you know, in most cases you have control over your data and your applications, especially if you're on Prem. However, if you're in the public cloud, there is a difference there. The ownership, it is still yours. But your resources are running on somebody else's or the public clouds. You know, e w s and so forth infrastructure. So people that are going to do this need to really especially banks and governments need to be aware off the regulatory constraints off running, uh, those applications in the public cloud. And we also help customers regionalize some of these choices and also on security. You will see that if you're running on premises or in a single cloud, you have more control, especially if you're on Prem. You can control this sensitive information that you have, however, in the cloud. That's a different situation, especially from personal information of employees and things like that. You need to be really careful off that. And also again, we help you rationalize some of those choices. And then the last one is compliant. Aziz. Well, you see that if you're running on Prem or a single cloud, um, regulations come into play again, right? And if you're running a problem, you have control over that. You can document everything you have access to everything that you need. But if you're gonna go to the public cloud again, you need to think about that. We have automation, and we have standards that can help you, uh, you know, address some of these challenges for security and compliance. >>So that's really strong insights, Potsie. I mean, first of all, answerable has a lot of market momentum. Red hats in a really good job with that acquisition, your point about repeatability is critical because you can't scale otherwise. And then that idea you're you're putting forth about control, security compliance It's so true is I called it the shared responsibility model. And there was a lot of misunderstanding in the early days of cloud. I mean, yeah, maybe a W s is gonna physically secure the, you know, s three, but in the bucket. But we saw so many Miss configurations early on. And so it's key to have partners that really understand this stuff and can share the experiences of other clients. So this all sounds great. A j. You're sharp, you know, financial background. What about the economics? >>You >>know, our survey data shows that security it's at the top of the spending priority list, but budgets are stretched thin. E especially when you think about the work from home pivot and and all the areas that they had toe the holes that they had to fill their, whether it was laptops, you know, new security models, etcetera. So how do organizations pay for this? What's the business case look like in terms of maybe reducing infrastructure costs so I could, you know, pay it forward or there's a There's a risk reduction angle. What can you share >>their? Yeah. I mean, the perspective I'd like to give here is, um, not being multi cloud is multi copies of an application or data. When I think about 20 years, a lot of the work in financial services I was looking at with managing copies of data that we're feeding different pipelines, different applications. Now what we're saying I talk a lot of the work that we're doing is reducing the number of copies of that data so that if I've got a product lifecycle management set of data, if I'm a manufacturer, I'm just gonna keep that in one location. But across my different clouds, I'm gonna have best of breed applications developed in house third parties in collaboration with my supply chain connecting securely to that. That single version of the truth. What I'm not going to do is to copy that data. So ah, lot of what we're seeing now is that interconnectivity using applications built on kubernetes. Um, that decoupled from the data source that allows us to reduce those copies of data within that you're gaining from the security capability and resilience because you're not leaving yourself open to those multiple copies of data on with that. Couldn't come. Cost, cost of storage on duh cost of compute. So what we're seeing is using multi cloud to leverage the best of what each cloud platform has to offer That goes all the way to Snowflake and Hiroko on Cloud manage databases, too. >>Well, and the people cost to a swell when you think about yes, the copy creep. But then you know when something goes wrong, a human has to come in and figured out um, you brought up snowflake, get this vision of the data cloud, which is, you know, data data. I think this we're gonna be rethinking a j, uh, data architectures in the coming decade where data stays where it belongs. It's distributed, and you're providing access. Like you said, you're separating the data from the applications applications as we talked about with Fozzie. Much more portable. So it Z really the last 10 years will be different than the next 10 years. A. >>J Definitely. I think the people cast election is used. Gone are the days where you needed thio have a dozen people governing managing black policies to data. Ah, lot of that repetitive work. Those tests can be in power automated. We've seen examples in insurance were reduced teams of 15 people working in the the back office China apply security controls compliance down to just a couple of people who are looking at the exceptions that don't fit. And that's really important because maybe two years ago the emphasis was on regulatory compliance of data with policies such as GDP are in CCP a last year, very much the economic effect of reduce headcounts on on enterprises of running lean looking to reduce that cost. This year, we can see that already some of the more proactive cos they're looking at initiatives such as net zero emissions how they use data toe under understand how cape how they can become more have a better social impact. Um, and using data to drive that, and that's across all of their operations and supply chain. So those regulatory compliance issues that may have been external we see similar patterns emerging for internal initiatives that benefiting the environment, social impact and and, of course, course, >>great perspectives. Yeah, Jeff Hammer, Bucker once famously said, The best minds of my generation are trying to get people to click on ads and a J. Those examples that you just gave of, you know, social good and moving. Uh, things forward are really critical. And I think that's where Data is gonna have the biggest societal impact. Okay, guys, great conversation. Thanks so much for coming on the program. Really appreciate your time. Keep it right there from, or insight and conversation around, creating a resilient digital business model. You're watching the >>Cube digital resilience, automated compliance, privacy and security for your multi cloud. Congratulations. You're on the journey. You have successfully transformed your organization by moving to a cloud based platform to ensure business continuity in these challenging times. But as you scale your digital activities, there is an inevitable influx of users that outpaces traditional methods of cybersecurity, exposing your data toe underlying threats on making your company susceptible toe ever greater risk to become digitally resilient. Have you applied controls your data continuously throughout the data Lifecycle? What are you doing to keep your customer on supply data private and secure? I owe Tahoe's automated, sensitive data. Discovery is pre programmed with over 300 existing policies that meet government mandated risk and compliance standards. Thes automate the process of applying policies and controls to your data. Our algorithm driven recommendation engine alerts you to risk exposure at the data level and suggests the appropriate next steps to remain compliant on ensure sensitive data is secure. Unsure about where your organization stands In terms of digital resilience, Sign up for a minimal cost commitment. Free data Health check. Let us run our sensitive data discovery on key unmapped data silos and sources to give you a clear understanding of what's in your environment. Book time within Iot. Tahoe Engineer Now >>Okay, let's now get into the next segment where we'll explore data automation. But from the angle of digital resilience within and as a service consumption model, we're now joined by Yusuf Khan, who heads data services for Iot, Tahoe and Shirish County up in. Who's the vice president and head of U. S. Sales at happiest Minds? Gents, welcome to the program. Great to have you in the Cube. >>Thank you, David. >>Trust you guys talk about happiest minds. This notion of born digital, foreign agile. I like that. But talk about your mission at the company. >>Sure. >>A former in 2011 Happiest Mind is a born digital born a child company. The reason is that we are focused on customers. Our customer centric approach on delivering digitals and seamless solutions have helped us be in the race. Along with the Tier one providers, Our mission, happiest people, happiest customers is focused to enable customer happiness through people happiness. We have Bean ranked among the top 25 i t services company in the great places to work serving hour glass to ratings off 41 against the rating off. Five is among the job in the Indian nineties services company that >>shows the >>mission on the culture. What we have built on the values right sharing, mindful, integrity, learning and social on social responsibilities are the core values off our company on. That's where the entire culture of the company has been built. >>That's great. That sounds like a happy place to be. Now you said you had up data services for Iot Tahoe. We've talked in the past. Of course you're out of London. What >>do you what? Your >>day to day focus with customers and partners. What you focused >>on? Well, David, my team work daily with customers and partners to help them better understand their data, improve their data quality, their data governance on help them make that data more accessible in a self service kind of way. To the stakeholders within those businesses on dis is all a key part of digital resilience that will will come on to talk about but later. You're >>right, e mean, that self service theme is something that we're gonna we're gonna really accelerate this decade, Yussef and so. But I wonder before we get into that, maybe you could talk about the nature of the partnership with happiest minds, you know? Why do you guys choose toe work closely together? >>Very good question. Um, we see Hyo Tahoe on happiest minds as a great mutual fit. A Suresh has said, uh, happiest minds are very agile organization um, I think that's one of the key things that attracts their customers on Io. Tahoe is all about automation. Uh, we're using machine learning algorithms to make data discovery data cataloging, understanding, data done. See, uh, much easier on. We're enabling customers and partners to do it much more quickly. So when you combine our emphasis on automation with the emphasis on agility that happiest minds have that that's a really nice combination work works very well together, very powerful. I think the other things that a key are both businesses, a serious have said, are really innovative digital native type type companies. Um, very focused on newer technologies, the cloud etcetera on. Then finally, I think they're both Challenger brands on happiest minds have a really positive, fresh ethical approach to people and customers that really resonates with us at Ideo Tahoe to >>great thank you for that. So Russia, let's get into the whole notion of digital resilience. I wanna I wanna sort of set it up with what I see, and maybe you can comment be prior to the pandemic. A lot of customers that kind of equated disaster recovery with their business continuance or business resilient strategy, and that's changed almost overnight. How have you seen your clients respond to that? What? I sometimes called the forced march to become a digital business. And maybe you could talk about some of the challenges that they faced along the way. >>Absolutely. So, uh, especially during this pandemic, times when you say Dave, customers have been having tough times managing their business. So happiest minds. Being a digital Brazilian company, we were able to react much faster in the industry, apart from the other services company. So one of the key things is the organisation's trying to adopt onto the digital technologies. Right there has bean lot off data which has been to manage by these customers on There have been lot off threats and risk, which has been to manage by the CEO Seo's so happiest minds digital resilient technology, right where we bring in the data. Complaints as a service were ableto manage the resilience much ahead off other competitors in the market. We were ableto bring in our business continuity processes from day one, where we were ableto deliver our services without any interruption to the services. What we were delivered to our customers So that is where the digital resilience with business community process enabled was very helpful for us. Toe enable our customers continue their business without any interruptions during pandemics. >>So I mean, some of the challenges that customers tell me they obviously they had to figure out how to get laptops to remote workers and that that whole remote work from home pivot figure out how to secure the end points. And, you know, those were kind of looking back there kind of table stakes, But it sounds like you've got a digital business. Means a data business putting data at the core, I like to say, but so I wonder if you could talk a little bit more about maybe the philosophy you have toward digital resilience in the specific approach you take with clients? >>Absolutely. They seen any organization data becomes. The key on that, for the first step is to identify the critical data. Right. So we this is a six step process. What we following happiest minds. First of all, we take stock off the current state, though the customers think that they have a clear visibility off their data. How are we do more often assessment from an external point off view on see how critical their data is, then we help the customers to strategies that right. The most important thing is to identify the most important critical herself. Data being the most critical assert for any organization. Identification off the data's key for the customers. Then we help in building a viable operating model to ensure these identified critical assets are secure on monitor dearly so that they are consumed well as well as protected from external threats. Then, as 1/4 step, we try to bring in awareness, toe the people we train them >>at >>all levels in the organization. That is a P for people to understand the importance off the digital ourselves and then as 1/5 step, we work as a back up plan in terms of bringing in a very comprehensive and a holistic testing approach on people process as well as in technology. We'll see how the organization can withstand during a crisis time, and finally we do a continuous governance off this data, which is a key right. It is not just a one step process. We set up the environment, we do the initial analysis and set up the strategy on continuously govern this data to ensure that they are not only know managed will secure as well as they also have to meet the compliance requirements off the organization's right. That is where we help organizations toe secure on Meet the regulations off the organizations. As for the privacy laws, so this is a constant process. It's not on one time effort. We do a constant process because every organization goes towards their digital journey on. They have to face all these as part off the evolving environment on digital journey. And that's where they should be kept ready in terms off. No recovering, rebounding on moving forward if things goes wrong. >>So let's stick on that for a minute, and then I wanna bring yourself into the conversation. So you mentioned compliance and governance when when your digital business, you're, as you say, you're a data business, so that brings up issues. Data sovereignty. Uh, there's governance, this compliance. There's things like right to be forgotten. There's data privacy, so many things. These were often kind of afterthoughts for businesses that bolted on, if you will. I know a lot of executives are very much concerned that these air built in on, and it's not a one shot deal. So do you have solutions around compliance and governance? Can you deliver that as a service? Maybe you could talk about some of the specifics there, >>so some of way have offered multiple services. Tow our customers on digital against. On one of the key service is the data complaints. As a service here we help organizations toe map the key data against the data compliance requirements. Some of the features includes in terms off the continuous discovery off data right, because organizations keep adding on data when they move more digital on helping the helping and understanding the actual data in terms off the residents of data, it could be a heterogeneous data soldiers. It could be on data basis, or it could be even on the data legs. Or it could be a no even on compromise all the cloud environment. So identifying the data across the various no heterogeneous environment is very key. Feature off our solution. Once we identify classify this sensitive data, the data privacy regulations on the traveling laws have to be map based on the business rules So we define those rules on help map those data so that organizations know how critical their digital assets are. Then we work on a continuous marching off data for anomalies because that's one of the key teachers off the solution, which needs to be implemented on the day to day operational basis. So we're helping monitoring those anomalies off data for data quality management on an ongoing basis. On finally, we also bringing the automated data governance where we can manage the sensory data policies on their later relationships in terms off mapping on manage their business roots on we drive reputations toe Also suggest appropriate actions to the customers. Take on those specific data sets. >>Great. Thank you, Yousef. Thanks for being patient. I want to bring in Iota ho thio discussion and understand where your customers and happiest minds can leverage your data automation capability that you and I have talked about in the past. I'm gonna be great if you had an example is well, but maybe you could pick it up from there, >>John. I mean, at a high level, assertions are clearly articulated. Really? Um, Hyoty, who delivers business agility. So that's by, um accelerating the time to operationalize data, automating, putting in place controls and actually putting helping put in place digital resilience. I mean way if we step back a little bit in time, um, traditional resilience in relation to data often met manually, making multiple copies of the same data. So you have a d b A. They would copy the data to various different places, and then business users would access it in those functional style owes. And of course, what happened was you ended up with lots of different copies off the same data around the enterprise. Very inefficient. ONDA course ultimately, uh, increases your risk profile. Your risk of a data breach. Um, it's very hard to know where everything is. And I realized that expression. They used David the idea of the forced march to digital. So with enterprises that are going on this forced march, what they're finding is they don't have a single version of the truth, and almost nobody has an accurate view of where their critical data is. Then you have containers bond with containers that enables a big leap forward so you could break applications down into micro services. Updates are available via a p I s on. So you don't have the same need thio to build and to manage multiple copies of the data. So you have an opportunity to just have a single version of the truth. Then your challenge is, how do you deal with these large legacy data states that the service has been referring Thio, where you you have toe consolidate and that's really where I attack comes in. Um, we massively accelerate that process of putting in a single version of the truth into place. So by automatically discovering the data, discovering what's dubica? What's redundant? Uh, that means you can consolidate it down to a single trusted version much more quickly. We've seen many customers have tried to do this manually, and it's literally taken years using manual methods to cover even a small percentage of their I T estates. With our tire, you could do it really very quickly on you can have tangible results within weeks and months on Ben, you can apply controls to the data based on context. So who's the user? What's the content? What's the use case? Things like data quality validations or access permissions on. Then, once you've done there. Your applications and your enterprise are much more secure, much more resilient. As a result, you've got to do these things whilst retaining agility, though. So coming full circle. This is where the partnership with happiest minds really comes in as well. You've got to be agile. You've gotta have controls. Um, on you've got a drug toward the business outcomes. Uh, and it's doing those three things together that really deliver for the customer. >>Thank you. Use f. I mean you and I. In previous episodes, we've looked in detail at the business case. You were just talking about the manual labor involved. We know that you can't scale, but also there's that compression of time. Thio get to the next step in terms of ultimately getting to the outcome. And we talked to a number of customers in the Cube, and the conclusion is, it's really consistent that if you could accelerate the time to value, that's the key driver reducing complexity, automating and getting to insights faster. That's where you see telephone numbers in terms of business impact. So my question is, where should customers start? I mean, how can they take advantage of some of these opportunities that we've discussed today. >>Well, we've tried to make that easy for customers. So with our Tahoe and happiest minds, you can very quickly do what we call a data health check. Um, this is a is a 2 to 3 week process, uh, to really quickly start to understand on deliver value from your data. Um, so, iota, who deploys into the customer environment? Data doesn't go anywhere. Um, we would look at a few data sources on a sample of data. Onda. We can very rapidly demonstrate how they discovery those catalog e on understanding Jupiter data and redundant data can be done. Um, using machine learning, um, on how those problems can be solved. Um, And so what we tend to find is that we can very quickly, as I say in the matter of a few weeks, show a customer how they could get toe, um, or Brazilian outcome on then how they can scale that up, take it into production on, then really understand their data state? Better on build. Um, Brasiliense into the enterprise. >>Excellent. There you have it. We'll leave it right there. Guys, great conversation. Thanks so much for coming on the program. Best of luck to you and the partnership Be well, >>Thank you, David Suresh. Thank you. Thank >>you for watching everybody, This is Dave Volonte for the Cuban are ongoing Siris on data automation without >>Tahoe, digital resilience, automated compliance, privacy and security for your multi cloud. Congratulations. You're on the journey. You have successfully transformed your organization by moving to a cloud based platform to ensure business continuity in these challenging times. But as you scale your digital activities, there is an inevitable influx of users that outpaces traditional methods of cybersecurity, exposing your data toe underlying threats on making your company susceptible toe ever greater risk to become digitally resilient. Have you applied controls your data continuously throughout the data lifecycle? What are you doing to keep your customer on supply data private and secure? I owe Tahoe's automated sensitive data. Discovery is pre programmed with over 300 existing policies that meet government mandated risk and compliance standards. Thes automate the process of applying policies and controls to your data. Our algorithm driven recommendation engine alerts you to risk exposure at the data level and suggests the appropriate next steps to remain compliant on ensure sensitive data is secure. Unsure about where your organization stands in terms of digital resilience. Sign up for our minimal cost commitment. Free data health check. Let us run our sensitive data discovery on key unmapped data silos and sources to give you a clear understanding of what's in your environment. Book time within Iot. Tahoe Engineer. Now. >>Okay, now we're >>gonna go into the demo. We want to get a better understanding of how you can leverage open shift. And I owe Tahoe to facilitate faster application deployment. Let me pass the mic to Sabetta. Take it away. >>Uh, thanks, Dave. Happy to be here again, Guys, uh, they've mentioned names to be the Davis. I'm the enterprise account executive here. Toyota ho eso Today we just wanted to give you guys a general overview of how we're using open shift. Yeah. Hey, I'm Noah Iota host data operations engineer, working with open ship. And I've been learning the Internets of open shift for, like, the past few months, and I'm here to share. What a plan. Okay, so So before we begin, I'm sure everybody wants to know. Noel, what are the benefits of using open shift. Well, there's five that I can think of a faster time, the operation simplicity, automation control and digital resilience. Okay, so that that's really interesting, because there's an exact same benefits that we had a Tahoe delivered to our customers. But let's start with faster time the operation by running iota. Who on open shift? Is it faster than, let's say, using kubernetes and other platforms >>are >>objective iota. Who is to be accessible across multiple cloud platforms, right? And so by hosting our application and containers were able to achieve this. So to answer your question, it's faster to create and use your application images using container tools like kubernetes with open shift as compared to, like kubernetes with docker cry over container D. Okay, so we got a bit technical there. Can you explain that in a bit more detail? Yeah, there's a bit of vocabulary involved, uh, so basically, containers are used in developing things like databases, Web servers or applications such as I have top. What's great about containers is that they split the workload so developers can select the libraries without breaking anything. And since Hammond's can update the host without interrupting the programmers. Uh, now, open shift works hand in hand with kubernetes to provide a way to build those containers for applications. Okay, got It s basically containers make life easier for developers and system happens. How does open shift differ from other platforms? Well, this kind of leads into the second benefit I want to talk about, which is simplicity. Basically, there's a lot of steps involved with when using kubernetes with docker. But open shift simplifies this with their source to image process that takes the source code and turns it into a container image. But that's not all. Open shift has a lot of automation and features that simplify working with containers, an important one being its Web console. Here. I've set up a light version of open ship called Code Ready Containers, and I was able to set up her application right from the Web console. And I was able to set up this entire thing in Windows, Mac and Lennox. So its environment agnostic in that sense. Okay, so I think I've seen the top left that this is a developers view. What would a systems admin view look like? It's a good question. So here's the administrator view and this kind of ties into the benefit of control. Um, this view gives insights into each one of the applications and containers that are running, and you could make changes without affecting deployment. Andi can also, within this view, set up each layer of security, and there's multiple that you can prop up. But I haven't fully messed around with it because with my luck, I'd probably locked myself out. So that seems pretty secure. Is there a single point security such as you use a log in? Or are there multiple layers of security? Yeah, there are multiple layers of security. There's your user login security groups and general role based access controls. Um, but there's also a ton of layers of security surrounding like the containers themselves. But for the sake of time, I won't get too far into it. Okay, eso you mentioned simplicity In time. The operation is being two of the benefits. You also briefly mention automation. And as you know, automation is the backbone of our platform here, Toyota Ho. So that's certainly grabbed my attention. Can you go a bit more in depth in terms of automation? Open shift provides extensive automation that speeds up that time the operation. Right. So the latest versions of open should come with a built in cryo container engine, which basically means that you get to skip that container engine insulation step and you don't have to, like, log into each individual container host and configure networking, configure registry servers, storage, etcetera. So I'd say, uh, it automates the more boring kind of tedious process is Okay, so I see the iota ho template there. What does it allow me to do? Um, in terms of automation in application development. So we've created an open shift template which contains our application. This allows developers thio instantly, like set up our product within that template. So, Noah Last question. Speaking of vocabulary, you mentioned earlier digital resilience of the term we're hearing, especially in the banking and finance world. Um, it seems from what you described, industries like banking and finance would be more resilient using open shift, Correct. Yeah, In terms of digital resilience, open shift will give you better control over the consumption of resource is each container is using. In addition, the benefit of containers is that, like I mentioned earlier since Hammond's can troubleshoot servers about bringing down the application and if the application does go down is easy to bring it back up using templates and, like the other automation features that open ship provides. Okay, so thanks so much. Know us? So any final thoughts you want to share? Yeah. I just want to give a quick recap with, like, the five benefits that you gained by using open shift. Uh, the five are timeto operation automation, control, security and simplicity. You could deploy applications faster. You could simplify the workload you could automate. A lot of the otherwise tedious processes can maintain full control over your workflow. And you could assert digital resilience within your environment. Guys, >>Thanks for that. Appreciate the demo. Um, I wonder you guys have been talking about the combination of a Iot Tahoe and red hat. Can you tie that in subito Digital resilience >>Specifically? Yeah, sure, Dave eso when we speak to the benefits of security controls in terms of digital resilience at Io Tahoe, we automated detection and apply controls at the data level, so this would provide for more enhanced security. >>Okay, But so if you were trying to do all these things manually. I mean, what what does that do? How much time can I compress? What's the time to value? >>So with our latest versions, Biota we're taking advantage of faster deployment time associated with container ization and kubernetes. So this kind of speeds up the time it takes for customers. Start using our software as they be ableto quickly spin up io towel on their own on premise environment are otherwise in their own cloud environment, like including aws. Assure or call GP on IBM Cloud a quick start templates allow flexibility deploy into multi cloud environments all just using, like, a few clicks. Okay, so so now just quickly add So what we've done iota, Who here is We've really moved our customers away from the whole idea of needing a team of engineers to apply controls to data as compared to other manually driven work flows. Eso with templates, automation, previous policies and data controls. One person can be fully operational within a few hours and achieve results straight out of the box on any cloud. >>Yeah, we've been talking about this theme of abstracting the complexity. That's really what we're seeing is a major trend in in this coming decade. Okay, great. Thanks, Sabina. Noah, How could people get more information or if they have any follow up questions? Where should they go? >>Yeah, sure. They've. I mean, if you guys are interested in learning more, you know, reach out to us at info at iata ho dot com to speak with one of our sales engineers. I mean, we love to hear from you, so book a meeting as soon as you can. All >>right. Thanks, guys. Keep it right there from or cube content with.

>> Narrator: From around the globe, it's theCUBE presenting enterprise digital resilience on hybrid and multicloud brought to you by Io-Tahoe. >> Okay, now we're going to go into the demo and we want to get a better understanding of how you can leverage OpenShift and Io-Tahoe to facilitate faster application deployment. Let me pass the mic to Sabita, take it away. >> Thanks, Dave. Happy to be here again. >> Guys as Dave mentioned my name's Sabita Davis. I'm the Enterprise Account Executive here at Io-Tahoe. So today we just wanted to give you guys a general overview of how we're using OpenShift. >> Yeah, hey, I'm Noah, Io-Tahoe's Data Operations Engineer working with OpenShift and I've been learning the ins and outs of OpenShift for like the past few months. And I'm here to share what I've learned. >> Okay so before we begin I'm sure everybody wants to know Noah. What are the benefits of using OpenShift? >> Well, there's five that I can think of, faster time to operations, simplicity, automation, control and digital resilience. >> Okay, so that's really interesting because those are the exact same benefits that we at Io-Tahoe deliver to our customers. But let's start with faster time to operation, by running Io-Tahoe on OpenShift is it faster than let's say using Kubernetes and other platforms? >> Well, our objective at Io-Tahoe is to be accessible across multiple cloud platforms, right? And so by hosting our application in containers we're able to achieve this. So to answer your question it's faster to create end user application images using container tools like Kubernetes with OpenShift as compared to like Kubernetes with Docker, Kryo >> or Containerd. >> Okay, so we got a bit technical there. Can you explain that in a bit more detail? >> Yeah, there's a bit of vocabulary involved. So basically containers are used in developing things like databases, web servers or applications such as Io-Tahoe. What's great about containers is that they split the workload. So developers can select the libraries without breaking anything. And CIS admins can update the host without interrupting the programmers. Now OpenShift works hand-in-hand with Kubernetes to provide a way to build those containers for applications. >> Okay, got it. So basically containers make life easier for developers and system admins. So how does OpenShift differ from other platforms? >> Well, this kind of leads into the second benefit I want to talk about which is simplicity. Basically there's a lot of steps involved with when using Kubernetes with Docker but OpenShift simplifies this with their source to image process that takes the source code and turns it into a container image but that's not all. OpenShift has a lot of automation and features that simplify working with containers an important one being its web console. So here I've set up a light version of OpenShift called CodeReady Containers. And I was able to set up for application right from the web console. And I was able to set up this entire thing in Windows, Mac and Linux. So it's environment agnostic in that sense. >> Okay, so I think I see in the top left that this is a developer's view. What would a systems admin view look like? >> That's a good question. So here's the administrator view and this kind of ties into the benefit of control. This view gives insights into each one of the applications and containers that are running and you can make changes without affecting deployment. And you can also within this view set up each layer of security and there's multiple that you can prop up but I haven't fully messed around with it because since with my luck, I'd probably lock myself out. >> Okay, so that seems pretty secure. Is there a single point security such as you user login or are there multiple layers of security? >> Yeah, there are multiple layers of security. There's your user login, security groups and general role based access controls but there's also a ton of layers of security surrounding like the containers themselves. But for the sake of time, I won't get too far into it. >> Okay, so you mentioned simplicity and time to operation as being two of the benefits. You also briefly mentioned automation and as you know automation is the backbone of our platform here at Io-Tahoe. So that certainly grabbed my attention. Can you go a bit more in depth in terms of automation? >> OpenShift provides extensive automation that speeds up that time to operation, right? So the latest versions of OpenShift come with a built-in cryo container engine which basically means that you get to skip that container engine installation step. And you don't have to like log into each individual container hosts and configure networking, configure registry servers, storage, et cetera. So I'd say it automates the more boring kind of tedious processes. >> Okay, so I see the Io-Tahoe template there. What does it allow me to do? >> In terms of automation in application development. So we've created an OpenShift template which contains our application. This allows developers to instantly like set up a product within that template or within that, yeah. >> Okay, so Noah, last question. Speaking of vocabulary, you mentioned earlier digital resilience is a term we're hearing especially in the banking and finance world. It seems from what you described industries like banking and finance would be more resilient using OpenShift, correct? >> Yeah, in terms of digital resilience, OpenShift will give you better control over the consumption of resources each container is using. In addition, the benefit of containers is that like I mentioned earlier sysadmins can troubleshoot the servers without bringing down the application. And if the application does go down it's easy to bring it back up using the templates and like the other automation features that OpenShift provides. >> Okay, so thanks so much Noah. So any final thoughts you want to share? >> Yeah, I just want to give a quick recap of like the five benefits that you gain by using OpenShift. The five are time to operation, automation, control, security and simplicity. You can deploy applications faster, you can simplify the workload, you can automate a lot of the otherwise tedious processes, and maintain full control over your workflow and you can assert digital resilience within your environment. >> So guys, thanks for that appreciate the demo. I wonder you guys have been talking about the combination of Io-Tahoe and Red Hat. Can you tie that in Sabita to digital resilience specifically? >> Yeah, sure Dave. So when we speak to the benefits of security controls in terms of digital resilience at Io-Tahoe we automated detection and apply controls at the data level. So this would provide for more enhanced security. >> Okay, but so if you were to try to do all these things manually I mean, what does that do? How much time can I compress? What's the time to value? >> So with our latest versions of Io-Tahoe we're taking advantage of faster deployment time associated with containerization and Kubernetes. So this kind of speeds up the time it takes for customers start using our softwares. They'd be able to quickly spin up Io-Tahoe in their own on-premise environment or otherwise in their own cloud environment like including AWS, Azure, Oracle GCP and IBM cloud. Our quick start templates allow flexibility to deploy into multicloud environments all just using like a few clicks. >> Okay, so now I'll just quickly add, so what we've done Io-Tahoe here is we've really moved our customers away from the whole idea of needing a team of engineers to apply controls to data as compared to other manually driven workflows. So with templates, automation, pre-built policies and data controls one person can be fully operational within a few hours and achieve results straight out of the box on any cloud. >> Yeah, we've been talking about this theme of abstracting the complexity that's really what we're seeing is a major trend in this coming decade. Okay, great. Thanks Sabita, Noah. How can people get more information or if they have any follow up questions, where should they go? >> Yeah, sure Dave I mean if you guys are interested in learning more reach out to us @infoatiotahoe.com to speak with one of our sales engineers. I mean, we'd love to hear from you. So book a meeting as soon as you can. >> All right, thanks guys. Keep it right there for more cube content with Io-Tahoe. (gentle music)

>>from around the globe. It's the Cube presenting enterprise, Digital resilience on hybrid and multi cloud Brought to You by Iota Ho. Okay, let's now get into the next segment where we'll explore data automation. But from the angle of digital resilience within and as a service consumption model, we're now joined by Yusuf Khan, who heads data services for Iota Ho and Shirish County. Up in Who's the vice president and head of U. S. Sales at happiest Minds. Gents, welcome to the program. Great to have you in the Cube. >>Thank you, David. >>Stretch. You guys talk about happiest minds. This notion of born digital, foreign agile. I like that. But talk about your mission at the company. >>Sure. A former in 2011 Happiest minds Up Born digital born a child company. >>The >>reason is that we are focused on customers. Our customer centric approach on delivering digitals and seamless solutions have helped us be in the race. Along with the Tier one providers, our mission, happiest people, happiest customers is focused to enable customer happiness through people happiness. We have Bean ranked among the top 25 I t services company in the great places to work serving hour glass to ratings off 4.1 against the rating off five is among the job in the Indian nineties services company that >>shows the >>mission on the culture. What we have built on the values, right sharing, mindful, integrity, learning and social on social responsibilities are the core values off our company on. That's where the entire culture of the company has been built. >>That's great. That sounds like a happy place to be. Now you have you head up data services for Iot Tahoe. We've talked in the past. Of course you're out of London. What do you what's your day to day focus with customers and partners? What you focused on? >>Well, David, my team work daily with customers and partners to help them better understand their data, improve their data quality, their data governance on help them make that data more accessible in a self service kind of way. To the stakeholders within those businesses on dis is all a key part of digital resilience that will will come on to talk about but later. You're >>right, e mean, that self service theme is something that we're gonna we're gonna really accelerate this decade, Yussef and so. But I wonder before we get into that, maybe you could talk about the nature of the partnership with happiest minds. You know, why do you guys choose toe work closely together? >>Very good question. Um, we see Io Tahoe on Happiest minds as a great mutual fit. A Suresh has said happiest minds are very agile organization. Um, I think that's one of the key things that attracts their customers on Io. Tahoe is all about automation. We're using machine learning algorithms to make data discovery data cataloging, understanding, data, redundancy, uh, much easier on. We're enabling customers and partners to do it much more quickly. So when you combine our emphasis on automation with the emphasis on agility, the happiest minds have that. That's a really nice combination. Work works very well together, very powerful. I think the other things that a key are both businesses, a serious have said are really innovative digital native type type companies. Um, very focused on newer technologies, the cloud etcetera, uh, on. Then finally, I think that both challenger brands Andi happiest minds have a really positive, fresh ethical approach to people and customers that really resonates with us that I have tied to its >>great thank you for that. So Russia, Let's get into the whole notion of digital resilience. I wanna I wanna sort of set it up with what I see. And maybe you can comment be prior to the pandemic. A lot of customers that kind of equated disaster recovery with their business continuance or business resilient strategy, and that's changed almost overnight. How have you seen your clients respond to that? What? I sometimes called the forced march to become a digital business. And maybe you could talk about some of the challenges that they faced along the way. >>Absolutely. So, uh, especially during this pandemic times when you see Dave customers have been having tough times managing their business. So happiest minds. Being a digital Brazilian company, we were able to react much faster in the industry, apart from the other services company. So one of the key things is the organizations trying to adopt onto the digital technologies right there has bean lot off data which has been to managed by these customers on. There have been lot off threats and risk, which has been to manage by the CEO Seo's so happiest minds digital resilient technology fight the where we're bringing the data complaints as a service, we were ableto manage the resilience much ahead off other competitors in the market. We were ableto bring in our business community processes from day one, where we were ableto deliver our services without any interruption to the services what we were delivering to our customers. >>So >>that is where the digital resilience with business community process enabled was very helpful for us who enable our customers continue there business without any interruptions during pandemics. >>So, I mean, some of the challenges that that customers tell me they obviously had to figure out how to get laptops to remote workers and that that whole remote, you know, work from home pivot figure out how to secure the end points. And, you know, those were kind of looking back there kind of table stakes, but it sounds like you've got a digital business means a data business putting data at the core, I like to say, but so I wonder if you could talk a little bit more about maybe the philosophy you have toward digital resilience in the specific approach you take with clients? >>Absolutely. They seen any organization data becomes. The key on this for the first step is to identify the critical data. Right. So we this is 1/6 process. What we following happiest minds. First of all, we take stock off the current state, though the customers think that they have a clear visibility off their data. How are we do more often assessment from an external point off view on See how critical their data is? Then we help the customers to strategies that right the most important thing is to identify the most important critical herself. Data being the most critical assault for any organization. Identification off the data's key for the customers. Then we help in building a viable operating model to ensure these identified critical assets are secure on monitor dearly so that they are consumed well as well as protected from external threats. Then, as 1/4 step, we try to bring in awareness, toe the people we train them at all levels in the organization. That is a P for people to understand the importance off the residual our cells. And then as 1/5 step, we work as a back up plan in terms of bringing in a very comprehensive and the holistic testing approach on people process as well as in technology. We'll see how the organization can withstand during a crisis time. And finally we do a continuous governance off this data, which is a key right. It is not just a one step process. We set up the environment. We do the initial analysis and set up the strategy on continuously govern this data to ensure that they are not only know managed will secure as well as they also have to meet the compliance requirements off the organization's right. That is where we help organizations toe secure on Meet the regulations off the organizations. As for the privacy laws, >>so >>this is a constant process. It's not on one time effort. We do a constant process because every organization goes towards the digital journey on. They have to face all these as part off the evolving environment on digital journey, and that's where they should be kept ready in terms off. No recovering, rebounding on moving forward if things goes wrong. >>So let's stick on that for a minute, and then I wanna bring yourself into the conversation. So you mentioned compliance and governance. When? When your digital business. Here, as you say, you're a data business. So that brings up issues. Data sovereignty. Uh, there's governance, this compliance. There's things like right to be forgotten. There's data privacy, so many things. These were often kind of afterthoughts for businesses that bolted on, if you will. I know a lot of executives are very much concerned that these air built in on, and it's not a one shot deal. So do you have solutions around compliance and governance? Can you deliver that as a service? Maybe you could talk about some of the specifics there, >>so some of way have offered multiple services. Tow our customers on digital race against. On one of the key service is the data complaints. As a service here we help organizations toe map the key data against the data compliance requirements. Some of the features includes in terms off the continuous discovery off data right, because organizations keep adding on data when they move more digital on helping the helping and understanding the actual data in terms off the residents of data, it could be a heterogeneous data sources. It could be on data basis or it could be even on the data lakes. Or it could be or no even on compromise, all the cloud environment. So identifying the data across the various no heterogeneous environment is very key. Feature off our solution. Once we identify, classify this sensitive data, the data privacy regulations on the traveling laws have to be map based on the business rules. So we define those rules on help map those data so that organizations know how critical their digital assets are. Then we work on a continuous marching off data for anomalies because that's one of the key teachers off the solution, which needs to be implemented on the day to day operational basis. So we're helping monitoring those anomalies off data for data quality management on an ongoing basis. And finally we also bringing the automatic data governance where we can manage the sensory data policies on their data relationships in terms off, mapping on manage their business rules on we drive reputations toe also suggest appropriate actions to the customers. Take on those specific data sets. >>Great. Thank you, Yousef. Thanks for being patient. I want to bring in Iota ho thio discussion and understand where your customers and happiest minds can leverage your data automation capability that you and I have talked about in the past. And I'm gonna be great if you had an example is well, but maybe you could pick it up from there. >>Sure. I mean, at a high level, assertions are clearly articulated. Really? Um, Iota, who delivers business agility. So that's by, um, accelerating the time to operationalize data, automating, putting in place controls and ultimately putting, helping put in place digital resilience. I mean, way if we step back a little bit in time, um, traditional resilience in relation to data are often met manually, making multiple copies of the same data. So you have a DB A. They would copy the data to various different places on business. Users would access it in those functional style owes. And of course, what happened was you ended up with lots of different copies off the same data around the enterprise. Very inefficient. Onda course ultimately, uh, increases your risk profile. Your risk of a data breach. Um, it's very hard to know where everything is, and I realized that expression they used David, the idea of the forced march to digital. So with enterprises that are going on this forced march, what they're finding is they don't have a single version of the truth, and almost nobody has an accurate view of where their critical data is. Then you have containers bond with containers that enables a big leap forward so you could break applications down into micro services. Updates are available via a P I s. And so you don't have the same need to build and to manage multiple copies of the data. So you have an opportunity to just have a single version of the truth. Then your challenge is, how do you deal with these large legacy data states that the service has been referring Thio, where you you have toe consolidate, and that's really where I Tahoe comes in. Um, we massively accelerate that process of putting in a single version of the truth into place. So by automatically discovering the data, um, discovering what's duplicate what's redundant, that means you can consolidate it down to a single trusted version much more quickly. We've seen many customers have tried to do this manually, and it's literally taken years using manual methods to cover even a small percentage of their I T estates with a tire. You could do it really very quickly on you can have tangible results within weeks and months. Um, and then you can apply controls to the data based on context. So who's the user? What's the content? What's the use case? Things like data quality validations or access permissions on. Then once you've done there, your applications and your enterprise are much more secure, much more resilient. As a result, you've got to do these things whilst retaining agility, though. So coming full circle. This is where the partnership with happiest minds really comes in as well. You've got to be agile. You've gotta have controls, um, on you've got a drug towards the business outcomes and it's doing those three things together that really deliver for the customer. Thank >>you. Use f. I mean you and I. In previous episodes, we've looked in detail at the business case. You were just talking about the manual labor involved. We know that you can't scale, but also there's that compression of time. Thio get to the next step in terms of ultimately getting to the outcome and we talked to a number of customers in the Cube. And the conclusion is really consistent that if you could accelerate the time to value, that's the key driver reducing complexity, automating and getting to insights faster. That's where you see telephone numbers in terms of business impact. So my question is, where should customers start? I mean, how can they take advantage of some of these opportunities that we've discussed >>today? Well, we've tried to make that easy for customers. So with our Tahoe and happiest minds, you can very quickly do what we call a data health check on. Dis is a is a 2 to 3 weeks process are two Really quickly start to understand and deliver value from your data. Um, so, iota, who deploys into the customer environment? Data doesn't go anywhere. Um, we would look at a few data sources on a sample of data Onda. We can very rapidly demonstrate how date discovery those catalog e understanding Jupiter data and redundant data can be done. Um, using machine learning, um, on how those problems can be solved. Um, and so what we tend to find is that we can very quickly as I say in a matter of a few weeks, show a customer how they could get toe, um, or Brazilian outcome on. Then how they can scale that up, take it into production on, then really understand their data state Better on build resilience into the enterprise. >>Excellent. There you have it. We'll leave it right there. Guys. Great conversation. Thanks so much for coming on the program. Best of luck to you in the partnership. Be well. >>Thank you, David. Sorry. Thank you. Thank >>you for watching everybody, This is Dave Volonte for the Cuban Are ongoing Siris on data Automation without Tahoe.

>> Announcer: From around the globe, it's theCUBE presenting Enterprise Digital Resilience on Hybrid and multicloud brought to you by io/tahoe >> Hello everyone, and welcome to our continuing series covering data automation brought to you by io/tahoe. Today we're going to look at how to ensure enterprise resilience for hybrid and multicloud, let's welcome in Ajay Vohora who's the CEO of io/tahoe Ajay, always good to see you again, thanks for coming on. >> Great to be back David, pleasure. >> And he's joined by Fadzi Ushewokunze, who is a global principal architect for financial services, the vertical of financial services at Red Hat. He's got deep experiences in that sector. Welcome Fadzi, good to see you. >> Thank you very much. Happy to be here. >> Fadzi, let's start with you. Look, there are a lot of views on cloud and what it is. I wonder if you could explain to us how you think about what is a hybrid cloud and how it works. >> Sure, Yeah. So, a hybrid cloud is an IT architecture that incorporates some degree of workload portability, orchestration and management across multiple clouds. Those clouds could be private clouds or public clouds or even your own data centers. And how does it all work? It's all about secure interconnectivity and on demand allocation of resources across clouds. And separate clouds can become hybrid when you're seamlessly interconnected. And it is that interconnectivity that allows the workloads to be moved and how management can be unified and orchestration can work. And how well you have these interconnections has a direct impact of how well your hybrid cloud will work. >> Okay, so well Fadzi, staying with you for a minute. So, in the early days of cloud that term private cloud was thrown around a lot. But it often just meant virtualization of an on-prem system and a network connection to the public cloud. Let's bring it forward. What, in your view does a modern hybrid cloud architecture look like? >> Sure, so, for modern hybrid clouds we see that teams or organizations need to focus on the portability of applications across clouds. That's very important, right. And when organizations build applications they need to build and deploy these applications as a small collections of independently loosely coupled services. And then have those things run on the same operating system, which means in other words, running it all Linux everywhere and building cloud native applications and being able to manage it and orchestrate these applications with platforms like Kubernetes or Red Hat OpenShift, for example. >> Okay, so, Fadzi that's definitely different from building a monolithic application that's fossilized and doesn't move. So, what are the challenges for customers, you know, to get to that modern cloud is as you've just described it as it skillsets, is it the ability to leverage things like containers? What's your View there? >> So, I mean, from what we've seen around the industry especially around financial services where I spend most of my time. We see that the first thing that we see is management, right. Now, because you have all these clouds, you know, all these applications. You have a massive array of connections, of interconnections. You also have massive array of integrations portability and resource allocation as well. And then orchestrating all those different moving pieces things like storage networks. Those are really difficult to manage, right? So, management is the first challenge. The second one is workload placement. Where do you place this cloud? How do you place these cloud native operations? Do you, what do you keep on site on prem and what do you put in the cloud? That is the other challenge. The major one, the third one is security. Security now becomes the key challenge and concern for most customers. And we're going to talk about how to address that. >> Yeah, we're definitely going to dig into that. Let's bring Ajay into the conversation. Ajay, you know, you and I have talked about this in the past. One of the big problems that virtually every company face is data fragmentation. Talk a little bit about how io/tahoe, unifies data across both traditional systems, legacy systems and it connects to these modern IT environments. >> Yeah, sure Dave. I mean, a Fadzi just nailed it there. It used to be about data, the volume of data and the different types of data, but as applications become more connected and interconnected the location of that data really matters. How we serve that data up to those apps. So, working with Red Hat and our partnership with Red Hat. Being able to inject our data discovery machine learning into these multiple different locations. whether it be an AWS or an IBM cloud or a GCP or on prem. Being able to automate that discovery and pulling that single view of where is all my data, then allows the CIO to manage cost. They can do things like, one, I keep the data where it is, on premise or in my Oracle cloud or in my IBM cloud and connect the application that needs to feed off that data. And the way in which we do that is machine learning that learns over time as it recognizes different types of data, applies policies to classify that data and brings it all together with automation. >> Right, and one of the big themes that we've talked about this on earlier episodes is really simplification, really abstracting a lot of that heavy lifting away. So, we can focus on things Ajay, as you just mentioned. I mean, Fadzi, one of the big challenges that of course we all talk about is governance across these disparate data sets. I'm curious as your thoughts how does Red Hat really think about helping customers adhere to corporate edicts and compliance regulations? Which of course are particularly acute within financial services. >> Oh yeah, yes. So, for banks and payment providers like you've just mentioned there. Insurers and many other financial services firms, you know they have to adhere to a standard such as say a PCI DSS. And in Europe you've got the GDPR, which requires stringent tracking, reporting, documentation and, you know for them to, to remain in compliance. And the way we recommend our customers to address these challenges is by having an automation strategy, right. And that type of strategy can help you to improve the security on compliance of of your organization and reduce the risk out of the business, right. And we help organizations build security and compliance from the start with our consulting services, residencies. We also offer courses that help customers to understand how to address some of these challenges. And there's also, we help organizations build security into their applications with our open source middleware offerings and even using a platform like OpenShift, because it allows you to run legacy applications and also containerized applications in a unified platform. Right, and also that provides you with, you know with the automation and the tooling that you need to continuously monitor, manage and automate the systems for security and compliance purposes. >> Ajay, anything, any color you could add to this conversation? >> Yeah, I'm pleased Fadzi brought up OpenShift. I mean we're using OpenShift to be able to take that security application of controls to the data level and it's all about context. So, understanding what data is there, being able to assess it to say, who should have access to it, which application permission should be applied to it. That's a great combination of Red Hat and io/tahoe. >> Fadzi, what about multi-cloud? Doesn't that complicate the situation even further, maybe you could talk about some of the best practices to apply automation across not only hybrid cloud, but multi-cloud as well. >> Yeah, sure, yeah. So, the right automation solution, you know can be the difference between, you know cultivating an automated enterprise or automation carries. And some of the recommendations we give our clients is to look for an automation platform that can offer the first thing is complete support. So, that means have an automation solution that provides, you know, promotes IT availability and reliability with your platform so that, you can provide enterprise grade support, including security and testing integration and clear roadmaps. The second thing is vendor interoperability in that, you are going to be integrating multiple clouds. So, you're going to need a solution that can connect to multiple clouds seamlessly, right? And with that comes the challenge of maintainability. So, you're going to need to look into a automation solution that is easy to learn or has an easy learning curve. And then, the fourth idea that we tell our customers is scalability. In the hybrid cloud space, scale is the big, big deal here. And you need to deploy an automation solution that can span across the whole enterprise in a consistent manner, right. And then also that allows you finally to integrate the multiple data centers that you have. >> So, Ajay, I mean, this is a complicated situation for if a customer has to make sure things work on AWS or Azure or Google. They're going to spend all their time doing that. What can you add to really just simplify that multi-cloud and hybrid cloud equation. >> Yeah, I can give a few customer examples here. One being a manufacturer that we've worked with to drive that simplification. And the real bonuses for them has been a reduction in cost. We worked with them late last year to bring the cost spend down by $10 million in 2021. So, they could hit that reduced budget. And, what we brought to that was the ability to deploy using OpenShift templates into their different environments, whether it was on premise or in, as you mentioned, AWS. They had GCP as well for their marketing team and across those different platforms, being able to use a template, use prebuilt scripts to get up and running and catalog and discover that data within minutes. It takes away the legacy of having teams of people having to jump on workshop calls. And I know we're all on a lot of teams zoom calls. And in these current times. They're just simply using enough hours of the day to manually perform all of this. So, yeah, working with Red Hat, applying machine learning into those templates, those little recipes that we can put that automation to work regardless which location the data's in allows us to pull that unified view together. >> Great, thank you. Fadzi, I want to come back to you. So, the early days of cloud you're in the Big Apple, you know financial services really well. Cloud was like an evil word and within financial services, and obviously that's changed, it's evolved. We talk about the pandemic has even accelerated that. And when you really dug into it, when you talk to customers about their experiences with security in the cloud, it was not that it wasn't good, it was great, whatever, but it was different. And there's always this issue of skill, lack of skills and multiple tools, set up teams. are really overburdened. But in the cloud requires, you know, new thinking you've got the shared responsibility model. You've got to obviously have specific corporate, you know requirements and compliance. So, this is even more complicated when you introduce multiple clouds. So, what are the differences that you can share from your experiences running on a sort of either on prem or on a mono cloud or, you know, versus across clouds? What, do you suggest there? >> Sure, you know, because of these complexities that you have explained here mixed configurations and the inadequate change control are the top security threats. So, human error is what we want to avoid, because as you know, as your clouds grow with complexity then you put humans in the mix. Then the rate of errors is going to increase and that is going to expose you to security threats. So, this is where automation comes in, because automation will streamline and increase the consistency of your infrastructure management also application development and even security operations to improve in your protection compliance and change control. So, you want to consistently configure resources according to a pre-approved, you know, pre-approved policies and you want to proactively maintain them in a repeatable fashion over the whole life cycle. And then, you also want to rapidly the identify system that require patches and reconfiguration and automate that process of patching and reconfiguring. So that, you don't have humans doing this type of thing, And you want to be able to easily apply patches and change assistance settings according to a pre-defined base like I explained before, you know with the pre-approved policies. And also you want ease of auditing and troubleshooting, right. And from a Red Hat perspective we provide tools that enable you to do this. We have, for example a tool called Ansible that enables you to automate data center operations and security and also deployment of applications. And also OpenShift itself, it automates most of these things and obstruct the human beings from putting their fingers and causing, you know potentially introducing errors, right. Now, in looking into the new world of multiple clouds and so forth. The differences that we're seeing here between running a single cloud or on prem is three main areas, which is control, security and compliance, right. Control here, it means if you're on premise or you have one cloud you know, in most cases you have control over your data and your applications, especially if you're on prem. However, if you're in the public cloud, there is a difference that the ownership it is still yours, but your resources are running on somebody else's or the public clouds, EWS and so forth infrastructure. So, people that are going to do these need to really, especially banks and governments need to be aware of the regulatory constraints of running those applications in the public cloud. And we also help customers rationalize some of these choices. And also on security, you will see that if you're running on premises or in a single cloud you have more control, especially if you're on prem. You can control the sensitive information that you have. However, in the cloud, that's a different situation especially from personal information of employees and things like that. You need to be really careful with that. And also again, we help you rationalize some of those choices. And then, the last one is compliance. As well, you see that if you're running on prem on single cloud, regulations come into play again, right? And if you're running on prem, you have control over that. You can document everything, you have access to everything that you need, but if you're going to go to the public cloud again, you need to think about that. We have automation and we have standards that can help you you know, address some of these challenges. >> So, that's really strong insights, Fadzi. I mean, first of all Ansible has a lot of market momentum, you know, Red Hat's done a really good job with that acquisition. Your point about repeatability is critical, because you can't scale otherwise. And then, that idea you're putting forth about control, security and compliance. It's so true, I called it the shared responsibility model. And there was a lot of misunderstanding in the early days of cloud. I mean, yeah, maybe AWS is going to physically secure the you know, the S3, but in the bucket but we saw so many misconfigurations early on. And so it's key to have partners that really understand this stuff and can share the experiences of other clients. So, this all sounds great. Ajay, you're sharp, financial background. What about the economics? You know, our survey data shows that security it's at the top of the spending priority list, but budgets are stretched thin. I mean, especially when you think about the work from home pivot and all the areas that they had to, the holes that they had to fill there, whether it was laptops, you know, new security models, et cetera. So, how to organizations pay for this? What's the business case look like in terms of maybe reducing infrastructure costs, so I can pay it forward or there's a there's a risk reduction angle. What can you share there? >> Yeah, I mean, that perspective I'd like to give here is not being multi-cloud as multi copies of an application or data. When I think back 20 years, a lot of the work in financial services I was looking at was managing copies of data that were feeding different pipelines, different applications. Now, what we're seeing at io/tahoe a lot of the work that we're doing is reducing the number of copies of that data. So that, if I've got a product lifecycle management set of data, if I'm a manufacturer I'm just going to keep that at one location. But across my different clouds, I'm going to have best of breed applications developed in-house, third parties in collaboration with my supply chain, connecting securely to that single version of the truth. What I'm not going to do is to copy that data. So, a lot of what we're seeing now is that interconnectivity using applications built on Kubernetes that are decoupled from the data source. That allows us to reduce those copies of data within that you're gaining from a security capability and resilience, because you're not leaving yourself open to those multiple copies of data. And with that come cost of storage and a cost to compute. So, what we're saying is using multi-cloud to leverage the best of what each cloud platform has to offer. And that goes all the way to Snowflake and Heroku on a cloud managed databases too. >> Well and the people cost too as well. When you think about, yes, the copy creep. But then, you know, when something goes wrong a human has to come in and figure it out. You know, you brought up Snowflake, I get this vision of the data cloud, which is, you know data. I think we're going to be rethinking Ajay, data architectures in the coming decade where data stays where it belongs, it's distributed and you're providing access. Like you said, you're separating the data from the applications. Applications as we talked about with Fadzi, much more portable. So, it's really the last 10 years it'd be different than the next 10 years ago Ajay. >> Definitely, I think the people cost reduction is used. Gone are the days where you needed to have a dozen people governing, managing byte policies to data. A lot of that repetitive work, those tasks can be in part automated. We're seen examples in insurance where reduced teams of 15 people working in the back office, trying to apply security controls, compliance down to just a couple of people who are looking at the exceptions that don't fit. And that's really important because maybe two years ago the emphasis was on regulatory compliance of data with policies such as GDPR and CCPA. Last year, very much the economic effect to reduce head counts and enterprises running lean looking to reduce that cost. This year, we can see that already some of the more proactive companies are looking at initiatives, such as net zero emissions. How they use data to understand how they can become more, have a better social impact and using data to drive that. And that's across all of their operations and supply chain. So, those regulatory compliance issues that might have been external. We see similar patterns emerging for internal initiatives that are benefiting that environment, social impact, and of course costs. >> Great perspectives. Jeff Hammerbacher once famously said, the best minds of my generation are trying to get people to click on ads and Ajay those examples that you just gave of, you know social good and moving things forward are really critical. And I think that's where data is going to have the biggest societal impact. Okay guys, great conversation. Thanks so much for coming to the program. Really appreciate your time. >> Thank you. >> Thank you so much, Dave. >> Keep it right there, for more insight and conversation around creating a resilient digital business model. You're watching theCube. (soft music)

>>Yeah, yeah. >>Welcome back to our final session in cultivating a data fluent culture track earlier today, we heard from experts like Valerie from the Data Lodge who shared best practices that you can apply to build that data flew into culture in your organization and tips on how to become the next analyst of the future from Yasmin at Comcast and Steve at all Terex. Then we heard from a captivating session with Cindy Hausen and Ruhollah Benjamin, professor at Princeton, on how now is our chance to change the patterns of injustice that we see have been woven into the fabric of society. If you do not have a chance to see today's content, I highly recommend that you check it out on demand. There's a lot of great information that you could start applying today. Now I'm excited to introduce our next session, which will take a look at how the democratization of data is powering digital transformation in the insurance industry. We have two prestigious guests joining us today. First Jim Bramblett, managing director of North America insurance practice, lead at its center. Throughout Jim's career, he's been focused on large scale transformation from large to midsize insurance carriers. His direct experience with clients has traditionally been in the intersection of technology, platform transformation and operating remodel redesign. We also have Michael cast Onus, executive VP and chief operating officer at DNA. He's responsible for all information technology, analytics and operating functions across the organization. Michael has led major initiatives to launch digital programs and incorporating modern AP I architectures ER, which was primarily deployed in the cloud. Jim, please take it away. >>Great. Thanks, Paula E thought we'd cover a few things today around around data. This is some of the trends we see in data within the insurance sector. And then I'll hand it over to Michael Teoh, take you through his story. You know, I think at the macro level, as we think about data and we think about data in the context of the insurance sector, it's interesting because the entire history of the insurance sector has been built on data and yet, at the same time, the entire future of it relies on that same data or similar similar themes for data. But but different. Right? So we think about the history, what has existed in an insurance companies. Four walls was often very enough, very enough to compete, right? So if you think about your customer data, claims, data, CRM, data, digital data, all all the data that was yeah, contained within the four walls of your company was enough to compete on. And you're able to do that for hundreds of years. But as we we think about now as we think about the future and the ability to kind of compete on data, this data comes from many more places just than inside your four walls. It comes from every device, every human, every vehicle, every property, every every digital interaction. Um in upon this data is what we believe insurers need to pivot to. To compete right. They need to be able to consume this data at scale. They need to be able to turn through this data to drive analytics, and they serve up insights based on those analytics really at the desktop of insurance professionals. And by the way, that has to be in the natural transition of national transaction. Of that employees work day. So an underwriter at a desktop claim him on the desktop, the sales associate of desktop. Those insights need to be served up at that point in time when most relevant. And you know. So if we think about how insurance companies are leveraging data, we see this really on kind of three horizons and starting from the left hand side of the page here, this is really brilliant basics. So how my leveraging core core data and core applied intelligence to monetize your existing strategy? And I think this brilliant based, brilliant basics concept is where most of most of my clients, at least within insurance are are today. You know, how are we leveraging data in the most effective way and putting it in the hands of business decision makers to make decisions largely through reporting and some applied intelligence? Um, Horizon two. We see, you know, definitely other industries blazing a trail here, and this is really about How do we integrate ecosystems and partners Now? I think within insurance, you know, we've had data providers forever, right? Whether it's NPR data, credit data risk data, you know, data aggregators and data providers have been a critical part of the insurance sector for for decades. I think what's different about this this ecosystem and partnership model is that it's much more Oneto one and it's much more, you know, kind of. How do we integrate more tightly and how do we become more embedded in each other's transactions? I think that we see some emergence of this, um, in insurance with automotive manufacturers with building management systems. But I think in the grand scheme of things, this is really very, very nascent for us as a sector. And I think the third horizon is is, you know, how do we fundamentally think about data differently to drive new business models? And I, you know, I don't know that we haven't ensure here in North America that's really doing this at any sort of scale. We certainly see pilots and proofs of concepts. We see some carriers in Europe farther down this path, but it's really it's really very new for us. A Z Think about these three horizons for insurance. So you know what's what's behind all this and what's behind. You know, the next powering of digital transformation and and we think at the end of the exercise, its data data will be the next engine that powers digital transformation. So in this exhibit, you know we see the three horizons across the top. You know, data is activated and activating digital transformation. And this, you know, this purple 3rd, 3rd road here is we think some of the foundational building blocks required to kind of get this right. But I think what's most important about about this this purple third bar here is the far right box, which is business adoption. Because you can build this infrastructure, you can have. You know, this great scalable cloud capability. Um, you can create a bunch of applications and intelligence, but unless it's adopted by the business, unless it's democratized, unless those insights and decisions air served up in the natural course of business, you're gonna have trouble really driving value. So that way, I think this is a really interesting time for data. We think this is kind of the next horizon to power the next age of digital transformation for insurance companies. With that brief prelude, I am, I'm honored. Thio, turn it over to Michael Stone Is the Cielo at CNN Insurance? >>Thanks, Jim, for that intro and very exciting Thio be here is part of part of beyond when I think a digital transformation within the context of insurance, actually look at it through the lens of competing in an era of near perfect information. So in order to be able to deliver all of the potential value that we talked about with regard to data and changing ecosystem and changing demands, the question becomes, How do you actually harness the information that's available to everybody to fundamentally change the business? So if you'll indulge me a bit here, let me tell you just a little bit more for those that don't know about insurance, what it really is. And I use a very long run on sentence to do that. It's a business model where capital is placed against risk in the form of products and associated services sold the customers through channels two companies to generate a return. Now, this sounds like a lot of other businesses in across multiple industries that were there watching today. But the difference within insurance is that every major word in that long run on sentence is changing sources of capital that we could draw on to be able to underwrite risk of going away. The nature of risk itself is changing from the perspective of policies that live six months to a year, the policies that could last six minutes. The products that we're creating are changing every day for our ability to actually put a satellite up in the air or ensure against the next pandemic. Our customers are not just companies or individuals, but they could be governments completely different entities than we would have been in sharing in the past and channels were changing. We sell direct, we sell through brokers and products are actually being embedded in other products. So you may buy something and not even know that insurance is a part of it. And what's most interesting here is the last word which is around return In the old world. Insurance was a cash flow business in which we could bring the premium in and get a level of interest income and being able to use that money to be able thio buffer the underwriting results that we would have. But those returns or dramatically reduced because of the interest income scenario, So we have to generate a higher rate of return. So what do we need to do? Is an insurance company in through this digital transformation to be able to get there? Well, fundamentally, we need to rethink how we're using information, and this is where thought spot and the cloud coming for us. We have two basic problems that we're looking to solve with information. The first one is information veracity. Do we believe it? When we get it? Can we actually trust it? Do we know what it means when we say that this is a policy in force or this is a new customer where this is the amount of attention or rate that we're going to get? Do we actually believe in that piece of data? The second is information velocity. Can we get it fast enough to be able to capitalize upon it? So in other words, we're We're working in a situation where the feedback loop is closing quickly and it's operating at a speed that we've never worked in before. So if we can't solve veracity and velocity, then we're never going to be able to get to where we need to go. So when we think of something like hot spot, what do we use it for? We use it to be able to put it in the hands of our business years so that they could ask the key questions about how the business is running. How much profit of my generating this month? What brokers do I need to talk? Thio. What is my rate retention? Look like what? The trends that I'm seeing. And we're using that mechanism not just to present nice visualizations, but to enable that really quick, dynamic question and answer and social, socially enabled search, which completely puts us in a different position of being able to respond to the market conditions. In addition, we're using it for pattern recognition. Were using it for artificial intelligence. We're gonna be capitalizing on the social aspect of of search that's that's enabled through thought spot and also connecting it into our advanced machine learning models and other capabilities that we currently have. But without it solving the two fundamental problems of veracity and velocity, we would be handicapped. So let me give you some advice about if I were in your position and you don't need to be in sleepy old industry like insurance to be able to do this, I'll leave you with three things. The first one is picking water holes so What are the things that you really want to be good at? What are the pieces of information that you really need to know more about? I mean, in insurance, its customers, it's businesses, locations, it's behavior. There are only a few water also really understand and pick those water holes that you're going to be really good at. The second is stand on the shoulders of giants. You know, in the world of technology, there's often a philosophy that says, Well, I can build it something better than somebody else create if I have it in house. But I'm happy to stand on the shoulders of giants like Thought Spot and Google and others to be able to create this capability because guess what? They're gonna out innovate any of the internal shops all day and every day. So don't be afraid. Thio. Stand side by side on the shoulders of giants as part of your journey. Unless you've got to build these organizations not just the technology for rapid experimentation and learning, because guess what? The moment you deliver insight, it begs another question, which also could change the business process, which could change the business model and If your organization the broader organization of business technology, analytics, customer service operations, etcetera is not built in a way that could be dynamic and flexible based on where the market is or is going, then you're gonna miss out on the opportunity. So again, I'm proud to be part of the fast black community. Really love the technology. And if if you look too, have the same kind of issues with your given industry about how you can actually speed up decision making, deliver insights and deliver this kind of search and recommended to use it. And with that, let's go to some questions. >>Awesome. Thank you so much, Michael and Jim for that in depth perspective and those tangible takeaways for our audience. We have a few minutes left and would love to ask a few questions. So here's the first one for Michael Michael. What are some of the most important things that you know now that you didn't know before you started this process? I think one of >>the things that's a great question. I think one of the things that really struck me is that, you know, traditional thinking would be very use case centric or pain point centric Show me, uh, this particular model or a particular question you want me to answer that can build your own analytics to do that or show me a deficiency in the system and I can go and develop a quick head that will do well, then you know, wallpaper over that particular issue. But what we've really learned is the foundation matters. So when we think about building things is building the things that are below the waterline, the pipes and plumbing about how you move data around how the engines work and how it all connects together gives you the above the waterline features that you could deliver to. You know, your employees into your customers much faster chasing use cases across the top above the waterline and ignoring what's below the water line to me. Is it really, uh, easy recipe too quick? Get your way to nothing. So again, focus on the foundation bill below the water line and then iterated above the water line that z what the lessons we've learned. It has been very effective for us. >>I think that's a very great advice for all those watching today on. But Here's one for Jim. Jim. What skills would you say are required for teams to truly adopt this digital transformation process? >>Yeah, well, I think that's a really good question, and I think I'd start with it's It's never one. Well, our experience has shown us number a one person show, right? So So we think to kind of drive some of the value that that that Michael spoke about. We really looked across disciplinary teams, which is a an amalgamation of skills and and team members, right? So if you think about the data science skills required, just kinda under under understand how toe toe work with data and drive insights, Sometimes that's high end analytic skills. Um, where you gonna find value? So some value architectural skills Thio really articulate, you know, Is this gonna move the needle for my business? I think there's a couple of critical critical components of this team. One is, you know, the operation. Whatever. That operation maybe has to be embedded, right, because they designed this is gonna look at a piece of data that seems interesting in the business Leader is going to say that that actually means nothing to me in my operation. So and then I think the last the last type of skill would be would be a data translator. Um, sitting between sometimes the technology in the business so that this amalgamation of skills is important. You know, something that Michael talked about briefly that I think is critical is You know, once you deliver insight, it leads to 10 more questions. So just in a intellectual curiosity and an understanding of, you know, if I find something here, here, the implications downstream from my business are really important. So in an environment of experimenting and learning thes thes cross discipline teams, we have found to be most effective. And I think we thought spot, you know, the platform is wired to support that type of analysis and wired to support that type of teaming. >>Definitely. I think that's though there's some really great skills. That's for people to keep in mind while they are going through this process. Okay, Michael, we have another question for you. What are some of the key changes you've had to make in your environment to make this digital transformation happen? >>That's a great question. I think if you look at our environment. We've got a mixture of, you know, space agent Stone age. We've got old legacy systems. We have all sorts of different storage. We have, you know, smatterings of things that were in cloud. The first thing that we needed to do was make a strong commitment to the cloud. So Google is our partner for for the cloud platform on unabashedly. The second thing that we needed to dio was really rethink the interplay between analytics systems in operational systems. So traditionally, you've got a large data warehouses that sit out over here that, you know, we've got some kind of extract and low that occurs, and we've got transactional operational systems that run the business, and we're thinking about them very differently from the perspective of bringing them together. How Doe I actually take advantage of data emotion that's in the cloud. So then I can actually serve up analytics, and I can also change business process as it's happening for the people that are transacting business. And in the meantime, I can also serve the multiple masters of total cost and consumption. So again, I didn't applications are two ships that pass in the night and never be in the world of Sienna. When you look at them is very much interrelated, especially as we want to get our analytics right. We want to get our A i m all right, and we want to get operational systems right By capturing that dated motion force across that architecture er that was an important point. Commit to the cloud, rethink the way we think analytics systems, work and operational systems work and then move them in tandem, as opposed to doing one without the other one in the vacuum. >>That's that's great advice, Michael. I think it's very important those key elements you just hit one question that we have final question we have for Jim. Jim, how do you see your client sustain the benefits that they've gained through this process? >>Yeah, it's a really good question. Um, you know, I think about some of the major themes around around beyond right, data fluency is one of them, right? And as I think about fluency, you only attain fluency through using the language every single day. They were day, week, over week, month over month. So you know, I think that applies to this. This problem too. You know, we see a lot of clients have to change probably two things at the same time. Number one is mindset, and number two is is structure. So if you want to turn these data projects from projects into processes, right, so so move away from spinning up teams, getting getting results and winding down. You wanna move away from that Teoh process, which is this is just the way working for these teams. Um, you have to change the mindset and often times you have to marry that with orb structure change. So So I'm gonna spin up these teams, but this team is going to deliver a set of insights on day. Then we're gonna be continuous improvement teams that that persist over time. So I think this shifting from project teams to persistent teams coupled with mindset coupled with with or structure changed, you know, a lot of times has to be in place for a period of time to get to get the fluency and achieve the fluency that that most organizations need. >>Thanks, Jim, for that well thought out answer. It really goes to show that the transformation process really varies when it comes to organizations, but I think this is a great way to close out today's track. I like to think Jim, Michael, as well as all the experts that you heard earlier today for sharing. There's best practice as to how you all can start transforming your organization's by building a data fluent culture, Um, and really empowering your employees to understand what data means and how to take actions with it. As we wrap up and get ready for the next session, I'd like to leave you all with just a couple of things. Number one if you miss anything or would like to watch any of the other tracks. Don't worry. We have everything available after this event on demand number two. If you want to ask more questions from the experts that you heard earlier today, you have a chance to do so. At the Meet The Experts Roundtable, make sure to attend the one for track four in cultivating a data fluent culture. Now, as we get ready for the product roadmap, go take a sip of water. This is something you do not want to miss. If you love what you heard yesterday, you're gonna like what you hear today. I hear there's some type of Indiana Jones theme to it all, so I won't say anything else, but I'll see you there.